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Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging

Recomendações da Sociedade Brasileira de Cirurgia Torácica, Sociedade Brasileira de Pneumologia e Tisiologia e Colégio Brasileiro de Radiologia e Diagnóstico por Imagem para o rastreamento do câncer de pulmão no Brasil

Luiz Fernando Ferreira Pereira1, Ricardo Sales dos Santos2,3, Daniel Oliveira Bonomi4, Juliana Franceschini3,5, Ilka Lopes Santoro6, André Miotto7, Thiago Lins Fagundes de Sousa8, Rodrigo Caruso Chate9, Bruno Hochhegger10, Artur Gomes Neto11, Airton Schneider12, César Augusto de Araújo Neto3,13, Dante Luiz Escuissato14, Gustavo Faibischew Prado15, Luciana Costa-Silva16, Mauro Musa Zamboni17,18, Mario Claudio Ghefter2,19, Paulo César Rodrigues Pinto Corrêa20, Pedro Paulo Teixeira e Silva Torres21, Ricardo Kalaf Mussi22, Valdair Francisco Muglia23, Irma de Godoy24, Wanderley Marques Bernardo25

DOI: https://dx.doi.org/10.36416/1806-3756/e20230233

ABSTRACT

Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation. In the last decade, a number of countries have adopted population-based LCS as a public health recommendation. Albeit still incipient, discussion on this topic in Brazil is becoming increasingly broad and necessary. With the aim of increasing knowledge and stimulating debate on LCS, the Brazilian Society of Thoracic Surgery, the Brazilian Thoracic Association, and the Brazilian College of Radiology and Diagnostic Imaging convened a panel of experts to prepare recommendations for LCS in Brazil. The recommendations presented here were based on a narrative review of the literature, with an emphasis on large population-based studies, systematic reviews, and the recommendations of international guidelines, and were developed after extensive discussion by the panel of experts. The following topics were reviewed: reasons for screening; general considerations about smoking; epidemiology of LC; eligibility criteria; incidental findings; granulomatous lesions; probabilistic models; minimum requirements for LDCT; volumetric acquisition; risks of screening; minimum structure and role of the multidisciplinary team; practice according to the Lung CT Screening Reporting and Data System; costs versus benefits of screening; and future perspectives for LCS.

Keywords: Lung neoplasms; Early detection of cancer; Tomography, X-ray computed; Tobacco use disorder.

RESUMO

O câncer de pulmão (CP) é uma das neoplasias mais comuns e letais no Brasil, e apenas 15% dos pacientes são diagnosticados nos estágios iniciais. O tabagismo persiste como o responsável por mais de 85% de todos os casos. O rastreamento do CP (RCP) por meio da TC de baixa dosagem de radiação (TCBD) reduz a mortalidade do CP em 20%, e, quando combinado com a cessação do tabagismo, essa redução chega a 38%. Na última década, diversos países adotaram o RCP como recomendação de saúde populacional. No Brasil, embora ainda incipiente, a discussão sobre o tema é cada vez mais ampla e necessária. Com o intuito de aumentar o conhecimento e estimular o debate sobre o RCP, a Sociedade Brasileira de Cirurgia Torácica, a Sociedade Brasileira de Pneumologia e Tisiologia e o Colégio Brasileiro de Radiologia e Diagnóstico por Imagem constituíram um painel de especialistas para elaborar as recomendações para o RCP. As recomendações aqui apresentadas foram baseadas em revisão narrativa da literatura, com ênfase em grandes estudos populacionais, em revisões sistemáticas e em recomendações de diretrizes internacionais, sendo construídas após ampla discussão pelo grupo de especialistas. Os temas revisados foram os seguintes: porque rastrear, considerações gerais sobre tabagismo, epidemiologia do CP, critérios de elegibilidade, achados incidentais, lesões granulomatosas, modelos probabilísticos, requisitos mínimos da TCBD, aquisições volumétricas, riscos do rastreamento, estrutura mínima e papel da equipe multidisciplinar, conduta segundo o Lung CT Screening Reporting and Data System (Lung-RADS), custos vs. benefícios e perspectivas do rastreamento.

Palavras-chave: Neoplasias pulmonares; Detecção precoce de câncer; Tomografia computadorizada por raios X; Tabagismo.

INTRODUCTION
 
Lung cancer screening (LCS) using low-dose CT (LDCT) of the chest has become the gold standard in the preventive approach to the population at high risk for lung cancer (LC). Over the last decade, various countries have adopted periodic population screening with LDCT as a public health recommendation, following the guidelines of specialized medical societies.
 
In Brazil, albeit still incipient, discussion on this topic is increasingly broad and necessary. To expand the knowledge of and stimulate debate regarding LCS, the Sociedade Brasileira de Cirurgia Torácica (SBCT, Brazilian Society of Thoracic Surgery), the Sociedade Brasileira de Pneumologia e Tisiologia (SBPT, Brazilian Thoracic Association), and the Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR, Brazilian College of Radiology and Diagnostic Imaging) convened a panel of experts to prepare these initial recommendations.
 
These recommendations are intended for all medical professionals involved in caring for patients with risk factors for LC. The group that conceived and coordinated the recommendations, including members from the SBCT, SBPT, and CBR, presented questions and general themes to the panel of 21 experts, who, in virtual meetings, defined the most relevant topics to be covered.
 
Each theme or question was written by two or three of the authors, on the basis of a narrative review of the current, most relevant evidence in the literature and internationally accepted guidelines. That was followed by two phases of text harmonization. In the first, four experts discussed and restructured the texts sent by the others, and, in the second, all of the experts reviewed, discussed, and validated the final text.
 
CONCEPTS ABOUT SCREENING AND WHY TO SCREEN
 
•             Diagnosing LC at an early stage reduces mortality and healthcare costs.
•             In organized screening, the target population is invited and monitored at a defined periodicity, within an examination quality program and decision flowcharts.
•             These are challenges for implementing screening programs in Brazil:
o             Budgetary limitations
o             Heterogeneity in the distribution of human resources and equipment
o             Sociocultural barriers
o             Lack of public health policies appropriate to the levels of prevention
 
Despite the growing number of advances in the diagnosis and treatment of LC, there are an estimated 2.2 million new cases and more than 2 million deaths each year worldwide, with an estimated 31,270 new cases and 27,000 deaths in Brazil.(1,2) Of the new cases in Brazil, only 15% are diagnosed in stage I, which is potentially curable(3); that translates to an overall five-year survival rate of less than 20%.
 
The clinical results in LC are directly related to the stage of cancer at the time of diagnosis. Screening and early detection significantly reduces the mortality associated with the disease. The impact can go beyond that, including lower public health expenditures, because the cost of treatment is lower for patients with early-stage LC than for those with advanced-stage LC.(4)
 
Screening is characterized by the application of tests in asymptomatic individuals, in a defined target population, with the aim of reducing the morbidity and mortality attributed to a specific disease.(5) The WHO classifies screening as one of two types:
 
1.            Opportunistic—Examinations are carried out on the basis of patient demand or are offered by the health care professional during a health care visit.
2.            Organized—The target population is invited and monitored at a defined frequency, within a quality program for examinations and following decision flow charts.
 
Screening for various cancers, such as prostate, skin, breast, uterine, and colorectal cancer, has been a reality for decades. Combining LCS with multidisciplinary management can also be cost-effective and is one of the best alternatives to minimize the consequences. However, it remains a major challenge in various countries, including high-income countries, where it is still limited in comparison with the screening for other neoplasms.
 
To diagnosis LC early and reduce mortality, a number of studies conducted in recent decades have evaluated LCS strategies. Initial protocols based on sputum smear cytology and chest X-ray proved to be innocuous.(6) Studies based on the Early Lung Cancer Action Project(7) and International Early Lung Cancer Action Project trials,(8) designated the ELCAP and IELCAP trials, respectively, have shown LDCT to be a method that is sensitive, safe, and feasible for early diagnosis. That was confirmed in 2011 by studies employing data from the National Lung Screening Trial (NLST),(9,10) which evaluated 53,454 high-risk volunteers, demonstrating a rate of positivity (positive nodule ≥ 4 mm) on LDCT of 39%, with confirmation of LC in 1% and a 20% reduction in cancer mortality.(9,10)
 
Some studies of LCS in Europe, with smaller sample sizes, did not show significant differences in LC mortality or overall mortality.(11-14) In Brazil, a prospective study, designated the First Brazilian Lung Cancer Screening Trial (BRELT1),(15) evaluated 790 volunteers with eligibility criteria similar to those of the NLST and showed the occurrence of positive findings to be 46% higher than in the NLST, with biopsies performed in 3.1% of the patients and cancer diagnosed in approximately 1.3%. The BRELT1(15) demonstrated that, despite there being a greater number of nodules > 4 mm, the prevalence of neoplasia was similar to that reported in the NLST.(9,10)
 
In 2020, the results of a study conducted in the Netherlands and Belgium, designated the NELSON trial (Registration no. NL580),(16) with a sample of 15,792 volunteers, showed a rate of positivity on LDCT (positive nodule: 500 mm3, approximately 10 mm) of 6.5%, and LC was confirmed in 2.1% of the cases evaluated. The NELSON trial also showed that, over a period of 10 years, there were reductions in the risk of death from cancer of 24% in men and more than 60% in women.(16)
 
A systematic review of data from 84,558 volunteers up to 2020, showed a 17% reduction in the risk of death from LC, albeit without evidence of a reduction in overall mortality.(17)
 
A more recent study, designated the BRELT2,(18) evaluated 3,470 individuals undergoing screening with LDCT at six different centers in Brazil. In that study sample, the prevalence of LC was 2.1%. It is noteworthy that, in 51% of those cases, LC was diagnosed at an early stage. The data confirm that, despite the obstacles, LCS is feasible in Brazil, with results similar to those reported for other countries.
 
Based on this evidence, international societies and expert panels began to recommend performing LCS with LDCT, although questions regarding feasibility, cost-effectiveness, and access still stand between the recommendations and the practical implementation of this strategy, especially in public health care systems. (19,20)
 
The use of LCS assumes that symptomatic disease is preceded by a period of presymptomatic disease detectable by LDCT. The interval of time between detection by screening and the time at which the neoplasm would be detected by the onset of its clinical manifestations is called the lead time (LT). According to most estimates, LT values for LC detection by LDCT range from 0.9 years to 3.5 years. Real-world studies that report mortality after LC diagnosis are subject to the so-called LT bias, although adjustments to the methods, aimed at minimizing that bias, have been proposed.(21)
 
A more adequate assessment of NLST data should also consider overdiagnosis and LT bias. The magnitude of overdiagnosis depends critically on the duration of follow-up after final screening.(21) In the NLST, the maximum follow-up period was initially 7 years but was later extended to 11.3 years.(9,10) After that extension, the overdiagnosis rate during the entire NLST period, originally predicted to be zero, was 3%. Using life expectancy gain instead of adjusting (for LT bias) for the expected number of lives saved overestimated the efficacy of life expectancy gain in the NLST by 38%.(21)
 
There are still a number of challenges to overcome before screening programs can be implemented in Brazil, such challenges including budgetary limitations, as well as the heterogeneous distribution of human resources and equipment in the public and private health care systems. In addition, cultural barriers, between patients and between physicians, indicate the need to construct health policies that encompass approaches aimed at each level of prevention.(22,23)
 
GENERAL CONSIDERATIONS ABOUT SMOKING
 
•             In Brazil, 9.3% of adults are smokers.
•             Smoking cessation increases the efficacy of screening programs.
•             Stopping smoking reduces the risk of complications and mortality from chronic diseases, including cancer, as well as increasing life expectancy and quality of life.
•             The foundations of smoking cessation are determination, behavioral support, and pharmacological treatment.
 
Smoking is the leading cause of chronic noncommunicable diseases and causes dozens of types of cancer, being responsible for more than 85% of all cases of LC.(24,25)
 
Tobacco can be consumed without combustion, by using snus or snuff, or with combustion and smoke inhalation, by using cigars, pipes, cigarettes, or hookahs. (26,27) In recent years, the use of electronic smoking devices (ESDs) has skyrocketed in many countries, including Brazil.(28-34) Although they release fewer substances harmful to health, new generations of ESDs release aerosols with greater amounts of nicotine, heavy metals, and fine particulate matter than do regular cigarettes, with cardiovascular and respiratory risks, as well as risks of cancer and death. (29,35) One recent study detected nearly 2,000 substances in ESDs,(36) and another showed that ESD users are at a three times greater risk of becoming smokers of regular cigarettes than are individuals who have never used an ESD.(37)
 
The proportion of individuals who consume tobacco products worldwide is trending downward for the first time in decades; it was 23.6% in 2020.(38) Tobacco control policies instituted in Brazil a few decades ago helped to substantially reduce tobacco consumption rates, according to the Telephone-based System for the Surveillance of Risk and Protective Factors for Chronic Diseases, from 35% in the 1980s to 9.3% in 2023.(34,39-41)
 
In 2015, cigarette smoking in Brazil resulted in the expenditure, in Brazilian reals (R$), of R$56.9 billion related to health care, disability, and deaths, whereas only R$12.9 billion were collected in the form of taxes on the manufacture and sale of tobacco products.(42)
 
Quitting smoking increases life expectancy, improves quality of life, and reduces the risks/complications associated with dozens of diseases, as well as reducing health care costs.(43,44) Smoking cessation also reduces LC mortality by a magnitude comparable to that of screening (20%), and the reduction is even greater (38%) when both strategies are implemented.(45) In addition, survival after surgical treatment for early-stage LC is better among patients who have quit smoking than among those who have not.(46) Therefore, it is essential to identify smokers and incorporate smoking cessation strategies into LCS protocols.
 
Quitting smoking is not an easy task, because of the combination of physical dependence, psychological dependence, and conditioning.(44,47-50) Smoking cessation treatment is based on the decisiveness/determination and motivation of the smoker, together with behavioral counseling and support (BCS) and the use of first-line medications.(43,44,47-50)
 
The foundations of BCS are the identification of situations that create a risk of relapse and the development of coping strategies through skills training. That support can be provided through a brief/minimal approach, in just a few minutes, by any and all health care professionals during routine care, and consists in interviewing, evaluating, and advising smokers in order to prepare them to quit smoking, comprising a basic approach, in which patients are monitored for the first few weeks after quitting smoking, and an intensive approach, in which at least seven sessions, each lasting at least 10 min, are held at specialized facilities.(43,44,47-50)
 
First-line medications are divided into two groups(43,44,48-50): nicotinic medications, collectively known as nicotine replacement therapy (NRT), including nicotine patches, gum, and lozenges; and non-nicotinic medications, including bupropion, antidepressants, and varenicline, the last being a nicotinic receptor inhibitor that is temporarily unavailable in several countries, including Brazil.
 
The success rate of treatment with bupropion is similar to that of NRT, and both have success rates lower than that achieved through treatment with varenicline. (51-54) The choice of medications is individualized, monotherapy is generally sufficient, and the usual duration of treatment is 3 months. Combining more than one medication can increase the success rate in patients who have greater difficulty in quitting smoking.(48-53,55) Recently issued guidelines recommend the use of varenicline or the combination of two NRTs as the first option to initiate treatment for patients with heart disease, lung disease, or cancer.(56-58)
 
Because ESDs are not medications for smoking cessation, first-line medications should be preferred,(55,59) and the majority of smokers who stop smoking by switching to an ESD continue to use ESDs, which perpetuates their dependence on nicotine and increases the health risks they face.(60)
 
In Brazil, intensive smoking cessation treatment can be provided via the Sistema Único de Saúde (SUS, Unified Health Care System), free of charge, at primary health care clinics in municipalities; via some supplementary health care networks; and via private physician offices and clinics.
 
BASIC ASPECTS AND EPIDEMIOLOGY OF LC
 
•             Smoking continues to be the main cause of LC.
•             LC is one of the most common and lethal types of tumor.
•             Only 15% of LCs are diagnosed at an early stage, when they are potentially curable.
 
For decades, smoking has been the most relevant risk factor for LC. Therefore, some of the most effective tobacco control measures are counseling to avoid taking up the habit of smoking, especially for young people, and advising current smokers to stop smoking as soon as possible.
 
There are two main types of LC: small-cell lung cancer and non-small-cell lung cancer (NSCLC). More than 80% of all cases of LC are NSCLC, which is divided into three subtypes(61): adenocarcinoma, squamous-cell carcinoma, and large-cell carcinoma.
 
A retrospective cohort study in Brazil showed a 30% decrease in the proportion of cases of small-cell lung cancer between the 1997-2002 and 2002-2008 periods.(62) Another nationwide epidemiological study involving more than 35,000 cases of NSCLC reported a change among the NSCLC subtypes in Brazil from 2003 onwards—adenocarcinomas accounting for 43.3% of cases and squamous-cell carcinomas accounting for 36.5%.(63)
 
Worldwide, LC is the leading cancer in men and the third leading cancer in women; in Brazil, it is the third leading cancer in men and the fourth leading cancer in women, with the exception of non-melanoma skin cancer.(64) In Brazil, 31,270 new cases of LC and approximately 27,000 LC-related deaths are recorded annually.(2) Only 15% of patients with LC are diagnosed at an early stage, when the disease is potentially curable, which translates to an overall five-year survival rate of less than 20% (Table 1).(62,65-72) Therefore, despite advances in diagnosis and staging—mainly in clinical treatment (targeted therapies and immunotherapy) and surgical treatment (video-assisted surgery and robotics)—the morbidity and mortality associated with LC remains high, as do its personal, family, public health, and supplementary health costs.


 
One of the reasons for a tumor being diagnosed at an advanced stage is the delay in diagnostic procedures via the SUS, such as CT and PET/CT, which are difficult to access in some regions of Brazil.(61)
 
In 2006, Barros et al.(69) reported that only 20% of patients with suspected LC had access to diagnostic CT. Nearly 90% of the patients in their cohort were diagnosed by chest X-ray.(69) Another study conducted in Brazil estimated that the median time from the onset of symptoms to diagnosis is 3 months.(73) That situation becomes even more complicated because few public health care facilities provide diagnostic procedures such as bronchoscopy and transthoracic biopsy.(61) The implementation of screening programs in the SUS will facilitate the development of regional LC diagnostic services in Brazil.
 
SCREENING ELIGIBILITY CRITERIA
 
•             Eligibility criteria
o             Being a smokers/former smoker, being ≥ 50 years of age, and having a smoking history > 20 pack-years
•             Exclusion criteria
o             Being > 80 years age
o             Having quit smoking > 15 years prior
o             Having symptoms suggestive of or a history of LC
o             Having a functional status or comorbidity that precludes curative treatment
 
The most important benefit of LCS is the increase in the number of cases diagnosed at an early stage (stage I or II) and the consequent reduction in that of those diagnosed at an advanced stage (stage III or IV).(74)
Studies using NLST data have demonstrated that LC-related mortality, in three annual rounds, was significantly lower when LCS employed LDCT than when it employed chest X-ray.(9,10) The incidence rate was 0.85, and the number needed to screen (NNS) to prevent one death was 323 over 6.5 years of follow-up.(10) Another study demonstrated a reduction in LC-related mortality in four rounds of follow-up, with an incidence rate of 0.75, and the NNS to prevent one death was 130 over 10 years of follow-up.(75)
 
Although there are variations in the inclusion criteria for LCS, the main international recommendations are based on the two largest trials (the NLST and the NELSON trial),(7,9,14-16,76-82) as detailed in Table 2.


 
On the basis of previous studies and microsimulation models, the U.S. Preventive Services Task Force (USPSTF) established, in 2013, guidelines for “real life” screening in the United States,(74,75) with the following inclusion criteria: being 55-74 years of age; having a smoking history of at least 30 pack-years; and having quit smoking less than 15 years prior.
 
At that time, the USPSTF guidelines did not take into account interracial differences in smoking patterns and LC risk, as had previously been demonstrated.(83,84) A few years after the screening program had been implemented in real-life scenarios (outside of clinical studies), it became obvious that there was a need to take such differences into account.
 
Aldrich et al.(85) found that the proportion of individuals diagnosed with LC who would not have been eligible for screening in the United States was higher among African-American smokers than among White smokers. That is because African-Americans typically develop LC with a smoking history of less than 30 pack-years and before 55 years of age. Therefore, it has been suggested that the smoking history criterion be reduced to 20 pack-years and that the age criterion be reduced to 50 years. Those new criteria were promptly adopted by the USPSTF and the National Comprehensive Cancer Network.(86,87)
 
Given such evidence, this panel of experts recommends that the inclusion criteria for LDCT screening consist of the following:
•             Being a smoker or former smoker, ≥ 50 years of age
•             Having a smoking history of more than 20 pack-years or having quit smoking less than 15 years prior
 
Screening should be discontinued when the volunteer is over 80 years of age or has been smoke-free for more than 15 years.
 
The exclusion criteria for screening are as follows(85-87):
 
•             The presence of symptoms highly suggestive of LC
•             A history of LC
•             Functional status or comorbidity that would prevent treatment with curative intent, given that the patient must be fit to undergo lung resection
 
It is recommended that the decision to start the screening program be shared between the individual and the multidisciplinary team, and that all smokers be encouraged to participate in BCS programs to quit smoking. That should permeate all consultations; it should be borne in mind that screening is not a substitute for smoking cessation.
 
The greatest challenge is still establishing the definition of a high-risk patient and, therefore, determining the inclusion criteria so that annual screening is even more cost-effective. In brief, it is necessary to improve the criteria for selecting asymptomatic individuals exposed to the main risk factors for LC, given that the relative risk of developing the disease increases in parallel with advancing age.
 
It is worth highlighting, however, that the recommendations above were based on population-level data from other countries. There is a need for studies on the appropriateness of these positivity criteria for use in the population of Brazil.
 
The criteria for indicating LCS are summarized in Figure 1.


 
INCIDENTAL FINDINGS ON LDCT AND THEIR IMPLICATIONS
 
•             Incidental findings on LDCT that are unrelated to LC are mostly irrelevant.
•             When the incidental findings are relevant and interpreted correctly, they can improve the cost-effectiveness of the examination, as well as the quality of life and life expectancy of those screened.
Incidental findings (IFs) are those that are unrelated to LC but can be identified on screening with LDCT (Chart 1). Most IFs are clinically insignificant and do not need to be reported, others require referral to specialists and further evaluation, and some require immediate medical intervention.(88,89)

 
Relevant findings, when interpreted correctly, can increase the benefits and cost-effectiveness of screening. However, findings without clinical significance identified through screening programs can lead to unnecessary investigations and additional costs.(90-92)
 
The prevalence of IFs in the chest or adjacent regions (the neck and abdomen) differs significantly between screening programs, with rates ranging from 41% to 94%, and their incidence is higher in the first LDCT. In the NLST, the IFs most commonly identified were related to the cardiovascular system (8.5%), followed by the kidneys (2.4%), liver/biliary tract (2.1%), adrenal glands (1.2%), and thyroid (0.6%).(93)
 
Among the cases in which there are IFs, additional investigation, including the use of other imaging methods, is required in 9-15%.(90) Of all of the deaths in the LDCT arm of the NLST, 10% were due to diseases other than LC.(10)
 
In the NLST, overall mortality was 6.7% lower in the group undergoing LDCT.(10) Therefore, it is possible that there is an advantage to LDCT in that it can identify other diseases, such as cardiovascular diseases (coronary arteriosclerosis, aortic aneurysm, pericardial thickening, and calcifications), COPD (emphysema and thickening of bronchial walls), and other diseases related or unrelated to smoking (e.g., interstitial lung lesions, sarcopenia, osteopenia, diaphragmatic hernias, neck cancer, and tracheal neoplasia).(88,94) The main IFs are described in Table 2.(91,92,94)
 
CHANGES CONSISTENT WITH GRANULOMATOUS LESIONS
 
•             The high prevalence of granulomatous diseases in Brazil is a challenge for the implementation and cost-effectiveness of LCS in the country.
•             The need for adjustments to the nodule management algorithms for use in the population of Brazil should be taken into consideration.
•             Algorithm-based assessment and multidisciplinary management can reduce the rates of positivity, false-positives, and unnecessary procedures, as well as bringing our rates of invasive procedures closer to those reported for high-income countries.
 
Chief among the various challenges for implementing LCS programs in low- and middle-income countries is the high prevalence of granulomatous diseases, which could increase the proportion of false-positive results, consequently increasing the number of diagnostic/surgical procedures and associated complications. (15,22,95,96) In recent data, the incidence of tuberculosis in Brazil was 45 cases/100,000 population, significantly higher than the 2 cases/100,000 population reported for the United States.(97)
 
In a study of LCS conducted in South Korea—the Korean Lung Cancer Screening Project (K-LUCAS), which used the Lung CT Screening Reporting and Data System (Lung-RADS) version 1.0—the proportion of positive results was higher among the patients with evidence of tuberculosis sequelae than among those without (21% vs. 16%) and a reported history of tuberculosis was associated with a positive screening result.(96) The authors also reported that the specificity and accuracy of LCS were lower for patients with tuberculosis sequelae than for those without (80% for both vs. 85% for both, respectively), indicating that false-positive results are associated with a history of infection. In addition, they detected no association between tuberculosis sequelae and a diagnosis of neoplasia at screening.(96)
 
In the first round of screening in the BRELT1, the positivity rate was 39.5%, significantly higher than that reported for other screening programs.(15) Although the biopsy rate in the BRELT1 (3.1%) was comparable to those of the largest screening studies, it is still difficult to extrapolate these results to Brazil as a whole because of the great epidemiological heterogeneity in the country.(98)
 
To implement LCS with LDCT in Brazil, it is possible that adjustments in nodule management are needed in order to reduce the rates of positive and false-positive results, thereby reducing the number of unnecessary procedures.
 
In the BRELT2,(18) which involved more than 3,000 patients from various regions of Brazil, the patients in whom the findings were characteristic of residual granulomatous inflammation, findings classified as Lung-RADS category 3 or 4, were followed clinically. That same trend of clinical follow-up was observed in the K-LUCAS protocol.(18,96) The authors of that study proposed a separate category to indicate lesions with a benign appearance that were classified as Lung-RADS category 3 or 4, considering a downgrade in the classification of these lesions from the baseline examinations. For example, noncalcified nodules measuring at least 8 mm, adjacent to scarring/calcified nodules, are to be reclassified to a new category—category 2b (b = benign). For category 2b, follow-up examinations would be still be annual, rather than every 3 months.(96) Given that the epidemiological situation of granulomatous diseases in Brazil is closer to that seen in South Korea than to that seen in high-income countries, a national screening program in Brazil could benefit from that adjustment.
 
DO PROBABILISTIC MODELS REDUCE THE NUMBER OF FALSE POSITIVES?
 
•             Yes, prediction models can improve clinical interventions, population care development and resource optimization
•             However, it is necessary to validate such models for use in heterogeneous populations and to define the cutoff score for practices related to the cancer risk.
 
The success of every LCS program is directly related to the assessment of the risk group, which can be complemented with prediction models. Prediction models can improve clinical interventions and the development of care for the population, as well as being ancillary tools for optimizing resources.
 
After the publication of the study conducted by Bach et al.,(99) research into risk prediction models for LC intensified.(100) Such probabilistic models, which were based on traditional variables, biomarkers, LDCT, and data exploration techniques, currently have good sensitivity and specificity. The most commonly used traditional variables are smoking intensity, occupational exposure to asbestos, the presence of emphysema, COPD, or pneumonia, and a family history of LC.(101)
 
The 2012 Prostatic, Lung, Colorectal and Ovarian Cancer Screening Model (PLCOm2012) was developed in smokers in the control arm of the PLCO study.(102) In comparison with the USPSTF criteria, the PLCOm2012 criteria include more personal factors (e.g., history of malignancy), a more detailed smoking history, family history, and the personal history of COPD.
 
The Lung Cancer Risk Assessment Tool risk model and Lung Cancer Death Risk Assessment Tool risk model were developed and validated in the control and chest X-ray arms of the PLCO study, respectively.(103,104)
 
Other LC risk models include the Kovalchik model, the Bach model, the Liverpool Lung Project model (and its simplified version), the Knoke model, the Hunt Lung Cancer model, and three two-stage clonal expansion models that predict the incidence of and death from LC.(105,106) Such models have included a variety of additional risk factors,(105,106) such as smoking intensity (cigarettes per day); occupational exposure to asbestos; emphysema, COPD, and pneumonia; and family history of LC.
 
The results are estimated by applying each risk model to previous cohorts, which serves as external validation. However, there is currently no consensus regarding the cutoff point that should be applied to LCS prediction models. In other words, the percentage of risk on which the recommendation for LCS should be based has not been defined.
 
In a systematic review of three different risk prediction models (a modified version of the PLCOm2012, the Lung Cancer Death Risk Assessment Tool model, and the Kovalchik model), estimation of outcomes in four different cohorts showed greater prevention of mortality in comparison with the risk factor-based criteria used by the NLST or USPSTF (2013 recommendations).(107)
 


Three of those studies demonstrated that screening efficiency (determined by the NNS) was better when screening employed risk prediction models than when risk factor-based screening was used, whereas one study showed mixed results.(108)
 
A recent study of LCS in Brazil demonstrated that the yield of LDCT screening is lower in low-risk individuals than in high-risk individuals, the rates of positivity and LC detection being significantly lower in the former.(109) Therefore, screening low-risk patients could increase the number of LDCT examinations because of the lower diagnostic yield, resulting in increased costs compared with screening only the high-risk population. However, incorporating the PLCOm2012 with a 6-year LC risk ≥ 0.0151 as the eligibility criterion appears to increase the efficacy of LCS.(109) In that same study, the false-positive rate for the PLCOm2012 criteria was lower than was that for the NLST criteria, indicating a possible improvement in screening efficiency, even in a country with a high incidence of granulomatous diseases like Brazil.(109)
 
In general, the LC risk models are highly accurate, indicating that their use is viable for identifying high-risk populations. However, the model development process and the reports generated from the models are still not ideal, because they present a high risk of bias, which limits their credibility and predictive accuracy, thus hindering their promotion and development.
MINIMUM REQUIREMENTS FOR LDCT
 
•             Slice thickness ≤ 2.5 mm, preferably ≤ 1.0 mm
•             Gantry rotation time of ≤ 500 ms
•             Chest scanning time < 10 s
•             Tube voltage of 100-120 kVp (for standard-sized patients)
•             Tube current (mAs) preferably automatically modulated by the CT device
•             Volumetric dose index of 3 mGy—effective radiation dose ≤ 1 mSv (for standard-sized patients)—the maximum radiation dose established for screening
 
Fundamental technical parameters for LCS using LDCT have been recommended by major international societies, especially the American College of Radiology (ACR) and the Society of Thoracic Radiology.(110)
 
The LDCT images should be acquired in scanners with at least 16 detector rows, with the helical technique and without intravenous administration of iodinated contrast. Obviously, the scan must cover the entire lungs, and it is extremely important that the patient performs a deep inspiration and adequate breath-hold, in order to guarantee the quality of the images, avoiding artifacts that could hinder the analysis of the examination.(110)
 
The slice thickness should be ≤ 2.5 mm, preferably ≤ 1.0 mm, and the gantry rotation time should be ≤ 500 ms. A chest scanning time of < 10 s is recommended.
 
For standard-sized patients (height, 170 cm; weight, 70 kg), the tube voltage should be set to 100-120 kVp, and the tube current (mAs), although it can be fixed, should preferably be modulated automatically by the CT scanner, which takes into account the physical characteristics of the patient, the tube voltage, and the table pitch (typically 0.7-1.5).
 
The maximum radiation dose established for LCS using LDCT corresponds to a volumetric dose index of 3 mGy—effective radiation dose ≤1 mSv—for a standard-sized patient, with appropriate dose reductions and increases for smaller and larger patients, respectively,(111) always following the premise that tomography should be performed with the lowest possible dose of radiation that guarantees a good quality diagnostic examination.
 
Suggested protocols for performing LDCT on a variety of devices from major manufacturers are available on the website maintained by the American Association of Physicists in Medicine.(74,75)
 
It is noteworthy that, in the wake of constant and important technological advances in the area, the most modern CT scanners currently available have features such as iterative reconstruction and deep learning, making it possible to obtain images of better quality (with less noise), even with greatly reduced radiation doses.
 
The radiation dose employed in LDCT is equivalent to approximately one-fifth of that of a “standard-dose” chest CT, and one-quarter of the average background radiation to which a person is exposed over the course of a year in the United States. The risk of radiation-induced malignancies in patients undergoing LCS with LDCT is considered low; greater attention should be paid to other risks such as false-positive results, overdiagnosis, and IFs without clinical relevance, which can prompt unnecessary additional interventions and generate anxiety in patients.(112)
 
After the examination has been performed, at least two image volumes should be reconstructed: one with a “standard” filter for evaluating soft tissues (including, for example, mediastinal structures); and another with a “lung” filter, which provides greater “spatial” (i.e., anatomical) resolution for evaluating the lung parenchyma, as well as for measuring and analyzing the contours of any nodules detected. Maximum intensity projections and multiplanar (coronal and sagittal) reconstructions are recommended for the detection and characterization of nodules, respectively.(113)
 
NODULE POSITIVITY CRITERIA: TWO-DIMENSIONAL MEASUREMENT VS. VOLUMETRY
 
•             Potential gains when using volumetric measurement:
o             Greater reproducibility of measurements
o             Three-dimensional assessment of nodules
o             Increased sensitivity for assessing nodule growth
 
•             Potential challenges when using volumetric measurement:
o             Difficulties in segmenting nodules adjacent to other lung structures
o             Difficulty in the assessment of subsolid nodules
o             Differences between measurements determined by different software
o             Variations according to CT reconstruction protocol
o             Issues related to equity in the availability of software throughout Brazil
 
Although several aspects, such as attenuation, shape, and location, should be considered when evaluating pulmonary nodules; size and growth are assumed to be the most important variables in estimating the probability of malignancy.(114) Regarding those two parameters, there are variations in nodule management algorithms in the screening protocols proposed to date, which differ in terms of positivity criteria and growth indicators. Therefore, the choice between linear measurements and volumetry is a sensitive point. For example, the NLST (conducted in the United States), as well as the BRELT1 and BRELT2 (both conducted in Brazil), used linear measurements in the assessment of solid nodules, whereas the NELSON trial primarily used volumetry, as have other European screening algorithms.(9,10,15,16,18)
 
The management protocol first suggested by the ACR—Lung-RADS, version 1.1—used linear measurements (specifically, calculating the mean nodule diameter to the first decimal place); however, volumetric notation was included as a possibility (ACR Lung-RADS 2019), a feature that was maintained in the latest version (ACR Lung-RADS 2022).(115,116)
 
The NELSON trial defined nodule growth as a 25% increase in the volume of a solid nodule or the solid component of a subsolid nodule, with subsequent stratification based on the volume doubling time (VDT), whereas the Lung-RADS defined it as an increase of 1.5 mm in the mean diameter or of 2 mm3 in volume. (16,115-117)
 
The potential gains achieved by using volumetry rather than linear measurements include greater reproducibility of measurements, three-dimensional assessment of nodules, and increased sensitivity for assessing nodule growth, allowing, for example, the calculation of VDT, which would be a better parameter for determining their behavior.(118)
 
The use of linear measurements to measure solid nodules is associated with significant intraobserver and interobserver variability. In a study conducted by Revel et al.,(119) changes in size < 1.7 mm had only a 5% chance of representing a real change in the size of the nodules, an aspect that could have an impact not only on the categorization of nodules and the positivity rate but also on the definition of their growth.
 
In a study evaluating the categorization of solid nodules within the Lung-RADS criteria, interobserver agreement on the dimensions of nodules was found to be better when automated volumetric assessment was used than when automated or manual diameter measurement was used, and automated volumetric assessment was found to result in some nodules being reclassified to lower categories.(120)
 
Lung nodule volume is determined through semi-automated or automated analysis with specific software based on segmentation. It should be borne in mind that calculating the volume of nodules directly from their diameters leads to a significant overestimation of that volume. Heuvelmans et al.(121) showed that calculating the volume of nodules directly from their diameters (thus assuming sphericity) overestimated that volume, in comparison with semi-automated volume analysis, by approximately 47.2% when the mean diameter was used and by 85.1% when the maximum diameter was used.
 
Although there are advantages to the use of volumetry, it poses many challenges in clinical practice, including the following(118): difficulties in segmenting nodules that are adjacent to other lung structures (e.g., pleural and vascular interfaces); difficulty in the evaluation of subsolid nodules; differences between measurements determined by the various types of software and the versions thereof; variations according to the CT reconstruction protocol (slice thickness, overlapping images, and different reconstruction algorithms); and, as one can imagine, issues related to equity in the availability of software throughout Brazil. Regarding variations in the measurements of nodule volume when different software is used, Zhao et al.,(122) for example, compared the performance of software from three different manufacturers, finding variations of up to 50% when comparing the measurements acquired.
 
Given the potential and challenges of volumetry, it would be acceptable for screening programs based on nodule diameter measurements to consider including a volume equivalent in their management algorithms.(91)
 
RISKS ASSOCIATED WITH LCS
 
•             Radiation exposure—relatively low risk with LDCT
•             Patient anxiety, unnecessary examinations/interventions, and poorer quality of life, due to the following:
o             False-positive results
o             Overdiagnosis
o             Irrelevant IFs
o             Incorrect decisions
 
Note: In relation to education and appropriate guidance on LCS, these risks can be minimized through the work of the multidisciplinary team and shared practice.
 
Prospective participants in an LCS program should be informed, through various means of communication but especially through a detailed explanation from their physician, about the benefits and potential risks of their participation.
 
Participation should be well documented, and written informed consent should be obtained before any procedure is performed. The authorization granted should extend to planned visits to carry out LDCT at regular intervals, as well as to the use of data, including the description of health status, test results, and reports of adverse effects, in subsequent studies.(123)
 
The following are the main risks related to LCS with LDCT:
 
Radiation exposure—Irradiation associated with one LDCT scan ranges from 0.65 mSv to 2.36 mSv, and the cumulative exposure over 25 years of annual screening would be 20.8-32.5 mSv. For example, the mean irradiation during a PET/CT scan is 4 mSv. To date, there have been no studies estimating the overall risk of cancer in general or of fatal cancer induced by irradiation in annual screening up to 80 years of age.(74,75)
 
False-positive results—Any result that leads to additional investigation and which does not result in a diagnosis of cancer is considered a false-positive. The false-positive rate depends on a series of confounding factors, such as the nodule size considered positive, the use of VDT, and the characteristics of the nodule to be considered in each study. In cohort studies, the reported proportion of false positives ranges from 9.6% to 49.3% at baseline (prevalent round), and that rate decreases with each additional round of screening (incident rounds), with a variation of 5.0-28.6%.(74,75) The false-positive rate in the baseline examination has been shown to be lower when a structured CT reading instrument with the Lung-RADS method is used than when the NSLT reading method is used (12.8% vs. 26.0%).(124)
 
The worst harm caused by a false-positive result is that it creates a need for diagnostic clarification, with or without invasive procedures.(74,75)
 
In a study involving 3,280 patients selected for LCS, 342 (10%) had category 4 findings according to the Lung-RADS reading. Of those, 100 (approximately 30%) were found to have LC, the vast majority diagnosed at an early stage, when the disease is potentially curable. That represents a 3% yield, and only 15 patients (0.45%) underwent some type of surgical procedure in which the result did not confirm cancer, with practically no morbidity and zero mortality.(125)
 
•             Overdiagnosis—Overdiagnosis can be defined as the detection of cancer that would not have become clinically significant during the lifetime of the patient. The overdiagnosis rate ranges from 0% to 67%.(74,75) In a meta-analysis, it was observed that there is a significant increase in overdiagnosis during the follow-up period.(126)
•             Psychological risk—Although participating in LDCT screening has not been found to worsen quality of life or anxiety over 2 years of follow-up, a significant increase in distress and anguish has been observed, especially in cases with indeterminate results.(127,128) The understanding that an early-stage cancer could be discovered during screening has served to overcome fears of undergoing an unnecessary procedure.(74,75,127,128)
•             IFs—The rate of IFs varies greatly, depending on the definition of what is considered an IF and on the mean age of the study participants.(74,75,129) Although the detection of some IFs can cause distress, it can improve the diagnosis and early management of potentially serious diseases.
 
The risks of LCS are relatively low and can be reduced with a quality diagnostic assessment, practices based on valid algorithms, and the involvement of a multidisciplinary team.
 
MINIMUM STRUCTURE AND THE ROLE OF A MULTIDISCIPLINARY TEAM
 
•             Screening centers
o             Multidisciplinary team for recruiting, as well as for the acquisition and interpretation of radiological images, with the ability to carry out the differential diagnosis in cases with positive results and appropriate treatment in cases of cancer
•             Minimal structure
o             Access to a smoking cessation program
o             Radiology clinic with LDCT (low voltage, 16 channels)
o             Specialized team and standardized (Lung-RADS) description in reports
o             Access to PET/CT for diagnosis and preoperative staging
o             Interventional radiology and bronchoscopy to perform biopsies
o             Surgical center with the capability to perform thoracotomy and video-assisted surgery
o             Structure for patient navigation
 
An LCS program is established on a population basis and therefore requires an articulated organizational structure to reconcile two important aspects:
 
•             It should be offered in the form of a large cohort with universal distribution, and there should therefore be centers that are close to the places of residence of the participants.
•             There should be local or regional screening centers with multidisciplinary teams for recruiting, as well as for the acquisition and interpretation of radiological images, with the ability to carry out the differential diagnosis in cases with positive results and to provide appropriate treatment in cases of cancer.(123)
 
It is known that the cost-effectiveness of LCS increases when it is applied in conjunction with a smoking cessation program, and a program structured for that purpose should therefore be part of the minimum structure.(130,131)
 
Local and regional centers must be certified, authorized, and accredited by a national organization. The minimum structure for an LCS center should include a radiology clinic with a 16-channel CT scanner (although it is possible with a 4-channel CT scanner, as was used in the NSLT), whenever possible with a computerized program for volumetric reading of the lesion, the ability to describe the results in a standardized way using the Lung-RADS system, and a quality control sector. The centers should have access to PET/CT for diagnostic follow-up of suspicious nodules and preoperative staging.
 
Another crucial point is the capacity to perform biopsy, which can be guided by CT, or another minimally invasive surgical procedure, preferably with preoperative markup in the case of lesions that are invisible or nonpalpable. Although an interventional pulmonology clinic with endobronchial bronchoscopy is desirable, the economic conditions of each center must be taken into account so as not to make the program unfeasible. The surgical center should be structured to allow thoracotomy and video-assisted thoracoscopic surgery to be performed.
 
Finally, the LCS center should have a professional structure to help patients navigate the program, guiding them through invasive investigation and periodic examinations of the lesions identified or referring them to the smoking cessation program.
 
The administrative structure of each center should have the capacity to record all data and results in order to store and report all information to the national screening center. Of equal importance is sector planning to promote continued training for the entire team.(132,133)
 
Interaction between the primary care clinician and the thoracic surgeon, pulmonologist, or both, as well as between them and the radiologist, pathologist, oncologist, and radiotherapist, is of fundamental importance for the success of the screening program. No less important is the participation of the nursing and social assistance sectors.
 
All of the professionals should be subject to regional or central administrative medical authority that is responsible for communication at different levels and a referral and counter-referral system, as well as for storing data and images to be consulted over time.(22,123) Test results should be communicated to participants in written form and orally, the impact of the result being weighed for each individual.(132) Everyone on the multidisciplinary team should have a clear understanding of their role, be familiar with the brief guidelines on smoking cessation, and know how to recommend facilities for intensive treatment.(134,135)
 
At LCS centers, decisions should be made jointly and should be based on the six pillars of quality health care, which are safety, effectiveness, efficiency, timeliness, equity, and patient-centeredness. Adherence to LCS is not high and could be improved through clear discussion about the advantages and potential risks of screening and not screening.(136) In addition, continuity of care must be guaranteed when a participant moves from one setting to another, and information about their goals, beliefs, and values, as well as their current clinical status, should always be reported in order to avoid misunderstandings.(134)
 
Ensuring the benefits of an LCS program requires an organized structure, trained staff, and appropriate equipment, concentrated at LCS centers.(123)
 
POST-LDCT MANAGEMENT ALGORITHM—LUNG-RADS
 
In 2014, the ACR developed the Lung-RADS, which was modeled on the success of its Breast Imaging Reporting and Data System.(116)
 
The Lung-RADS allows uniform reporting and management of abnormal findings on LDCT examinations in LCS and aims to facilitate successful implementation in radiology practice outside the scope of clinical trials.(116) The Lung-RADS is also an essential part of quality assurance and screening log reports. The latest Lung-RADS version, released by the ACR in 2022, was based on evidence collected in previous years,(116) as detailed in Tables 3 and 4.
 
The Lung-RADS Committee is made up of 8 of the most prominent experts in the field, who carry out studies of the existing literature and publish periodic updates. We believe that using the Lung-RADS recommendations is the way to make the most accurate decisions after LDCT in an LCS program.
 
COST-BENEFIT ANALYSIS OF SCREENING
 
LCS with LDCT is probably cost-effective, and its cost-benefit ratio, despite involving multiple factors, also tends to be adequate.
 
Cost-benefit analysis is one of the most important aspects of public health policies. When evaluating screening, for benign and malignant diseases alike, it is necessary to demonstrate its advantages in relation to its costs, especially for the funding sources.(137)
 
In relation to LCS, it is expected that there will be a high number of LDCT examinations for each patient diagnosed and treated, which increases the overall cost of the program. Cost-effectiveness, as well as the benefit of reducing mortality and increasing early diagnosis, should be clearly demonstrated.(137-139)
 
It is also necessary to understand the difference between a cost-effectiveness analysis, which considers the cost of the program only for the examination and the determined outcome, and a cost-benefit analysis, which also takes into account other benefits, such as smoking cessation.(137,138)
 
The cost-effectiveness analysis model that comes closest to reality is the MIcrosimulation SCreening Analysis-Lung (MISCAN-Lung), which uses a semi-Markov model to simulate the appearance of neoplasms at the population scale.(139) A study conducted in Canada showed that, according to the MISCAN-Lung model, LCS is cost-effective for high-risk populations and that the cost decreases as smoking history in pack-years increases, although the number of life-years gained does not increase.(139)
 
To analyze the cost-benefit of screening, the cost-effectiveness relationship was initially assessed in a systematic review that included 45 studies and employed a Patients of interest, Intervention to be studied, Comparison of interventions, and Outcome of interest (PICO) type of strategy, as follows(140): patients/population of interest—smokers (or former smokers) between 55 and 79 years of age with a smoking history > 20 pack-years; intervention—LDCT; comparison—chest X-ray or no screening; and outcome of interest—cost-effectiveness of screening with LDCT.
 
In that study,(140) it was clear that annual screening with LDCT is cost-effective for the desired population, and the cost-effectiveness ratio is even greater for biennial screening, although the roles of risk prediction models and smoking cessation interventions were unclear.
 
Another systematic review corroborated the cost-effectiveness findings and suggested that such screening programs should be implemented even in situations of limited financial resources and even if LDCT has to be performed at a lower (biennial) frequency. (141) However, that review does not necessarily reflect the reality in Brazil.
 
A study carried out in China, an upper-middle-income country with a high prevalence of granulomatous diseases and whose indicators are comparable to those of in Brazil, showed, using the Markov model, that screening with LDCT for patients over 60 years of age cost US$113.88 million but was cost-effective, reducing LC-related deaths by 16.1%.(142)




 
To arrive at the cost-benefit ratio based on cost-effectiveness, we should consider, in addition to the cost-effectiveness ratio of LDCT in relation to LC-related mortality, the following aspects(4,137,143,144):
 
1.            Treating early-stage disease is potentially less costly than is treating advanced-stage disease and has better outcomes. Screening will likely increase the number of individuals diagnosed at an early stage.
2.            Screening ends up changing the staging of LC that would be diagnosed late, as observed in the IELCAP study.(144)
3.            There are costs associated with ancillary tests, such as biopsies.
4.            The treated patient, even if still asymptomatic, tends to return to work more quickly, thus reducing the socioeconomic impact of the disease.
5.            There is an increase in the number of hospitalizations due to factors associated with advanced-stage disease, such as dyspnea, thromboembolism, and intractable pain, which increases costs.
6.            The screening program should be associated with the smoking history, which in itself leads to the prevention of other diseases and therefore to a cost reduction.
7.            The cost of LDCT is low (approximately US$250 in the United States in 2023), and its availability has increased, even in low- and middle-income countries.
8.            LDCT examinations end up diagnosing diseases other than LC, which can be treated in a timely manner. Their diagnosis and treatment increase the program costs but tend to reduce overall nonspecific mortality.
9.           
The analysis considering such factors is complex, and no predictive model can accurately estimate the costs. There are estimates for the United States, although with divergent values, depending on health insurance and other factors.(137) Nevertheless, there is agreement on the possibility of a good cost-benefit ratio for the at-risk population.(145) Although there is a lack of data on cost-effectiveness and cost-benefit in Brazil, it is possible to assume, by interpreting the results of international studies, that LCS will produce similar results in the country.
 
After that analysis, it can be concluded that LCS with LDCT is probably cost-effective, and its cost-benefit ratio, despite involving multiple factors, also tends to be adequate. Although data from Brazil are needed in order to validate these models, this is an open field that is of great interest, especially to patients who would benefit from early diagnosis and treatment, with reduced mortality.
 
SCREENING PERSPECTIVES (NEW MARKERS)
 
•             New markers are promising, although their efficacy is still under evaluation and their costs are high.
•             The use of molecular or protein-based tumor biomarkers, bronchoscopy with autofluorescence, DNA methylation, exhaled breath, circulating free DNA, microRNA, metabolomics, and the combination of images (deep learning) with biomarkers are being studied.
 
In recent years, new LCS modalities have been investigated. The main unmet clinical needs are risk refinement to improve the selection of individuals undergoing screening and the characterization of indeterminate nodules found during LDCT-based screening.
 
In the NLST, blood, urine, and sputum samples from more than 10,000 participants were stored for later analysis.(146,147) However, there are as yet no molecular or protein-based tumor biomarkers that can be used efficiently and implemented reliably in a screening program.(92)
 
Autofluorescence bronchoscopy has greater sensitivity for detecting precancerous lesions of the bronchial mucosa than does conventional bronchoscopy. However, the results of most previous studies do not support its use as an LCS tool.(148)
 
Some studies have pointed to DNA methylation as one of the key factors in the progression of LC. Recent studies have been performed on tumor tissue; findings in blood and other samples showed lower sensitivity and specificity.(149) Another study found that, for five of the six genes evaluated (SOX17, TAC1, HOXA7, CDO1, HOXA9, and ZFP42), DNA methylation in plasma and sputum was more common in patients with LC than in control patients (p < 0.001).(150)
 
It is possible to detect volatile fragments of cells and DNA in exhaled breath condensate. Some studies have suggested that this matrix can be used in order to differentiate between benign and malignant nodules, as well as to predict the treatment response and recurrence. Studies for training in and validation of the use of a portable electronic nose for LCS have found it to have a diagnostic accuracy of 83%. These findings suggest that exhaled breath is a valid marker of LC and could be useful for triage.(151,152)
 
Circulating free DNA appears to be more suitable for identifying mutations in the driver gene in patients with known neoplasia than for making an early diagnosis. Initial studies have shown that it does not predict the risk of LC but does predict perioperative survival. However, a retrospective analysis of microRNAs showed their potential to increase the specificity of LDCT, with a notable (five-time) reduction in the false-positive rate.(153) In combination with LDCT findings, microRNA can help stratify the risk of LC. That risk stratification is now being tested prospectively in a screening trial involving more than 4,000 people.(154,155)
 
Changes in LC metabolites (metabolomics: changes in glycolysis, citric acid cycle, amino acid metabolism, and cell membrane synthesis) provide a direct functional reading of phenotypic changes associated with the development of lung tumors and can help differentiate between histological subtypes or target mutations.(156)
 
Combining image-based deep learning with biomarkers can be an effective means of characterizing lung nodules. Radiomics analysis is capable of identifying EGFR and KRAS mutations, as well as of predicting survival. Some studies have shown that integrating biomarkers and radiological characteristics is a good method for predicting LC. The use of integrated models has been shown to be superior to that of serum biomarkers in isolation and represents a quite promising approach for the future of early LC detection, especially if artificial intelligence is incorporated.(147)
 
The scientific community is also awaiting the results of the Circulating Cell-Free Genome Atlas study for the early detection of cancer. In that study, plasma samples collected during a 5-year follow-up period will be analyzed by whole genome sequencing and integrated with patient clinical information.(157,158)
 
All of these tools could be of great importance for the future of screening. However, the high cost of developing and implementing them could hinder their incorporation into clinical practice in population-based health care.
 
FINAL CONSIDERATIONS
 
Early detection of LC is essential for improving clinical outcomes. The approach to the vulnerable population, especially smokers, should be carried out in a multidisciplinary manner, with the help and participation of public authorities, community health agents, family members, and patient support organizations.
 
In this document, experts from three of the main medical societies dedicated to the treatment of chest diseases (the SBPT, SBCT, and CBR) came together to form the study group, aiming to formulate the first LCS recommendations for Brazil, and this is a first step toward discussions on the topic, which is of great importance.
 
In Figure 2, we present an infographic summarizing the main points of these recommendations.


 
ACKNOWLEDGMENTS
 
The authors would like to thank the Grupo Brasileiro de Oncologia Torácica (GBOT, Brazilian Thoracic Oncology Group) for their contribution.
 
AUTHOR CONTRIBUTIONS
 
All of the authors participated in one or more phases of the drafting of this consensus: 1) study conception and planning, as well as interpretation of evidence; 2) drafting and revision of the preliminary and final versions of the manuscript; and 3) approval of the final version of the manuscript. The final version was prepared by LFFP, RSS, DOB, and JF, after agreement by all members of the working group.
 
CONFLICTS OF INTEREST
 
None declared.
 
REFERENCES
 
1.            Global Burden of Disease 2019 Cancer Collaboration; Kocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, et al. Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019. JAMA Oncol. 2022;8(3):420-444. https://doi.org/10.1001/jamaoncol.2021.6987
2.            Santos MO. Estimativa 2018: Incidência de Câncer no Brasil. Rev Bras Cancerol. 2018;64(1):119-120. https://doi.org/10.32635/2176-9745.RBC.2018v64n1.115
3.            Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7-33. https://doi.org/10.3322/caac.21708
4.            Guzman R, Guirao À, Vela E, Clèries M, García-Altés A, Sagarra J, et al. Outcomes and cost of lung cancer patients treated surgically or medically in Catalunya: cost-benefit implications for lung cancer screening programs. Eur J Cancer Prev. 2020;29(6):486-492. https://doi.org/10.1097/CEJ.0000000000000566
5.            Brasil. Ministério da Saúde. Instituto Nacional de Câncer José Alencar Gomes da Silva. [homepage on the Internet]. Rio de Janeiro: INCA, 2021. [cited 2023 May 25]. Detecção precoce do câncer. [Adobe Acrobat document, 74p.]. Available from: https://www.inca.gov.br/sites/ufu.sti.inca.local/files/media/document/deteccao-precoce-do-cancer.pdf
6.            Oken MM, Hocking WG, Kvale PA, Andriole GL, Buys SS, Church TR, et al. Screening by chest radiograph and lung cancer mortality: the Prostate, Lung, Colorectal, and Ovarian (PLCO) randomized trial. JAMA. 2011;306(17):1865-1873. https://doi.org/10.1001/jama.2011.1591
7.            Henschke CI, McCauley DI, Yankelevitz DF, Naidich DP, McGuinness G, Miettinen OS, et al. Early Lung Cancer Action Project: overall design and findings from baseline screening. The Lancet. 1999;354(9173):99-105. https://doi.org/10.1016/S0140-6736(99)06093-6
8.            Henschke CI, Boffetta P, Yankelevitz DF, Altorki N. Computed tomography screening: the international early lung cancer action program experience. Thorac Surg Clin. 2015;25(2):129-143. https://doi.org/10.1016/j.thorsurg.2014.12.001
9.            National Lung Screening Trial Research Team; Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5):395-409. https://doi.org/10.1056/NEJMoa1102873
10.          National Lung Screening Trial Research Team. Lung Cancer Incidence and Mortality with Extended Follow-up in the National Lung Screening Trial. J Thorac Oncol. 2019;14(10):1732-1742. https://doi.org/10.1016/j.jtho.2019.05.044
11.          Wille MM, Dirksen A, Ashraf H, Saghir Z, Bach KS, Brodersen J, et al. Results of the Randomized Danish Lung Cancer Screening Trial with Focus on High-Risk Profiling. Am J Respir Crit Care Med. 2016;193(5):542-551. https://doi.org/10.1164/rccm.201505-1040OC
12.          Becker N, Motsch E, Trotter A, Heussel CP, Dienemann H, Schnabel PA, et al. Lung cancer mortality reduction by LDCT screening-Results from the randomized German LUSI trial. Int J Cancer. 2020;146(6):1503-1513. https://doi.org/10.1002/ijc.32486
13.          Paci E, Puliti D, Lopes Pegna A, Carrozzi L, Picozzi G, Falaschi F, et al. Mortality, survival and incidence rates in the ITALUNG randomised lung cancer screening trial. Thorax. 2017;72(9):825-831. https://doi.org/10.1136/thoraxjnl-2016-209825
14.          Infante M, Cavuto S, Lutman FR, Passera E, Chiarenza M, Chiesa G, et al. Long-Term Follow-up Results of the DANTE Trial, a Randomized Study of Lung Cancer Screening with Spiral Computed Tomography. Am J Respir Crit Care Med. 2015;191(10):1166-1175. https://doi.org/10.1164/rccm.201408-1475OC
15.          dos Santos RS, Franceschini JP, Chate RC, Ghefter MC, Kay F, Trajano AL, et al. Do Current Lung Cancer Screening Guidelines Apply for Populations with High Prevalence of Granulomatous Disease? Results From the First Brazilian Lung Cancer Screening Trial (BRELT1). Ann Thorac Surg. 2016;101(2):481-488. https://doi.org/10.1016/j.athoracsur.2015.07.013
16.          de Koning HJ, van der Aalst CM, de Jong PA, Scholten ET, Nackaerts K, Heuvelmans MA, et al. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med. 2020;382(6):503-513. https://doi.org/10.1056/NEJMoa1911793
17.          Sadate A, Occean BV, Beregi JP, Hamard A, Addala T, de Forges H, et al. Systematic review and meta-analysis on the impact of lung cancer screening by low-dose computed tomography. Eur J Cancer Oxf Engl 2020;134:107-114. https://doi.org/10.1016/j.ejca.2020.04.035
18.          Hochhegger B, Camargo S, da Silva Teles GB, Chate RC, Szarf G, Guimarães MD, et al. Challenges of Implementing Lung Cancer Screening in a Developing Country: Results of the Second Brazilian Early Lung Cancer Screening Trial (BRELT2). JCO Glob Oncol. 2022.8:e2100257. https://doi.org/10.1200/GO.21.00257
19.          Oudkerk M, Liu S, Heuvelmans MA, Walter JE, Field JK. Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives. Nat Rev Clin Oncol. 2021;18(3):135-151. https://doi.org/10.1038/s41571-020-00432-6
20.          Adams SJ, Stone E, Baldwin DR, Vliegenthart R, Lee P, Fintelmann FJ. Lung cancer screening. Lancet. 2023;401(10374):390-408. https://doi.org/10.1016/S0140-6736(22)01694-4
21.          Yang SC, Wang JD, Wang SY. Considering lead-time bias in evaluating the effectiveness of lung cancer screening with real-world data. Sci Rep. 2021;11(1):12180. https://doi.org/10.1038/s41598-021-91852-6
22.          Raez LE, Nogueira A, Santos ES, Dos Santos RS, Franceschini J, Ron DA, et al. Challenges in lung cancer screening in Latin America. J Glob Oncol. 2018;4:1-10. https://doi.org/10.1200/JGO.17.00040
23.          Edelman SE, Guerra RB, Edelman SM, Lopes da Silva L, Aleixo GFP, Matuda RMK, et al. The challenges of implementing low-dose computed tomography for lung cancer screening in low- and middle-income countries. Nat Cancer. 2020;1(12):1140–52. https://doi.org/10.1038/s43018-020-00142-z
24.          Warren GW, Alberg AJ, Kraft AS, Cummings KM. The 2014 Surgeon General’s report: “The health consequences of smoking--50 years of progress”: a paradigm shift in cancer care. Cancer. 120(13):1914-1916. https://doi.org/10.1002/cncr.28695
25.          National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2014.
26.          Almeida A. Tipos e formas mais comuns de consumo de nicotina: tabaco sem fumaça. Em: Tabagismo: prevenção e tratamento. 1st ed. Rio de Janeiro, RJ: DiLivros Editora; 2021. p. 29-34.
27.          Viegas CAA. Tipos e formas mais comuns de consumo de nicotina: tabaco com fumaça. Em: Tabagismo: prevenção e tratamento. 1st ed. Rio de Janeiro, RJ: DiLivros Editora; 2021. p. 35-39.
28.          Martins S. Tipos e formas mais comuns de consumo de nicotina: dispositivos eletrônicos para fumar. Em: Tabagismo: prevenção e tratamento. 1st ed. Rio de Janeiro, RJ: DiLivros Editora; 2021. p. 40-48.
29.          National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. E-Cigarette Use Among Youth and Young Adults: A Report of the Surgeon General [monograph on the Internet]. Atlanta (GA): Centers for Disease Control and Prevention (US); 2016. [cited 2023 May 25]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK538680/
30.          Lyzwinski LN, Naslund JA, Miller CJ, Eisenberg MJ. Global youth vaping and respiratory health: epidemiology, interventions, and policies. Npj Prim Care Respir Med. 2022;32(1):14. https://doi.org/10.1038/s41533-022-00277-9
31.          Bertoni N, Szklo AS. Electronic nicotine delivery systems in Brazilian state capitals: prevalence, profile of use, and implications for the National Tobacco Control Policy [Article in Portuguese]. Cad Saude Publica. 2021;37(7): e00261920. https://doi.org/10.1590/0102-311X00261920
32.          Martins S, Araújo AJ, Wehrmeister FC, Freitas BM, Basso RG, Santana ANC, et al. Prevalence and associated factors of experimentation with and current use of water pipes and electronic cigarettes among medical students: a multicentric study in Brazil. J. Brasil Pneumol. 49(1):e20210467. https://doi.org/ 10.36416/1806-3756/e20210467
33.          Corrêa PCRP. No controversy: e-cigarettes are not a treatment for tobacco/nicotine cessation. J Bras Pneumol. 2022;48(5):e20220283. https://doi.org/10.36416/1806-3756/e20220283
34.          IBGE. [homepage on the Internet] Rio de Janeiro, RJ: IBGE; c2020 [cited 2023 Jun 20]. PESQUISA NACIONAL DE SAÚDE 2019: PERCEPÇÃO DO ESTADO DE SAÚDE, ESTILOS DE VIDA, DOENÇAS CRÔNICAS E SAÚDE BUCAL: Brasil e Grandes Regiões. [Adobe Acrobat document, 113p.]. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101764.pdf
35.          Pisinger C, Døssing M. A systematic review of health effects of electronic cigarettes. Prev Med. 2014;69:248-260. https://doi.org/10.1016/j.ypmed.2014.10.009
36.          Tehrani MW, Newmeyer MN, Rule AM, Prasse C. Characterizing the Chemical Landscape in Commercial E-Cigarette Liquids and Aerosols by Liquid Chromatography–High-Resolution Mass Spectrometry. Chem Res Toxicol. 2021;34(10):2216-2226. https://doi.org/10.1021/acs.chemrestox.1c00253
37.          Adermark L, Galanti MR, Ryk C, Gilljam H, Hedman L. Prospective association between use of electronic cigarettes and use of conventional cigarettes: a systematic review and meta-analysis. ERJ Open Res. 2021;7(3):00976-2020. https://doi.org/10.1183/23120541.00976-2020
38.          World Health Organization. [homepage on the Internet]. Geneva: WHO;;c2022 [updated 2019 Dec 18; cited 2022 Jun 20]. WHO global report on trends in prevalence of tobacco use 2000-2025, third edition. Available from: https://www.who.int/publications-detail-redirect/who-global-report-on-trends-in-prevalence-of-tobacco-use-2000-2025-third-edition
39.          Instituto Nacional de Câncer José Alencar Gomes da Silva. [homepage on the Internet]. Rio de Janeiro: INCA; c2022 [updated 2023 Feb 7; cited 2023 Jul 5]. Dados e números da prevalência do tabagismo - Página com informações estatísticas da prevalência do tabagismo no Brasil. Available from: https://www.inca.gov.br/observatorio-da-politica-nacional-de-controle-do-tabaco/dados-e-numeros-prevalencia-tabagismo
40.          Instituto Nacional de Câncer José de Alencar Gomes da Silva; Pan American Health Organization, organizadores. Pesquisa especial de tabagismo - PETab: relatório Brasil. Rio de Janeiro (RJ) : Instituto Nacional do Câncer; Brasília (DF): Ministério da Saúde and Organização Pan-Americana da Saúde - Representação Brasil; 2011.
41.          Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Departamento de Análise Epidemiológica e Vigilância de Doenças Não Transmissíveis. [homepage on the Internet]. Brasília: o Ministério; c2023 [cited 2023 Nov 5]. Vigitel Brasil 2023: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2023. [Adobe Acrobat document, 133p.]. Available from https://www.gov.br/saude/pt-br/centrais-de-conteudo/publicacoes/svsa/vigitel/vigitel-brasil-2023-vigilancia-de-fatores-de-risco-e-protecao-para-doencas-cronicas-por-inquerito-telefonico
42.          Pinto M, Bardach A, Palacios A, Biz A, Alcaraz A, Rodriguez B, et al. Burden of smoking in Brazil and potential benefit of increasing taxes on cigarettes for the economy and for reducing morbidity and mortality. Cad Saude Publica. 2019;35(8):e00129118. https://doi.org/10.1590/0102-311X00129118
43.          United States Public Health Service Office of the Surgeon General; National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. Smoking Cessation: A Report of the Surgeon General [monograph on the Internet]. Washington (DC): US Department of Health and Human Services; 2020. Available from: https://pubmed.ncbi.nlm.nih.gov/32255575/
44.          Brasil. Ministério da Saúde. Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Estratégias para o cuidado da pessoa com doença crônica: o cuidado da pessoa tabagista (Cadernos de Atenção Básica, n. 40). Brasília: Ministério da Saúde, 2015. [Adobe Acrobat document, 156p.]. Available from: http://www.as.saude.ms.gov.br/wp-content/uploads/2016/06/caderno_40.pdf
45.          Tanner NT, Kanodra NM, Gebregziabher M, Payne E, Halbert CH, Warren GW, et al. The Association between Smoking Abstinence and Mortality in the National Lung Screening Trial. Am J Respir Crit Care Med. 2016;193(5):534-541. https://doi.org/10.1164/rccm.201507-1420OC
46.          Heiden BT, Eaton DB, Chang SH, Yan Y, Schoen MW, Chen LS, et al. The Impact of Persistent Smoking After Surgery on Long-term Outcomes After Stage I Non-small Cell Lung Cancer Resection. Chest. 2022;161(6):1687-1696. https://doi.org/10.1016/j.chest.2021.12.634
47.          Brasil. Ministério da Saúde. Instituto Nacional do Câncer (INCA). Coordenação de Prevenção e Vigilância. Consenso sobre Abordagem e Tratamento do Fumante. Rio de Janeiro: INCA; 2001.
48.          Reichert J, Araújo AJ, Gonçalves CM, Godoy I, Chatkin JM, Sales MP, et al. Smoking cessation guidelines--2008. J Bras Pneumol. 2008;34(10):845-880. https://doi.org/10.1590/s1806-37132008001000014
49.          Fiore MC, Jaén CR, Baker TB, Bailey WC, Benowitz NL, Curry SJ, et al. Treatment tobacco use and dependence; 2008 guideline. [monograph on the Internet]. Rockville, MD: US Department of Health and Human Services [updated 2008 May 16; cited 2023 May 25]. Available from: https://stacks.cdc.gov/view/cdc/6964
50.          Brasil. Ministério da Saúde. Instituto Nacional do Câncer [homepage on the Internet]. Brasília: Ministério da Saúde; c2023 [updated 2020 Sep 24; cited 2023 May 25]. Protocolo Clínico e Diretrizes Terapêuticas do Tabagismo. Available from: https://www.inca.gov.br/publicacoes/relatorios/protocolo-clinico-e-diretrizes-terapeuticas-do-tabagismo
51.          Cahill K, Stevens S, Perera R, Lancaster T. Pharmacological interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. 2013;2013(5):CD009329. https://doi.org/10.1002/14651858.CD009329.pub2
52.          Cahill K, Lindson-Hawley N, Thomas KH, Fanshawe TR, Lancaster T. Nicotine receptor partial agonists for smoking cessation. Cochrane Database Syst Rev. 2016;2016(5):CD006103 https://doi.org/10.1002/14651858.CD006103.pub7
53.          Lindson N, Chepkin SC, Ye W, Fanshawe TR, Bullen C, Hartmann-Boyce J. Different doses, durations and modes of delivery of nicotine replacement therapy for smoking cessation. Cochrane Database Syst Rev. 2019;4(4):CD013308. https://doi.org/10.1002/14651858.CD013308
54.          Howes S, Hartmann-Boyce J, Livingstone-Banks J, Hong B, Lindson N. Antidepressants for smoking cessation. Cochrane Database Syst Rev. 2020;4(4):CD000031. https://doi.org/10.1002/14651858.CD000031.pub5
55.          Leone FT, Zhang Y, Evers-Casey S, Evins AE, Eakin MN, Fathi J, et al. Initiating Pharmacologic Treatment in Tobacco-Dependent Adults. An Official American Thoracic Society Clinical Practice Guideline. Am J Respir Crit Care Med. 2020;202(2):e5-e31. https://doi.org/10.1164/rccm.202005-1982ST
56.          Jiménez-Ruiz CA, Andreas S, Lewis KE, Tonnesen P, van Schayck CP, Hajek P, et al. Statement on smoking cessation in COPD and other pulmonary diseases and in smokers with comorbidities who find it difficult to quit. Eur Respir J. 2015;46(1):61-79. https://doi.org/10.1183/09031936.00092614
57.          National Comprehensive Cancer Network Smoking cessation (version 1.2018). Available from: https://www.nccn.org/professionals/physician_gls/pdf/smoking.pdf
58.          Barua RS, Rigotti NA, Benowitz NL, Cummings KM, Jazayeri MA, Morris PB, et al. 2018 ACC Expert Consensus Decision Pathway on Tobacco Cessation Treatment: A Report of the American College of Cardiology Task Force on Clinical Expert Consensus Documents. J Am Coll Cardiol. 2018;72(25):3332-3365. https://doi.org/10.1016/j.jacc.2018.10.027
59.          Hartmann-Boyce J, McRobbie H, Butler AR, Lindson N, Bullen C, Begh R, et al. Electronic cigarettes for smoking cessation. Cochrane Database Syst Rev. 2021;9(9):CD010216. https://doi.org/10.1002/14651858.CD010216.pub6
60.          Hanewinkel R, Niederberger K, Pedersen A, Unger JB, Galimov A. E-cigarettes and nicotine abstinence: a meta-analysis of randomised controlled trials. Eur Respir Rev. 2022;31(163):210215. https://doi.org/10.1183/16000617.0215-2021
61.          Araujo LH, Baldotto C, Castro G Jr, Katz A, Ferreira CG, Mathias C, et al. Lung cancer in Brazil. J Bras Pneumol. 2018;44(1):55-64. https://doi.org/10.1590/S1806-37562017000000135
62.          Ismael GFV, Coradazzi AL, Neto FAM, Abdalla KC, Milhomem P, Oliveira J. Aspectos clínicos e histopatológicos em câncer de pulmão: análise dos dados de uma instituição no interior paulista entre 1997 e 2008. Rev Bras Oncol Clinica. 2010;7(22):72-78.
63.          Costa G, Thuler LC, Ferreira CG. Epidemiological changes in the histological subtypes of 35,018 non-small-cell lung cancer cases in Brazil. Lung Cancer Amst Neth. 2016;97:66-72. https://doi.org/10.1016/j.lungcan.2016.04.019
64.          Brasil. Ministério da Saúde. Instituto Nacional do Câncer (INCA) [homepage on the Internet]. c2022 [updated 2022 Jul 18; cited 2022 Oct 5]. Câncer de pulmão. Available from: https://www.gov.br/inca/pt-br/assuntos/cancer/tipos/pulmao.
65.          Siegel R, Naishadham D, Jemal A. Cancer Statistics, 2013. CA Cancer J Clin. 2013;63(1):11-30. https://doi.org/10.3322/caac.21166
66.          Younes RN, Deutsch F, Badra C, Gross J, Haddad F, Deheinzelin D. Nonsmall cell lung cancer: evaluation of 737 consecutive patients in a single institution. Rev Hosp Clin Fac Med Sao Paulo 2004;59(3):119-127. https://doi.org/10.1590/s0041-87812004000300005
67.          Costa GJ, Mello MJG, Bergmann A, Ferreira CG, Thuler LCS. Tumor-node-metastasis staging and treatment patterns of 73,167 patients with lung cancer in Brazil. J Bras Pneumol. 2020;46(1):e20180251. https://doi.org/10.1590/1806-3713/e20180251
68.          Westphal FL, Lima LC, Andrade EO, Lima Netto JC, Silva AS, Carvalho BC. Characteristics of patients with lung cancer in the city of Manaus, Brazil. J Bras Pneumol. 2009;35(2):157-163. https://doi.org/10.1590/s1806-37132009000200009
69.          Barros JA, Valladares G, Faria AR, Fugita EM, Ruiz AP, Vianna GD, et al. Early diagnosis of lung cancer: the great challenge. Epidemiological variables, clinical variables, staging and treatment. J Bras Pneumol. 2006;32(3):221-227.
70.          Novaes F, Cataneo D, Ruiz R, Defaveri J, Michelin O, Cataneo A. Lung cancer: Histology, staging, treatment and survival. J Bras Pneumol. 2008;34(8):595-600. https://doi.org/10.1590/s1806-37132008000800009
71.          Araujo LH, Baldotto CS, Zukin M, Vieira FM, Victorino AP, Rocha VR, et al. Survival and prognostic factors in patients with Non-Small Cell Lung Cancer treated in private health care. Rev Bras Epidemiol. 2014;17(4):1001-1014. https://doi.org/10.1590/1809-4503201400040017
72.          Mascarenhas E, Lessa G. Perfil clínico e sócio-demográfico de pacientes com câncer de pulmão não-pequenas células atendidos num serviço privado. Rev Bras Oncol Clínica. 2010;7(22):49-54.
73.          Abrao FC, Abreu IRLB, Rocha RO, Munhoz FD, Rodrigues JHG, Younes RN. Impact of the delay to start treatment in patients with lung cancer treated in a densely populated area of Brazil. Clinics (Sao Paulo). 2017;72(11):675-680. https://doi.org/10.6061/clinics/2017(11)05
74.          Jonas DE, Reuland DS, Reddy SM, Nagle M, Clark SD, Weber RP, et al. Screening for Lung Cancer with Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2021;325(10):971-987. https://doi.org/10.1001/jama.2021.0377
75.          Jonas DE, Reuland DS, Reddy SM, Nagle M, Clark SD, Weber RP, et al. Screening for Lung Cancer with Low-Dose Computed Tomography: An Evidence Review for the U.S. Preventive Services Task Force. Evidence Synthesis No. 198. AHRQ Publication No. 20-05266-EF-1. Rockville, MD: Agency for Healthcare Research and Quality; 2021 Mar.
76.          Gohagan J, Marcus P, Fagerstrom R, Pinsky P, Kramer B, Prorok P; et al. Baseline findings of a randomized feasibility trial of lung cancer screening with spiral CT scan vs chest radiograph: the Lung Screening Study of the National Cancer Institute. Chest. 2004;126(1):114-121. https://doi.org/10.1378/chest.126.1.114
77.          Wilson DO, Weissfeld JL, Fuhrman CR, Fisher SN, Balogh P, Landreneau RJ, et al. The Pittsburgh Lung Screening Study (PLuSS): outcomes within 3 years of a first computed tomography scan. Am J Respir Crit Care Med. 2008;178(9):956-961. https://doi.org/10.1164/rccm.200802-336OC
78.          Lopes Pegna A, Picozzi G, Mascalchi M, Maria Carozzi F, Carrozzi L, Comin C, et al. Design, recruitment and baseline results of the ITALUNG trial for lung cancer screening with low-dose CT. Lung Cancer. 2009;64(1):34-40. https://doi.org/10.1016/j.lungcan.2008.07.003
79.          Saghir Z, Dirksen A, Ashraf H, Bach KS, Brodersen J, Clementsen PF, et al. CT screening for lung cancer brings forward early disease. The randomised Danish Lung Cancer Screening Trial: status after five annual screening rounds with low-dose CT. Thorax. 2012;67(4):296-301. https://doi.org/10.1136/thoraxjnl-2011-200736
80.          Becker N, Motsch E, Gross ML, Eigentopf A, Heussel CP, Dienemann H, et al. Randomized study on early detection of lung cancer with MSCT in Germany: study design and results of the first screening round. J Cancer Res Clin Oncol. 2012;138(9):1475-1486. https://doi.org/10.1007/s00432-012-1228-9
81.          Chiarantano RS, Vazquez FL, Franco A, Ferreira LC, Cristina da Costa M, Talarico T, et al. Implementation of an Integrated Lung Cancer Prevention and Screening Program Using a Mobile Computed Tomography (CT) Unit in Brazil. Cancer Control. 2022;29:10732748221121385. https://doi.org/10.1177/10732748221121385
82.          Svartman FM, Leite MMR, Sartori APG, Gutierrez RS, Cadore AC, Oliveira CTM, et al. Lung cancer screening with low-dose CT integrated with pulmonary care in a public hospital in southern Brazil: results from the first 712 patients. J Bras Pneumol. 2022;48(5):e20220146. https://doi.org/10.36416/1806-3756/e20220146
83.          Haiman CA, Stram DO, Wilkens LR, Pike MC, Kolonel LN, Henderson BE, et al. Ethnic and racial differences in the smoking-related risk of lung cancer. N Engl J Med. 2006;354(4):333-342. https://doi.org/10.1056/NEJMoa033250
84.          Pinsky PF. Racial and ethnic differences in lung cancer incidence: how much is explained by differences in smoking patterns? (United States). Cancer Causes Control. 2006;17(8):1017-1024. https://doi.org/10.1007/s10552-006-0038-2
85.          Aldrich MC, Mercaldo SF, Sandler KL, Blot WJ, Grogan EL, Blume JD. Evaluation of USPSTF Lung Cancer Screening Guidelines Among African American Adult Smokers. JAMA Oncol. 2019;5(9):1318-1324. https://doi.org/10.1001/jamaoncol.2019.1402
86.          US Preventive Services Task Force; Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, et al. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021;325(10):962-970. https://doi.org/10.1001/jama.2021.1117
87.          Wood DE, Kazerooni EA, Aberle D, Berman A, Brown LM, Eapen GA, et al. NCCN Guidelines® Insights: Lung Cancer Screening, Version 1.2022: Featured Updates to the NCCN Guidelines. J Natl Compr Canc Netw. 2022;20(7):754-764. https://doi.org/10.6004/jnccn.2022.0036
88.          Penha D, Pinto E, Monaghan C, Hochhegger B, Marchiori E, Taborda-Barata L, et al. Incidental findings on lung cancer screening: pictorial essay and systematic checklist. J Bras Pneumol. 2022;48(1):e20210371. https://doi.org/10.36416/1806-3756/e20210371
89.          Tanoue LT, Sather P, Cortopassi I, Dicks D, Curtis A, Michaud G, et al. Standardizing the Reporting of Incidental, Non-Lung Cancer (Category S) Findings Identified on Lung Cancer Screening Low-Dose CT Imaging. Chest. 2022;161(6):1697-1706. https://doi.org/10.1016/j.chest.2021.12.662
90.          Mazzone PJ, Silvestri GA, Patel S, Kanne JP, Kinsinger LS, Wiener RS, et al. Screening for Lung Cancer: CHEST Guideline and Expert Panel Report. Chest. 2018;153(4):954-985. https://doi.org/10.1016/j.chest.2018.01.016
91.          Mazzone PJ, Silvestri GA, Souter LH, Caverly TJ, Kanne JP, Kathi HA, et al. Screening for Lung Cancer: CHEST Guideline and Expert Panel Report. Chest. 2021;160(5):e427-e494. https://doi.org/10.1016/j.chest.2021.06.063
92.          Kauczor HU, Baird AM, Blum TG, Bonomo L, Bostantzoglou C, Burghuber O, et al. ESR/ERS statement paper on lung cancer screening. Eur Respir J. 2020;55(2):1900506. https://doi.org/10.1183/13993003.00506-2019
93.          Veronesi G, Baldwin DR, Henschke CI, Ghislandi S, Iavicoli S, Oudkerk M, et al. Recommendations for Implementing Lung Cancer Screening with Low-Dose Computed Tomography in Europe. Cancers (Basel). 2020;12(6):0. https://doi.org/10.3390/cancers12061672
94.          Gierada DS, Black WC, Chiles C, Pinsky PF, Yankelevitz DF. Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of Study. Radiol Imaging Cancer. 2020;2(2):e190058. https://doi.org/10.1148/rycan.2020190058
95.          Shankar A, Saini D, Dubey A, Roy S, Bharati SJ, Singh N, et al. Feasibility of lung cancer screening in developing countries: challenges, opportunities and way forward. Transl Lung Cancer Res. 2019;8(Suppl 1):S106-S121. https://doi.org/10.21037/tlcr.2019.03.03
96.          Kim H, Kim HY, Goo JM, Kim Y. Lung Cancer CT Screening and Lung-RADS in a Tuberculosis-endemic Country: The Korean Lung Cancer Screening Project (K-LUCAS). Radiology. 2020;296(1):181-188. https://doi.org/10.1148/radiol.2020192283
97.          The World Bank [homepage on the Internet]. Washington (DC): The World Bank; c2023 [cited 2023 Jun 9]. Incidence of tuberculosis (per 100,000 people). Available from: https://data.worldbank.org/indicator/SH.TBS.INCD
98.          Miranda-Filho A, Charvat H, Bray F, Migowski A, Cheung LC, Vaccarella S, et al. A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil. EClinicalMedicine. 2021;42:101176. https://doi.org/10.1016/j.eclinm.2021.101176
99.          Bach PB, Kattan MW, Thornquist MD, Kris MG, Tate RC, Barnett MJ, Hsieh LJ, Begg CB. Variations in lung cancer risk among smokers. J Natl Cancer Inst. 2003;95(6):470-478. https://doi.org/10.1093/jnci/95.6.470
100.        Toumazis I, Bastani M, Han SS, Plevritis SK. Risk-Based lung cancer screening: A systematic review. Lung Cancer. 2020;147:154-186. https://doi.org/10.1016/j.lungcan.2020.07.007
101.        Tammemägi MC, Katki HA, Hocking WG, Church TR, Caporaso N, Kvale PA, et al. Selection criteria for lung-cancer screening. N Engl J Med. 2013;368(8):728-736. https://doi.org/10.1056/NEJMoa1211776
102.        Tammemagi CM, Pinsky PF, Caporaso NE, Kvale PA, Hocking WG, Church TR, et al. Lung cancer risk prediction: Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial models and validation. J Natl Cancer Inst. 2011;103(13):1058-1068. https://doi.org/10.1093/jnci/djr173
103.        Katki HA, Kovalchik SA, Berg CD, Cheung LC, Chaturvedi AK. Development and Validation of Risk Models to Select Ever-Smokers for CT Lung Cancer Screening. JAMA. 2016;315(21):2300-2311. https://doi.org/10.1001/jama.2016.6255
104.        Cheung LC, Berg CD, Castle PE, Katki HA, Chaturvedi AK. Life-Gained-Based Versus Risk-Based Selection of Smokers for Lung Cancer Screening. Ann Intern Med. 2019;171(9):623-632. https://doi.org/10.7326/M19-1263
105.        Ten Haaf K, Bastani M, Cao P, Jeon J, Toumazis I, Han SS, et al. A Comparative Modeling Analysis of Risk-Based Lung Cancer Screening Strategies. J Natl Cancer Inst. 2020;112(5):466-479. https://doi.org/10.1093/jnci/djz164
106.        Katki HA, Kovalchik SA, Petito LC, Cheung LC, Jacobs E, Jemal A, et al. Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening. Ann Intern Med. 2018;169(1):10-19. https://doi.org/10.7326/M17-2701
107.        Moyer VA; US Preventive Services Task Force. Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2014;160(5):330-338. https://doi.org/10.7326/M13-2771
108.        Kumar V, Cohen JT, van Klaveren D, Soeteman DI, Wong JB, Neumann PJ, et al. Risk-Targeted Lung Cancer Screening: A Cost-Effectiveness Analysis. Ann Intern Med. 2018;168(3):161-169. https://doi.org/10.7326/M17-1401
109.        Teles GBDS, Macedo ACS, Chate RC, Valente VAT, Funari MBG, Szarf G. LDCT lung cancer screening in populations at different risk for lung cancer. BMJ Open Respir Res. 2020 Feb;7(1):e000455. https://doi.org/10.1136/bmjresp-2019-000455
110.        Kazerooni EA, Austin JH, Black WC, Dyer DS, Hazelton TR, Leung AN, et al. ACR-STR practice parameter for the performance and reporting of lung cancer screening thoracic computed tomography (CT): 2014 (Resolution 4). J Thorac Imaging. 2014;29(5):310-316. https://doi.org/10.1097/RTI.0000000000000097
111.        Fintelmann FJ, Bernheim A, Digumarthy SR, Lennes IT, Kalra MK, Gilman MD, et al. The 10 Pillars of Lung Cancer Screening: Rationale and Logistics of a Lung Cancer Screening Program. RadioGraphics. 2015;35(7):1893-1908. https://doi.org/10.1148/rg.2015150079
112.        American Association of Physicists in Medicine. [homepage on the Internet]. Alexandria (VA): AAPM; c2023 [updated 2019 Sep 2019; cited 2023 Jun 13]. Lung Cancer Screening CT Protocols Version 5.1. Available from: https://www.aapm.org/pubs/CTProtocols/documents/LungCancerScreeningCT.pdf 
113.        Vonder M, Dorrius MD, Vliegenthart R. Latest CT technologies in lung cancer screening: protocols and radiation dose reduction. Transl Lung Cancer Res. 2021;10(2):1154-1164. https://doi.org/10.21037/tlcr-20-808
114.        MacMahon H, Naidich DP, Goo JM, Lee KS, Leung ANC, Mayo JR, et al. Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017. Radiology. 2017;284(1):228-243. https://doi.org/10.1148/radiol.2017161659
115.        American College of Radiology Committee on Lung-RADS. [homepage on the Internet]. Reston (VA): ACR; c2023 [cited 2023 Jun 28]. Lung-RADS assessment categories version 1.1. Available from: www.acr.org/-/media/ACR/Files/RADS/Lung-RADS/LungRADSAssessmentCategoriesv1-1.pdf
116.        American College of Radiology Committee on Lung-RADS. [homepage on the Internet]. Reston (VA): ACR; c2023 [updated 2022; cited 2023 Jun 20]. Lung CT Screening Reporting & Data System (Lung-RADS®). Available from: https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/Lung-Rads
117.        Xu DM, Gietema H, de Koning H, Vernhout R, Nackaerts K, Prokop M, et al. Nodule management protocol of the NELSON randomised lung cancer screening trial. Lung Cancer. 2006; 54(2):177-184. https://doi.org/10.1016/j.lungcan.2006.08.006 
118.        Devaraj A, van Ginneken B, Nair A, Baldwin D. Use of Volumetry for Lung Nodule Management: Theory and Practice. Radiology. 2017;284(3):630–644. https://doi.org/10.1148/radiol.2017151022
119.        Revel MP, Bissery A, Bienvenu M, Aycard L, Lefort C, Frija G. Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable? Radiology. 2004;231(2):453-458. https://doi.org/10.1148/radiol.2312030167
120.        Gierada DS, Rydzak CE, Zei M, Rhea L. Improved Interobserver Agreement on Lung-RADS Classification of Solid Nodules Using Semiautomated CT Volumetry. Radiology. 2020;297(3):675-684. https://doi.org/10.1148/radiol.2020200302
121.        Heuvelmans MA, Walter JE, Vliegenthart R, van Ooijen PMA, De Bock GH, de Koning HJ, et al. Disagreement of diameter and volume measurements for pulmonary nodule size estimation in CT lung cancer screening. Thorax. 2018;73(8):779-781. https://doi.org/10.1136/thoraxjnl-2017-210770
122.        Zhao YR, van Ooijen PM, Dorrius MD, Heuvelmans M, de Bock GH, Vliegenthart R, Oudkerk M. Comparison of Three Software Systems for Semi-Automatic volumetry of Pulmonary Nodules on Baseline and Follow-Up CT Examinations. Acta Radiol 2014;55(6):691-698. https://doi.org/10.1177/0284185113508177
123.        Delorme S, Kaaks R. Lung Cancer Screening by Low-Dose Computed Tomography: Part 2 - Key Elements for Programmatic Implementation of Lung Cancer Screening. Rofo. 2021;193(6):644-651. https://doi.org/10.1055/a-1290-7817
124.        Pinsky PF, Gierada DS, Black W, Munden R, Nath H, Aberle D, et al. Performance of Lung-RADS in the National Lung Screening Trial. Ann Intern Med. 2015;162(7):485-491. https://doi.org/10.7326/M14-2086
125.        Ho H, Williamson C, Regis SM, Stock CT, Quadri SM, McKee BJ, et al. Surgery and invasive diagnostic procedures for benign disease are rare in a large low dose computed tomography lung cancer screening program. J Thorac Cardiovasc Surg. 2021;161(3):790-802.e2. https://doi.org/10.1016/j.jtcvs.2020.08.109
126.        Passiglia F, Cinquini M, Bertolaccini L, Del Re M, Facchinetti F, Ferrara R, et al. Benefits and Harms of Lung Cancer Screening by Chest Computed Tomography: A Systematic Review and Meta-Analysis. J Clin Oncol. 2021;39(23):2574-2585. https://doi.org/10.1200/JCO.20.02574
127.        Field JK, Duffy SW, Baldwin DR, Brain KE, Devaraj A, Eisen T, et al. The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer. Health Technol Assess Winch Engl. 2016;20(40):1-146. https://doi.org/10.3310/hta20400
128.        Dunn CE, Edwards A, Carter B, Field JK, Brain K, Lifford KJ. The role of screening expectations in modifying short-term psychological responses to low-dose computed tomography lung cancer screening among high-risk individuals. Patient Educ Couns. 2017;100(8):1572-1579. https://doi.org/10.1016/j.pec.2017.02.024
129.        Penha D, Pinto E, Monaghan C, Hochhegger B, Marchiori E, Taborda-Barata L, et al. Incidental findings on lung cancer screening: pictorial essay and systematic checklist J Bras Pneumol. 2022;48(1):e20210371. https://doi.org/10.36416/1806-3756/e20210371
130.        Clark MA, Gorelick JJ, Sicks JD, Park ER, Graham AL, Abrams DB, et al. The Relations Between False Positive and Negative Screens and Smoking Cessation and Relapse in the National Lung Screening Trial: Implications for Public Health. Nicotine Tob Res. 2016;18(1):17-24. https://doi.org/10.1093/ntr/ntv037
131.        Iaccarino JM, Duran C, Slatore CG, Wiener RS, Kathuria H. Combining smoking cessation interventions with LDCT lung cancer screening: A systematic review. Prev Med. 2019;121:24-32. https://doi.org/10.1016/j.ypmed.2019.02.016
132.        Pedersen JH, Ashraf H. Implementation and organization of lung cancer screening. Ann Transl Med. 2016;4(8):152. https://doi.org/10.21037/atm.2016.03.59
133.        van der Aalst CM, Ten Haaf K, de Koning HJ. Implementation of lung cancer screening: what are the main issues? Transl Lung Cancer Res. 2021;10(2):1050-1063. https://doi.org/10.21037/tlcr-20-985
134.        Dobler CC, Midthun DE, Montori VM. Quality of Shared Decision Making in Lung Cancer Screening: The Right Process, With the Right Partners, at the Right Time and Place. Mayo Clin Proc. 2017;92(11):1612-1616. https://doi.org/10.1016/j.mayocp.2017.08.010
135.        Field JK, deKoning H, Oudkerk M, Anwar S, Mulshine J, Pastorino U, et al. Implementation of lung cancer screening in Europe: challenges and potential solutions: summary of a multidisciplinary roundtable discussion. ESMO Open. 2019;4(5):e000577. https://doi.org/10.1136/esmoopen-2019-000577
136.        Lin Y, Fu M, Ding R, Inoue K, Jeon CY, Hsu W, et al. Patient Adherence to Lung CT Screening Reporting & Data System-Recommended Screening Intervals in the United States: A Systematic Review and Meta-Analysis. J Thorac Oncol. 2021;17(1):38-55. https://doi.org/10.1016/j.jtho.2021.09.013
137.        Pyenson B, Dieguez G. 2016 reflections on the favorable cost-benefit of lung cancer screening. Ann Transl Med. 2016;4(8):155. https://doi.org/10.21037/atm.2016.04.02
138.        Pyenson BS, Tomicki SM. Lung Cancer Screening: A Cost-Effective Public Health Imperative. Am J Public Health. 2018;108(10):1292-1293. https://doi.org/10.2105/AJPH.2018.304659
139.        Ten Haaf K, Tammemägi MC, Bondy SJ, van der Aalst CM, Gu S, McGregor SE, et al. Performance and Cost-Effectiveness of Computed Tomography Lung Cancer Screening Scenarios in a Population-Based Setting: A Microsimulation Modeling Analysis in Ontario, Canada. PLOS Med. 2017;14(2):e1002225. https://doi.org/10.1371/journal.pmed.1002225
140.        Grover H, King W, Bhattarai N, Moloney E, Sharp L, Fuller L. Systematic review of the cost-effectiveness of screening for lung cancer with low dose computed tomography. Lung Cancer. 2022;170:20-33. https://doi.org/10.1016/j.lungcan.2022.05.005
141.        Liu CC, Shi JF, Liu GX, Tang W, Zhang X, Li F, et al. Cost-effectiveness of lung cancer screening worldwide: a systematic review [Article in Chinese]. Zhonghua Liu Xing Bing Xue Za Zhi Zhonghua Liuxingbingxue Zazhi. 2019;40(2):218-226. https://doi.org/10.3760/cma.j.issn.0254-6450.2019.02.018
142.        Sun C, Zhang X, Guo S, Liu Y, Zhou L, Shi J, et al. Determining cost-effectiveness of lung cancer screening in urban Chinese populations using a state-transition Markov model. BMJ Open. 2021;11(7):e046742. https://doi.org/10.1136/bmjopen-2020-046742
143.        Snowsill T, Yang H, Griffin E, Long L, Varley-Campbell J, Coelho H, et al. Low-dose computed tomography for lung cancer screening in high-risk populations: a systematic review and economic evaluation. Health Technol Assess. 2018;22(69):1-276. https://doi.org/10.3310/hta22690
144.        International Early Lung Cancer Action Program Investigators; Henschke CI, Yankelevitz DF, Libby DM, Pasmantier MW, Smith JP, Miettinen OS. Survival of patients with stage I lung cancer detected on CT screening. N Engl J Med. 2006;355(17):1763-1771. https://doi.org/10.1056/NEJMoa060476
145.        Du Y, Sidorenkov G, Heuvelmans MA, Groen HJM, Vermeulen KM, Greuter MJW, et al. Cost-effectiveness of lung cancer screening with low-dose computed tomography in heavy smokers: a microsimulation modelling study. Eur J Cancer. 2020;135:121-129. https://doi.org/10.1016/j.ejca.2020.05.004
146.        Hensing TA, Salgia R. Molecular biomarkers for future screening of lung cancer. J Surg Oncol. 2013;108(5):327-333. https://doi.org/10.1002/jso.23382
147.        Seijo LM, Peled N, Ajona D, Boeri M, Field JK, Sozzi G, et al. Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges. J Thorac Oncol. 2019;14(3):343-357. https://doi.org/10.1016/j.jtho.2018.11.023
148.        Zaric B, Perin B, Carapic V, Stojsic V, Matijasevic J, Andrijevic I, et al. Diagnostic value of autofluorescence bronchoscopy in lung cancer. Thorac Cancer. 2013;4(1):1-8. https://doi.org/10.1111/j.1759-7714.2012.00130.x
149.        Li Y, Zhang T, Zhang H, Wang X, Liu X, Huang Q, et al. Clinical Significance of P16 Gene Methylation in Lung Cancer. Adv Exp Med Biol. 2020;1255:133-142. https://doi.org/10.1007/978-981-15-4494-1_11
150.        Hulbert A, Jusue-Torres I, Stark A, Chen C, Rodgers K, Lee B, et al. Early Detection of Lung Cancer Using DNA Promoter Hypermethylation in Plasma and Sputum. Clin Cancer Res. 2017;23(8):1998-2005. https://doi.org/10.1158/1078-0432.CCR-16-1371
151.        Nardi-Agmon I, Abud-Hawa M, Liran O, Gai-Mor N, Ilouze M, Onn A, et al. Exhaled Breath Analysis for Monitoring Response to Treatment in Advanced Lung Cancer. J Thorac Oncol. 2016;11(6):827-837. https://doi.org/10.1016/j.jtho.2016.02.017
152.        Peled N, Hakim M, Bunn P, Miller Y, Kennedy T, Mattei J, et al. Non-invasive Breath Analysis of Pulmonary Nodules. J Thorac Oncol. 2012;7(10):1528-1533. https://doi.org/10.1097/JTO.0b013e3182637d5f
153.        Sozzi G, Boeri M, Rossi M, Verri C, Suatoni P, Bravi F, et al. Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: a correlative MILD trial study. J Clin Oncol. 2014;32(8):768-773. https://doi.org/10.1200/JCO.2013.50.4357
154.        Pastorino U, Boeri M, Sestini S, Sabia F, Milanese G, Silva M, et al. Baseline computed tomography screening and blood microRNA predict lung cancer risk and define adequate intervals in the BioMILD trial. Ann Oncol. 2022;33(4):395-405. https://doi.org/0.1016/j.annonc.2022.01.008
155.        Sozzi G, Roz L, Conte D, Mariani L, Andriani F, Lo Vullo S, et al. Plasma DNA quantification in lung cancer computed tomography screening: five-year results of a prospective study. Am J Respir Crit Care Med. 2009;179(1):69-74. https://doi.org/10.1164/rccm.200807-1068OC
156.        Rezola A, Pey J, Rubio Á, Planes FJ. In-Silico prediction of key metabolic differences between two non-small cell lung cancer subtypes. PLoS One. 2014;9(8):e103998. https://doi.org/10.1371/journal.pone.0103998
157.        Cohn AL, Seiden M, Kurtzman KN, Hubbell E, Gross S, Venn O, et al. The Circulating Cell-free Genome Atlas (CCGA) Study: Follow-up (F/U) on non-cancer participants with cancer-like cell-free DNA signals. J Clin Oncol 2019;3715_suppl):5574-5574. https://doi.org/10.1200/JCO.2019.37.15_suppl.5574
158.        ClinicalTrials.gov [homepage on the Internet]. Bethesda: National Institutes of Health [updated 2022 Aug 20; cited 2023 Jun 9]. The Circulating Cell-free Genome Atlas Study (CCGA) [NCT02889978]. Available from: https://clinicaltrials.gov/ct2/show/record/NCT02889978
159.        McWilliams A, Tammemagi M, Mayo J, Roberts H, Liu G, Soghrati K, et al. Probability of cancer in pulmonary nodules detected on first screening computed tomography. N Engl J Med. 2013;369(10):910-919. https://doi.org/10.1056/NEJMoa1214726

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