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EDITORIAL
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Lung cancer screening: An unending tale


1 Department of Surgical Oncology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
2 Department of Medical Oncology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
3 Department of Radiation Oncology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India

Date of Submission30-Jun-2020
Date of Decision27-Jul-2020
Date of Acceptance30-Sep-2020
Date of Web Publication17-Jul-2021

Correspondence Address:
Manoj Kumar Gupta,
Department of Radiation Oncology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.JCRT_888_20



How to cite this URL:
Poonia DR, Sehrawat A, Gupta MK. Lung cancer screening: An unending tale. J Can Res Ther [Epub ahead of print] [cited 2021 Jul 29]. Available from: https://www.cancerjournal.net/preprintarticle.asp?id=321715




 > Background Top


Incidences and mortality of lung cancer are falling in the Western world owing to change in smoking habits and advancement in management with improvement in precision medicine.[1] Lung cancer, which has a well-established causal relationship to smoking that is a completely modifiable risk factor, remains the most common cancer over the last four decades across the globe, needs serious thought on what went wrong? Can we reproduce the success story of cervix cancer? “No root, no fruit” is the best way to go for such cancers, but we are far from ultimate success. Screening is a secondweapon that provides the opportunity to gain control over them before they grow incurable.[2]

As per Wilson and Jungner's criteria, lung cancer is an ideal disease to be taken up for the screening owing to its high burden, well-established risk factors, symptomatic nature only in the advanced stages, availability of effective therapy, and fairly predictable natural history.[3] The goal of a screening test is to improve life expectancy without affecting the quality of life at a population level.[1] Recently, the NELSON trial has started a buzz again about lung cancer screening. Initial attempts of using sputum cytology and chest X-ray (CXR) failed to aid in early diagnosis.[4] The widespread availability of low-dose computed tomography (LDCT) brings new hope for lung cancer screening, but multiple small randomized trials from Europe failed to show any impact on lung cancer-related mortality (LCRM). The second decade of this century brings two positive trials. The National Lung Screening Trial (NLST) from the USA in 2011 and NELSON in 2020 (The Netherlands-Belgium). We can still notice the circumspection for lung cancer screening, with only 5% uptake in the USA despite having strong evidence, while Pap smear for cervical cancer is established before the publication of any randomized controlled trial (RCT).[2] The level of confidence we can acquire in breast cancer and cervical cancer is not established in lung cancer, owing to the undeclared but real worry associated with screening.[5],[6] In this article, we will briefly discuss the evolution of screening in lung cancer, potential benefits and harms, an appraisal on applicability in the Indian settings, and unmet needs.


 > Evolution of Evidence Top


The causal association of smoking with lung cancer was established in the 1950s, and attempts of both smoking cessation program and screening are well in function since the 1960s. Initial attempts were made using CXR with or without sputum cytology till 2000, but they failed to demonstrate benefit in terms of cancer detection or mortality rates. The largest and most talked-about of them was the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial, which put the brakes on CXR for screening.[4],[7]

The first LDCT trial was published in the 1990s, but initial small European trials did not show benefit in LCRM reduction. It was realized that screening the general population does not provide many dividends, hence lately studies included high-risk populations largely based on smoking status and age.[4] The NLST trial[8] compared three annual LDCT with three annual CXRs in a high-risk population (people between the ages of 55 and 74 years, 30 pack-years, current or former smokers). This is the largest trial, including 53,454 participants, and powered enough to identify LCRM and all-cause mortality (ACM). They concluded that the LDCT arm was associated with 20% and 6.7% relative risk reduction in LCRM and ACM, respectively, at 6.5 years. Based on the results of NLST, most of the recommending authorities in the USA advised LDCT lung cancer screening in high-risk populations as per the NLST criteria.[1],[2],[9] On the other hand, Europe has been awaiting the results of the NELSON trial.[10] The National Cancer Institute-funded USPSTF study[11] was undertaken to analyze the optimum screening policy based on the results of the PLCO, the NLST, the Surveillance, Epidemiology, and End Results program, and US smoking history generator. They concluded that application of annual LDCT in populations aged between 55 and 80 years with 30 or more pack-years smoking history, provides the most favorable benefit–harm ratio among five comparative models.

The Dutch-Belgian trial,[12] the largest of all European trials, included >13,000 men and 2594 women, had different high-risk populations, age groups, smoking burden, screening interval (four LDCT at 0, 1, 2, and 2.5 years), and method of LDCT evaluation (volume based) than that of the NLST trial. The LDCT screening was associated with 24% of risk reduction of LCRM in men (P = 0.01) and 33% (P > 0.05) in women at 10-year follow-up. For female participants, they observed LCRM benefits through 7–9-year follow-ups, which faded on the 10-year analysis. This equates to one lung cancer death prevention per 132 participants screened at 10 years. The NELSON trial was not adequately powered to assess the impact of screening on ACM.

Two recent meta-analyses[13],[14] have reported LCRM reduction of 17% (confidence interval [CI] 0.76–0.90, I2 = 1%) and ACM risk reduction of 5% (CI 0.90–1.00, I2 = 0%). Furthermore, their analysis suggested that 294 participants needed to be screened to prevent one death. The success of the screening test is measured in terms of performance characteristics, the overall rate of cancer detection, stage, aggressive disease detection rate, quality-of-life outcomes, cost-effectiveness, and relative and absolute reduction on cancer-specific and overall mortality. Now, we have powered RCTs and meta-analyses conclusively establishing the role of LDCT to reduce LCRM. The relative risk may be a deceptive outcome and provides a false sense of benefit particularly when applied in the populations across different geographical areas. Smoking affects almost every organ and is responsible for death apart from causing lung cancer, hence we must look into an overall benefit in survival rather merely focusing on lung cancer mortality only.[15]


 > Critical Appraisal and Limitations of Available Information Top


Beyond survival statistics, we must look into certain other aspects of screening with LDCT. It is being noted consistently across various trials that nearly 10% of patients are diagnosed in metastatic stage despite screening. Nearly 14% of cancer cases were diagnosed in Stage IV during screening in the NLST trial, while 9.4% in the NELSON trial.[5],[7],[8],[12] These findings suggest that certain subtypes of lung cancer are so aggressive that they rapidly progress to advanced stages between two screening intervals, which criticize the rationale of screening.

The definition of false positivity has been variable across different trials. Considering the need for diagnostic imaging as a measure of false positivity, the rate was 24% in the NLST trial. It was 19.7% and 9.2% at first and fourth scans respectively in the NELSON trial. This reduction is a welcome finding and can be credited to LDCT evaluation, but notably, only 0.9% of these false-positive scans had lung cancer, suggesting that still a substantial number of participants have to go through futile investigations.[5],[7],[8],[12],[16] The higher false positivity in the NLST trial is in part criticized due to the use of a diameter-based manual analysis of nodules. To standardize the reporting, Lung-Imaging-Reporting and data system has been adopted for screening in lung cancer.[2] A false positive result affects the mental health and quality of life of the individual[5],[6]. An analysis on NLST trail[15], shown no difference in the levels of anxiety and quality of life at 1 and 6 months. True-positive people have inferior outcomes, but their anxiety and quality of life remain essentially a valid concern with generalized adoption of lung cancer screening. LDCT is likely to detect nearly 40% of the participants with chronic lung disease and coronary calcification and such diagnosis requires referral and care, which might otherwise be needed only if someone becomes symptomatic. Confounding effects of granulomatous disease such as tuberculosis (TB) and sarcoidosis on imaging were highlighted by Brazilian Lung Cancer Screening Trial (BRELT1),[17] where they conclusively declined the utility of LDCT in their country owing to these lesions causing higher false positivity.

The definition of high-risk populations used in both the NLST and the NELSON trials is probably not perfect as there are multiple risk factors of lung cancer. If the screening is limiting only to NLST criteria, only one-fourth of the lung cancer cases would be diagnosed. The NCCN recommends additional risk factors such as personal history of cancer, lung disease, family history of cancer, radon exposure, and occupational exposure to carcinogens for screening using LDCT.[18] Multiple risk-based models such as modified PLCO, Bach, Liverpool Lung Project, and Spitz have been validated and found effective as well as cost-effective, though these are yet to be adopted in guidelines. Furthermore, multiple studies are underway to identify the molecular biomarkers to select high-risk populations for screening.[2],[10] Another approach is to develop predictive statistical or machine learning models, is using information beyond age and smoking. A Canadian study group[19] developed statistical models to predict the probability of malignancy using radiological appearance, age, gender, smoking, chronic lung disease, and history of cancer, and validated in German Lung Cancer Screening Intervention trial populations.

Overdiagnosis is a condition, which diagnoses cancer that is either indolent or cancers that even diagnosing them will not affect survival at all. Such events add to the burden on health care and illusive benefits. The true incidence of the overdiagnosis is difficult to ascertain owing to its dynamic nature. A systemic meta-analysis[20] of five RCTs excluding NLST and NELSON trials concluded that screening using LDCT increases the cumulative incidence of lung cancer (hazard ratio [HR]: 1.5; 1.06–2.14) and nearly 49% of them are overdiagnosed which equates to twenty additional cancer detection per 1000 population. On analysis of NLST trial data, Patz et al.[21] estimated the overdiagnosis of 18.5% (95% CI: 5.4–30.6%), which highlights the lacuna of using LDCT on its specificity to detect clinically significant cancer as the rate of overdiagnosis was similar to that of CXR-based screening. The rate of overdiagnosis was 22.5% for non-small cell carcinoma, while it was 78.9% for bronchioloalveolar carcinoma. The NELSON trial researcher reported an 8.9% overdetection of lung cancer with LDCT screen, making the upper limit of overdiagnosis.[5],[12] To find whether the detection of cancer is mere lead-time bias, long-term follow-ups are needed. Even at a 25-year follow-up in Mayo Lung Project, the lung cancer rate curves did not meet, suggesting that overdiagnosis and lead time is a reality. Long-term results of the NLST and the NELSON trials would further clarify the impact of LDCT on overdiagnosis and lead-time bias.

The radiation exposure per LDCT scan is 1.4 mSv, as compared to the diagnostic computed tomography chest, which has 8 mSv. However, the cumulative exposure of radiation with interval scans has the potential to increase radiation-induced carcinogenesis.[9] As per one estimate on the NLST database, considering standard screening recommendations, one radiation-induced death is anticipated for each 2500 screen. As per the European COSMOS study,[22] at 10 years of screening, LDCT induced an additional risk of 0.05% that equates to one radiation-induced cancer for every 108 lung cancer diagnosis. For every 10,000 screening participants, 2.6-8.1 of lung cancers are due to LDCT. Though it seems a small number, definitely worth taking into consideration before prescribing it.

An optimal screening interval and screening regimen is another area of concern. A negative baseline screen is associated with a lower rate of further cancer detection, but how long this effect remains is still undetermined.[23],[24],[25] Only 2% of the participants with baseline negative screening developed lung cancer at 5 years in the NLST trial, only 0.48% at 2 years. The NELSON trial reported 0.6% lung cancer detection at 2 years if baseline imaging was negative.[22] However, the story doesn't end here. Yousaf-Khan et al.[26] pointed out that interval cancer detection rate and frequency of advanced cancers keep on the rise with subsequent rounds of scans, suggesting that the optimal duration of scans is somewhere between 1 and 2 years. A German analysis suggested selected morphology with risk-based patient characteristics, allowing personalized screening.[27],[28] Subsolid nodules are though more likely to harbor cancer but it didn't translate into higher LRCM, suggesting its less aggressiveness. For such lesions, a longer imaging interval is an acceptable option.

The cost-effectiveness of implementing the screening is a perplexing matter, particularly the additional cost incurred due to testing associated with overdiagnosis and false positives. Cost-effectiveness analysis studies showed mixed results.[29],[30] More so, the meager uptake of LDCT makes assessment difficult. Data suggest that if it is implemented as a lung control program, then it has the potential to be a cost-effective intervention.


 > Indian Setting Top


Smoking contributes to nearly 85% of lung cancer in the Western world, while nonsmoke-related cancer is common, contributing nearly 45% of the total lung cancer burden.[2],[31],[32],[33],[34] The opportunistic cancer registries suffer from fallacious and nonuniform reporting of cancer burden. India is currently in the state of expansion of such cancer registries; hence, it is obvious that the reported statistics may not be a true picture of cancer in India. Lung cancer in India is seen at a comparatively younger age, 60% of the patients are under the age of 60 years.[31],[32] Overall, it suggests that there is a biological difference from the Western world. High-risk populations suggested by Western trials are irrelevant in the Indian setting. Nearly 171 million Indians are between the age group of 50 and 74 years, which makes 14% of the total population.[35] These populations have 35%–40% prevalence of chronic smoking as per the Global Adult Tobacco Survey and Special Fertility and Mortality Survey.[36],[37] The exact numbers are difficult to predict, but nearly 60–70 million people would be screening eligible. The cost and associated logistics are extremely difficult to meet for such a huge number. The cost incurred would be substantial. Lack of dedicated screening centers, workforce, and immaculate referral – treatment, make the generalized acceptance of screening an onerous task.

The confounding effect of benign conditions such as TB is not well reported from India, but the BRELT1 trial from Brazil raises some kind of discombobulation, due to granulomatous diseases.[17] There is an ongoing trial from India to detect the effectiveness of LDCT in lung cancer screening in a TB-endemic region initiated from Postgraduate Institute of Medical Education and Research, and results are expected by the end of this year.[38] Digital CXR with computer-aided diagnostics or artificial intelligence-based model generation might be an alternative cost-effective option for screening in resource-constraint regions. The American Cancer Society had initiated the National Lung Cancer Roundtable in 2017 with a coalition of public, private, and nonprofit organizations of the USA, which aims prompt prevention, awareness, screening, and treatment with capacity building of providers and health research in lung cancer by collaborative efforts and advocacy.[1],[2] Such public and private collaborative actions are of immense help in India.

Web- based screening decision model (VA-LCSDecTool) trials[39] are underway, which are using the clinical and demographic information's in decision making before initiation of screening. It would be interesting to know the outcome of these studies. Development of molecular markers of potential high-risk cases, autofluorescence bronchoscopy, volatile organic compound analysis, and Breath Print analysis are still in their infancy.[40]


 > Conclusions Top


LDCT has been proven effective to detect lung cancer and halt LCRM, but its effectiveness is yet to be seen with a generalized application and longer follow-ups. Moreover, it is imperative to keep in mind the potential harms associated with screening. In the face of these strong shreds of evidence with few limitations, the applicability of the results in Indian setting is still vexed, considering the facts such as the high incidence of benign conditions such as TB and sarcoidosis leading to diagnostic difficulties, the significant pool of lung cancer patients being nonsmokers, cost-effectiveness, and lack of structural referral system.



 
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