Lung Cancer Screening: Optimization through risk stratification

Lung cancer is the leading cause of cancer related mortality worldwide. However, results from randomized controlled trials indicate that lung cancer mortality can be reduced by early detection through computed tomography screening. This thesis describes the development of a microsimulation model for the evaluation of lung cancer screening programs, based on individual-level data from two large randomized controlled trials. It then evaluates the long-term benefits and harms of implementing lung cancer screening programs. Finally, it investigates how risk stratification may be used to optimize lung cancer screening programs

Uptake of minimally invasive surgery and stereotactic body radiation therapy for early stage non-small cell lung cancer in the USA

BACKGROUND: We aimed to assess the uptake of minimally invasive surgery (MIS) and stereotactic body radiation therapy (SBRT) among early stage (stage IA-IIB) non-small cell lung cancer (NSCLC) cases in the USA, and the rate of conversions from MIS to open surgery. MATERIALS AND METHODS: Data were obtained from the US National Cancer Database, a nationwide facility-based cancer registry capturing up to 70% of incident cancer cases in the USA. We included cases diagnosed with early stage (clinical stages IA-IIB) NSCLC between 2010 and 2014. In an ecological analysis, we assessed changes in treatment by year of diagnosis. Among surgically treated cases, we assessed the uptake of MIS and whether conversion to open surgery took place. For cases that received thoracic radiotherapy, we assessed the uptake of SBRT. RESULTS: Among 117 370 selected cases, radiotherapy use increased 3.4 percentage points between 2010 and 2014 (p<0.0001). Surgical treatments decreased 3.5 percentage points (p<0.0001). Rates of non-treatment remained stable (range: 10.0%-10.6% (p=0.4066)). Among surgically treated stage IA cases, uptake of MIS increased from 28.7% (95% CI 27.8% to 29.7%) in 2010 to 48.6% (95% CI 47.6% to 49

Extrapolation of pre-screening trends: Impact of assumptions on overdiagnosis estimates by mammographic screening

Background: Overdiagnosis by mammographic screening is defined as the excess in breast cancer incidence in the presence of screening compared to the incidence in the absence of screening. The latter is often estimated by extrapolating the pre-screening incidence trend. The aim of this theoretical study is to investigate the impact of assumptions in extrapolating the pre-screening incidence trend of invasive breast cancer on the estimated percentage of overdiagnosis. Methods: We extracted data on invasive breast cancer incidence and person-years by calendar year (1975-2009) and 5-year age groups (0-85 years) from Dutch databases. Different combinations of assumptions for extrapolating the pre-screening period were investigated, such as variations in the type of regre

Trends in lung cancer risk and screening eligibility affect overdiagnosis estimates

Objectives: The degree of overdiagnosis due to lung cancer screening in the general US population remains unknown. Estimates may be influenced by the method used and by decreasing smoking trends, which reduce lung cancer risk and screening eligibility over time. Therefore, we aimed to estimate the degree of overdiagnosis due to lung cancer screening in the general US population, using three distinct methods. Material and methods: The MISCAN-Lung model was used to project lung cancer incidence and overdiagnosis in the general US population between 2018–2040, assuming perfect adherence to the United States Preventive Task Force recommendations. MISCAN-Lung was calibrated to the NLST and PLCO trials and incorporates birth-cohort-specific smoking trends and life expectancies. We estimated overdiagnosis using the cumulative excess-incidence approach, the annual excess-incidence approach, and the microsimulation approach. Results: Using the cumulative excess-incidence approach, 10.5 % of screen-detected cases were overdiagnosed in the 1950 birth-cohort compared to 5.9 % in the 1990 birth-cohort. Incidence peaks and drops due to screening were larger for older birth-cohorts than younger birth-cohorts. In the general US population, these differing incidence peaks and drops across birth-cohorts overlap. Therefore, annual excess-incidence would be absent between 2029–2040, suggesting no overdiagnosis occurs. Using the microsimulation approach, overdiagnosis among screen-detected cases increased from 7.1 % to 9.5 % between 2018–2040, while overdiagnosis among all lung cancer cases decreased from 3.7 % to 1.4 %. Conclusion: Overdiagnosis studies should use appropriate methods to account for trends in background risk and screening eligibility in the general population. Estimates from randomized trials, based on the cumulative excess-incidence app

The impact of overdiagnosis on the selection of efficient lung cancer screening strategies

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136362/1/ijc30602_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136362/2/ijc30602.pd

All-cause mortality versus cancer-specific mortality as outcome in cancer screening trials: A review and modeling study

Background: All-cause mortality has been suggested as an end-point in cancer screening trials in order to avoid biases in attributing the cause of death. The aim of this study was to investigate which sample size and follow-up is needed to find a significant reduction in all-cause mortality. Methods: A literature review was conducted to identify previous studies that modeled the effect of screening on all-cause mortality. Microsimulation modeling was used to simulate breast cancer, lung cancer, and colorectal cancer screening trials. Model outputs were: cancer-specific deaths, all-cause deaths, and life-years gained per year of follow-up. Results: There were large differences between the evaluated cancers. For lung cancer, when 40 000 high-risk people are randomized to each arm, a significant reduction in all-cause mortality could be expected between 11 and 13 years of follow-up. For breast cancer, a significant reduction could be found between 16 and 26 years of follow-up for a sample size of over 300 000 women in each arm. For colorectal cancer, 600 000 persons in each arm were required to be followed for 15-20 years. Our systematic literature review identified seven papers, which showed highly similar results to our estimates. Conclusion: Cancer screening trials are able to demonstrate a significant reduction in all-cause mortality due to screening, but require very large sample sizes. Depending on the cancer, 40 000-600 000 participants per arm are needed to demonstrate a significant reduction. The reduction in all-cause mortality can only be detected between specific years of follow-up, more limited than the timeframe to detect a reduction in cancer-specific mortality

Selection of eligible participants for screening for lung cancer using primary care data

Lung cancer screening is effective if offered to people at increased risk of the disease. Currently, direct contact with potential participants is required for evaluating risk. A way to reduce the number of ineligible people contacted might be to apply risk-prediction models directly to digital primary care data, but model performance in this setting is unknown.Method: The Clinical Practice Research Datalink, a computerised, longitudinal primary care database, was used to evaluate the LLPv2 and PLCOm2012 models. Lung cancer occurrence over 5-6 years was measured in ever-smokers aged 50-80 years and compared with 5-year (LLPv2) and 6-year (PLCOm2012) predicted risk. Results: Over 5 and 6 years, 7,123 and 7,876 lung cancers occurred respectively from a cohort of 842,109 ever smokers. After recalibration, LLPV2 produced a c-statistic of 0.700 (0.694-0.710) but mean predicted risk was over-estimated (predicted: 4.61%, actual: 0.9%). PLCOm2012 showed similar performance (c-statistic: 0.679 (0.673–0.685), predicted risk: 3.76%. Applying risk-thresholds of 1% (LLPv2) and 0.15% (PLCOm2012), would avoid contacting 42.7% and 27.4% of ever-smokers who did not develop lung cancer for screening eligibility assessment, at the cost of missing 15.6% and 11.4% of lung cancers.Conclusion: Risk-prediction models showed only moderate discrimination when applied to routinely collected primary care data, which may be explained by quality and completeness of data. However, they may substantially reduce the number of people for initial evaluation of screening eligibility, at the cost of missing some lung cancers. Further work is needed to establish whether newer models have improved performance in primary care data

Comparing Benefits from Many Possible Computed Tomography Lung Cancer Screening Programs: Extrapolating from the National Lung Screening Trial Using Comparative Modeling

Background: The National Lung Screening Trial (NLST) demonstrated that in current and former smokers aged 55 to 74 years, with at least 30 pack-years of cigarette smoking history and who had quit smoking no more than 15 years ago, 3 annual computed tomography (CT) screens reduced lung cancer-specific mortality by 20% relative to 3 annual chest X-ray screens. We compared the benefits achievable with 576 lung cancer screening programs that varied CT screen number and frequency, ages of screening, and eligibility based on smoking. Methods and Findings: We used five independent microsimulation models with lung cancer natural history parameters previously calibrated to the NLST to simulate life histories of the US cohort born in 1950 under all 576 programs. ‘Efficient’ (within model) programs prevented the greatest number of lung cancer deaths, compared to no screening, for a given number of CT screens. Among 120 ‘consensus efficient’ (identified as efficient across models) programs, the average starting age was 55 years, the stopping age was 80 or 85 years, the average minimum pack-years was 27, and the maximum years since quitting was 20. Among consensus efficient programs, 11% to 40% of the cohort was screened, and 153 to 846 lung cancer deaths were averted per 100,000 people. In all models, annual screening based on age and smoking eligibility in NLST was not efficient; continuing screening to age 80 or 85 years was more efficient. Conclusions: Consensus results from five models identified a set of efficient screening programs that include annual CT lung cancer screening using criteria like NLST eligibility but extended to older ages. Guidelines for screening should also consider harms of screening and individual patient characteristics

Cost-effectiveness evaluation of the 2021 US Preventive Services Task Force recommendation for lung cancer screening

IMPORTANCE: The US Preventive Services Task Force (USPSTF) issued its 2021 recommendation on lung cancer screening, which lowered the starting age for screening from 55 to 50 years and the minimum cumulative smoking exposure from 30 to 20 pack-years relative to its 2013 recommendation. Although costs are expected to increase because of the expanded screening eligibility criteria, it is unknown whether the new guidelines for lung cancer screening are cost-effective. OBJECTIVE: To evaluate the cost-effectiveness of the 2021 USPSTF recommendation for lung cancer screening compared with the 2013 recommendation and to explore the cost-effectiveness of 6 alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years and an ending age for screening of 80 years but varied the starting ages for screening (50 or 55 years) and the number of years since smoking cessation (≤15, ≤20, or ≤25). DESIGN, SETTING, AND PARTICIPANTS: A comparative cost-effectiveness analysis using 4 independently developed microsimulation models that shared common inputs to assess the population-level health benefits and costs of the 2021 recommended screening strategy and 6 alternative screening strategies compared with the 2013 recommended screening strategy. The models simulated a 1960 US birth cohort. Simulated individuals entered the study at age 45 years and were followed up until death or age 90 years, corresponding to a study period from January 1, 2005, to December 31, 2050. EXPOSURES: Low-dose computed tomography in lung cancer screening programs with a minimum cumulative smoking exposure of 20 pack-years. MAIN OUTCOMES AND MEASURES: Incremental cost-effectiveness ratio (ICER) per quality-adjusted life-year (QALY) of the 2021 vs 2013 USPSTF lung cancer screening recommendations as well as 6 alternative screening strategies vs the 2013 USPSTF screening strategy. Strategies with a mean ICER lower than $100 000 per QALY were deemed cost-effective. RESULTS: The 2021 USPSTF recommendation was estimated to be cost-effective compared with the 2013 recommendation, with a mean ICER of$72 564 (range across 4 models, $59 493-$85 837) per QALY gained. The 2021 recommendation was not cost-effective compared with 6 alternative strategies that used the 20 pack-year criterion. Strategies associated with the most cost-effectiveness included those that expanded screening eligibility to include a greater number of former smokers who had not smoked for a longer duration (ie, ≤20 years and ≤25 years since smoking cessation vs ≤15 years since smoking cessation). In particular, the strategy that screened former smokers who quit within the past 25 years and began screening at age 55 years was associated with screening coverage closest to that of the 2021 USPSTF recommendation yet yielded greater cost-effectiveness, with a mean ICER of $66 533 (range across 4 models,$55 693-$80 539). CONCLUSIONS AND RELEVANCE: This economic evaluation found that the 2021 USPSTF recommendation for lung cancer screening was cost-effective; however, alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years but included individuals who quit smoking within the past 25 years may be more cost-effective and warrant further evaluation.Accepted manuscrip

Comparing benefits from many possible computed tomography lung cancer screening programs: Extrapolating from the National Lung Screening Trial using comparative modeling

Background: The National Lung Screening Trial (NLST) demonstrated that in current and former smokers aged 55 to 74 years, with at least 30 pack-years of cigarette smoking history and who had quit smoking no more than 15 years ago, 3 annual computed tomography (CT) screens reduced lung cancer-specific mortality by 20% relative to 3 annual chest X-ray screens. We compared the benefits achievable with 576 lung cancer screening programs that varied CT screen number and frequency, ages of screening, and eligibility based on smoking. Methods and Findings: We used five independent microsimulation models with lung cancer natural history parameters previously calibrated to the NLST to simulate life histories of the US cohort born in 1950 under all 576 programs. 'Efficient' (within model) programs prevented the greatest number of lung cancer deaths, compared to no screening, for a given number of CT screens. Among 120 'consensus efficient' (identified as efficient across models) programs, the average starting age was 55 years, the stopping age was 80 or 85 years, the average minimum pack-years was 27, and the maximum years since quitting was 20. Among consensus efficient programs, 11% to 40% of the cohort was screened, and 153 to 846 lung cancer deaths were averted per 100,000 people. In all models, annual screening based on age and smoking eligibility in NLST was not efficient; continuing screening to age 80 or 85 years was more efficient. Conclusions: Consensus results from five models identified a set of efficient screening programs that include annual CT lung cancer screening using criteria like NLST eligibility but extended to older ages. Guidelines for screening should also consider harms of screening and individual patient characteristics