Vahdat, Vahab

ABSTRACT Background Several colorectal cancer (CRC) screening modalities are guideline-recommended in the United States, yet they vary considerably in screening interval and real-world adherence. As a result, single-round test performance may not reflect cumulative effectiveness over time. This study compared the 10-year longitudinal outcomes of two CRC screening strategies— triennial next-generation multitarget stool DNA testing (ng mt-sDNA) and decennial screening colonoscopy. Methods This study used the validated, microsimulation-based Colorectal Cancer and Adenoma Incidence and Mortality (CRC-AIM) model to estimate 10-year cumulative outcomes for two guideline-recommended screening strategies: triennial ng mt-sDNA and decennial colonoscopy. Model inputs included test-specific performance and real-world adherence. Outcomes included CRC and precancerous lesions detected, CRC mortality reductions, and life-years gained (LYG). Sensitivity analyses examined the effects of varying both screening adherence and follow-up colonoscopy adherence. Results Over 10 years per 1,000 individuals offered screening, the ng mt-sDNA screening test detected 13% more precancerous lesions and 11% more CRC cases than colonoscopy, with a greater proportion of CRCs identified through screening rather than symptomatic detection. ng mt-sDNA resulted in greater CRC mortality reduction (33% vs 20%) and 62% more life-years gained, with consistent findings across sensitivity analyses. Conclusions With real-world adherence, screening with triennial ng mt-sDNA demonstrates superior cumulative effectiveness compared with decennial colonoscopy, driven by higher adherence and favorable longitudinal performance. These findings support the expanded use of noninvasive stool-based screening to reduce CRC mortality and alleviate capacity constraints associated with colonoscopy-based screening. Broader adoption of ng mt-sDNA may enhance population-level CRC prevention by increasing participation and improving early detection across the screening eligible population. Plain language summary Colorectal cancer screening tests are recommended at different time intervals and completed at different adherence rates in clinical practice. The analysis used a validated simulation model to compare 10-year outcomes of triennial next-generation multi-target stool DNA test (ng mt-sDNA) with a single colonoscopy, accounting for real-world screening and follow-up colonoscopy adherence. Our findings indicate that repeated ng mt-sDNA provides greater cumulative screening effectiveness than colonoscopy over a 10-year period.

Abstract Background Recommended noninvasive strategies for average-risk colorectal cancer (CRC) screening include multitarget stool DNA and fecal immunochemical test from ages 45 to 75 years. With new clinical trials, performance data for next-generation multitarget stool DNA, multitarget stool RNA, and blood-based screening tests are now available. This decision analytical model study evaluated the estimated benefit-to-burden ratio by means of efficient frontiers for noninvasive established and emerging CRC screening strategies. Methods Outcomes were estimated using the Colorectal Cancer and Adenoma Incidence and Mortality microsimulation model for average-risk individuals in the United States. Screening strategies were next-generation multitarget stool DNA (an updated marker panel), fecal immunochemical tests, multitarget stool RNA, or blood-based tests every 1-3 years, over various age ranges. Test performance inputs were derived from recent large clinical trials. A strategy was deemed efficient if no other strategy provided more life-years gained with equivalent or fewer lifetime colonoscopies and near-efficient if within 3 days of life-years gained of the efficient frontier. Results All modeled screening strategies resulted in life-years gained vs no screening. No strategy using blood-based tests was efficient or near-efficient. Overall, 10 strategies were efficient (6 next-generation multitarget stool DNA and 4 fecal immunochemical tests), including 2 strategies among those ages 45-75 years (biennial and triennial next-generation multitarget stool DNA). Overall, 22 strategies were near-efficient, including 4 strategies among those ages 45-75 years (annual, biennial, or triennial fecal immunochemical test; annual next-generation multitarget stool DNA). Conclusion Based on this modeling study, next-generation multitarget stool DNA was the only noninvasive screening test at guideline-endorsed interval and age-recommended ranges that was deemed efficient. Blood-based and multitarget stool RNA strategies were deemed not efficient for primary screening.

Abstract The substantial carbon footprint imparted by medical services warrants increased attention to their environmental impact. National guideline organizations such as the US Preventive Services Task Force (USPSTF) recommend multiple modalities for average-risk colorectal cancer (CRC) screening with varying resource intensity. The aim of this study was to quantify the environmental burden for 2 of the most used CRC screening modalities, colonoscopy and the multi-target stool DNA (mt-sDNA) test. A validated CRC microsimulation model was used to estimate the number of screening and follow-up tests for a cohort of 1 million average-risk individuals who underwent screening between ages 45 and 75. Component resources used for mt-sDNA, including waste products, energy, and transportation for colonoscopy and mt-sDNA, were collected from January 1, 2023, to January 1, 2024, and converted to carbon-equivalent emissions. Resources used for colonoscopy were captured from the literature. Resources devoted to screening colonoscopy were substantially (59%) higher than those to mt-sDNA, even when including follow-up colonoscopy. Of note, follow-up colonoscopy accounted for the majority (64%) of total emissions for the mt-sDNA screening strategy. Compared with colonoscopy screening, mt-sDNA substantially reduces the carbon emissions attributable to population-level CRC screening. Environmental impact should be included as a factor when choosing among guideline-recommended CRC screening strategies.

Abstract Colorectal cancer is the second leading cause of cancer-related mortality in adults in the United States. Despite compelling evidence of improved outcomes in colorectal cancer, screening rates are not optimal. This study aimed to characterize colorectal cancer screening trends over the last two decades and assess the impact of various screening modalities on overall colorectal cancer screening rates. Using National Health Interview Survey data from 2005 to 2021, we examined colorectal cancer screening [colonoscopy, multitarget stool DNA (mt-sDNA), fecal occult blood test (FOBT)/fecal immunochemical test, sigmoidoscopy, CT colonography] rates among adults ages 50–75 years (n = 85,571). A pseudo-time-series cross-sectional (pseudo-TSCS) analysis was conducted including a random effects generalized least squares regression model to estimate the relative impact of each modality on changes in colorectal cancer screening rates. Among 50 to 75 year olds, the estimated colorectal cancer screening rate increased from 47.7% in 2005 to 69.9% in 2021, with the largest increase between 2005 and 2010 (47.7%–60.7%). Rates subsequently plateaued until 2015 but increased from 63.5% in 2015 to 69.9% in 2018. This was primarily driven by the increased use of mt-sDNA (2.5% in 2018 to 6.6% in 2021). Pseudo-TSCS analysis results showed that mt-sDNA contributed substantially to the increase in overall screening rates (77.3%; P < 0.0001) between 2018 and 2021. While colorectal cancer screening rates increased from 2005 to 2021, they remain below the 80% goal. The introduction of mt-sDNA, a noninvasive screening test may have improved overall rates. Sustained efforts are required to further increase screening rates to improve patient outcomes and offering a range of screening options is likely to contribute to achieving this goal. Prevention Relevance: This retrospective study highlights the importance of convenient stool-based colorectal cancer screening options to achieve the national goal of 80% for overall colorectal cancer screening rates. Empowering screening-eligible individuals with a choice for their colorectal cancer screening tests is imperative.

Objectives Machine learning (ML)–based emulators improve the calibration of decision-analytical models, but their performance in complex microsimulation models is yet to be determined. Methods We demonstrated the use of an ML-based emulator with the Colorectal Cancer (CRC)-Adenoma Incidence and Mortality (CRC-AIM) model, which includes 23 unknown natural history input parameters to replicate the CRC epidemiology in the United States. We first generated 15,000 input combinations and ran the CRC-AIM model to evaluate CRC incidence, adenoma size distribution, and the percentage of small adenoma detected by colonoscopy. We then used this data set to train several ML algorithms, including deep neural network (DNN), random forest, and several gradient boosting variants (i.e., XGBoost, LightGBM, CatBoost) and compared their performance. We evaluated 10 million potential input combinations using the selected emulator and examined input combinations that best estimated observed calibration targets. Furthermore, we cross-validated outcomes generated by the CRC-AIM model with those made by CISNET models. The calibrated CRC-AIM model was externally validated using the United Kingdom Flexible Sigmoidoscopy Screening Trial (UKFSST). Results The DNN with proper preprocessing outperformed other tested ML algorithms and successfully predicted all 8 outcomes for different input combinations. It took 473 s for the trained DNN to predict outcomes for 10 million inputs, which would have required 190 CPU-years without our DNN. The overall calibration process took 104 CPU-days, which included building the data set, training, selecting, and hyperparameter tuning of the ML algorithms. While 7 input combinations had acceptable fit to the targets, a combination that best fits all outcomes was selected as the best vector. Almost all of the predictions made by the best vector laid within those from the CISNET models, demonstrating CRC-AIM’s cross-model validity. Similarly, CRC-AIM accurately predicted the hazard ratios of CRC incidence and mortality as reported by UKFSST, demonstrating its external validity. Examination of the impact of calibration targets suggested that the selection of the calibration target had a substantial impact on model outcomes in terms of life-year gains with screening. Conclusions Emulators such as a DNN that is meticulously selected and trained can substantially reduce the computational burden of calibrating complex microsimulation models. Highlights Calibrating a microsimulation model, a process to find unobservable parameters so that the model fits observed data, is computationally complex. We used a deep neural network model, a popular machine learning algorithm, to calibrate the Colorectal Cancer Adenoma Incidence and Mortality (CRC-AIM) model. We demonstrated that our approach provides an efficient and accurate method to significantly speed up calibration in microsimulation models. The calibration process successfully provided cross-model validation of CRC-AIM against 3 established CISNET models and also externally validated against a randomized controlled trial.

Abstract Commercial insurance covers a follow-up colonoscopy after a positive colorectal cancer–screening test with no patient cost-sharing. Instituting a similar policy for Medicare beneficiaries may increase screening adherence and improve outcomes. The cost-effectiveness of stool-based colorectal cancer screening was compared across adherence scenarios that assumed Medicare coinsurance status quo (20% for follow-up colonoscopy) or waived coinsurance. The CRC-AIM model simulated previously unscreened eligible Medicare beneficiaries undergoing stool-based colorectal cancer screening at age 65 for 10 years. Medicare costs, colorectal cancer cases, colorectal cancer–related deaths, life-years gained (LYG), and quality-adjusted life-years (QALY) were estimated versus no screening. Scenario 1 (S1) assumed 20% coinsurance for follow-up colonoscopy. Scenario 2 (S2) assumed waived coinsurance without adherence changes. Scenarios 3–7 (S3–S7) assumed that waiving coinsurance increased real-world stool-based screening and/or follow-up colonoscopy adherence by 5% or 10%. Sensitivity analyses assumed 1%–4% increased adherence. Cost-effectiveness threshold was ≤$100,000/QALY. Waiving coinsurance without adherence changes (S2) did not affect outcomes versus S1. S3–S7 versus S1 over 10 years estimated up to 3.6 fewer colorectal cancer cases/1,000 individuals, up to 2.1 fewer colorectal cancer deaths, up to 20.7 more LYG, and had comparable total costs per-patient (≤$6,478 vs. $6,449, respectively) as reduced colorectal cancer medical costs offset increased screening and colonoscopy costs. In sensitivity analyses, any increase in adherence after waiving coinsurance was cost-effective and increased LYG. In simulated Medicare beneficiaries, waiving coinsurance for follow-up colonoscopy after a positive stool-based test improved outcomes and was cost-effective when assumed to modestly increase colorectal cancer screening and/or follow-up colonoscopy adherence. Prevention Relevance: Follow-up colonoscopy after a positive stool-based test is necessary to complete the colorectal cancer-screening process. This analysis demonstrated that in a simulated Medicare population, waiving coinsurance for a follow-up colonoscopy improved estimated outcomes and was cost-effective when it was assumed that waiving the coinsurance modestly increased screening adherence. See related Spotlight, p. 641