Colorectal cancer (CRC) screening accounts for over 60% of cancer screening costs in the United States, prompting recurrent debates about its value. Yet CRC screening remains the main tool to curb overall CRC incidence, mortality, and disparities that affect Black Americans. Using the race-specific CRC-SPIN microsimulation model, we show that CRC screening in the United States simultaneously achieves three goals: it saves lives by preventing 24 deaths per 1000 Black Americans screened with the fecal immunochemical test (FIT) and 26 screened with colonoscopy; saves tax dollars by shifting costs from Medicare to private payers; and reduces racial incidence and mortality disparities, helping offset disparities in CRC survival. Both FIT and colonoscopy screening are cost-effective relative to no screening, with annual FIT remaining the most cost-effective option. Changes to policy requiring coverage of preventive care services must avoid compromising the effectiveness of CRC screening-arguably the greatest equalizer of cancer disparities.

Simulation models inform health policy decisions by integrating data from multiple sources and forecasting outcomes when there is a lack of comprehensive evidence from empirical studies. Such models have long supported health policy for cancer, the first or second leading cause of death in over 100 countries. Discrete-event simulation (DES) and Bayesian calibration have gained traction in the field of decision science because they enable flexible modeling of complex health conditions and produce estimates of model parameters that reflect real-world disease epidemiology and data uncertainty given model constraints. This uncertainty is then propagated to model-generated outputs, enabling decision-makers to assess confidence in recommendations and estimate the value of collecting additional information. However, there is limited end-to-end guidance on structuring a DES model for cancer progression, estimating its parameters using Bayesian calibration, and applying the calibration outputs to policy evaluation. To fill this gap, we introduce the DES Modeling Framework for Cancer Interventions and Population Health in R (DESCIPHR), an open-source codebase integrating a flexible DES model for the natural history of cancer, Bayesian calibration for parameter estimation, and an example application of screening strategy evaluation. To illustrate the framework, we apply DESCIPHR to calibrate bladder and colorectal cancer models to real-world cancer registry targets. We also introduce an automated method for generating data-informed parameter prior distributions and increase the functionality of a neural network emulator-based Bayesian calibration algorithm. We anticipate that the adaptable DESCIPHR modeling template will facilitate the construction of future decision models evaluating the risks and benefits of health interventions.

Importance:In colorectal cancer (CRC) screening, too many patients fail to receive follow-up colonoscopy after an abnormal fecal immunochemical test (FIT), and transportation is a frequently reported barrier. Objective:To determine the outcomes and cost-effectiveness of providing a rideshare intervention to patients with abnormal FIT results. Design, Setting, and Participants:The CRC-Simulated Population Model for Incidence and Natural History microsimulation model was used to simulate the outcomes and cost-effectiveness of a rideshare intervention to improve colonoscopy completion in a population-based CRC screening program. Cohorts were adherent to annual FIT-based screening; baseline analyses assumed that 35% would complete a follow-up colonoscopy. Data were analyzed from November 14, 2023, to July 8, 2025. Intervention:A $40 or $100 rideshare to increase completion of follow-up colonoscopy. Main Outcomes and Measures:Lifetime outcomes included the number of CRC cases, deaths, and life-years gained (LYG) per 1000 people screened and costs associated with improved completion of a colonoscopy after an abnormal FIT result. Results:Four single-age cohorts (ages 45, 55, 65, and 70 years on January 1, 2024) of 10 million people each were simulated. In cohorts with similar sex distribution as the US population (aged 45 years, 50.0% male; aged 55 years, 49.4% male); aged 65 years, 48.0% male; and aged 70 years, 46.9% male), compared with no intervention, using a rideshare intervention starting at age 45 years that costs $100 per ride to increase colonoscopy completion from 35% to 70% was associated with a reduction in CRC cases per 1000 by 26.3% (30.7 vs 41.6 cases per 1000), CRC deaths per 1000 by 32.5% (9.8 vs 14.6 cases per 1000), 24.9 LYG per 1000, and at $100 per ride cost $43 308 per 1000 people screened and saved $330 587 per 1000 people screened. Conclusions and Relevance:In a microsimulation model, increasing colonoscopy completion in a population with abnormal FIT results via a rideshare intervention was cost saving up to $100 per ride due to the combined outcome of cancer prevention and early detection.

Chronic hepatitis B virus (HBV) infection poses a significant global health threat, causing severe liver diseases including cirrhosis and hepatocellular carcinoma. We characterized HBV DNA kinetics in primary human hepatocytes (PHH) over 32 days post-inoculation (pi) and used agent-based modeling (ABM) to gain insights into HBV lifecycle and spread. Parallel PHH cultures were mock-treated or HBV entry inhibitor Myr-preS1 (6.25 μg/mL) was initiated 24h pi. In untreated PHH, 3 viral DNA kinetic patterns were identified: (1) an initial decline, followed by (2) rapid amplification, and (3) slower amplification/accumulation. In the presence of Myr-preS1, viral DNA and infected cell numbers in phase 3 were effectively blocked, with minimal to no increase. This suggests that phase 2 represents viral amplification in initially infected cells, while phase 3 corresponds to viral spread to naïve cells. The ABM reproduced well the HBV kinetic patterns observed and predicted that the viral eclipse phase lasts between 18 and 38 hours. After the eclipse phase, the viral production rate increases over time, starting with a slow production cycle of 1 virion per day, which gradually accelerates to 1 virion per hour after 3 days. Approximately 4 days later, virion production reaches a steady state production rate of 4 virions/hour. The estimated median efficacy of Myr-preS1 in blocking HBV spread was 91% (range: 90-92%). The HBV kinetics and the predicted estimates of the HBV eclipse phase duration and HBV production cycles in PHH are similar of those predicted in uPA/SCID mice with human livers.

OBJECTIVE: To describe the effect of geographically limited disasters on health plan (ie, contract) quality performance scores using a broad set of clinical quality and patient experience measures. STUDY DESIGN: Retrospective analyses to assess the impact of disasters on Medicare Advantage contracts' quality-of-care performance scores in 2017 and 2018 for 11 Part C clinical quality and patient experience measures used in the Medicare Advantage Star Ratings. METHODS: We calculated each Medicare Advantage contract's disaster exposure using the percentage of the contract's beneficiaries residing in a Federal Emergency Management Agency-designated disaster area during the measurement period. Using linear mixed models, we estimated the association between contract-level disaster exposures and performance scores during the performance period measured, with random effects for contract and fixed effects for year, contract characteristics, and the disaster exposure, using repeated cross-sectional data on contracts from 2016 to 2018. RESULTS: We found no evidence that geographically limited disasters meaningfully affected contract quality performance scores. The disasters studied were associated with statistically significant but small changes in performance scores for 1 of 11 measures in both years. CONCLUSIONS: The lack of evidence that being in a disaster-affected area had a meaningful negative impact on quality measure performance suggests that performance measurement programs are robust to the impact of shortterm localized disasters and continue to function as intended.

PurposeThe 2023 American College of Physicians (ACP) guidelines for colorectal cancer (CRC) screening are at odds with the United States Preventive Task Force (USPSTF) guidelines, with the former recommending screening starting at age 50 y and the latter at age 45 y. This article "stress tests" CRC colonoscopy screening strategies to investigate their robustness to uncertainties stemming from the natural history of disease and sensitivity of colonoscopy.MethodsThis study uses the CRC-SPIN microsimulation model to project the life-years gained (LYG) under several colonoscopy CRC screening strategies. The model was extended to include birth cohort effects on adenoma risk. We estimated natural history parameters under 2 different assumptions about the youngest age of adenoma initiation. For each, we generated 500 parameter sets to reflect uncertainty in the natural history parameters. We simulated 26 colonoscopy screening strategies and examined 4 different colonoscopy sensitivity assumptions, encompassing the range of sensitivities consistent with prior tandem colonoscopy studies. Across this set of scenarios, we identify efficient screening strategies and report posterior credible intervals for benefits of screening (LYG), burden (number of colonoscopies), and incremental burden-effectiveness ratios.ResultsProjected absolute screening benefits varied widely based on assumptions, but strategies starting at age 45 y were consistently in the efficiency frontier. Strategies in which screening starts at age 50 y with 10-y intervals were never efficient, saving fewer life-years than starting screening at age 45 y and performing colonoscopies every 15 y while requiring more colonoscopies per person.ConclusionsDecennial colonoscopy screening initiation at age 45 y remained a robust recommendation. Colonoscopy screening with a 10-y interval starting at age 50 y did not result in an efficient use of colonoscopies in any of the scenarios evaluated.HighlightsColorectal cancer colonoscopy screening strategies initiated at age 45 y were projected to yield more life-years gained while requiring the least number of colonoscopies across different model assumptions about disease natural history and colonoscopy sensitivity.Colonoscopy screening starting at age 50 y with a 10-y interval consistently underperformed strategies that started at age 45 y.

BACKGROUND:Fecal immunochemical test (FIT) performance for colorectal cancer screening varies by age and sex, yet most FIT-based screening programs use uniform positivity thresholds. This study assessed the potential benefits of stratifying FIT thresholds based on age and sex. METHODS:We conducted a meta-analysis of FIT sensitivity and specificity at various positivity thresholds by age and sex. We then used these estimates in 2 microsimulation models of colorectal cancer and projected lifetime clinical outcomes, incremental costs, and quality-adjusted life-years (QALYs) gained from age- and sex-stratified FIT strategies. FIT thresholds ranged from 10 to 50 µg hemoglobin per gram of feces. RESULTS:For current uniform FIT screening (20 µg hemoglobin/gram of feces), models projected 85.67 to 122.15 QALYs gained at incremental costs of ‒$982 to $504 per 1000 individuals compared with no screening. At equivalent costs to current uniform screening, only 1 model found stratified FIT approaches cost-effective, yielding a marginal increase of 1.04 and 1.10 QALYs gained/1000 female and male individuals, respectively. At a willingness-to-pay threshold of $100 000/QALYs gained, both models found stratified FIT cutoffs to be the best strategy, with cutoffs being equal to or higher for males and lowest at older ages (70-75 years). Uniform strategies showed comparable effectiveness, falling within 1 quality-adjusted life-day per person of efficient strategies at up to $112 more per person. Results were sensitive to FIT test performance characteristics and 1-time setup costs. CONCLUSION:Stratifying FIT thresholds by age and sex may be cost-effective compared to current screening. The gain in expected health benefits with stratified FIT screening, however, is likely small.

ImportanceSeveral noninvasive tests for colorectal cancer screening are available, but their effectiveness in settings with low adherence to screening and follow-up colonoscopy is not well documented.ObjectiveTo assess the cost-effectiveness of and outcomes associated with noninvasive colorectal cancer screening strategies, including new blood-based tests, in a population with low adherence to screening and ongoing surveillance colonoscopy.Design, Setting, and ParticipantsThe validated microsimulation model used for the decision analytical modeling study projected screening outcomes from 2025 to 2124 for a simulated cohort of 10 million individuals aged 50 years in 2025 and representative of a predominantly Hispanic or Latino patient population served by a Federally Qualified Health Center in Southern California. The simulated population had low adherence to first-step noninvasive testing (45%), second-step follow-up colonoscopy after an abnormal noninvasive test result (40%), and ongoing surveillance colonoscopy among patients with high-risk findings at follow-up colonoscopy (80%).ExposuresColorectal cancer screening strategies included no screening, an annual or biennial fecal immunochemical test, a triennial multitarget stool DNA test, and a triennial blood-based test. Using a blood-based test was assumed to increase first-step adherence by 17.5 percentage points.Main Outcomes and MeasuresOutcomes included colorectal cancer incidence and mortality, life-years gained and quality-adjusted life-years gained relative to no screening, costs, and net monetary benefit assuming a willingness to pay of $100 000 per quality-adjusted life-year gained.ResultsUnder realistic adherence assumptions, a program of annual fecal immunochemical testing was the most effective and cost-effective strategy, yielding 121 life-years gained per 1000 screened individuals and a net monetary benefit of $5883 per person. Triennial blood testing was the least effective, yielding 23 life-years gained per 1000, and was not cost-effective, with a negative net monetary benefit. Annual fecal immunochemical testing with 45% first-step adherence and 80% adherence to follow-up and surveillance colonoscopy yielded greater benefit than triennial blood testing with perfect adherence (88 vs 77 life-years gained per 1000).Conclusions and RelevanceThis study suggests that in a federally qualified health care setting, prioritizing the convenience of blood tests over less costly and more effective existing stool-based tests could result in higher costs and worse population-level outcomes. Novel screening modalities should be carefully evaluated for performance in community settings before widespread adoption.

Purpose To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET)’s SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets. Methods We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANNs) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo–based algorithms to obtain the joint posterior distributions of the CISNET-CRC models’ parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets. Results The optimal ANN for SimCRC had 4 hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had 1 hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 h for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN. Conclusions Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, such as the CISNET CRC models. In this work, we present a step-by-step guide to constructing emulators for calibrating 3 realistic CRC individual-level models using a Bayesian approach. Highlights We use artificial neural networks (ANNs) to build emulators that surrogate complex individual-based models to reduce the computational burden in the Bayesian calibration process. ANNs showed good performance in emulating the CISNET-CRC microsimulation models, despite having many input parameters and outputs. Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis. This work aims to support health decision scientists who want to quantify the uncertainty of calibrated parameters of computationally intensive simulation models under a Bayesian framework.

During the COVID-19 pandemic, health systems, including federally qualified health centers, experienced disruptions in colorectal cancer (CRC) screening. National organizations called for greater use of at-home stool-based testing followed by colonoscopy for those with abnormal test results to limit (in-person) colonoscopy exams to people with acute symptoms or who were high risk. This stool-test-first strategy may also be useful for adults with low-risk adenomas who are due for surveillance colonoscopy. We argue that colonoscopy is overused as a first-line screening method in low- and average-risk adults and as a surveillance tool among adults with small adenomas. Yet, simultaneously, many people do not receive much-needed colonoscopies. Delivering the right screening tests at intervals that reduce the risk of CRC, while minimizing patient inconvenience and procedural risks, can strengthen health-care systems. Risk stratification could improve efficiency of CRC screening, but because models that adequately predict risk are years away from clinical use, we need to optimize use of currently available technology—that is, low-cost fecal testing followed by colonoscopy for those with abnormal test results. The COVID-19 pandemic highlighted the urgent need to adapt to resource constraints around colonoscopies and showed that increased use of stool-based testing was possible. Learning how to adapt to such constraints without sacrificing patients’ health, particularly for patients who receive care at federally qualified health centers, should be a priority for CRC prevention research.

Novel liquid biopsy technologies are creating a watershed moment in cancer early detection. Evidence supporting population screening is nascent, but a rush to market the new tests is prompting cancer early detection researchers to revisit the standard blueprint that the Early Detection Research Network established to evaluate novel screening biomarkers. In this commentary, we review the Early Detection Research Network's Phases of Biomarker Development (PBD) for rigorous evaluation of novel early detection biomarkers and discuss both hazards and opportunities involved in expedited evaluation. According to the PBD, for a biomarker-based test to be considered for population screening, 1) test sensitivity in a prospective screening setting must be adequate, 2) the shift to early curable stages must be meaningful, and 3) any stage shift must translate into clinically significant mortality benefit. In the past, determining mortality benefit has required lengthy randomized screening trials, but interest is growing in expedited trial designs with shorter-term endpoints. Whether and how best to use such endpoints in a manner that retains the rigor of the PBD remains to be determined. We discuss how computational disease modeling can be harnessed to learn about screening impact and meet the needs of the moment.

BACKGROUND:Blood-based biomarker tests can potentially change the landscape of colorectal cancer (CRC) screening. We characterize the conditions under which blood test screening would be as effective and cost-effective as annual fecal immunochemical testing or decennial colonoscopy. METHODS:We used the 3 Cancer Information and Surveillance Modeling Network-Colon models to compare scenarios of no screening, annual fecal immunochemical testing, decennial colonoscopy, and a blood test meeting Centers for Medicare & Medicaid (CMS) coverage criteria (74% CRC sensitivity and 90% specificity). We varied the sensitivity to detect CRC (74%-92%), advanced adenomas (10%-50%), screening interval (1-3 years), and test cost ($25-$500). Primary outcomes included quality-adjusted life-years (QALY) gained from screening and costs for a US average-risk cohort of individuals aged 45 years. RESULTS:Annual fecal immunochemical testing yielded 125-163 QALY gained per 1000 at a cost of $3811-$5384 per person, whereas colonoscopy yielded 132-177 QALY gained at a cost of $5375-$7031 per person. A blood test with 92% CRC sensitivity and 50% advanced adenoma sensitivity yielded 117-162 QALY gained if used every 3 years and 133-173 QALY gained if used every year but would not be cost-effective if priced above $125 per test. If used every 3 years, a $500 blood test only meeting CMS coverage criteria yielded 83-116 QALY gained at a cost of $8559-$9413 per person. CONCLUSION:Blood tests that only meet CMS coverage requirements should not be recommended to patients who would otherwise undergo screening by colonoscopy or fecal immunochemical testing because of lower benefit. Blood tests need higher advanced adenoma sensitivity (above 40%) and lower costs (below $125) to be cost-effective.

BACKGROUND & AIMS:A blood-based colorectal cancer (CRC) screening test may increase screening participation. However, blood tests may be less effective than current guideline-endorsed options. The Centers for Medicare & Medicaid Services (CMS) covers blood tests with sensitivity of at least 74% for detection of CRC and specificity of at least 90%. In this study, we investigate whether a blood test that meets these criteria is cost-effective. METHODS:Three microsimulation models for CRC (MISCAN-Colon, CRC-SPIN, and SimCRC) were used to estimate the effectiveness and cost-effectiveness of triennial blood-based screening (from ages 45 to 75 years) compared to no screening, annual fecal immunochemical testing (FIT), triennial stool DNA testing combined with an FIT assay, and colonoscopy screening every 10 years. The CMS coverage criteria were used as performance characteristics of the hypothetical blood test. We varied screening ages, test performance characteristics, and screening uptake in a sensitivity analysis. RESULTS:Without screening, the models predicted 77-88 CRC cases and 32-36 CRC deaths per 1000 individuals, costing $5.3-$5.8 million. Compared to no screening, blood-based screening was cost-effective, with an additional cost of $25,600-$43,700 per quality-adjusted life-year gained (QALYG). However, compared to FIT, triennial stool DNA testing combined with FIT, and colonoscopy, blood-based screening was not cost-effective, with both a decrease in QALYG and an increase in costs. FIT remained more effective (+5-24 QALYG) and less costly (-$3.2 to -$3.5 million) than blood-based screening even when uptake of blood-based screening was 20 percentage points higher than uptake of FIT. CONCLUSION:Even with higher screening uptake, triennial blood-based screening, with the CMS-specified minimum performance sensitivity of 74% and specificity of 90%, was not projected to be cost-effective compared with established strategies for colorectal cancer screening.

Colorectal Cancer (CRC) is a leading cause of cancer deaths in the United States. Despite significant overall declines in CRC incidence and mortality, there has been an alarming increase in CRC among people younger than 50. This study uses an established microsimulation model, CRC-SPIN, to perform a 'stress test' of colonoscopy screening strategies. First, we expand CRC-SPIN to include birth-cohort effects. Second, we estimate natural history model parameters via Incremental Mixture Approximate Bayesian Computation (IMABC) for two model versions to characterize uncertainty while accounting for increased early CRC onset. Third, we simulate 26 colonoscopy screening strategies across the posterior distribution of estimated model parameters, assuming four different colonoscopy sensitivities (104 total scenarios). We find that model projections of screening benefit are highly dependent on natural history and test sensitivity assumptions, but in this stress test, the policy recommendations are robust to the uncertainties considered.

Supplementary Table S1. Characteristics of PROSPR participants with a positive fecal occult blood test with no covariate information missing, 2011-2012 (N=47,827). Supplementary Table S2. Associations between patient characteristics and time to colonoscopy follow-up after positive fecal occult blood test in PROSPR healthcare systems, 2011-2012, over different follow-up periods.