Effectiveness and Cost-Effectiveness of Colorectal Cancer Screening With a Blood Test That Meets the Centers for Medicare & Medicaid Services Coverage Decision.

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.

Maximizing scarce colonoscopy resources: the crucial role of stool-based tests.

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.

Black-White disparities in colorectal cancer outcomes: a simulation study of screening benefit.

The US Black population has higher colorectal cancer (CRC) incidence rates and worse CRC survival than the US White population, as well as historically lower rates of CRC screening. The Surveillance, Epidemiology, and End Results incidence rate data in people diagnosed between the ages of 20 and 45 years, before routine CRC screening is recommended, were analyzed to estimate temporal changes in CRC risk in Black and White populations. There was a rapid rise in rectal and distal colon cancer incidence in the White population but not the Black population, and little change in proximal colon cancer incidence for both groups. In 2014-2018, CRC incidence per 100 000 was 17.5 (95% confidence interval [CI] = 15.3 to 19.9) among Black individuals aged 40-44 years and 16.6 (95% CI = 15.6 to 17.6) among White individuals aged 40-44 years; 42.3% of CRCs diagnosed in Black patients were proximal colon cancer, and 41.1% of CRCs diagnosed in White patients were rectal cancer. Analyses used a race-specific microsimulation model to project screening benefits, based on life-years gained and lifetime reduction in CRC incidence, assuming these Black-White differences in CRC risk and location. The projected benefits of screening (via either colonoscopy or fecal immunochemical testing) were greater in the Black population, suggesting that observed Black-White differences in CRC incidence are not driven by differences in risk. Projected screening benefits were sensitive to survival assumptions made for Black populations. Building racial disparities in survival into the model reduced projected screening benefits, which can bias policy decisions.

Projected long-term effects of colorectal cancer screening disruptions following the COVID-19 pandemic.

The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in colorectal cancer (CRC) outcomes due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term CRC outcomes was measured by the number of life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in CRC outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

Randomized Trial of Facilitated Adherence to Screening Colonoscopy vs Sequential Fecal-Based Blood Test.

BACKGROUND & AIMS: Colorectal cancer (CRC) screening guidelines include screening colonoscopy and sequential high-sensitivity fecal occult blood testing (HSgFOBT), with expectation of similar effectiveness based on the assumption of similar high adherence. However, adherence to screening colonoscopy compared with sequential HSgFOBT has not been reported. In this randomized clinical trial, we assessed adherence and pathology findings for a single screening colonoscopy vs sequential and nonsequential HSgFOBTs. METHODS: Participants aged 40-69 years were enrolled at 3 centers representing different clinical settings. Participants were randomized into a single screening colonoscopy arm vs sequential HSgFOBT arm composed of 4-7 rounds. Initial adherence to screening colonoscopy and sequential adherence to HSgFOBT, follow-up colonoscopy for positive HSgFOBT tests, crossover to colonoscopy, and detection of advanced neoplasia or large serrated lesions (ADN-SERs) were measured. RESULTS: There were 3523 participants included in the trial; 1761 and 1762 participants were randomized to the screening colonoscopy and HSgFOBT arms, respectively. Adherence was 1473 (83.6%) for the screening colonoscopy arm vs 1288 (73.1%) for the HSgFOBT arm after 1 round (relative risk [RR], 1.14; 95% CI, 1.10-1.19; P ≤ .001), but only 674 (38.3%) over 4 sequential HSgFOBT rounds (RR, 2.19; 95% CI, 2.05-2.33). Overall adherence to any screening increased to 1558 (88.5%) in the screening colonoscopy arm during the entire study period and 1493 (84.7%) in the HSgFOBT arm (RR, 1.04; 95% CI, 1.02-1.07). Four hundred thirty-six participants (24.7%) crossed over to screening colonoscopy during the first 4 rounds. ADN-SERs were detected in 121 of the 1473 participants (8.2%) in the colonoscopy arm who were adherent to protocol in the first 12 months of the study, whereas detection of ADN-SERs among those who were not sequentially adherent (n = 709) to HSgFOBT was subpar (0.6%) (RR, 14.72; 95% CI, 5.46-39.67) compared with those who were sequentially adherent (3.3%) (n = 647) (RR, 2.52; 95% CI, 1.61-3.98) to HSgFOBT in the first 4 rounds. When including colonoscopies from HSgFOBT patients who were never positive yet crossed over (n = 1483), 5.5% of ADN-SERs were detected (RR, 1.50; 95% CI, 1.15-1.96) in the first 4 rounds. CONCLUSIONS: Observed adherence to sequential rounds of HSgFOBT was suboptimal compared with a single screening colonoscopy. Detection of ADN-SERs was inferior when nonsequential HSgFOBT adherence was compared with sequential adherence. However, the greatest number of ADN-SERs was detected among those who crossed over to colonoscopy and opted to receive a colonoscopy. The effectiveness of an HSgFOBT screening program may be enhanced if crossover to screening colonoscopy is permitted. CLINICALTRIALS: gov, Number: NCT00102011.

Robustness Analysis of Colorectal Cancer Colonoscopy Screening Strategies.

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.

Impact and Recovery from COVID-19-Related Disruptions in Colorectal Cancer Screening and Care in the US: A Scenario Analysis.

BACKGROUND: Many colorectal cancer-related procedures were suspended during the COVID-19 pandemic. In this study, we predict the impact of resulting delays in screening (colonoscopy, FIT, and sigmoidoscopy) and diagnosis on colorectal cancer-related outcomes, and compare different recovery scenarios. METHODS: Using the MISCAN-Colon model, we simulated the US population and evaluated different impact and recovery scenarios. Scenarios were defined by the duration and severity of the disruption (percentage of eligible adults affected), the length of delays, and the duration of the recovery. During recovery (6, 12 or 24 months), capacity was increased to catch up missed procedures. Primary outcomes were excess colorectal cancer cases and -related deaths, and additional colonoscopies required during recovery. RESULTS: With a 24-month recovery, the model predicted that the US population would develop 7,210 (0.18%) excess colorectal cancer cases during 2020-2040, and 6,950 (0.65%) excess colorectal cancer-related deaths, and require 108,500 (8.6%) additional colonoscopies per recovery month, compared with a no-disruption scenario. Shorter recovery periods of 6 and 12 months, respectively, decreased excess colorectal cancer-related deaths to 4,190 (0.39%) and 4,580 (0.43%), at the expense of 260,200-590,100 (20.7%-47.0%) additional colonoscopies per month. CONCLUSIONS: The COVID-19 pandemic will likely cause more than 4,000 excess colorectal cancer-related deaths in the US, which could increase to more than 7,000 if recovery periods are longer. IMPACT: Our results highlight that catching-up colorectal cancer-related services within 12 months provides a good balance between required resources and mitigation of the impact of the disruption on colorectal cancer-related deaths.

Use of 2-Stage Modeling to Identify How Colorectal Cancer Risk Changes With Period and Cohort.

Colorectal cancer (CRC) incidence rates have decreased among adults aged 50 years or older while increasing in adults under age 50 years. Understanding these trends is challenging because of the multiple related time scales of age, diagnosis period, and birth cohort. We analyzed incidence rates of rectal, distal colon, and proximal colon cancer for individuals aged 20 years or more from the Surveillance, Epidemiology, and End Results Program for diagnosis years 1978-2017. We used a 2-stage generalized linear model to determine age, period, and cohort effects for CRC incidence. We first estimated birth cohort effects among people under age 45 years. We used these results to specify prior distributions for cohort effects in a Bayesian model to estimate period effects among people aged 45 years or more. There was no evidence of period effects for people under age 45 years. Risks of rectal and distal colon cancer increased for later birth cohorts. Compared with the 1943-1952 birth cohort, the 1983-1992 birth cohort had 2.2 times the risk of rectal cancer, 1.9 times the risk of distal colon cancer, and 1.3 times the risk of proximal colon cancer. For people aged ≥45 years, period effects showed declines in CRC risk that were attributable to screening.

The Impact of Mindfulness Meditation Programs on Performance-Related Outcomes: Implications for the U.S. Army.

Although studies have suggested that mindfulness-based interventions might be effective in enhancing military readiness and resilience, this has not been rigorously evaluated. This study presents results from a systematic review and meta-analyses of research examining how mindfulness meditation affects 13 performance-related outcomes of interest to the U.S. Army and broader military. The authors supplemented the systematic review by examining how mindfulness meditation could support stress management and exploring characteristics of selected mindfulness programs. The goal was to develop recommendations for mindfulness meditation programs for soldiers, should the Army choose to implement such programs in the future. Findings suggest that mindfulness may improve some aspects of attention and emotion regulation, impulsivity, and work-related morale and social support. The available evidence does not suggest that mindfulness improves other outcomes of interest to the Army. Notably, mindfulness meditation programs reduce stress and may reduce parental stress, which could benefit Army families. Yet more research is needed to identify best practices for implementing mindfulness programs in the military. The authors recommend conducting high-quality evaluations of mindfulness meditation with soldiers and assessing the effect of mindfulness meditation on military families.

Reopening Under Uncertainty: Stress-Testing California's COVID-19 Exit Strategy.

The coronavirus disease 2019 pandemic required significant public health interventions from local governments. Early in the pandemic, RAND researchers developed a decision support tool to provide policymakers with insight into the trade-offs they might face when choosing among nonpharmaceutical intervention levels. Using an updated version of the model, the researchers performed a stress-test of a variety of alternative reopening plans, using California as an example. This article presents the general lessons learned from these experiments and discusses four characteristics of the best reopening strategies.

Sequentially calibrating a Bayesian microsimulation model to incorporate new information and assumptions.

BACKGROUND: Microsimulation models are mathematical models that simulate event histories for individual members of a population. They are useful for policy decisions because they simulate a large number of individuals from an idealized population, with features that change over time, and the resulting event histories can be summarized to describe key population-level outcomes. Model calibration is the process of incorporating evidence into the model. Calibrated models can be used to make predictions about population trends in disease outcomes and effectiveness of interventions, but calibration can be challenging and computationally expensive. METHODS: This paper develops a technique for sequentially updating models to take full advantage of earlier calibration results, to ultimately speed up the calibration process. A Bayesian approach to calibration is used because it combines different sources of evidence and enables uncertainty quantification which is appealing for decision-making. We develop this method in order to re-calibrate a microsimulation model for the natural history of colorectal cancer to include new targets that better inform the time from initiation of preclinical cancer to presentation with clinical cancer (sojourn time), because model exploration and validation revealed that more information was needed on sojourn time, and that the predicted percentage of patients with cancers detected via colonoscopy screening was too low. RESULTS: The sequential approach to calibration was more efficient than recalibrating the model from scratch. Incorporating new information on the percentage of patients with cancers detected upon screening changed the estimated sojourn time parameters significantly, increasing the estimated mean sojourn time for cancers in the colon and rectum, providing results with more validity. CONCLUSIONS: A sequential approach to recalibration can be used to efficiently recalibrate a microsimulation model when new information becomes available that requires the original targets to be supplemented with additional targets.

Unequal Recovery in Colorectal Cancer Screening Following the COVID-19 Pandemic: A Comparative Microsimulation Analysis.

The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in access to colorectal cancer (CRC) screening due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term colorectal cancer (CRC) outcomes was measured by the number of Life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in colorectal cancer outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

A Simple Method for Simulating Dementia Onset and Death within an Existing Demographic Model.

BACKGROUND: Dementia is a common disease that has an impact on both the affected individual and family members who provide caregiving. Simulation models can assist in setting policy that anticipates public health needs by predicting the demand for and availability of care. OBJECTIVE: We developed a relatively simple method for simulating the onset of dementia that can be used in combination with an existing microsimulation model. METHODS: We started with Socsim, a demographic microsimulation model that simulates a population with family kinship networks. We simulated dementia in the Socsim population by simulating the number of individuals diagnosed with dementia in their lifetime and the ages of onset and death from dementia for each of these dementia cases. We then matched dementia cases to the simulated population based on age at death, so for each individual, we simulate whether they develop dementia and, if so, their age at onset. This approach simulates dementia onset but does not alter the demographic model's simulated age of death. RESULTS: We selected model dementia parameters so that the combined Socsim-Dementia model reproduces published dementia prevalence rates and survival times after diagnosis. CONCLUSIONS: Adding simulation of dementia to a kinship network model enables prediction of the availability of family caregivers for people with dementia under a range of different assumptions about future fertility, mortality, and dementia risk. We demonstrated how to add simulation of dementia onset and death to an existing microsimulation model to obtain a method for predicting dementia prevalence in the context of another more detailed model. The approach we developed can be generalized to simulate other progressive health conditions that affect mortality.

Too Good to Be True? Evaluation of Colonoscopy Sensitivity Assumptions Used in Policy Models.

BACKGROUND: Models can help guide colorectal cancer screening policy. Although models are carefully calibrated and validated, there is less scrutiny of assumptions about test performance. METHODS: We examined the validity of the CRC-SPIN model and colonoscopy sensitivity assumptions. Standard sensitivity assumptions, consistent with published decision analyses, assume sensitivity equal to 0.75 for diminutive adenomas (<6 mm), 0.85 for small adenomas (6-10 mm), 0.95 for large adenomas (≥10 mm), and 0.95 for preclinical cancer. We also selected adenoma sensitivity that resulted in more accurate predictions. Targets were drawn from the Wheat Bran Fiber study. We examined how well the model predicted outcomes measured over a three-year follow-up period, including the number of adenomas detected, the size of the largest adenoma detected, and incident colorectal cancer. RESULTS: Using standard sensitivity assumptions, the model predicted adenoma prevalence that was too low (42.5% versus 48.9% observed, with 95% confidence interval 45.3%-50.7%) and detection of too few large adenomas (5.1% versus 14.% observed, with 95% confidence interval 11.8%-17.4%). Predictions were close to targets when we set sensitivities to 0.20 for diminutive adenomas, 0.60 for small adenomas, 0.80 for 10- to 20-mm adenomas, and 0.98 for adenomas 20 mm and larger. CONCLUSIONS: Colonoscopy may be less accurate than currently assumed, especially for diminutive adenomas. Alternatively, the CRC-SPIN model may not accurately simulate onset and progression of adenomas in higher-risk populations. IMPACT: Misspecification of either colonoscopy sensitivity or disease progression in high-risk populations may affect the predicted effectiveness of colorectal cancer screening. When possible, decision analyses used to inform policy should address these uncertainties.See related commentary by Etzioni and Lange, p. 702.

The impact of cumulative colorectal cancer screening delays: A simulation study.

OBJECTIVE: Annual fecal immunochemical tests can reduce colorectal cancer incidence and mortality. However, screening is a multi-step process and most patients do not perfectly adhere to guideline-recommended screening schedules. Our objective was to compare the reduction in colorectal cancer incidence and life-years gained based on US guideline-concordant fecal immunochemical test screening to scenarios with a range of delays. METHOD: The Colorectal Cancer Simulated Population model for Incidence and Natural history (CRC-SPIN) microsimulation model was used to estimate the effect of systematic departures from fecal immunochemical test screening guidelines on lifetime screening benefit. RESULTS: The combined effect of consistent modest delays in screening initiation (1 year), repeated fecal immunochemical test screening (3 months), and receipt of follow-up or surveillance colonoscopy (3 months) resulted in up to 1.3 additional colorectal cancer cases per 10,000, 0.4 additional late-stage colorectal cancer cases per 10,000 and 154.7 fewer life-years gained per 10,000. A 5-year delay in screening initiation had a larger impact on screening effectiveness than consistent small delays in repeated fecal immunochemical test screening or receipt of follow-up colonoscopy after an abnormal fecal immunochemical test. The combined effect of consistent large delays in screening initiation (5 years), repeated fecal immunochemical test screening (6 months), and receipt of follow-up or surveillance colonoscopy (6 months) resulted in up to 3.7 additional colorectal cancer cases per 10,000, 1.5 additional late-stage colorectal cancer cases per 10,000 and 612.3 fewer life-years gained per 10,000. CONCLUSIONS: Systematic delays across the screening process can result in meaningful reductions in colorectal cancer screening effectiveness, especially for longer delays. Screening delays could drive differences in colorectal cancer incidence across patient groups with differential access to screening.

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies.

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.

Reopening California : Seeking Robust, Non-Dominated COVID-19 Exit Strategies.

Amid global scarcity of COVID-19 vaccines and the threat of new variant strains, California and other jurisdictions face the question of when and how to implement and relax COVID-19 Nonpharmaceutical Interventions (NPIs). While policymakers have attempted to balance the health and economic impacts of the pandemic, decentralized decision-making, deep uncertainty, and the lack of widespread use of comprehensive decision support methods can lead to the choice of fragile or inefficient strategies. This paper uses simulation models and the Robust Decision Making (RDM) approach to stress-test California's reopening strategy and other alternatives over a wide range of futures. We find that plans which respond aggressively to initial outbreaks are required to robustly control the pandemic. Further, the best plans adapt to changing circumstances, lowering their stringent requirements to reopen over time or as more constituents are vaccinated. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower.