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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.

Background: To reduce colorectal cancer mortality, positive fecal blood tests must be followed by colonoscopy.Methods: We identified 62,384 individuals ages 50 to 89 years with a positive fecal blood test between January 1, 2011 and December 31, 2012 in four health care systems within the Population-Based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium. We estimated the probability of follow-up colonoscopy and 95% confidence intervals (CI) using the Kaplan–Meier method. Overall differences in cumulative incidence of follow-up across health care systems were assessed with the log-rank test. HRs and 95% CIs were estimated from multivariate Cox proportional hazards models.Results: Most patients who received a colonoscopy did so within 6 months of their positive fecal blood test, although follow-up rates varied across health care systems (P Conclusion: Individual characteristics and health care system were associated with colonoscopy after positive fecal blood tests. Patterns were consistent across health care systems, but proportions of patients receiving follow-up varied. These findings suggest that there is room to improve follow-up of positive colorectal cancer screening tests.Impact: Understanding the timing of colonoscopy after positive fecal blood tests and characteristics associated with lack of follow-up may inform future efforts to improve follow-up. Cancer Epidemiol Biomarkers Prev; 25(2); 344–50. ©2016 AACR.

PDF file, 45K, Supplementary Information: Data used to Jointly Estimate Sensitivity and MST, among individuals with an index FOBT between January, 1997 and December 31, 2010.

PDF file, 37K, Schematic description of how cohort data are used to inform the sojourn time model. Each line indicates one type of patient. Patients enter the cohort either at the time of a positive FOBT test (indicted by "⊕") or a negative FOBT test (indicated by "Θ") and exit the cohort either at the time of censoring (indicated by "l") or CRC diagnosis (indicated by "C").

Background: Annual colorectal cancer screening with fecal occult blood test (FOBT) is a noninvasive alternative to screening colonoscopy once every 10 years. If false-positive FOBT results are common, then many patients selecting an FOBT regimen will be exposed to the same invasive testing as those selecting a colonoscopy regimen. The objective of this study was to estimate the probability of experiencing a false-positive after receiving annual FOBT screening for 10 years.Methods: Medical records for patients aged 50 to 79 years receiving FOBT screening with Hemoccult Sensa between 1997 and 2009 at Group Health of Washington State captured the date and results of each FOBT, along with subsequent colorectal cancer diagnoses. We used logistic regression to analyze associations between patient characteristics and odds of a positive FOBT with no invasive cancer diagnosis within 1 year (FOBT+, CRC−). We estimated the probability of receiving at least one FOBT+, CRC− result after 10 years of screening.Results: We observed 181,950 FOBTs from 94,637 individuals. Older patients, males, and non-White patients were significantly more likely to receive FOBT+, CRC− results (P < 0.001 for all risk factors). After 10 years of annual FOBT, 23.0% [95% confidence interval (CI), 18.2–27.0] will receive at least one FOBT+, CRC− result.Conclusions: Most patients participating in annual FOBT screening for 10 years will not have a positive result, reinforcing the potential value of this regimen as a noninvasive alternative to colonoscopy.Impact: Annual stool-based screening is a screening alternative resulting in substantially fewer colonoscopies than once per decade colonoscopy. Cancer Epidemiol Biomarkers Prev; 22(9); 1612–9. ©2013 AACR.

PDF file, 50K, Supplementary Information: Patterns of Censoring due to CRC Tests Across Age Groups and Time Periods.

PDF file, 50K, Forest plot of specificities of the five studies of average risk populations.

PDF - 98K, We used a censoring-bias adjusted discrete survival model for cumulative false positive probability that allows for variation in false-positive risk as a function of covariates, screening round number, and round at which a subject was censored.

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.

Background: Sojourn time is the length of the preclinical screen-detectable phase, a period when a test can detect asymptomatic disease. Mean sojourn time (MST) is an important factor in determining appropriate screening intervals. Available estimates of MST for colorectal cancer (CRC) are imprecise and are associated with the older Hemoccult II test. This article presents MST estimates associated with the newer Hemoccult SENSA test and describes differences in MST by the location of cancer in the colorectum and age at the time of screening.Methods: MST was estimated from a cohort of 42,079 patients who underwent Hemoccult SENSA between January 1, 1997 and December 31, 2010. The precision of MST estimates was improved by incorporating information from a meta-analysis of the sensitivity of Hemoccult SENSA into the analytic model.Results: Estimated MST for cancers in the proximal and distal colorectum, with 95% credible intervals (CrI) in years, were: 3.86 (1.55–6.91) and 3.35 (2.11–4.93) among 45- to 54-year olds; 3.78 (2.18–5.77) and 2.24 (1.48–3.17) among 55- to 64-year olds; and 2.70 (1.41–4.31) and 2.10 (1.34–3.04) among 65- to 74-year olds.Conclusions: MST associated with Hemoccult SENSA was longer for CRC in the proximal versus distal colon. We found no evidence that MST increases with age and some evidence that it may decrease.Impact: These results add new information about the natural history of CRC and information about the performance of Hemoccult SENSA. Cancer Epidemiol Biomarkers Prev; 21(10); 1722–30. ©2012 AACR.

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.

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.

ObjectiveAnnual 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.MethodThe 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.ResultsThe 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.ConclusionsSystematic 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.

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.

Objective : To identify and suggest strategies to make insufficient evidence ratings in systematic reviews more actionable. Study Design and Setting : A workgroup comprising members from the Evidence-Based Practice (EPC) Program of the Agency for Healthcare Research and Quality convened throughout 2020. We conducted iterative discussions considering information from three data sources: a literature review for relevant publications and frameworks, a review of a convenience sample of past systematic reviews conducted by the EPCs, and an audit of methods used in past EPC technical briefs. Results : We identified five strategies for supplementing systematic review findings when evidence on benefits or harms is expected to be, or found to be, insufficient: 1) reconsider eligible study designs, 2) summarize indirect evidence, 3) summarize contextual and implementation evidence, 4) consider modelling, and 5) incorporate unpublished health system data in the evidence synthesis. While these strategies may not increase the strength of evidence, they may improve the utility of reports for decisionmakers. Adopting these strategies depends on feasibility, timeline, funding, and expertise of the systematic reviewers. Conclusion : Throughout the process of evidence synthesis of early scoping, protocol development, review conduct, and review presentation, authors can consider these five strategies to supplement evidence with insufficient rating to make it more actionable for end-users.

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.

Importance: The US Preventive Services Task Force (USPSTF) is updating its 2016 colorectal cancer screening recommendations. Objective: To provide updated model-based estimates of the benefits, burden, and harms of colorectal cancer screening strategies and to identify strategies that may provide an efficient balance of life-years gained (LYG) from screening and colonoscopy burden to inform the USPSTF. Design, Setting, and Participants: Comparative modeling study using 3 microsimulation models of colorectal cancer screening in a hypothetical cohort of 40-year-old US individuals at average risk of colorectal cancer. Exposures: Screening from ages 45, 50, or 55 years to ages 70, 75, 80, or 85 years with fecal immunochemical testing (FIT), multitarget stool DNA testing, flexible sigmoidoscopy alone or with FIT, computed tomography colonography, or colonoscopy. All persons with an abnormal noncolonoscopy screening test result were assumed to undergo follow-up colonoscopy. Screening intervals varied by test. Full adherence with all procedures was assumed. Main Outcome and Measures: Estimated LYG relative to no screening (benefit), lifetime number of colonoscopies (burden), number of complications from screening (harms), and balance of incremental burden and benefit (efficiency ratios). Efficient strategies were those estimated to require fewer additional colonoscopies per additional LYG relative to other strategies. Results: Estimated LYG from screening strategies ranged from 171 to 381 per 1000 40-year-olds. Lifetime colonoscopy burden ranged from 624 to 6817 per 1000 individuals, and screening complications ranged from 5 to 22 per 1000 individuals. Among the 49 strategies that were efficient options with all 3 models, 41 specified screening beginning at age 45. No single age to end screening was predominant among the efficient strategies, although the additional LYG from continuing screening after age 75 were generally small. With the exception of a 5-year interval for computed tomography colonography, no screening interval predominated among the efficient strategies for each modality. Among the strategies highlighted in the 2016 USPSTF recommendation, lowering the age to begin screening from 50 to 45 years was estimated to result in 22 to 27 additional LYG, 161 to 784 additional colonoscopies, and 0.1 to 2 additional complications per 1000 persons (ranges are across screening strategies, based on mean estimates across models). Assuming full adherence, screening outcomes and efficient strategies were similar by sex and race and across 3 scenarios for population risk of colorectal cancer. Conclusions and Relevance: This microsimulation modeling analysis suggests that screening for colorectal cancer with stool tests, endoscopic tests, or computed tomography colonography starting at age 45 years provides an efficient balance of colonoscopy burden and life-years gained.

Calibration of a microsimulation model (MSM) is a challenging but crucial step for the development of a valid model. Numerous calibration methods for MSMs have been suggested in the literature, most of which are usually adjusted to the specific needs of the model and based on subjective criteria for the selection of optimal parameter values. This article compares 2 general approaches for calibrating MSMs used in medical decision making, a Bayesian and an empirical approach. We use as a tool the MIcrosimulation Lung Cancer (MILC) model, a streamlined, continuous-time, dynamic MSM that describes the natural history of lung cancer and predicts individual trajectories accounting for age, sex, and smoking habits. We apply both methods to calibrate MILC to observed lung cancer incidence rates from the Surveillance, Epidemiology and End Results (SEER) database. We compare the results from the 2 methods in terms of the resulting parameter distributions, model predictions, and efficiency. Although the empirical method proves more practical, producing similar results with smaller computational effort, the Bayesian method resulted in a calibrated model that produced more accurate outputs for rare events and is based on a well-defined theoretical framework for the evaluation and interpretation of the calibration outcomes. A combination of the 2 approaches is an alternative worth considering for calibrating complex predictive models, such as microsimulation models.

Racial disparities in colorectal cancer incidence are widely documented. There are two potential mechanisms for these disparities: differences in access to screening, including screening follow-up, and differences in underlying risk of colorectal cancer. We reviewed the literature for evidence of these two mechanisms. We show that higher colorectal cancer incidence in blacks relative to whites emerged only after the dissemination of screening and describe evidence of racial disparities in screening rates. In contrast to the strong evidence for differences in colorectal cancer screening utilization, there is limited evidence for racial differences in adenoma prevalence. In general, black and white patients who are screened have similar adenoma prevalence, though there is some evidence that advanced adenomas and adenomas in the proximal colon are somewhat more likely in black than white patients. We conclude that higher rates of colorectal cancer incidence among black patients are primarily driven by lower rates of colorectal cancer screening. Our findings highlight the need to increase black patients' access to quality screening to reduce colorectal cancer incidence and mortality.

Accurately describing treatment effects using plain language and narrative statements is a critical step in communicating research findings to end users. However, the process of developing these narratives has not been historically guided by a specific framework. The Agency for Healthcare Research and Quality Evidence-based Practice Center Program developed guidance for narrative summaries of treatment effects that identifies five constructs. We explicitly identify these constructs to facilitate developing narrative statements: (1) direction of effect, (2) size of effect, (3) clinical importance, (4) statistical significance, and (5) strength or certainty of evidence. These constructs clearly overlap. It may not always be feasible to address all five constructs. Based on context and intended audience, investigators can determine which constructs will be most important to address in narrative statements.

Microsimulation models are often used to predict long-term outcomes and guide policy decisions regarding cancer screening. The United Kingdom Flexible Sigmoidoscopy Screening (UKFSS) Trial examines a one-time intervention of flexible sigmoidoscopy that was implemented before a colorectal cancer (CRC) screening program was established. Long-term study outcomes, now a full 17 years following randomization, have been published. We use the outcomes from this trial to validate three microsimulation models for CRC to long-term study outcomes. We find that two of three models accurately predict the relative effect of screening (the hazard ratios) on CRC-specific incidence 17 years after screening. We find that all three models yield predictions of the relative effect of screening on CRC incidence and mortality (i.e., the hazard ratios) that are reasonably close to the UKFSS results. Two of the three models accurately predict the relative reduction in CRC incidence 17-years after screening. One model accurately predicted absolute incidence and mortality rates in the screened group. The models differ in their estimates related to adenoma detection at screening. While high-quality screening results help to inform models, trials are expensive, last many years, and can be complicated by ethical issues and technological changes across the duration of the trial. Thus, well-calibrated and validated models are necessary to predict outcomes for which data are not available. The results from this validation demonstrate the utility of models in predicting long-term outcomes, and in collaborative modeling to account for uncertainty.

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 ( 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

Background Cancer screening is a complex process encompassing risk assessment, the initial screening examination, diagnostic evaluation, and treatment of cancer precursors or early cancers. Metrics that enable comparisons across different screening targets are needed. We present population-based screening metrics for breast, cervical, and colorectal cancers for nine sites participating in the Population-based Research Optimizing Screening through Personalized Regimens consortium. Methods We describe how selected metrics map to a trans-organ conceptual model of the screening process. For each cancer type, we calculated calendar year 2013 metrics for the screen-eligible target population (breast: ages 40–74 years; cervical: ages 21–64 years; colorectal: ages 50–75 years). Metrics for screening participation, timely diagnostic evaluation, and diagnosed cancers in the screened and total populations are presented for the total eligible population and stratified by age group and cancer type. Results The overall screening-eligible populations in 2013 were 305 568 participants for breast, 3 160 128 for cervical, and 2 363 922 for colorectal cancer screening. Being up-to-date for testing was common for all three cancer types: breast (63.5%), cervical (84.6%), and colorectal (77.5%). The percentage of abnormal screens ranged from 10.7% for breast, 4.4% for cervical, and 4.5% for colorectal cancer screening. Abnormal breast screens were followed up diagnostically in almost all (96.8%) cases, and cervical and colorectal were similar (76.2% and 76.3%, respectively). Cancer rates per 1000 screens were 5.66, 0.17, and 1.46 for breast, cervical, and colorectal cancer, respectively. Conclusions Comprehensive assessment of metrics by the Population-based Research Optimizing Screening through Personalized Regimens consortium enabled systematic identification of screening process steps in need of improvement. We encourage widespread use of common metrics to allow interventions to be tested across cancer types and health-care settings.

Background Pragmatic clinical trials often use automated data sources such as electronic health records, claims, or registries to identify eligible individuals and collect outcome information. A specific advantage that this automated data collection often yields is having data on potential participants when design decisions are being made. We outline how this data can be used to inform trial design. Methods Our work is motivated by a pragmatic clinical trial evaluating the impact of suicide-prevention outreach interventions on fatal and non-fatal suicide attempts in the 18 months after randomization. We illustrate our recommended approaches for designing pragmatic clinical trials using historical data from the health systems participating in this study. Specifically, we illustrate how electronic health record data can be used to inform the selection of trial eligibility requirements, to estimate the distribution of participant characteristics over the course of the trial, and to conduct power and sample size calculations. Results Data from 122,873 people with patient health questionnaire (PHQ) responses, recorded in their electronic health records between 1 July 2010 and 31 March 2012, were used to show that the suicide attempt rate in the 18 months following completion of the questionnaire varies by response to item nine of the PHQ. We estimated that the proportion of individuals with a prior recorded elevated PHQ (i.e. history of suicidal ideation) would decrease from approximately 50% at the beginning of a trial to about 5%, 50 weeks later. Using electronic health record data, we conducted simulations to estimate the power to detect a 25% reduction in suicide attempts. Simulation-based power calculations estimated that randomizing 8000 participants per randomization arm would allow 90% power to detect a 25% reduction in the suicide attempt rate in the intervention arm compared to usual care at an alpha rate of 0.05. Conclusions Historical data can be used to inform the design of pragmatic clinical trials, a strength of trials that use automated data collection for randomizing participants and assessing outcomes. In particular, realistic sample size calculations can be conducted using real-world data from the health systems in which the trial will be conducted. Data-informed trial design should yield more realistic estimates of statistical power and maximize efficiency of trial recruitment.

Background: Healthcare decision makers strive to operate on the best available evidence. The Agency for Healthcare Research and Quality Evidence-based Practice Center (EPC) Program aims to support healthcare decision makers by producing evidence reviews that rate the strength of evidence. However, the evidence base is often sparse or heterogeneous, or otherwise results in a high degree of uncertainty and insufficient evidence ratings. Objective: To identify and suggest strategies to make insufficient ratings in systematic reviews more actionable. Methods: A workgroup comprising EPC Program members convened throughout 2020. We conducted interative discussions considering information from three data sources: a literature review for relevant publications and frameworks, a review of a convenience sample of past systematic reviews conducted by the EPCs, and an audit of methods used in past EPC technical briefs. Results: Several themes emerged across the literature review, review of systematic reviews, and review of technical brief methods. In the purposive sample of 43 systematic reviews, the use of the term “insufficient” covered both instances of no evidence and instances of evidence being present but insufficient to estimate an effect. The results of the literature review and review of the EPC Program systematic reviews illustrated the importance of clearly stating the reasons for insufficient evidence. Results of both the literature review and review of systematic reviews highlighted the factors decision makers consider when making decisions when evidence of benefits or harms is insufficient, such as costs, values, preferences, and equity. We identified five strategies for supplementing systematic review findings when evidence on benefit or harms is expected to be or found to be insufficient, including: reconsidering eligible study designs, summarizing indirect evidence, summarizing contextual and implementation evidence, modelling, and incorporating unpublished health system data. Conclusion: Throughout early scoping, protocol development, review conduct, and review presentation, authors should consider five possible strategies to supplement potential insufficient findings of benefit or harms. When there is no evidence available for a specific outcome, reviewers should use a statement such as “no studies” instead of “insufficient.” The main reasons for insufficient evidence rating should be explicitly described.

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.

This chapter discusses validation of simulation models used to inform health policy. Confidence in a model’s validity can be weaker or stronger depending on several factors. These factors include verifying whether model specifications were implemented correctly, evaluating the extent to which model-predicted results are consistent with empirical results, and examining whether model predictions are robust to alternative structural assumptions. Systematic evaluation of these factors can be used to gauge the extent to which a model is validated for a given application. It reviews types of validation, discusses the related concepts of calibration and nonidentifiability, takes a deeper dive into cancer model validation studies, and concludes with questions that consumers of models should ask (and modelers should answer) to inform judgment about a model’s fitness for purpose. Final judgments about when model results can be trusted ultimately rely on the evolving understanding of the disease and intervention effects, available data relevant to the application, and access to reporting of model validation exercises.

Background There is a lack of research on the effectiveness of online peer support groups for reducing social isolation and depressive symptoms among caregivers, and previous research has mixed results. Objective This study aimed to test whether military caregivers who joined a new online peer support community or engaged with an existing online community experienced decreased perceived social isolation and improved depressive symptoms over 6 months. Methods We conducted a longitudinal study of 212 military caregivers who had newly joined an online community and those who were members of other military caregiver groups. Multiple indicators of perceived social isolation and depressive symptoms were assessed at baseline and at 3 and 6 months. Results Compared with caregivers in the comparison group, caregivers who joined the new group experienced less perceived social isolation at 3 months (eg, number of caregivers in social network [unstandardized regression coefficients] b=0.49, SE 0.19, 95% CI 0.87 to 0.02), but this effect did not persist at 6 months. Those who engaged more with new or existing groups experienced less perceived social isolation over time (eg, number of caregivers in social network b=0.18, SE 0.06, 95% CI 0.02 to 0.27), and this relationship was mediated by increased interactions with other military caregivers (95% CI 0.0046 to 0.0961). Engagement with an online group was not associated with improvements in depressive symptoms. Conclusions Online communities might help reduce social isolation when members engage with the group, but more intensive treatment is needed to improve depressive symptoms.

The adequacy of disability benefits for workers with occupational cancer is an issue of considerable public concern. In this report, the authors conduct an empirical analysis of earnings losses, disability ratings, and benefit payments for occupational cancer claims in the California workers' compensation system. Findings from this study may inform ongoing debate over California's approach to compensating workers with industrial cancer.

Microsimulation models (MSMs) are used to predict population-level effects of health care policies by simulating individual-level outcomes. Simulated outcomes are governed by unknown parameters that are chosen so that the model accurately predicts specific targets, a process referred to as model calibration. Calibration targets can come from randomized controlled trials, observational studies, and expert opinion, and are typically summary statistics. A well calibrated model can reproduce a wide range of targets. MSM calibration generally involves searching a high dimensional parameter space and predicting many targets through model simulation. This requires efficient methods for exploring the parameter space and sufficient computational resources. We develop Incremental Mixture Approximate Bayesian Computation (IMABC) as a method for MSM calibration and implement it via a high-performance computing workflow, which provides the necessary computational scale. IMABC begins with a rejection-based approximate Bayesian computation (ABC) step, drawing a sample of parameters from the prior distribution and simulating calibration targets. Next, the sample is iteratively updated by drawing additional points from a mixture of multivariate normal distributions, centered at the points that yield simulated targets that are near observed targets. Posterior estimates are obtained by weighting sampled parameter vectors to account for the adaptive sampling scheme. We demonstrate IMABC by calibrating a MSM for the natural history of colorectal cancer to obtain simulated draws from the joint posterior distribution of model parameters.

Objectives Chronic low back pain (CLBP) and chronic neck pain (CNP) are the most common types of chronic pain, and chiropractic spinal manipulation is a common nonpharmacologic treatment. This study presents the characteristics of a large United States sample of chiropractic patients with CLBP and CNP. Methods Data were collected from chiropractic patients using multistage systematic stratified sampling with 4 sampling levels: regions and states, sites (ie, metropolitan areas), providers and clinics, and patients. The sites and regions were San Diego, California; Tampa, Florida; Minneapolis, Minnesota; Seneca Falls and Upstate New York; Portland, Oregon; and Dallas, Texas. Data were collected from patients through an iPad-based prescreening questionnaire in the clinic and emailed links to full screening and baseline online questionnaires. The goal was 20 providers or clinics and 7 patients with CLBP and 7 with CNP from each clinic. Results We had 6342 patients at 125 clinics complete the prescreening questionnaire, 3333 patients start the full screening questionnaire, and 2024 eligible patients completed the baseline questionnaire: 518 with CLBP only, 347 with CNP only, and 1159 with both. In general, most of this sample were highly-educated, non-Hispanic, white females with at least partial insurance coverage for chiropractic care who have been in pain and using chiropractic care for years. Over 90% reported high satisfaction with their care, few used narcotics, and avoiding surgery was the most important reason they chose chiropractic care. Conclusions Given the prevalence of CLBP and CNP, the need to find effective nonpharmacologic alternatives for chronic pain, and the satisfaction these patients found with their care, further study of these patients is worthwhile.

Background: Patients who receive an abnormal cancer screening result require follow-up for diagnostic testing, but the time to follow-up varies across patients and practices. Methods: We used a simulation study to estimate the change in lifetime screening benefits when time to follow-up for breast, cervical, and colorectal cancers was increased. Estimates were based on four independently developed microsimulation models that each simulated the life course of adults eligible for breast (women ages 50–74 years), cervical (women ages 21–65 years), or colorectal (adults ages 50–75 years) cancer screening. We assumed screening based on biennial mammography for breast cancer, triennial Papanicolaou testing for cervical cancer, and annual fecal immunochemical testing for colorectal cancer. For each cancer type, we simulated diagnostic testing immediately and at 3, 6, and 12 months after an abnormal screening exam. Results: We found declines in screening benefit with longer times to diagnostic testing, particularly for breast cancer screening. Compared to immediate diagnostic testing, testing at 3 months resulted in reduced screening benefit, with fewer undiscounted life years gained per 1,000 screened (breast: 17.3%, cervical: 0.8%, colorectal: 2.0% and 2.7%, from two colorectal cancer models), fewer cancers prevented (cervical: 1.4% fewer, colorectal: 0.5% and 1.7% fewer, respectively), and, for breast and colorectal cancer, a less favorable stage distribution. Conclusions: Longer times to diagnostic testing after an abnormal screening test can decrease screening effectiveness, but the impact varies substantially by cancer type. Impact: Understanding the impact of time to diagnostic testing on screening effectiveness can help inform quality improvement efforts. Cancer Epidemiol Biomarkers Prev; 27(2); 158–64. ©2017 AACR.

Background: Despite the importance of characterizing colonoscopy indication for quality monitoring and cancer screening program evaluation, there is no standard approach to documenting colonoscopy indication in medical records.Methods: We applied two algorithms in three health care systems to assign colonoscopy indication to persons 50–89 years old who received a colonoscopy during 2010–2013. Both algorithms used standard procedure, diagnostic, and laboratory codes. One algorithm, the KPNC algorithm, used a hierarchical approach to classify exam indication into: diagnostic, surveillance, or screening; whereas the other, the SEARCH algorithm, used a logistic regression-based algorithm to provide the probability that colonoscopy was performed for screening. Gold standard assessment of indication was from medical records abstraction.Results: There were 1,796 colonoscopy exams included in analyses; age and racial/ethnic distributions of participants differed across health care systems. The KPNC algorithm’s sensitivities and specificities for screening indication ranged from 0.78–0.82 and 0.78–0.91, respectively; sensitivities and specificities for diagnostic indication ranged from 0.78–0.89 and 0.74–0.82, respectively. The KPNC algorithm had poor sensitivities (ranging from 0.11–0.67) and high specificities for surveillance exams. The Area Under the Curve (AUC) of the SEARCH algorithm for screening indication ranged from 0.76–0.84 across health care systems. For screening indication, the KPNC algorithm obtained higher specificities than the SEARCH algorithm at the same sensitivity.Conclusion: Despite standardized implementation of these indication algorithms across three health care systems, the capture of colonoscopy indication data was imperfect. Thus, we recommend that standard, systematic documentation of colonoscopy indication should be added to medical records to ensure efficient and accurate data capture.

Men and women might respond differently to some treatments for alcohol use disorder. If so, this would be important to consider when selecting treatment. The purpose of this systematic review was to synthesize evidence for gender differences in effects of treatments. While researchers did not identify systematic differences across studies, a paucity of reporting on treatment effects according to gender hindered analysis.

From Coverage to Care launched in 2014 with the dual goals of helping consumers understand their health insurance coverage and connect to care and supporting organizations in the community as they assist consumers at various points in this process. In this report, the authors present the results of their analysis of From Coverage to Care's effectiveness in meeting these goals.

BackgroundIn 2014, the Centers for Medicare and Medicaid Services (CMS) began covering a multitarget stool DNA (mtSDNA) test for colorectal cancer (CRC) screening of Medicare beneficiaries. In this study, we evaluated whether mtSDNA testing is a cost-effective alternative to other CRC screening strategies reimbursed by CMS, and if not, under what conditions it could be.MethodsWe use three independently-developed microsimulation models to simulate a cohort of previously unscreened US 65-year-olds who are screened with triennial mtSDNA testing, or one of six other reimbursed screening strategies. Main outcome measures are discounted life-years gained (LYG) and lifetime costs (CMS perspective), threshold reimbursement rates, and threshold adherence rates. Outcomes are expressed as the median and range across models.ResultsCompared to no screening, triennial mtSDNA screening resulted in 82 (range: 79-88) LYG per 1,000 simulated individuals. This was more than for five-yearly sigmoidoscopy (80 (range: 71-89) LYG), but fewer than for every other simulated strategy. At its 2017 reimbursement rate of $512, mtSDNA was the most costly strategy, and even if adherence were 30% higher than with other strategies, it would not be a cost-effective alternative. At a substantially reduced reimbursement rate ($6-18), two models found that triennial mtSDNA testing was an efficient and potentially cost-effective screening option.ConclusionsCompared to no screening, triennial mtSDNA screening reduces CRC incidence and mortality at acceptable costs. However, compared to nearly all other CRC screening strategies reimbursed by CMS it is less effective and considerably more costly, making it an inefficient screening option.

Introduction Timely follow-up of abnormal tests is critical to the effectiveness of cancer screening, but may vary by screening test, healthcare system, and sociodemographic group. Methods Timely follow-up of abnormal mammogram and fecal occult blood testing or fecal immunochemical tests (FOBT/FIT) were compared by race/ethnicity using Population-Based Research Optimizing Screening through Personalized Regimens consortium data. Participants were women with an abnormal mammogram (aged 40–75 years) or FOBT/FIT (aged 50–75 years) in 2010–2012. Analyses were performed in 2015. Timely follow-up was defined as colonoscopy ≤3 months following positive FOBT/FIT; additional imaging or biopsy ≤3 months following Breast Imaging Reporting and Data System Category 0, 4, or 5 mammograms; or ≤9 months following Category 3 mammograms. Logistic regression was used to model receipt of timely follow-up adjusting for study site, age, year, insurance, and income. Results Among 166,602 mammograms, 10.7% were abnormal; among 566,781 FOBT/FITs, 4.3% were abnormal. Nearly 96% of patients with abnormal mammograms received timely follow-up versus 68% with abnormal FOBT/FIT. There was greater variability in receipt of follow-up across healthcare systems for positive FOBT/FIT than for abnormal mammograms. For mammography, black women were less likely than whites to receive timely follow-up (91.8% vs 96.0%, OR=0.71, 95% CI=0.51, 0.97). For FOBT/FIT, Hispanics were more likely than whites to receive timely follow-up than whites (70.0% vs 67.6%, OR=1.12, 95% CI=1.04, 1.21). Conclusions Timely follow-up among women was more likely for abnormal mammograms than FOBT/FITs, with small variations in follow-up rates by race/ethnicity and larger variation across healthcare systems.

Expert recommendations differ for colorectal cancer screening in the elderly. Recent studies suggest that healthy adults aged75 years may benefit from screening. This study examined screening use and follow-up, and how they varied by health status within age strata, among a large cohort of elderly individuals in community settings.A population-based, longitudinal cohort study was conducted among health plan members aged 65-89 years enrolled during 2011-2012 in three integrated healthcare systems participating in the Population-Based Research Optimizing Screening through Personalized Regimens consortium. Comorbidity measurements used the Charlson index. Analyses, conducted in 2015, comprised descriptive statistics and multivariable modeling that estimated age by comorbidity-specific percentages of patients for two outcomes: colorectal cancer screening uptake and follow-up of abnormal fecal blood tests.Among 846,267 patients, 72% were up-to-date with colorectal cancer screening. Of patients with a positive fecal blood test, 65% received follow-up colonoscopy within 3 months. Likelihood of being up-to-date and receiving timely follow-up was significantly lower for patients aged ≥76 years than their younger counterparts (p0.001). Comorbidity was less influential than age and more strongly related to timely follow-up than being up-to-date. In all age groups, considerable numbers of patients with no/low comorbidity were not up-to-date or did not receive timely follow-up.In three integrated healthcare systems, many older, relatively healthy patients were not screening up-to-date, and some relatively young, healthy patients did not receive timely follow-up. Findings suggest a need for re-evaluating age-based screening guidelines and improving screening completion among the elderly.