Characteristics of a cost-effective blood test for colorectal cancer screening.

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 (FIT) or decennial colonoscopy. METHODS: We used the three CISNET-Colon models to compare scenarios of no screening, annual FIT, decennial colonoscopy, and a blood test meeting CMS coverage criteria (74% CRC sensitivity and 90% specificity). We varied the sensitivity to detect CRC (74%-92%), advanced adenomas (AAs, 10%-50%), screening interval (1-3 years), and test cost ($25-$500). Primary outcomes included quality-adjusted life-years gained (QALYG) from screening and costs for an US average-risk 45-year-old cohort. RESULTS: Annual FIT yielded 125-163 QALYG per 1,000 at a cost of $3,811-5,384 per person, whereas colonoscopy yielded 132-177 QALYG at a cost of $5,375-7,031 per person. A blood test with 92% CRC sensitivity and 50% AA sensitivity yielded 117-162 QALYG if used every three years and 133-173 QALYG if used every year but would not be cost-effective if priced above $125 per test. If used every three years, a $500 blood test only meeting CMS coverage criteria yielded 83-116 QALYG, at a cost of $8,559-9,413 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 FIT due to lower benefit. Blood tests need higher AA sensitivity (above 40%) and lower costs (below $125) to be cost-effective.

Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models.

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.

How well do participants in clinical trials represent the U.S. population with chronic neck or back pain?

BACKGROUND: Randomized clinical trials (RCTs) are the gold standard for assessing treatment effectiveness; however, they have been criticized for generalizability issues such as how well trial participants represent those who receive the treatments in clinical practice. We assessed the representativeness of participants from eight RCTs for chronic spine pain in the U.S., which were used for an individual participant data meta-analysis on the cost-effectiveness of spinal manipulation for spine pain. In these clinical trials, spinal manipulation was performed by chiropractors. METHODS: We conducted a retrospective secondary analysis of RCT data to compare trial participants' socio-demographic characteristics, clinical features, and health outcomes to a representative sample of (a) U.S. adults with chronic spine pain and (b) U.S. adults with chronic spine pain receiving chiropractic care, using secondary data from the National Health Interview Survey (NHIS) and Medical Expenditure Panel Survey (MEPS). We assessed differences between trial and U.S. spine populations using independent t-tests for means and z-tests for proportions, accounting for the complex multi-stage survey design of the NHIS and MEPS. RESULTS: We found the clinical trials had an under-representation of individuals from health disparity populations with lower percentages of racial and ethnic minority groups (Black/African American 7% lower, Hispanic 8% lower), less educated (No high school degree 19% lower, high school degree 11% lower), and unemployed adults (25% lower) with worse health outcomes (physical health scores 2.5 lower and mental health scores 5.3 lower using the SF-12/36) relative to the U.S. population with spine pain. While the odds of chiropractic use in the U.S. are lower for individuals from health disparity populations, the trials also under-represented these populations relative to U.S. adults with chronic spine pain who visit a chiropractor. CONCLUSIONS: Health disparity populations are not well represented in spine pain clinical trials. Embracing key community-based approaches, which have shown promise for increasing participation of underserved communities, is needed.

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.

Emulator-based Bayesian calibration of the CISNET colorectal cancer models.

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 (ANN) 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 four hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had one hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 hours 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, like the CISNET CRC models. In this work, we present a step-by-step guide to constructing emulators for calibrating three realistic CRC individual-level models using a Bayesian approach.

A Guide to an Iterative Approach to Model-Based Decision Making in Health and Medicine: An Iterative Decision-Making Framework.

Decision makers frequently face decisions about optimal resource allocation. A model-based economic evaluation can be used to guide decision makers in their choices by systematically evaluating the magnitude of expected health effects and costs of decision options and by making trade-offs explicit. We provide a guide to an iterative approach to the medical decision-making process by following a coherent framework, and outline the overarching iterative steps of model-based decision making. We systematized the framework by performing three steps. First, we compiled the existing guidelines provided by the ISPOR-SMDM Modeling Good Research Practices Task Force, and the ISPOR Value of Information Task Force. Second, we identified other previous work related to frameworks and guidelines for model-based decision analyses through a literature search in PubMed. Third, we assessed the role of the evidence and iterative process in decision making and formalized key steps in a model-based decision-making framework. We provide guidance on an iterative approach to medical decision making by applying the compiled iterative model-based decision-making framework. The framework formally combines the decision problem conceptualization (Part I), the model conceptualization and development (Part II), and the process of model-based decision analysis (Part III). Following the overarching steps of the framework ensures compliance to the principles of evidence-based medicine and regular updates of the evidence, given that value of information analysis represents an essential component of model-based decision analysis in the framework. Following the provided guide and the steps outlined in the framework can help inform various health care decisions, and therefore it has the potential to improve decision making.

Adaptive COVID-19 Mitigation Strategies: Tradeoffs between Trigger Thresholds, Response Timing, and Effectiveness.

Background. To support proactive decision making during the COVID-19 pandemic, mathematical models have been leveraged to identify surveillance indicator thresholds at which strengthening nonpharmaceutical interventions (NPIs) is necessary to protect health care capacity. Understanding tradeoffs between different adaptive COVID-19 response components is important when designing strategies that balance public preference and public health goals. Methods. We considered 3 components of an adaptive COVID-19 response: 1) the threshold at which to implement the NPI, 2) the time needed to implement the NPI, and 3) the effectiveness of the NPI. Using a compartmental model of SARS-CoV-2 transmission calibrated to Minnesota state data, we evaluated different adaptive policies in terms of the peak number of hospitalizations and the time spent with the NPI in force. Scenarios were compared with a reference strategy, in which an NPI with an 80% contact reduction was triggered when new weekly hospitalizations surpassed 8 per 100,000 population, with a 7-day implementation period. Assumptions were varied in sensitivity analysis. Results. All adaptive response scenarios substantially reduced peak hospitalizations relative to no response. Among adaptive response scenarios, slower NPI implementation resulted in somewhat higher peak hospitalization and a longer time spent under the NPIs than the reference scenario. A stronger NPI response resulted in slightly less time with the NPIs in place and smaller hospitalization peak. A higher trigger threshold resulted in greater peak hospitalizations with little reduction in the length of time under the NPIs. Conclusions. An adaptive NPI response can substantially reduce infection circulation and prevent health care capacity from being exceeded. However, population preferences as well as the feasibility and timeliness of compliance with reenacting NPIs should inform response design. Highlights: This study uses a mathematical model to compare different adaptive nonpharmaceutical intervention (NPI) strategies for COVID-19 management across 3 dimensions: threshold when the NPI should be implemented, time it takes to implement the NPI, and the effectiveness of the NPI.All adaptive NPI response scenarios considered substantially reduced peak hospitalizations compared with no response.Slower NPI implementation results in a somewhat higher peak hospitalization and longer time spent with the NPI in place but may make an adaptive strategy more feasible by allowing the population sufficient time to prepare for changing restrictions.A stronger, more effective NPI response results in a modest reduction in the time spent under the NPIs and slightly lower peak hospitalizations.A higher threshold for triggering the NPI delays the time at which the NPI starts but results in a higher peak hospitalization and does not substantially reduce the time the NPI remains in force.

Characterization and Valuation of the Uncertainty of Calibrated Parameters in Microsimulation Decision Models.

Background: We evaluated the implications of different approaches to characterize the uncertainty of calibrated parameters of microsimulation decision models (DMs) and quantified the value of such uncertainty in decision making. Methods: We calibrated the natural history model of CRC to simulated epidemiological data with different degrees of uncertainty and obtained the joint posterior distribution of the parameters using a Bayesian approach. We conducted a probabilistic sensitivity analysis (PSA) on all the model parameters with different characterizations of the uncertainty of the calibrated parameters. We estimated the value of uncertainty of the various characterizations with a value of information analysis. We conducted all analyses using high-performance computing resources running the Extreme-scale Model Exploration with Swift (EMEWS) framework. Results: The posterior distribution had a high correlation among some parameters. The parameters of the Weibull hazard function for the age of onset of adenomas had the highest posterior correlation of -0.958. When comparing full posterior distributions and the maximum-a-posteriori estimate of the calibrated parameters, there is little difference in the spread of the distribution of the CEA outcomes with a similar expected value of perfect information (EVPI) of $653 and $685, respectively, at a willingness-to-pay (WTP) threshold of $66,000 per quality-adjusted life year (QALY). Ignoring correlation on the calibrated parameters' posterior distribution produced the broadest distribution of CEA outcomes and the highest EVPI of $809 at the same WTP threshold. Conclusion: Different characterizations of the uncertainty of calibrated parameters affect the expected value of eliminating parametric uncertainty on the CEA. Ignoring inherent correlation among calibrated parameters on a PSA overestimates the value of uncertainty.

Opportunities for personalizing colorectal cancer care: an analysis of SEER-medicare data.

United States clinical practice guidelines for metastatic colorectal cancer recommend use of medications impacted by genetic variants but do not recommend testing. We analyzed real-world treatment using a cancer registry and claims dataset to explore pharmacogenomic (PGx) medication treatment patterns and characterize exposure. In a cohort of 6957 patients, most (86.9%) were exposed to at least one chemotherapy medication with PGx guidelines. In a cohort of 2223 patients with retail pharmacy claims available, most (79.2%) were treated with at least one non-chemotherapy (79.2%) medication with PGx guidelines. PGx-associated chemotherapy exposure was associated with age, race/ethnicity, educational attainment, and rurality. PGx-associated non-chemotherapy exposure was associated with medication use and comorbidities. The potential impact of PGx testing is large and policies aimed at increasing PGx testing at diagnosis may impact treatment decisions for patients with metastatic colorectal cancer as most patients are exposed to medications with pharmacogenomics implications during treatment.

CDX2 Biomarker Testing and Adjuvant Therapy for Stage II Colon Cancer: An Exploratory Cost-Effectiveness Analysis.

OBJECTIVES: Adjuvant chemotherapy is not recommended for patients with average-risk stage II (T3N0) colon cancer. Nevertheless, a subgroup of these patients who are CDX2-negative might benefit from adjuvant chemotherapy. We evaluated the cost-effectiveness of testing for the absence of CDX2 expression followed by adjuvant chemotherapy (fluorouracil combined with oxaliplatin [FOLFOX]) for patients with stage II colon cancer. METHODS: We developed a decision model to simulate a hypothetical cohort of 65-year-old patients with average-risk stage II colon cancer with 7.2% of these patients being CDX2-negative under 2 different interventions: (1) test for the absence of CDX2 expression followed by adjuvant chemotherapy for CDX2-negative patients and (2) no CDX2 testing and no adjuvant chemotherapy for any patient. We derived disease progression parameters, adjuvant chemotherapy effectiveness and utilities from published analyses, and cancer care costs from the Surveillance, Epidemiology, and End Results (SEER)-Medicare data. Sensitivity analyses were conducted. RESULTS: Testing for CDX2 followed by FOLFOX for CDX2-negative patients had an incremental cost-effectiveness ratio of $5500/quality-adjusted life-years (QALYs) compared with no CDX2 testing and no FOLFOX (6.874 vs 6.838 discounted QALYs and $89 991 vs $89 797 discounted US dollar lifetime costs). In sensitivity analyses, considering a cost-effectiveness threshold of $100 000/QALY, testing for CDX2 followed by FOLFOX on CDX2-negative patients remains cost-effective for hazard ratios of <0.975 of the effectiveness of FOLFOX in CDX2-negative patients in reducing the rate of developing a metastatic recurrence. CONCLUSIONS: Testing tumors of patients with stage II colon cancer for CDX2 and administration of adjuvant treatment to the subgroup found CDX2-negative is a cost-effective and high-value management strategy across a broad range of plausible assumptions.

Reevaluating the Evidence for Intensive Postoperative Extracolonic Surveillance for Nonmetastatic Colorectal Cancer.

OBJECTIVES: The FACS, GILDA, and COLOFOL trials have cast doubt on the value of intensive extracolonic surveillance for resected nonmetastatic colorectal cancer and by extension metastasectomy. We reexamined this pessimistic interpretation. We evaluate an alternative explanation: insufficient power to detect a realistically sized survival benefit that may be clinically meaningful. METHODS: A microsimulation model of postdiagnosis colorectal cancer was constructed assuming an empirically plausible efficacy for metastasectomy and thus surveillance. The model was used to predict the large-sample mortality reduction expected for each trial and the implied statistical power. A potential recurrence imbalance in the FACS trial was investigated. Goodness of fit between model predictions and trial results were evaluated. Downstream life expectancy was estimated and power calculations performed for future trials evaluating surveillance and metastasectomy. RESULTS: For all 3 trials, the model predicted a mortality reduction of ≤5% and power of <10%. The FACS recurrence imbalance likely led to a large relative bias (>2.5) in the hazard ratio for overall survival favoring control. After adjustment, both COLOFOL and FACS results were consistent with model predictions (P>.5). A 2.6 (95% credible interval 0.5-5.1) and 3.6 (95% credible interval 0.8-7.0) month increase in life expectancy is predicted comparing intensive extracolonic surveillance-routine computed tomography scans and carcinoembryonic antigen assays-with 1 computed tomography scan at 12 months or no surveillance, respectively. An adequately sized surveillance trial is not feasible. A metastasectomy trial should randomize at least 200 to 300 patients. CONCLUSIONS: Recent trial results do not warrant de novo skepticism of metastasectomy nor targeted extracolonic surveillance. Given the potential for clinically meaningful life-expectancy gain and significant uncertainty, a trial of metastasectomy is needed.

Return to work after deceased donor kidney transplant under the kidney allocation system.

BACKGROUND: The Kidney Allocation System (KAS) includes a scoring system to match transplant candidate life expectancy with expected longevity of the donor kidney, and a backdating policy that gives waitlist time credit to patients waitlisted after starting dialysis treatment (post-dialysis). We estimated the effect of the KAS on employment among patient subgroups targeted by the policy. METHODS: We used a sample selection model to compare employment after transplant before and after KAS implementation among patients on the kidney-only transplant waitlist between December 4, 2011 and December 31, 2017. RESULTS: Post-dialysis transplant recipients aged 18-49 were significantly more likely to be employed 1-year post transplant in the post-KAS era compared to the pre-KAS era. Transplant recipients aged 35-64 with no dialysis treatment were significantly less likely to be employed 1 year after transplant in the post-KAS era compared to the pre-KAS era. CONCLUSIONS: This study provides the first assessment of employment after DDKT under the KAS and provides important information about both the methods used to measure employment after transplant and the outcome under the KAS. Changes in employment after DDKT among various patient subgroups have important implications for assessing long-term patient and societal effects of the KAS and organ allocation policy.

Colorectal Cancer Screening: An Updated Modeling Study for the US Preventive Services Task Force.

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.

The effectiveness and value of novel treatments for cystic fibrosis.

DISCLOSURES: Funding for this summary was contributed by Arnold Ventures, California Health Care Foundation, Harvard Pilgrim Health Care, and Kaiser Foundation Health Plan to the Institute for Clinical and Economic Review (ICER), an independent organization that evaluates the evidence on the value of health care interventions. ICER's annual policy summit is supported by dues from Aetna, America's Health Insurance Plans, Anthem, Allergan, Alnylam, AstraZeneca, Biogen, Blue Shield of CA, Boehringer-Ingelheim, Cambia Health Services, CVS, Editas, Express Scripts, Genentech/Roche, GlaxoSmithKline, Harvard Pilgrim, Health Care Service Corporation, HealthFirst, Health Partners, Johnson & Johnson (Janssen), Kaiser Permanente, LEO Pharma, Mallinckrodt, Merck, Novartis, National Pharmaceutical Council, Pfizer, Premera, Prime Therapeutics, Regeneron, Sanofi, Spark Therapeutics, and United Healthcare. Seidner, Rind, and Pearson are employed by ICER. Tice reports contracts to his institution, University of California, San Francisco, from ICER during the conduct of this study. Wherry has nothing to disclose.

A Cost-Effectiveness Evaluation of Surgical Approaches to Proctectomy.

BACKGROUND: Robotic surgery is increasingly used for proctectomy, but the cost-effectiveness of this approach is uncertain. Robotic surgery is considered more expensive than open or laparoscopic approaches, but in certain situations has been demonstrated to be cost-effective. We examined the cost-effectiveness of open, laparoscopic, and robotic approaches to proctectomy from societal and healthcare system perspectives. METHODS: We developed a decision-analytic model to evaluate one-year costs and outcomes of robotic, laparoscopic, and open proctectomy based on data from the available literature. The robustness of our results was tested with one-way and multi-way sensitivity analyses. RESULTS: Open proctectomy had increased cost and lower quality of life (QOL) compared with laparoscopy and robotic approaches. In the societal perspective, robotic proctectomy costs $497/case more than laparoscopy, with minimal QOL improvements, resulting in an incremental cost-effectiveness ratio (ICER) of $751,056 per quality-adjusted life year (QALY). In the healthcare sector perspective, robotic proctectomy resulted in $983/case more and an ICER of $1,485,139/QALY. One-way sensitivity analyses demonstrated factors influencing cost-effectiveness primarily pertained to the operative cost and the postoperative length of stay (LOS). In a probabilistic sensitivity analysis, the cost-effective approach to proctectomy was laparoscopic in 42% of cases, robotic in 39%, and open in 19% at a willingness-to-pay (WTP) of $100,000/QALY. CONCLUSIONS: Laparoscopic and robotic proctectomy cost less and have higher QALY than the open approach. Based on current data, laparoscopy is the most cost-effective approach. Robotic proctectomy can be cost-effective if modest differences in costs or postoperative LOS can be achieved.

Cost-Effectiveness of Ivacaftor Therapy for Treatment of Cystic Fibrosis Patients With the G551D Gating Mutation.

OBJECTIVES: Cystic fibrosis (CF) is a rare genetic disease with no cure. Until recently, treatment has targeted symptoms of the disease and not the disease-causing genetic defect. Ivacaftor is included in a new class of breakthrough drugs targeting the genetic defects of CF. We sought to estimate the long-term cost-effectiveness of ivacaftor from a US payer perspective. METHODS: We developed an individual-level microsimulation model that followed a cohort of heterogeneous US CF patients over a lifetime. The primary outcome of interest was quality-adjusted life years (QALYs). We also compared unadjusted life years, count of acute pulmonary exacerbations, and count of lung transplants over a lifetime between patients treated with ivacaftor plus best supportive care and patients treated with best supportive care alone. We conducted one-way and probabilistic sensitivity analyses to test the impact of various model inputs and uncertainties. RESULTS: We found a substantial increase in QALYs, life years, and treatment costs over a lifetime for patients treated with ivacaftor plus best supportive care versus best supportive care alone. Discounted results for ivacaftor were 22.92 QALYs and $8 797 840 in total lifetime costs compared to 16.12 QALYs and $2 336 366 lifetime costs for best supportive care alone. The incremental cost-effectiveness ratios (ICERs) were $950 217 per QALY. Results from the probabilistic sensitivity analysis indicated a 0% chance that ivacaftor was cost-effective at a willingness-to-pay (WTP) threshold of $500 000 per QALY. CONCLUSIONS: Treatment with ivacaftor plus best supportive care versus best supportive care alone is not cost-effective at or near commonly accepted WTP thresholds.

Validation of Colorectal Cancer Models on Long-term Outcomes from a Randomized Controlled Trial.

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 y following randomization, have been published. We use the outcomes from this trial to validate 3 microsimulation models for CRC to long-term study outcomes. We find that 2 of 3 models accurately predict the relative effect of screening (the hazard ratios) on CRC-specific incidence 17 y after screening. We find that all 3 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 3 models accurately predict the relative reduction in CRC incidence 17 y after screening. One model accurately predicted the absolute incidence and mortality rates in the screened group. The models differ in their estimates related to adenoma detection at screening. Although 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.

Estimating Population-Based Recurrence Rates of Colorectal Cancer over Time in the United States.

BACKGROUND: Population-based metastatic recurrence rates for patients diagnosed with nonmetastatic colorectal cancer cannot be estimated directly from population-based cancer registries because recurrence information is not reported. We derived population-based colorectal cancer recurrence rates using disease-specific survival data based on our understanding of the colorectal cancer recurrence-death process. METHODS: We used a statistical continuous-time multistate survival model to derive population-based annual colorectal cancer recurrence rates from 6 months to 10 years after colorectal cancer diagnosis using relative survival data from the Surveillance, Epidemiology, and End Results Program. The model was based on the assumption that, after 6 months of diagnosis, all colorectal cancer-related deaths occur only in patients who experience a metastatic recurrence first, and that the annual colorectal cancer-specific death rate among patients with recurrence was the same as in those diagnosed with de novo metastatic disease. We allowed recurrence rates to vary by post-diagnosis time, age, stage, and location for two diagnostic time periods. RESULTS: In patients diagnosed in 1975-1984, annual recurrence rates 6 months to 5 years after diagnosis ranged from 0.054 to 0.060 in stage II colon cancer, 0.094 to 0.105 in stage II rectal cancer, and 0.146 to 0.177 in stage III colorectal cancer, depending on age. We found a statistically significant decrease in colorectal cancer recurrence among patients diagnosed in 1994-2003 compared with those diagnosed in 1975-1984 for 6 months to 5 years after diagnosis (hazard ratios between 0.43 and 0.70). CONCLUSIONS: We derived population-based annual recurrence rates for up to 10 years after diagnosis using relative survival data. IMPACT: Our estimates can be used in decision-analytic models to facilitate analyses of colorectal cancer interventions that are more generalizable.

Cost-effectiveness of surveillance with CT colonography after resection of colorectal cancer.

OBJECTIVE: Surveillance following colorectal cancer (CRC) resection uses optical colonoscopy (OC) to detect intraluminal disease and CT to detect extracolonic recurrence. CT colonography (CTC) might be an efficient use of resources in this situation because it allows for intraluminal and extraluminal evaluations with one test. DESIGN: We developed a simulation model to compare lifetime costs and benefits for a cohort of patients with resected CRC. Standard of care involved annual CT for 3 years and OC for years 1, 4 and every 5 years thereafter. For the CTC-based strategy, we replace CT+OC at year 1 with CTC. Patients with lesions greater than 6 mm detected by CTC underwent OC. Detection of an adenoma 10 mm or larger was followed by OC at 1 year, then every 3 years thereafter. Test characteristics and costs for CTC were derived from a clinical study. Medicare costs were used for cancer care costs as well as alternative test costs. We discounted costs and effects at 3% per year. RESULTS: For persons with resected stage III CRC, the standard-of-care strategy was more costly (US$293) and effective (2.6 averted CRC cases and 1.1 averted cancer deaths per 1000) than the CTC-based strategy, with an incremental cost-effectiveness ratio of US$55 500 per quality-adjusted life-year gained. Our analysis was most sensitive to the sensitivity of CTC for detecting polyps 10 mm or larger and assumptions about disease progression. CONCLUSION: In a simulation model, we found that replacing the standard-of-care approach to postdiagnostic surveillance with a CTC-based strategy is not an efficient use of resources in most situations.