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.

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.

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.

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.

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.

Introduction:Guidelines for routine antibiotic prophylaxis (AP) before dental procedures to prevent periprosthetic joint infection (PJI) have been hampered by the lack of prospective clinical trial...

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.

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.

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.

OBJECTIVE: Evaluate the cost-effectiveness of open, laparoscopic, and robotic colectomy. BACKGROUND: The use of robotic-assisted colon surgery is increasing. Robotic technology is more expensive and whether a robotically assisted approach is cost-effective remains to be determined. METHODS: A decision-analytic model was constructed to evaluate the 1-year costs and quality-adjusted time between robotic, laparoscopic, and open colectomy. Model inputs were derived from available literature for costs, quality of life (QOL), and outcomes. Results are presented as incremental cost-effectiveness ratios (ICERs), defined as incremental costs per quality-adjusted life year (QALY) gained. One-way and probabilistic sensitivity analyses were performed to test the effect of clinically reasonable variations in the inputs on our results. RESULTS: Open colectomy cost more and achieved lower QOL than robotic and laparoscopic approaches. From the societal perspective, robotic colectomy costs $745 more per case than laparoscopy, resulting in an ICER of $2,322,715/QALY because of minimal differences in QOL. From the healthcare sector perspective, robotics cost $1339 more per case with an ICER of $4,174,849/QALY. In both models, laparoscopic colectomy was more frequently cost-effective across a wide range of willingness-to-pay thresholds. Sensitivity analyses suggest robotic colectomy becomes cost-effective at $100,000/QALY if robotic disposable instrument costs decrease below $1341 per case, robotic operating room time falls below 172 minutes, or robotic hernia rate is less than 5%. CONCLUSIONS: Laparoscopic and robotic colectomy are more cost-effective than open resection. Robotics can surpass laparoscopy in cost-effectiveness by achieving certain thresholds in QOL, instrument costs, and postoperative outcomes. With increased use of robotic technology in colorectal surgery, there is a burden to demonstrate these benefits.

OBJECTIVES/GOALS: This project seeks to understand how personalized medicine can optimize care for patients with colorectal cancer. It identifies opportunities for personalized medicine to improve clinical outcomes, and uses cost-effectiveness analysis to assess the clinical and financial impact of this approach. METHODS/STUDY POPULATION: This project uses two methods to understand the impact of personalized medicine. First, this project has used SEER-Medicare data in conjunction with Clinical Pharmacogenetics Implementation Consortium guidelines to identify medications used by patients with colorectal cancer that can be impacted by genetic variants. This data will then be combined with population genetic variant rates to understand the likely impact screening for a given variant will have on medication response and adverse events. Medication use frequencies and genetic variant rates are then used to populate cost-effectiveness models that simulate the clinical and financial outcomes, identifying optimal genes to screen. RESULTS/ANTICIPATED RESULTS: The first result will be a comprehensive overview of treatment patterns for patients with colorectal cancer in the United States, as well as the treatments used for disease-induced comorbidities. The second result will be the identification of genetic variants based on population rates and medication utilization that should be screened in this patient population. The final result will be a breakdown of the clinical and financial outcomes associated with implementing screening for the identified genes. Preliminary results from a two-gene cost-effectiveness analysis demonstrates that screening for variants in those genes improves both clinical and financial outcomes. DISCUSSION/SIGNIFICANCE OF IMPACT: This project demonstrates how current treatment approaches can be optimized via personalized medicine. It uses epidemiological methods to identify opportunities to integrate genetic findings from other diseases, and uses cost-effectiveness analysis to understand the impact of transforming care. CONFLICT OF INTEREST DESCRIPTION: Stocks-Aurinia, Syndax, Adaptimmune, Rigel pharma

Objectives: Genetically-guided dosing of anti-cancer agents for mCRC presents the opportunity to improve patient outcomes and reduce direct patient costs, but the impact of this approach from the perspective of a health care system is uncertain. This project examines the budgetary impact of DPYD and UGT1A1 guided dosing for patients receiving FOLFIRI+bev for mCRC. Methods: We conducted a budget impact analysis following the recommendations of the joint ISPOR-SMDM taskforce. This analysis was conducted from the perspective of a US health care system, with a time horizon of 5 years after implementation. The model assumed that 100 new cases of mCRC were treated at this system with FOLFIRI+bev each year. Patients were dosed either based on their genetic variant status and anthropometrics or based on their anthropometrics alone. We included costs for genetic testing, medications and administration costs incurred to treat the disease, medications and administration costs to manage adverse events, clinic and hospitalization costs, and the salaries of providers needed to interpret and implement the genetic dosing approach. Costs were discounted at a 3% per annum rate and reported in 2018 dollars. Sensitivity analyses were conducted to test the impact of assumptions on the validity of the model. Results: The expected total cost over five years was $12,974,000 for a health care system that did not adopt genetic dosing. When 100% of the patients within the system received genetic dosing, the expected cost incurred by the system was $12,819,000, which is a savings of $155,000 or 1.2%. Conclusions: Implementation of genetically-guided dosing for FOLFIRI+bev in patients with mCRC is cost-saving from the perspective of the health care system over a 5-year time horizon. Further work should be done to determine how to implementation, and the impact of improved outcomes due to a reduction of avoidable adverse events.

INTRODUCTION AND OBJECTIVE:Intravesical chemotherapy has been demonstrated to delay recurrence in low-risk non-muscle invasive bladder cancer (LR NMIBC). Mitomycin C has been the most commonly util...

168Background: Variants in DPYD and UGT1A1 impact toxicities experienced by patients being treated with FOLFIRI+bev. Testing allows providers to preemptively adjust dosing, reducing the toxicity th...

<p>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.</p>

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. 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. 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. 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.