Aim: Hemophilia A is a genetic, chronic disorder classified by deficient or defective coagulation factor VIII (FVIII) that puts those affected at risk for spontaneous bleeding episodes, which lead to joint damage and chronic pain over time. Currently, most severe hemophilia A patients are treated with prophylactic FVIII, which requires costly and frequent infusions and lifelong adherence to medication. A gene therapy (valoctocogene roxaparvovec) is currently in development for the treatment of severe hemophilia A. This model assessed the potential cost-effectiveness of treating patients with valoctocogene roxaparvovec rather than prophylactic therapy. Materials and methods: We developed an individual-based, state-transition microsimulation model for assessing the likely cost-effectiveness of valoctocogene roxaparvovec compared to prophylactic FVIII. Men aged 30 with severe hemophilia A were modeled over a lifetime horizon, and costs were reported from the perspective of the United States health care system. Through microsimulation, patient-level heterogeneity was captured in starting weight, starting Pettersson score (PS), durability of valoctocogene roxaparvovec, and annual bleed rate (ABR). Results: The model projects that treatment with single-administration valoctocogene roxaparvovec would be cost-saving to people with hemophilia A at a price point comparable to other currently available gene therapy products due to its potential to reduce FVIII utilization, direct medical costs, lifetime bleeds, and accumulated joint damage. Limitations: The model relies upon evidence-based assumptions for clinical inputs due to limited data availability. Such uncertainty was mitigated by modeling heterogeneity across the population, specifically with regards to long-term gene therapy durability, lifetime bleed rates, and joint damage progression. Conclusion: Valoctocogene roxaparvovec was found to be cost-saving-on average by about $6.8 million per patient-and more effective than prophylactic therapy for treatment of hemophilia A. The comparative benefit of gene therapy was observed across a broad range of simulated patients that were representative of the real-world severe hemophilia A population.

BACKGROUND: Observational analysis methods can be refined by benchmarking against randomized trials. We reviewed studies systematically comparing observational analyses using propensity score methods against randomized trials to explore whether intervention or outcome characteristics predict agreement between designs. METHODS: We searched PubMed (from January 1, 2000, to April 30, 2017), the AHRQ Scientific Resource Center Methods Library, reference lists, and bibliographies to identify systematic reviews that compared estimates from observational analyses using propensity scores against randomized trials across three or more clinical topics; reported extractable relative risk (RR) data; and were published in English. One reviewer extracted data from all eligible systematic reviews; a second reviewer verified the extracted data. RESULTS: Six systematic reviews matching published observational studies to randomized trials, published between 2012 and 2016, met our inclusion criteria. The reviews reported on 127 comparisons overall, in cardiology (29 comparisons), surgery (49), critical care medicine and sepsis (46), nephrology (2), and oncology (1). Disagreements were large (relative RR < 0.7 or > 1.43) in 68 (54%) and statistically significant in 12 (9%) of the comparisons. The degree of agreement varied among reviews but was not strongly associated with intervention or outcome characteristics. DISCUSSION: Disagreements between observational studies using propensity score methods and randomized trials can occur for many reasons and the available data cannot be used to discern the reasons behind specific disagreements. Better benchmarking of observational analyses using propensity scores (and other causal inference methods) is possible using observational studies that explicitly attempt to emulate target trials.

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Introduction: Randomized controlled trials (RCTs) are not impervious to bias especially when there are substantial numbers of patients who cross over from the treatment assigned by randomization to another treatment group, leading to loss of confidence in study results. The goals of this study were to (1) quantify the effects of crossovers on RCTs, (2) describe the specific effects of crossovers on RCTs for arthroscopic meniscectomy for osteoarthritis of the knee (APM/OAK), and (3) assess the confidence in APM/OAK in which there have been substantial numbers of patients crossing over to another treatment group than that assigned. Methods: Studies were included that were RCTs of APM/OAK with intention-to-treat (ITT) analysis and illustrated the problem of crossovers on confidence in the analysis. Studies were excluded if they consisted of APM for conditions other than OAK or had unavailability of data needed for the analysis. For eligible RCTs, the ITT effect was calculated; bounds for the average treatment effect (ATE) and the complier ATE were assessed by estimating confidence intervals for the bound through robust Bayesian analysis. Results: The eligible studies had different comparators and, therefore, were analyzed individually. Data were not pooled. The most extreme point estimates (with 95% confidence interval) for ITT ranged from 20.01 to 0.04 (20.16 to 0.16); for ATE with no assumptions, 0.38 (20.58 to 0.43) to 0.62 (0.56 to 0.70); for ATE with minimum assumptions, 20.50 (20.22 to 0.10) to 0.61 (0.53 to 0.57); and for complier ATE, 20.01 to 0.07 (20.22 to 0.24). Discussion: These data suggest large bounds, crossing the threshold of "no effect," which indicates a high degree of uncertainty and low confidence in the RCTs studied. The results demonstrate that when there are crossovers, ITT analyses do not estimate the ATE and confidence in the results of these RCTs is low. Data Availability: All analyzed data are provided in the article. Level of Evidence: Level I (therapeutic study = RCT