Jason Shafrin

Utility of Cancer Value Frameworks for Patients, Payers, and Physicians

This Viewpoint describes differences between various cancer value frameworks and provides recommendations for improving them for clinicians, patients, and payers.

Quality-Adjusted Cost Of Care: A Meaningful Way To Measure Growth In Innovation Cost Versus The Value Of Health Gains

Technology drives both health care spending and health improvement. Yet policy makers rarely see measures of cost growth that account for both effects. To fill this gap, we present the quality-adjusted cost of care, which illustrates cost growth net of growth in the value of health improvements, measured as survival gains multiplied by the value of survival. We applied the quality-adjusted cost of care to two cases. For colorectal cancer, drug cost per patient increased by

Predicting Real-World Effectiveness of Cancer Therapies Using Overall Survival and Progression-Free Survival from Clinical Trials: Empirical Evidence for the ASCO Value Framework

34,493 between 1998 and 2005 as a result of new drug launches, but value from offsetting health improvements netted a modest

Access to credible information on schizophrenia patients’ medication adherence by prescribers can change their treatment strategies: evidence from an online survey of providers

1,377 increase in quality-adjusted cost of care. For multiple myeloma, new therapies increased treatment cost by

The value of surrogate endpoints for predicting real-world survival across five cancer types

72,937 between 2004 and 2009, but offsetting health benefits lowered overall quality-adjusted cost of care by

The Economic Burden of ACPA-Positive Status Among Patients with Rheumatoid Arthritis

67,863. However, patients with multiple myeloma on established first-line therapies saw costs rise without corresponding benefits. All three examples document rapid cost growth, but they provide starkly different answers to the question of whether society got what it paid for.

The association between observed mobility and quality of life in the near elderly

OBJECTIVES To measure the relationship between randomized controlled trial (RCT) efficacy and real-world effectiveness for oncology treatments as well as how this relationship varies depending on an RCTs use of surrogate versus overall survival (OS) endpoints. METHODS We abstracted treatment efficacy measures from 21 phase III RCTs reporting OS and either progression-free survival or time to progression endpoints in breast, colorectal, lung, ovarian, and pancreatic cancers. For these treatments, we estimated real-world OS as the mortality hazard ratio (RW MHR) among patients meeting RCT inclusion criteria in Surveillance and Epidemiology End Results-Medicare data. The primary outcome variable was real-world OS observed in the Surveillance and Epidemiology End Results-Medicare data. We used a Cox proportional hazard regression model to calibrate the differences between RW MHR and the hazard ratios on the basis of RCTs using either OS (RCT MHR) or progression-free survival/time to progression surrogate (RCT surrogate hazard ratio [SHR]) endpoints. RESULTS Treatment arm therapies reduced mortality in RCTs relative to controls (average RCT MHR = 0.85; range 0.56-1.10) and lowered progression (average RCT SHR = 0.73; range 0.43-1.03). Among real-world patients who used either the treatment or the control arm regimens evaluated in the relevant RCT, RW MHRs were 0.6% (95% confidence interval -3.5% to 4.8%) higher than RCT MHRs, and RW MHRs were 15.7% (95% confidence interval 11.0% to 20.5%) higher than RCT SHRs. CONCLUSIONS Real-world OS treatment benefits were similar to those observed in RCTs based on OS endpoints, but were 16% less than RCT efficacy estimates based on surrogate endpoints. These results, however, varied by tumor and line of therapy.

The effect of medication nonadherence on progression-free survival among patients with renal cell carcinoma

Objective Overestimating patients’ medication adherence diminishes the ability of psychiatric care providers to prescribe the most effective treatment and to identify the root causes of treatment resistance in schizophrenia. This study was conducted to determine how credible patient drug adherence information (PDAI) might change prescribers’ treatment decisions. Methods In an online survey containing 8 clinical case vignettes describing patients with schizophrenia, health care practitioners who prescribe antipsychotics to patients with schizophrenia were instructed to choose a preferred treatment recommendation from a set of predefined pharmacologic and non-pharmacologic options. The prescribers were randomly assigned to an experimental or a control group, with only the experimental group receiving PDAI. The primary outcome was the prescribers’ treatment choice for each case. Between-group differences were analyzed using multinomial logistic regression. Results A convenience sample (n=219) of prescribers completed the survey. For 3 nonadherent patient vignettes, respondents in the experimental group were more likely to choose a long-acting injectable antipsychotic compared with those in the control group (77.7% experimental vs 25.8% control; P<0.001). For 2 adherent but poorly controlled patient vignettes, prescribers who received PDAI were more likely to increase the antipsychotic dose compared with the control group (49.1% vs 39.1%; P<0.001). For the adherent and well-controlled patient vignette, respondents in both groups made similar treatment recommendations across all choices (P=0.099), but respondents in the experimental arm were more likely to recommend monitoring clinical stability (87.2% experimental vs 75.5% control, reference group). Conclusion The results illustrate how credible PDAI can facilitate more appropriate clinical decisions for patients with schizophrenia.

The Long-Term Health and Economic Value of Improved Mobility among Older Adults in the United States

Abstract Objective It is unclear how well different outcome measures in randomized controlled trials (RCTs) perform in predicting real-world cancer survival. We assess the ability of RCT overall survival (OS) and surrogate endpoints – progression-free survival (PFS) and time to progression (TTP) – to predict real-world OS across five cancers. Methods We identified 20 treatments and 31 indications for breast, colorectal, lung, ovarian, and pancreatic cancer that had a phase III RCT reporting median OS and median PFS or TTP. Median real-world OS was determined using a Kaplan–Meier estimator applied to patients in the Surveillance and Epidemiology End Results (SEER)-Medicare database (1991–2010). Performance of RCT OS and PFS/TTP in predicting real-world OS was measured using t-tests, median absolute prediction error, and R2 from linear regressions. Results Among 72,600 SEER-Medicare patients similar to RCT participants, median survival was 5.9 months for trial surrogates, 14.1 months for trial OS, and 13.4 months for real-world OS. For this sample, regression models using clinical trial OS and trial surrogates as independent variables predicted real-world OS significantly better than models using surrogates alone (P = 0.026). Among all real-world patients using sample treatments (N = 309,182), however, adding trial OS did not improve predictive power over predictions based on surrogates alone (P = 0.194). Results were qualitatively similar using median absolute prediction error and R2 metrics. Conclusions Among the five tumor types investigated, trial OS and surrogates were each independently valuable in predicting real-world OS outcomes for patients similar to trial participants. In broader real-world populations, however, trial OS added little incremental value over surrogates alone.

Estimated prevalence of undiagnosed atrial fibrillation in the United States

BACKGROUND Anticitrullinated protein antibodies (ACPAs) are serological biomarkers associated with early, rapidly progressing rheumatoid arthritis (RA), including more severe disease and joint damage. ACPA testing has become a routine tool for RA diagnosis and prognosis. Furthermore, treatment efficacy has been shown to vary by ACPA-positive status. However, it is not clear if the economic burden of patients with RA varies by ACPA status. OBJECTIVE To determine if the economic burden of RA varies by patient ACPA status. METHODS IMS PharMetrics Plus health insurance claims and electronic medical record (EMR) data from 2010-2015 were used to identify patients with incident RA. Patients were aged ≥ 18 years, had ≥ 1 inpatient or ≥ 2 outpatient claims reporting an RA diagnosis code (ICD-9-CM code 714.0), and had an anticyclic citrullinated peptide (anti-CCP; a surrogate of ACPA) antibody test within 6 months of diagnosis. Incident patients were defined as those who had no claims with an RA diagnosis code in the 6 months before the first observed RA diagnosis. The primary outcome of interest was RA-related medical expenditures, defined as the sum of payer- and patient-paid amounts for all claims with an RA diagnosis code. Secondary outcomes included health care utilization metrics such as treatment with a disease-modifying antirheumatic drug (DMARD) and physician visits. Generalized linear regression models were used for each outcome, controlling for ACPA-positive status (defined as anti-CCP ≥ 20 AU/mL), age, sex, and Charlson Comorbidity Index score as explanatory variables. RESULTS Of 647,171 patients diagnosed with RA, 89,296 were incident cases, and 47% (n = 42,285) had an anti-CCP test. After restricting this sample to patients with a linked EMR and reported anti-CCP test result, 859 remained, with 24.7% (n = 212) being ACPA-positive. Compared with ACPA-negative patients, adjusted results showed that ACPA-positive patients were more likely to use either conventional (71.2% vs. 49.6%; P < 0.001) or biologic (20.3% vs. 11.8%; P < 0.001) DMARDs during the first year after diagnosis and had more physician visits (5.58 vs. 3.91 times per year; P < 0.001). Annual RA-associated total expenditures were