Clinical outcomes of adjuvant nivolumab in resected stage III melanoma: comparison of CheckMate 238 trial and real-world data.

OBJECTIVES: Nivolumab is approved as adjuvant therapy for resected stage III/IV melanoma based on the phase 3 CheckMate 238 trial. This analysis compared outcomes from CheckMate 238 with those from the real-world Flatiron Health electronic health record-derived de-identified database in patients with resected stage III melanoma (per AJCC-8) treated with adjuvant nivolumab. MATERIALS: Outcomes included baseline characteristics, overall survival (OS) in the CheckMate 238 cohort (randomization until death or last known alive), and real-world overall survival (rwOS) in the Flatiron Health cohort (nivolumab initiation until death or data cutoff). rwOS was compared with OS using unadjusted and adjusted Cox proportional hazards models. Inverse probability of treatment weighting (IPTW) was combined with the adjusted model to reduce baseline discrepancies. RESULTS: The CheckMate 238 and real-world cohorts included 369 and 452 patients, respectively (median age, 56.0 and 63.0 years; median follow-up, 61.4 vs. 25.5 months). rwOS was not different from OS in the unadjusted (hazard ratio [HR] 1.27; 95% CI 0.92-1.74), adjusted (HR 1.01; 95% CI 0.67-1.54), and adjusted IPTW (HR 1.07; 95% CI 0.70-1.63) analyses. In the adjusted analysis, 2-year OS and rwOS rates were 84%. Median OS and rwOS were not reached. After IPTW, OS and rwOS were not different (HR 1.07; 95% CI 0.70-1.64). CONCLUSIONS: In this comparative analysis, OS in the CheckMate 238 trial was similar to rwOS in the Flatiron Health database after adjustments in patients with resected stage III melanoma (per AJCC-8) treated with adjuvant nivolumab, validating the trial results.

Older adults' understanding of hypothetical community pharmacy quality report cards.

BACKGROUND: Quality ratings for health plans and health services have become increasingly available to patients. OBJECTIVE: We sought to explore older adults' understanding of hypothetical community pharmacy report cards and the information they valued on the report card. METHODS: We recruited participants aged 50 years or older to complete a 59-question telephone survey. The participants reviewed 3 different pairs of report cards, which represented a hypothetical pharmacy, and each pair contained different quality metrics. The participants identified which pharmacy of the pair they preferred, and this served as the primary outcome. We asked the participants to rate the level of importance (4-point unidirectional scale, not at all to very important) of the star ratings, source of information, and quality metrics. We also gathered information about the participants personal experiences with medications and pharmacy services, their self-reported health, health literacy, health numeracy, and demographics. The frequency that the pharmacy with higher quality metrics was selected was reported. We used logistic regression to examine factors associated with correctly identifying the highest quality pharmacy for all 3 sets of report cards. RESULTS: Most participants (n = 152) correctly identified all 3 (n = 120, 79.0%) report cards for pharmacies with higher quality metrics. The source of the information, individual quality metrics, and star ratings were all perceived as moderately or very important by most participants. Ratings of importance were strongly correlated (r, 0.70-1.00). CONCLUSION: More than 75% were able to correctly identify all 3 report cards with higher quality ratings. Most participants believed that the source of the information, the individual quality metrics, and the star rating were all important. Research is needed to explore to what extent patients would use these types of quality metric report cards to make decisions about where to obtain their medications.