Pfizer Inc, New York, NY, USA.
Clarify Health Solutions, New York, NY, USA.
Sci Rep. 2024 Jul 15;14(1):16261. doi: 10.1038/s41598-024-62660-5.
Tafamidis is the only disease-modifying therapy approved to treat patients in the United States with transthyretin amyloid cardiomyopathy (ATTR-CM), which most commonly affects patients aged ≥ 65 years. The manufacturer operates a patient assistance program (PAP) to support access to tafamidis. This study conducted Privacy Preserving Record Linking (PPRL) using Datavant tokens to match patients across Medicare prescription drug plan (PDP) and PAP databases to evaluate the impact of PAPs on treatment exposure classification, adherence, and persistence determined using Medicare PDP data alone. We found 35% of Medicare PDP patients received tafamidis through the PAP only; 14% through both Medicare PDP and the PAP, and 51% through Medicare PDP only. Adherence and persistence were comparable between these cohorts but underestimated among patients who received ≥ 2 prescriptions through Medicare PDP and ≥ 1 through the PAP when solely using Medicare data versus pooled Medicare and PAP data (modified Medication Possession Ratio: 84% [69% ≥ 80% adherent] vs. 96% [93%]; Proportion of Days Covered: 77% [66% ≥ 80% adherent] vs. 88% [88%]; mean days to discontinuation: 186 vs. 252; total discontinuation: 13% vs. 11%). Cross-database PPRL is a valuable method to build more complete treatment journeys and reduce the risk of exposure misclassification in real-world analyses.
他替昔单抗是唯一一种获得批准用于治疗美国转甲状腺素蛋白淀粉样心肌病(ATTR-CM)患者的疾病修正疗法,这种疾病最常影响年龄≥65 岁的患者。该药物的制造商运营着一项患者援助计划(PAP),以支持替昔单抗的可及性。本研究使用 Datavant 令牌进行了隐私保护记录链接(PPRL),以在医疗保险处方药计划(PDP)和 PAP 数据库中匹配患者,评估 PAP 对仅使用医疗保险 PDP 数据确定的治疗暴露分类、依从性和持久性的影响。我们发现,35%的医疗保险 PDP 患者仅通过 PAP 接受替昔单抗治疗;14%的患者同时通过医疗保险 PDP 和 PAP 接受治疗,51%的患者仅通过医疗保险 PDP 接受治疗。这些队列之间的依从性和持久性相当,但仅使用医疗保险数据与合并医疗保险和 PAP 数据相比,通过医疗保险 PDP 接受≥2 次处方和通过 PAP 接受≥1 次处方的患者的依从性和持久性被低估(修正后的用药维持率:84%[69%≥80%依从]与 96%[93%];覆盖率:77%[66%≥80%依从]与 88%[88%];停药平均天数:186 天与 252 天;总停药人数:13%与 11%)。跨数据库 PPRL 是一种构建更完整治疗历程和降低真实世界分析中暴露错误分类风险的有价值方法。