PURPOSE This pilot study examined the ability to operationalize the collection of real-world data to explore the potential use of real-world end points extracted from data from diverse health care data organizations and to assess how these relate to similar end points in clinical trials for immunotherapy-treated advanced non–small-cell lung cancer. PATIENTS AND METHODS Researchers from six organizations followed a common protocol using data from administrative claims and electronic health records to assess real-world end points, including overall survival (rwOS), time to next treatment, time to treatment discontinuation (rwTTD), time to progression, and progression-free survival, among patients with advanced non–small-cell lung cancer treated with programmed death 1/programmed death-ligand 1 inhibitors in real-world settings. Data sets included from 269 to 6,924 patients who were treated between January 2011 and October 2017. Results from contributors were anonymized. RESULTS Correlations between real-world intermediate end points (rwTTD and time to next treatment) and rwOS were moderate to high (range, 0.6 to 0.9). rwTTD was the most consistent end points as treatment detail was available in all data sets. rwOS at 1 year post–programmed death-ligand 1 initiation ranged from 40% to 57%. In addition, rwOS as assessed via electronic health records and claims data fell within the range of median OS values observed in relevant clinical trials. Data sources had been used extensively for research with ongoing data curation to assure accuracy and practical completeness before the initiation of this research. CONCLUSION These findings demonstrate that real-world end points are generally consistent with each other and with outcomes observed in randomized clinical trials, which substantiates the potential validity of real-world data to support regulatory and payer decision making. Differences observed likely reflect true differences between real-world and protocol-driven practices.

No abstract

Continued education and advocacy on the importance of targeted donor screening are needed.

The purpose of this study was to evaluate the potential collective opportunities and challenges of transforming real-world data (RWD) to real-world evidence for clinical effectiveness by focusing on aligning analytic definitions of oncology end points. Patients treated with a qualifying therapy for advanced non-small cell lung cancer in the frontline setting meeting broad eligibility criteria were included to reflect the real-world population. Although a trend toward improved outcomes in patients receiving PD-(L)1 therapy over standard chemotherapy was observed in RWD analyses, the magnitude and consistency of treatment effect was more heterogeneous than previously observed in controlled clinical trials. The study design and analysis process highlighted the identification of pertinent methodological issues and potential innovative approaches that could inform the development of high-quality RWD studies.The 21st Century Cures Act was enacted in 2016, to evaluate the health policy goals of trial design modernization and use of realworld evidence (RWE) creating numerous synergistic efforts. 1 These efforts aim to further understand ways in which RWE may complement or supplement randomized controlled trial data for regulatory purposes. [2][3][4][5][6] Evaluating applied examples of real-world data (RWD) and the generation of RWE are central to this effort. We build on the foundational work from the Duke-Margolis Center for Health Policy 2,3,6 and the National Academies of Science, Engineering, and Medicine (NASEM) 5 by highlighting

Because anemia is one of the markers of morbidity associated with schistosomiasis, it has been proposed as a potential measure to evaluate the impact of control programs. However, anemia is also a common consequence of malaria, and schistosomiasis and malaria are often co-endemic. To estimate the attributable fraction of anemia due to and infections, we applied a log-binomial model to four studies measuring these parameters of a combined 5,849 children in western Kenya. In our studies, malaria contributed 23.3%, schistosomiasis contributed 6.6%, and co-infection contributed 27.6% of the anemia. We conclude that in areas where and are co-endemic, the contribution of schistosomiasis to anemia is masked by anemia resulting from malaria, thus limiting anemia as a useful measure for schistosomiasis control programs in these settings.