PURPOSE: This study tested whether a composite mortality score could overcome gaps and potential biases in individual real-world mortality data sources. Complete and accurate mortality data are necessary to calculate important outcomes in oncology, including overall survival. However, in the United States, there is not a single complete and broadly applicable mortality data source. It is further likely that available data sources are biased in their coverage of sex, race, age, and socioeconomic status (SES). METHODS: Six individual real-world data sources were combined to develop a high-quality composite mortality score. The composite score was benchmarked against the gold standard for mortality data, the National Death Index. Subgroup analyses were then conducted to evaluate the completeness and accuracy by sex, race, age, and SES. RESULTS: The composite mortality score achieved a sensitivity of 94.9% and specificity of 92.8% compared with the National Death Index, with concordance within 1 day of 98.6%. Although some individual data sources show significant coverage gaps related to sex, race, age, and SES, the composite score maintains high sensitivity (84.6%-96.1%) and specificity (77.9%-99.2%) across subgroups. CONCLUSION: A composite score leveraging multiple scalable sources for mortality in the real-world setting maintained strong sensitivity, specificity, and concordance, including across sex, race, age, and SES subgroups.
PURPOSE: This study tested whether a composite mortality score could overcome gaps and potential biases in individual real-world mortality data sources. Complete and accurate mortality data are necessary to calculate important outcomes in oncology, including overall survival. However, in the United States, there is not a single complete and broadly applicable mortality data source. It is further likely that available data sources are biased in their coverage of sex, race, age, and socioeconomic status (SES). METHODS: Six individual real-world data sources were combined to develop a high-quality composite mortality score. The composite score was benchmarked against the gold standard for mortality data, the National Death Index. Subgroup analyses were then conducted to evaluate the completeness and accuracy by sex, race, age, and SES. RESULTS: The composite mortality score achieved a sensitivity of 94.9% and specificity of 92.8% compared with the National Death Index, with concordance within 1 day of 98.6%. Although some individual data sources show significant coverage gaps related to sex, race, age, and SES, the composite score maintains high sensitivity (84.6%-96.1%) and specificity (77.9%-99.2%) across subgroups. CONCLUSION: A composite score leveraging multiple scalable sources for mortality in the real-world setting maintained strong sensitivity, specificity, and concordance, including across sex, race, age, and SES subgroups.
Authors: Jonathan M Loree; Seerat Anand; Arvind Dasari; Joseph M Unger; Anirudh Gothwal; Lee M Ellis; Gauri Varadhachary; Scott Kopetz; Michael J Overman; Kanwal Raghav Journal: JAMA Oncol Date: 2019-10-10 Impact factor: 31.777
Authors: Melissa D Curtis; Sandra D Griffith; Melisa Tucker; Michael D Taylor; William B Capra; Gillis Carrigan; Ben Holzman; Aracelis Z Torres; Paul You; Brandon Arnieri; Amy P Abernethy Journal: Health Serv Res Date: 2018-05-14 Impact factor: 3.402
Authors: Donna R Rivera; Henry J Henk; Elizabeth Garrett-Mayer; Jennifer B Christian; Andrew J Belli; Suanna S Bruinooge; Janet L Espirito; Connor Sweetnam; Monika A Izano; Yanina Natanzon; Nicholas J Robert; Mark S Walker; Aaron B Cohen; Marley Boyd; Lindsey Enewold; Eric Hansen; Rebecca Honnold; Lawrence Kushi; Pallavi S Mishra Kalyani; Ruth Pe Benito; Lori C Sakoda; Elad Sharon; Olga Tymejczyk; Emily Valice; Joseph Wagner; Laura Lasiter; Jeff D Allen Journal: Clin Pharmacol Ther Date: 2021-11-11 Impact factor: 6.903