OBJECTIVE: To compare the assumptions and estimands across three approaches to estimate the effect of erythropoietin-stimulating agents (ESAs) on mortality. STUDY DESIGN AND SETTING: Using data from the Renal Management Information System, we conducted two analyses using a change to bundled payment that, we hypothesized, mimicked random assignment to ESA (pre-post, difference-in-difference, and instrumental variable analyses). A third analysis was based on multiply imputing potential outcomes using propensity scores. RESULTS: There were 311,087 recipients of ESAs and 13,095 non-recipients. In the pre-post comparison, we identified no clear relationship between bundled payment (measured by calendar time) and the incidence of death within 6 months (risk difference -1.5%; 95% confidence interval [CI] -7.0%, 4.0%). In the instrumental variable analysis, the risk of mortality was similar among ESA recipients (risk difference -0.9%; 95% CI -2.1, 0.3). In the multiple imputation analysis, we observed a 4.2% (95% CI 3.4%, 4.9%) absolute reduction in mortality risk with the use of ESAs, but closer to the null for patients with baseline hematocrit level >36%. CONCLUSION: Methods emanating from different disciplines often rely on different assumptions but can be informative about a similar causal contrast. The implications of these distinct approaches are discussed.
OBJECTIVE: To compare the assumptions and estimands across three approaches to estimate the effect of erythropoietin-stimulating agents (ESAs) on mortality. STUDY DESIGN AND SETTING: Using data from the Renal Management Information System, we conducted two analyses using a change to bundled payment that, we hypothesized, mimicked random assignment to ESA (pre-post, difference-in-difference, and instrumental variable analyses). A third analysis was based on multiply imputing potential outcomes using propensity scores. RESULTS: There were 311,087 recipients of ESAs and 13,095 non-recipients. In the pre-post comparison, we identified no clear relationship between bundled payment (measured by calendar time) and the incidence of death within 6 months (risk difference -1.5%; 95% confidence interval [CI] -7.0%, 4.0%). In the instrumental variable analysis, the risk of mortality was similar among ESA recipients (risk difference -0.9%; 95% CI -2.1, 0.3). In the multiple imputation analysis, we observed a 4.2% (95% CI 3.4%, 4.9%) absolute reduction in mortality risk with the use of ESAs, but closer to the null for patients with baseline hematocrit level >36%. CONCLUSION: Methods emanating from different disciplines often rely on different assumptions but can be informative about a similar causal contrast. The implications of these distinct approaches are discussed.
Authors: Tobias Kurth; Alexander M Walker; Robert J Glynn; K Arnold Chan; J Michael Gaziano; Klaus Berger; James M Robins Journal: Am J Epidemiol Date: 2005-12-21 Impact factor: 4.897
Authors: A Besarab; W K Bolton; J K Browne; J C Egrie; A R Nissenson; D M Okamoto; S J Schwab; D A Goodkin Journal: N Engl J Med Date: 1998-08-27 Impact factor: 91.245
Authors: Taylor A Melanson; Jason M Hockenberry; Laura Plantinga; Mohua Basu; Stephan Pastan; Sumit Mohan; David H Howard; Rachel E Patzer Journal: Health Aff (Millwood) Date: 2017-06-01 Impact factor: 6.301
Authors: Francesca L Beaudoin; Roee Gutman; Roland C Merchant; Melissa A Clark; Robert A Swor; Jeffrey S Jones; David C Lee; David A Peak; Robert M Domeier; Niels K Rathlev; Samuel A McLean Journal: Pain Date: 2017-02 Impact factor: 7.926