Illustration of the Impact of Unmeasured Confounding Within an Economic Evaluation Based on Nonrandomized Data.

Autor:	Guertin JR; Programs for Assessment of Technology in Health, The Research Institute of St. Joe's Hamilton, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Social and Preventive Medicine, Université Laval, Quebec City, Quebec, Canada (JRG).; Centre de recherche du CHU de Québec-Université Laval, Axe Santé des Populations et Pratiques Optimales en Santé, Hôpital du St-Sacrement, Quebec City, Quebec, Canada (JRG).; Division of Vascular Surgery, Department of Surgery, London Health Sciences Centre, London, Ontario, Canada (GDR).; Division of Vascular Surgery, Department of Surgery, Faculty of Medicine, Western University, London, Ontario, Canada (GDR)., Bowen JM; Programs for Assessment of Technology in Health, The Research Institute of St. Joe's Hamilton, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Social and Preventive Medicine, Université Laval, Quebec City, Quebec, Canada (JRG).; Centre de recherche du CHU de Québec-Université Laval, Axe Santé des Populations et Pratiques Optimales en Santé, Hôpital du St-Sacrement, Quebec City, Quebec, Canada (JRG).; Division of Vascular Surgery, Department of Surgery, London Health Sciences Centre, London, Ontario, Canada (GDR).; Division of Vascular Surgery, Department of Surgery, Faculty of Medicine, Western University, London, Ontario, Canada (GDR)., De Rose G; Programs for Assessment of Technology in Health, The Research Institute of St. Joe's Hamilton, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Social and Preventive Medicine, Université Laval, Quebec City, Quebec, Canada (JRG).; Centre de recherche du CHU de Québec-Université Laval, Axe Santé des Populations et Pratiques Optimales en Santé, Hôpital du St-Sacrement, Quebec City, Quebec, Canada (JRG).; Division of Vascular Surgery, Department of Surgery, London Health Sciences Centre, London, Ontario, Canada (GDR).; Division of Vascular Surgery, Department of Surgery, Faculty of Medicine, Western University, London, Ontario, Canada (GDR)., O'Reilly DJ; Programs for Assessment of Technology in Health, The Research Institute of St. Joe's Hamilton, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Social and Preventive Medicine, Université Laval, Quebec City, Quebec, Canada (JRG).; Centre de recherche du CHU de Québec-Université Laval, Axe Santé des Populations et Pratiques Optimales en Santé, Hôpital du St-Sacrement, Quebec City, Quebec, Canada (JRG).; Division of Vascular Surgery, Department of Surgery, London Health Sciences Centre, London, Ontario, Canada (GDR).; Division of Vascular Surgery, Department of Surgery, Faculty of Medicine, Western University, London, Ontario, Canada (GDR)., Tarride JE; Programs for Assessment of Technology in Health, The Research Institute of St. Joe's Hamilton, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada (JRG, JMB, DJO, JT).; Department of Social and Preventive Medicine, Université Laval, Quebec City, Quebec, Canada (JRG).; Centre de recherche du CHU de Québec-Université Laval, Axe Santé des Populations et Pratiques Optimales en Santé, Hôpital du St-Sacrement, Quebec City, Quebec, Canada (JRG).; Division of Vascular Surgery, Department of Surgery, London Health Sciences Centre, London, Ontario, Canada (GDR).; Division of Vascular Surgery, Department of Surgery, Faculty of Medicine, Western University, London, Ontario, Canada (GDR).
Jazyk:	angličtina
Zdroj:	MDM policy & practice [MDM Policy Pract] 2017 Mar 16; Vol. 2 (1), pp. 2381468317697711. Date of Electronic Publication: 2017 Mar 16 (Print Publication: 2017).
DOI:	10.1177/2381468317697711
Abstrakt:	Background: Propensity score (PS) methods are frequently used within economic evaluations based on nonrandomized data to adjust for measured confounders, but many researchers omit the fact that they cannot adjust for unmeasured confounders. Objective: To illustrate how confounding due to unmeasured confounders can bias an economic evaluation despite PS matching. Methods: We used data from a previously published nonrandomized study to select a prematched population consisting of 121 patients (46.5%) who received endovascular aneurysm repair (EVAR) and 139 patients (53.5%) who received open surgical repair (OSR), in which sufficient data regarding eight measured confounders were available. One-to-one PS matching was used within this population to select two PS-matched subpopulations. The Matched PS-Smoking Excluded Subpopulation was selected by matching patients using a PS model that omitted patients' smoking status (one of the measured confounders), whereas the Matched PS-Smoking Included Subpopulation was selected by matching patients using a PS model that included all eight measured confounders. Incremental cost-effectiveness ratios (ICERs) were assessed within both subpopulations. Results: Both subpopulations were composed of two different sets of 164 patients. Balance within the Matched PS-Smoking Excluded Subpopulation was achieved on all confounders except for patients' smoking status, whereas balance within the Matched PS-Smoking Included Subpopulation was achieved on all confounders. Results indicated that the ICER of EVAR over OSR differed between both subpopulations; the ICER was estimated at $157,909 per life-year gained (LYG) within the Matched PS-Smoking Excluded Subpopulation, while it was estimated at $235,074 per LYG within the Matched PS-Smoking Included Subpopulation. Discussion: Although effective in controlling for measured confounding, PS matching may not adjust for unmeasured confounders that may bias the results of an economic evaluation based on nonrandomized data.
Databáze:	MEDLINE
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