Predicting an SF-6D preference-based score using MCS and PCS scores from the SF-12 or SF-36

54Citations
Citations of this article
55Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: The SF-6D preference-based scoring system was developed several years after the SF-12 and SF-36 instruments. A method to predict SF-6D scores from information in previous reports would facilitate backwards comparisons and the use of these reports in cost-effectiveness analyses. Methods: This report uses data from the 2001-2003 Medical Expenditures Panel Survey (MEPS), the Beaver Dam Health Outcomes Survey, and the National Health Measurement Study. SF-6D scores were modeled using age, sex, mental component summary (MCS) score, and physical component summary (PCS) score from the 2002 MEPS. The resulting SF-6D prediction equation was tested with the other datasets for groups of different sizes and groups stratified by age, MCS score, PCS score, sum of MCS and PCS scores, and SF-6D score. Results: The equation can be used to predict an average SF-6D score using average age, proportion female, average MCS score, and average PCS score. Mean differences between actual and predicted average SF-6D scores in out-of-sample tests was -0.001 (SF-12 version 1), -0.013 (SF-12 version 2), -0.007 (SF-36 version 1), and -0.010 (SF-36 version 2). Ninety-five percent credible intervals around these point estimates range from ±0.045 for groups with 10 subjects to ±0.008 for groups with more than 300 subjects. These results were consistent for a wide range of ages, MCS scores, PCS scores, sum of MCS and PCS scores, and SF-6D scores. SF-6D scores from the SF-36 and SF-12 from the same data set were found to be substantially different. Conclusions: Simple equation predicts an average SF-6D preference-based score from widely published information. © 2009, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).

Author supplied keywords

Cite

CITATION STYLE

APA

Hanmer, J. (2009). Predicting an SF-6D preference-based score using MCS and PCS scores from the SF-12 or SF-36. Value in Health, 12(6), 958–966. https://doi.org/10.1111/j.1524-4733.2009.00535.x

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free