| アブストラクト | OBJECTIVE: Some previously developed risk scores contained a mathematical error in their construction: risk ratios were added to derive weights to construct a summary risk score. This study demonstrates the mathematical error and derived different versions of the Charlson comorbidity score (CCS) using regression coefficient-based and risk ratio-based scoring systems to further demonstrate the effects of incorrect weighting on performance in predicting mortality. STUDY DESIGN AND SETTING: This retrospective cohort study included elderly people from the Clinical Practice Research Datalink. Cox proportional hazards regression models were constructed for time to 1-year mortality. Weights were assigned to 17 comorbidities using regression coefficient-based and risk ratio-based scoring systems. Different versions of CCS were compared using Akaike information criteria (AIC), McFadden's adjusted R(2), and net reclassification improvement (NRI). RESULTS: Regression coefficient-based models (Beta, Beta10/integer, Beta/Schneeweiss, Beta/Sullivan) had lower AIC and higher R(2) compared to risk ratio-based models (HR/Charlson, HR/Johnson). Regression coefficient-based CCS reclassified more number of people into the correct strata (NRI range, 9.02-10.04) compared to risk ratio-based CCS (NRI range, 8.14-8.22). CONCLUSION: Previously developed risk scores contained an error in their construction adding ratios instead of multiplying them. Furthermore, as demonstrated here, adding ratios fail to even work adequately from a practical standpoint. CCS derived using regression coefficients performed slightly better than in fitting the data compared to risk ratio-based scoring systems. Researchers should use a regression coefficient-based scoring system to develop a risk index, which is theoretically correct. |
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| ジャーナル名 | Journal of clinical epidemiology |
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| Pubmed追加日 | 2016/5/18 |
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| 投稿者 | Mehta, Hemalkumar B; Mehta, Vinay; Girman, Cynthia J; Adhikari, Deepak; Johnson, Michael L |
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| 組織名 | Department of Surgery, University of Texas Medical Branch, 300 University Blvd,;Galveston, TX 77555, USA.;Department of Pharmacoepidemiology, Merck, 351 N Sumneytown Pike, North Wales, PA;19454, USA. Electronic address: vinay_mehta@merck.com.;CERobs Consulting LLC, PO Box 16041, Chapel Hill, NC 27516, USA.;Department of Pharmaceutical Health Outcomes and Policy, College of Pharmacy,;University of Houston, 1441 Moursund Street, Houston, TX 77030, USA. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/27181564/ |
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