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Regression Coefficient Based Scoring System Should be Used to Assign Weights to the Risk Index

Mehta, Hemalkumar B ; Mehta, Vinay ; Girman, Cynthia J ; Adhikari, Deepak ; Johnson, Michael L

Journal of clinical epidemiology, 2016-11, Vol.79, p.22-28 [Periódico revisado por pares]

United States: Elsevier Inc

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Título:
Regression Coefficient Based Scoring System Should be Used to Assign Weights to the Risk Index
Autor: Mehta, Hemalkumar B ; Mehta, Vinay ; Girman, Cynthia J ; Adhikari, Deepak ; Johnson, Michael L
Assuntos: Age ; Aged ; Algorithms ; Beta ; Charlson comorbidity score ; Clinical medicine ; Cohort Studies ; Comorbidity ; Diabetes ; Epidemiologic Research Design ; Female ; Gender ; Humans ; Internal Medicine ; Kidney diseases ; Liver diseases ; Logistics ; Longitudinal Studies ; Male ; Metastasis ; Mortality ; Odds Ratio ; Proportional Hazards Models ; Ratios ; Regression analysis ; Regression coefficient ; Retrospective Studies ; Risk ; Risk index ; Risk ratio ; Scoring algorithm ; Scoring system ; Standard deviation ; Studies ; Variables
É parte de: Journal of clinical epidemiology, 2016-11, Vol.79, p.22-28
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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Descrição: Abstract Objective Some previously developed risk scores contained a major 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 and risk ratio based scoring systems to further demonstrate the effects of incorrect weighting on performance in predicting mortality. Study Design and Settings: This retrospective cohort study included elderly people from the Clinical Practice Research Datalink. Cox proportional hazards regression models were constructed for time to one-year mortality. Weights were assigned to 17 comorbidities using regression coefficient and risk ratio based scoring systems. Different versions of CCS were compared using Akaike information criteria (AIC), McFadden's adjusted R2 and net reclassification improvement (NRI). Results Regression coefficient based models (Beta, Beta10/integer, Beta/Schneeweiss, Beta/Sullivan) had lower AIC and higher R2 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. Further, 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.
Editor: United States: Elsevier Inc
Idioma: Inglês

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Regression Coefficient Based Scoring System Should be Used to Assign Weights to the Risk Index

Mehta, Hemalkumar B ; Mehta, Vinay ; Girman, Cynthia J ; Adhikari, Deepak ; Johnson, Michael L

United States: Elsevier Inc

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