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A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies

OBJECTIVE: Estimating calibration performance of clinical prediction rules (CPRs) in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe...

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Autores principales: Dimitrov, Borislav D, Motterlini, Nicola, Fahey, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404967/
https://www.ncbi.nlm.nih.gov/pubmed/25931829
http://dx.doi.org/10.2147/CLEP.S67632
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author Dimitrov, Borislav D
Motterlini, Nicola
Fahey, Tom
author_facet Dimitrov, Borislav D
Motterlini, Nicola
Fahey, Tom
author_sort Dimitrov, Borislav D
collection PubMed
description OBJECTIVE: Estimating calibration performance of clinical prediction rules (CPRs) in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe a simplified approach for outcomes prediction and calibration assessment and evaluate its functionality and validity. STUDY DESIGN AND METHODS: Methodological study of systematic reviews of validation studies of CPRs: a) ABCD(2) rule for prediction of 7 day stroke; and b) CRB-65 rule for prediction of 30 day mortality. Predicted outcomes in a sample validation study were computed by CPR distribution patterns (“derivation model”). As confirmation, a logistic regression model (with derivation study coefficients) was applied to CPR-based dummy variables in the validation study. Meta-analysis of validation studies provided pooled estimates of “predicted:observed” risk ratios (RRs), 95% confidence intervals (CIs), and indexes of heterogeneity (I(2)) on forest plots (fixed and random effects models), with and without adjustment of intercepts. The above approach was also applied to the CRB-65 rule. RESULTS: Our simplified method, applied to ABCD(2) rule in three risk strata (low, 0–3; intermediate, 4–5; high, 6–7 points), indicated that predictions are identical to those computed by univariate, CPR-based logistic regression model. Discrimination was good (c-statistics =0.61–0.82), however, calibration in some studies was low. In such cases with miscalibration, the under-prediction (RRs =0.73–0.91, 95% CIs 0.41–1.48) could be further corrected by intercept adjustment to account for incidence differences. An improvement of both heterogeneities and P-values (Hosmer-Lemeshow goodness-of-fit test) was observed. Better calibration and improved pooled RRs (0.90–1.06), with narrower 95% CIs (0.57–1.41) were achieved. CONCLUSION: Our results have an immediate clinical implication in situations when predicted outcomes in CPR validation studies are lacking or deficient by describing how such predictions can be obtained by everyone using the derivation study alone, without any need for highly specialized knowledge or sophisticated statistics.
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spelling pubmed-44049672015-04-30 A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies Dimitrov, Borislav D Motterlini, Nicola Fahey, Tom Clin Epidemiol Original Research OBJECTIVE: Estimating calibration performance of clinical prediction rules (CPRs) in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe a simplified approach for outcomes prediction and calibration assessment and evaluate its functionality and validity. STUDY DESIGN AND METHODS: Methodological study of systematic reviews of validation studies of CPRs: a) ABCD(2) rule for prediction of 7 day stroke; and b) CRB-65 rule for prediction of 30 day mortality. Predicted outcomes in a sample validation study were computed by CPR distribution patterns (“derivation model”). As confirmation, a logistic regression model (with derivation study coefficients) was applied to CPR-based dummy variables in the validation study. Meta-analysis of validation studies provided pooled estimates of “predicted:observed” risk ratios (RRs), 95% confidence intervals (CIs), and indexes of heterogeneity (I(2)) on forest plots (fixed and random effects models), with and without adjustment of intercepts. The above approach was also applied to the CRB-65 rule. RESULTS: Our simplified method, applied to ABCD(2) rule in three risk strata (low, 0–3; intermediate, 4–5; high, 6–7 points), indicated that predictions are identical to those computed by univariate, CPR-based logistic regression model. Discrimination was good (c-statistics =0.61–0.82), however, calibration in some studies was low. In such cases with miscalibration, the under-prediction (RRs =0.73–0.91, 95% CIs 0.41–1.48) could be further corrected by intercept adjustment to account for incidence differences. An improvement of both heterogeneities and P-values (Hosmer-Lemeshow goodness-of-fit test) was observed. Better calibration and improved pooled RRs (0.90–1.06), with narrower 95% CIs (0.57–1.41) were achieved. CONCLUSION: Our results have an immediate clinical implication in situations when predicted outcomes in CPR validation studies are lacking or deficient by describing how such predictions can be obtained by everyone using the derivation study alone, without any need for highly specialized knowledge or sophisticated statistics. Dove Medical Press 2015-04-16 /pmc/articles/PMC4404967/ /pubmed/25931829 http://dx.doi.org/10.2147/CLEP.S67632 Text en © 2015 Dimitrov et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Dimitrov, Borislav D
Motterlini, Nicola
Fahey, Tom
A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies
title A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies
title_full A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies
title_fullStr A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies
title_full_unstemmed A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies
title_short A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies
title_sort simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404967/
https://www.ncbi.nlm.nih.gov/pubmed/25931829
http://dx.doi.org/10.2147/CLEP.S67632
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