2003
DOI: 10.1002/sim.1333
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Methods for categorizing a prognostic variable in a multivariable setting

Abstract: The literature is filled with examples of categorization of a continuous prognostic variable in a univariable setting followed by the addition of this categorical variable to an existing multivariable model. Typically, an "optimal" cutpoint for a new prognostic variable is obtained through a systematic search relating the variable to the outcome in an univariable manner. The corresponding categorical variable is then fitted in a multivariable model along with other already established prognostic covariates to … Show more

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Cited by 113 publications
(98 citation statements)
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References 19 publications
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“…Cut-off points of INHBA were evaluated in a multivariate Cox proportional-hazards model with prognostic factors that were significantly related to overall survival in the univariate analysis. "Optimal" cut-off points were selected by the minimum p-value method, whereas the internal validity of the cut-off points was evaluated with a two-fold cross-validation approach (7). Relations between gene expression and potential prognostic variables were evaluated using the χ 2 test.…”
Section: Quantitative Real-time Reverse-transcriptase Polymerase Chamentioning
confidence: 99%
“…Cut-off points of INHBA were evaluated in a multivariate Cox proportional-hazards model with prognostic factors that were significantly related to overall survival in the univariate analysis. "Optimal" cut-off points were selected by the minimum p-value method, whereas the internal validity of the cut-off points was evaluated with a two-fold cross-validation approach (7). Relations between gene expression and potential prognostic variables were evaluated using the χ 2 test.…”
Section: Quantitative Real-time Reverse-transcriptase Polymerase Chamentioning
confidence: 99%
“…To dichotomise prognostic variables, CD3, CD8, and CD45RO, a two-fold cross-validation methodology and a minimum P-value approach (Mazumdar et al, 2003) were used. The dataset was randomly divided into two subsets.…”
Section: Two-fold Cross-validation Approachmentioning
confidence: 99%
“…In the final multivariate model, a χ² test using the minimum p-value approach was used for all categorised variables associated with nephrolithiasis or SAR, in order to choose the more discriminating threshold among those best separating patients with nephrolithiasis or SAR from patients without (30). To avoid biased relative risk, it was followed by a cross validation (31). SAS software (version 8.2 ; SAS Institute Inc, Cary, NC, USA) was used for statistical analysis.…”
Section: Methodsmentioning
confidence: 99%