This article helped a lot,
Thank you so much !
Diego
----- Messaggio originale -----
Da: Richard Goldstein <[email protected]>
A: [email protected]
Inviato: Marted� 6 marzo 2007, 15:46:59
Oggetto: Re: st: RE: Survival analysis: finding best cut-off values
I'm not sure exactly what you are looking for or want;
however, if the formulation of something like the
Framingham heart risk score is at all related, you
might want to look at: Sullivan, LM, et al. (2004),
"Presentation of multivariate data for clinical use:
the Framingham Study risk score functions," _Statistics
in Medicine_, 23: 1631-1660
Rich
Diego Bellavia wrote:
> mmhh, Ok.
>
> I will not do that in the future, but then, what is the most efficient way to find
> cut-off values for predictors ?
>
> Diego
>
> ----- Messaggio originale -----
> Da: Nick Cox <[email protected]>
> A: [email protected]
> Inviato: Marted� 6 marzo 2007, 15:29:04
> Oggetto: st: RE: Survival analysis: finding best cut-off values
>
>
> The practice of dividing good continuous
> variables into categories is retrograde.
> See Frank Harrell's book on "Regression modeling
> strategies" from Springer in 2001.
>
> Nick
> [email protected]
>
> Diego Bellavia
>
>
>>I am performing a survival analysis on a dataset with many
>>variables. Multivariate cox proportional-hazard models
>>defined the best predictors (around 7 out of 270 variables).
>>I would like to give the readers some cut-off values
>>they can use in the clinical practice, so I divided the most
>>significant predictors in tertiles, create the dummy variables
>>and run Cox models for each variable (groups of dummy vars).
>>Doing so, I obtain significant/unsignificant tertiles and
>>Kaplan-Meyer graphs
>>stratified by tertiles. Thsi way works pretty well. But what
>>if I would like to find only one cut-off per variable ?
>>I thought to use ROC curves to define the best diagnostic
>>cut-offs and see if they are good also for prognosis, but
>>unfortunately not all the best
>>predictors are so good also to discriminate groups of patients.
>>In conclusion my question is: there is a way to obtain the
>>best prognostic cut-off value using Cox models ?
>
>
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