Hi all, the reference for this method was: “Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modeling and estimation of treatment effects” published in Stat Med (2002) 21: 2175 The abstract is: Modelling of censored survival data is almost always done by Cox proportional-hazards regression. However, use of parametric models for such data may have some advantages. For example, non-proportional hazards, a potential difficulty with Cox models, may sometimes be handled in a simple way, and visualization of the hazard function is much easier. Extensions of the Weibull and log-logistic models are proposed in which natural cubic splines are used to smooth the baseline log cumulative hazard and log cumulative odds of failure functions. Further extensions to allow non-proportional effects of some or all of the covariates are introduced. A hypothesis test of the appropriateness of the scale chosen for covariate effects (such as of treatment) is proposed. The new models are applied to two data sets in cancer. The results throw interesting light on the behaviour of both the hazard function and the hazard ratio over time. The tools described here may be a step towards providing greater insight into the natural history of the disease and into possible underlying causes of clinical events. We illustrate these aspects by using the two examples in cancer. Hope this helps someone give me some hints how to do this in R. Thanks John ----- Original Message ----- From: array chip <arrayprof...@yahoo.com> To: r-help <r-help@r-project.org> Cc: Sent: Thursday, August 4, 2011 11:44 AM Subject: [R] survival probability estimate method
Hi, I was reading a paper published in JCO "Prediction of risk of distant recurrence using 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study" (ICO 2010 28: 1829). The author uses a method to estimate the 9-year risk of distant recurrence as a function of continuous recurrence score (RS). The method is special as author states: "To define the continuous relation between RS, as a linear covariate, and 9-year risk of distant recurrence, the logarithm of the baseline cumulative hazard function was fitted by constrained cubic splines with 3 df. These models tend to be more robust for prediction of survival probabilities and corresponding confidence limits at late follow-up time as a result of the modeling of the baseline cumulative hazard function by natural cubic splines (in contrast to using the crude hazard function itself)." Does R provide a package/function to do this particular method for estimating survival probability as a function of a continuous variable? Is the survest.cph() in rms package doing estimation with just the crude hazard function? Thanks very much! John ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
