Dynamic Prediction in Clinical Survival Analysis

Chapter 19 Erratum, pictureSummary

There is a huge amount of literature on statistical models for the prediction of survival after diagnosis of a wide range of diseases like cancer, cardiovascular disease, and chronic kidney disease. Current practice is to use prediction models based on the Cox proportional hazards model and to present those as static models for remaining lifetime after diagnosis or treatment. In contrast, Dynamic Prediction in Clinical Survival Analysis focuses on dynamic models for the remaining lifetime at later points in time, for instance using landmark models.

Designed to be useful to applied statisticians and clinical epidemiologists, each chapter in the book has a practical focus on the issues of working with real life data. Chapters conclude with additional material either on the interpretation of the models, alternative models, or theoretical background. The book consists of four parts:

Part I deals with prognostic models for survival data using (clinical) information available at baseline, based on the Cox model

Part II is about prognostic models for survival data using (clinical) information available at baseline, when the proportional hazards assumption of the Cox model is violated

Part III is dedicated to the use of time-dependent information in dynamic prediction

Part IV explores dynamic prediction models for survival data using genomic data

 

The dynpred package

A package for R, dynpred, has been developed, containing R functions for dynamic prediction and for assessing accuracy of dynamic predictions. The package also contains the ovarian cancer, ALL, Benelux CML, and NKI breast cancer data used in the book. The dynpred package is available from CRAN.

Data

Most of the data used in the book is available within the dynpred package. The genomic part of the NKI data has not been included in the package, due to its size. It can be downloaded as VanDeVijver.Rdata.

R code

Below, the R code of the analyses performed in the book can be downloaded, organized by chapter. For each chapter the R code is provided, as well as the resulting output and plots.

Chapter 1, code, output and plots from Chap 1.R

Chapter 2, code, output and plots from Chap 2.R

Chapter 3, code, output and plots from Chap 3.R

Chapter 4, code, output and plots from Chap 4.R

Chapter 5, code, output and plots from Chap 5.R

Chapter 6, code, output and plots from Chap 6.R

Chapter 7, code, output and plots from Chap 7.R

Chapter 8, code, output and plots from Chap 8.R

Chapter 9, code, output and plots from Chap 9.R

Chapter 10, code, output and plots from Chap 10.R

Chapter 11, code, output and plots from Chap 11.R

Chapter 12, code, output and plots from Chap 12.R

Appendix A, code, output and plots from Chap 13.R

All Material, All the material for analyses of the book