Dynamic Prediction in Clinical Survival Analysis

Title Page
......Page 6
Contents......Page 8
Preface......Page 12
About the Authors......Page 16
I. Prognostic models for survival data using (clinical) information available at baseline, based on the Cox model......Page 18
1. The special nature of survival data......Page 20
2. Cox regression model......Page 32
3. Measuring the predictive value of a Cox model......Page 52
4. Calibration and revision of Cox models......Page 74
II. Prognostic models for survival data using (clinical) information available at baseline, when the proportional hazards assumption of the Cox model is violated......Page 88
5. Mechanisms explaining violation of the Cox model......Page 90
6. Non-proportional hazards models......Page 102
7. Dealing with non-proportional hazards......Page 118
III. Dynamic prognostic models for survival data using time-dependent information......Page 136
8. Dynamic predictions using biomarkers......Page 138
9. Dynamic prediction in multi-state models......Page 152
10. Dynamic prediction in chronic disease......Page 170
IV. Dynamic prognostic models for survival data using genomic data......Page 186
11. Penalized Cox models......Page 188
12. Dynamic prediction based on genomic data......Page 202
V. Appendices......Page 210
A. Data sets......Page 212
B. Software and website......Page 228
References......Page 234