Plotting summary predictions in multistate survival models: probabilities of relapse and death in remission for bone marrow transplantation patients

Stat Med. 1993 Dec 30;12(24):2315-32. doi: 10.1002/sim.4780122408.

Abstract

Multistate survival analysis usually involves a series of detailed regressional analyses describing transitions between various states. There is an often neglected need for the many estimates resulting from such an analysis to be re-synthesized into summary statements, such as prediction of various outcomes from specified patient histories. Arjas and Erola recently proposed a framework for dynamic probabilistic causality which has calculation of such prediction statements as a central tool. We illustrate these procedures on data from a multicentre bone marrow transplantation study, with death while in remission and relapse as terminal events and recovery of the patients's platelets to a normal level and the onset of acute graft-versus-host disease as intermediate events, using Cox regression models throughout. Among the features illustrated by the resulting plots is a strong effect on death while in remission if the platelets do not recover within the first three months.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Bone Marrow Transplantation / mortality*
  • Clinical Trials as Topic / statistics & numerical data*
  • Follow-Up Studies
  • Graft vs Host Disease / mortality*
  • Humans
  • Leukemia / mortality*
  • Leukemia / surgery
  • Leukemia, Myeloid, Acute / mortality
  • Leukemia, Myeloid, Acute / surgery
  • Multicenter Studies as Topic / statistics & numerical data*
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma / mortality
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma / surgery
  • Probability
  • Regression Analysis
  • Remission Induction
  • Risk Factors
  • Survival Analysis*