A STOCHASTIC MODEL FOR THE INTERPRETATION OF CLINICAL TRIALS

Abstract

Some diseases can be characterized by the patient being in one of a finite number of states; e.g. relapse, remissive, toxic, etc. These states may be both transient and absorbing. Other authors have proposed similar models to describe data dealing with time dependent phenomena which have assumed that the distribution spent within any state is exponential. These models are all Markovian. In this paper we develop non Markovian models which allow arbitrary distri butions within a state. The model is applied to clinical trials of patients with acute leuke mia who are undergoing experimental therapy. The agreement of the model and the data is very good.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1963
Accession Number
AD0403760

Entities

People

  • George H. Weiss
  • Marvin Zelen

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Clinical Trials
  • Contracts
  • Data Analysis
  • Discrete Distribution
  • Diseases And Disorders
  • Drug Therapy
  • Leukemia
  • Markov Models
  • Markov Processes
  • Mathematics
  • Models
  • Probability
  • Probability Density Functions
  • Time Intervals
  • United States

Readers

  • Computational Modeling and Simulation
  • Mathematical Modeling and Probability Theory.
  • Oncology