Skip to main content
Log in

Comparing the Survival of Two Groups with an Intermediate Clinical Event

  • Published:
Lifetime Data Analysis Aims and scope Submit manuscript

Abstract

Consider a subject entered on a clinicaltrial in which the major endpoint is a time metric such as deathor time to reach a well defined event. During the observationalperiod the subject may experience an intermediate clinical event.The intermediate clinical event may induce a change in the survivaldistribution. We consider models for the one and two sample problem.The model for the one sample problem enables one to test if theoccurrence of the intermediate event changed the survival distribution.This models provides a way of carrying out non-randomized clinicaltrial to determine if a therapy has benefit. The two sample problemconsiders testing if the probability distributions, with andwithout an intermediate event, are the same. Statistical testsare derived using a semi-Markov or a time dependent mixture model.Simulation studies are carried out to compare these new procedureswith the log rank, stratified log rank and landmark tests. Thenew tests appear to have uniformly greater power than these competitortests. The methods are applied to a randomized clinical trialcarried out by the Aids Clinical Trial Group (ACTG) which comparedlow versus high doses of zidovudine (AZT).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • A. Agresti, Categorical Data Analysis, Wiley: New York, 1990, Chap. 12.

    Google Scholar 

  • J.R. Anderson, K.C. Cain, and R.D. Gelber, Analysis of survival by tumor response, J. Clin. Oncol. vol. 1 pp. 710–719, 1983.

    Google Scholar 

  • P.K. Andersen, “Time dependent covariates and Markov processes,” Modern Statistical Methods in Chronic Disease Epidemiology, (S. Moolgavhar and R.L. Prentice, eds), Wiley: New York, 1986, pp. 82–103.

    Google Scholar 

  • Andersen P. K., O. Borgan, R. D. Gill and N. Keiding, Statistical Methods Based on Counting Processes, Springer: New York, 1993.

    Google Scholar 

  • D.M. Finkelstein and D.A. Schoenfeld, “Analyzing survival in the presence of an auxiliary variable,” Stat. Med., vol. 13 pp. 1747–1754, 1994.

    Google Scholar 

  • M.A. Fischl, C.B. Parker, C. Pettinelli, M. Wulfsohn, et al., “A Randomized controlled trial of a reduced daily dose of Zidovudine in patients with the Acquired Immunodeficiency Syndrome,” N. Engl. J. Med., vol. 323 pp. 1009–1014, 1990.

    Google Scholar 

  • T.R. Fleming, R.L. Prentice, M.S. Pepe, and D. Glidden, “Surrogate and auxiliary endpoints in clinical trials, with potential applications in cancer and AIDS research,” Stat. Med., vol. 13 pp. 955–968, 1994.

    Google Scholar 

  • R.J. Gray, “A kernel method for incorporating information on disease progression in the analysis of survival,” Biometrika, vol. 81 pp. 527–539, 1994.

    Google Scholar 

  • S.W. Lagakos, “A stochastic model for censored-survival data in the presence of an auxiliary variable,” Biometrics, vol. 32 pp. 551–559, 1976.

    Google Scholar 

  • M. Lefkopoulou and M. Zelen, “Intermediate clinical events, surrogate markers and survival,” Lifetime Data Analysis, vol. 1 pp. 73–85, 1995.

    Google Scholar 

  • H.M. Malani, “A modification of the redistribution to the right algorithm using disease markers,” Biometrika, vol. 82 pp. 515–526, 1995.

    Google Scholar 

  • N. Mantel, D.P. Byar, “Evaluation of response-time data involving transient states: An illustration using hearttransplant data,” J. Am. Stat. Assoc., vol. 69 pp. 81–86, 1974.

    Google Scholar 

  • S. Murray and A.A. Tsiatis, “Nonparametric survival estimation using prognostic longitudinal covariates,” Biometrics, vol. 52 pp. 137–151, 1996.

    Google Scholar 

  • J.M. Robins and S. Greenland, “Adjusting for differential rates of prophylaxis therapy for PCP in high-versus low-dose AZT treatment arms in an AIDS randomized trial,” J. Am. Stat. Assoc., vol. 89 pp. 737–749, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nam, C.M., Zelen, M. Comparing the Survival of Two Groups with an Intermediate Clinical Event. Lifetime Data Anal 7, 5–19 (2001). https://doi.org/10.1023/A:1009609925212

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1009609925212

Navigation