Literature DB >> 2616934

The analysis of relapse clinical trials, with application to a comparison of two ulcer treatments.

J Whitehead1.   

Abstract

Patients cured of ulcers, carcinomas or other recurrent conditions are randomized between two treatments designed to maintain their recovery. Spontaneous reporting of relapse is supplemented by periodic asymptomatic screening. Interest centres on the difference in times to relapse between the two treatments. However, the analysis is complicated by the times to diagnoses at screens being qualitatively different from the times to symptomatic diagnoses between screens. In this paper a number of approaches to the analysis of such data are explored, and one of them is recommended. An extensive example with data on ulcer recurrence is presented to illustrate the method.

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Year:  1989        PMID: 2616934     DOI: 10.1002/sim.4780081204

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  5 in total

1.  Generalized additive models for current status data.

Authors:  S C Shiboski
Journal:  Lifetime Data Anal       Date:  1998       Impact factor: 1.588

2.  A parametric estimation procedure for relapse time distributions.

Authors:  L Ahlström; M Olsson; O Nerman
Journal:  Lifetime Data Anal       Date:  1999-06       Impact factor: 1.588

3.  Efficient Computation of Reduced Regression Models.

Authors:  Stuart R Lipsitz; Garrett M Fitzmaurice; Debajyoti Sinha; Nathanael Hevelone; Edward Giovannucci; Quoc-Dien Trinh; Jim C Hu
Journal:  Am Stat       Date:  2017-02-28       Impact factor: 8.710

4.  Vandetanib in patients with locally advanced or metastatic medullary thyroid cancer: a randomized, double-blind phase III trial.

Authors:  Samuel A Wells; Bruce G Robinson; Robert F Gagel; Henning Dralle; James A Fagin; Massimo Santoro; Eric Baudin; Rossella Elisei; Barbara Jarzab; James R Vasselli; Jessica Read; Peter Langmuir; Anderson J Ryan; Martin J Schlumberger
Journal:  J Clin Oncol       Date:  2011-10-24       Impact factor: 44.544

5.  Self-reporting and screening: Data with right-censored, left-censored, and complete observations.

Authors:  Jonathan Yefenof; Yair Goldberg; Jennifer Wiler; Avishai Mandelbaum; Ya'acov Ritov
Journal:  Stat Med       Date:  2022-05-24       Impact factor: 2.497

  5 in total

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