Literature DB >> 8318401

Assessing the impact of adjuvant therapy on cure rate for stage 2 breast carcinoma.

J W Gamel1, R L Vogel, I W McLean.   

Abstract

The log-rank test is commonly used to assess therapeutic effect in prospective, randomised clinical trials. This test is sensitive to differences in survival between treatment groups at a specific endpoint, but cannot determine whether such a difference is due to an enhanced cure rate or an enhanced survival time among uncured patients. To investigate the clinical impact of such limitations, an algorithm was constructed to simulate clinical, randomised, adjuvant therapy trials in patients with a cured fraction of 0.27 and a median survival time for uncured patients of 3.4 years. Hypothetical therapies were introduced to increase rate of cure, increase median survival time, or achieve a combination of these effects. For 500 simulated patients recruited over a 5 year period and then followed for three additional years, a 50% enhancement of median survival time (to 5.1 years) led to a survival increase detectable at the P = 0.05 level in 780 of 1000 trials, whereas a 50% enhancement of cured fraction (to 40.5%) led to a detectable increase at the same level in only 449 of 1000 trials. These findings suggest that, in clinical trials of adjuvant therapy for stage 2 breast cancer, the log rank test may be more sensitive to increases in tumour-related survival time than to increases in cured fraction.

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Year:  1993        PMID: 8318401      PMCID: PMC1968304          DOI: 10.1038/bjc.1993.296

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


  6 in total

1.  Proportion cured and mean log survival time as functions of tumour size.

Authors:  J W Gamel; I W McLean; S H Rosenberg
Journal:  Stat Med       Date:  1990-08       Impact factor: 2.373

2.  Tables of the number of patients required in clinical trials using the logrank test.

Authors:  L S Freedman
Journal:  Stat Med       Date:  1982 Apr-Jun       Impact factor: 2.373

3.  Is breast cancer a curable disease? A study of 14,731 women with breast cancer from the Cancer Registry of Norway.

Authors:  L E Rutqvist; A Wallgren; B Nilsson
Journal:  Cancer       Date:  1984-04-15       Impact factor: 6.860

4.  A test of several parametic statistical models for estimating success rate in the treatment of carcinoma cervix uteri.

Authors:  R F Mould; J W Boag
Journal:  Br J Cancer       Date:  1975-11       Impact factor: 7.640

5.  Design and analysis of randomized clinical trials requiring prolonged observation of each patient. I. Introduction and design.

Authors:  R Peto; M C Pike; P Armitage; N E Breslow; D R Cox; S V Howard; N Mantel; K McPherson; J Peto; P G Smith
Journal:  Br J Cancer       Date:  1976-12       Impact factor: 7.640

6.  Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. analysis and examples.

Authors:  R Peto; M C Pike; P Armitage; N E Breslow; D R Cox; S V Howard; N Mantel; K McPherson; J Peto; P G Smith
Journal:  Br J Cancer       Date:  1977-01       Impact factor: 7.640

  6 in total
  2 in total

1.  Estimating Cure Rates From Survival Data: An Alternative to Two-Component Mixture Models.

Authors:  A D Tsodikov; J G Ibrahim; A Y Yakovlev
Journal:  J Am Stat Assoc       Date:  2003-12-01       Impact factor: 5.033

2.  A model of long-term survival following adjuvant therapy for stage 2 breast cancer.

Authors:  J W Gamel; R L Vogel
Journal:  Br J Cancer       Date:  1993-12       Impact factor: 7.640

  2 in total

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