Literature DB >> 16345025

Modelling menstrual status during and after adjuvant treatment for breast cancer.

Suzanne E Szwarc1, Marco Bonetti.   

Abstract

Failure time data may consist of the observation of an event whose cause is unknown due to the censoring or lack of a second event that could identify the cause of the first event. Standard competing-risks methodology does not apply to this setting because the cause of the event is not always identifiable. Moreover, one cannot assume that the entire population will eventually experience the event of interest, and the observation is potentially censored for all patients. The model that we describe in this article is motivated by a breast cancer clinical trial conducted by the International Breast Cancer Study Group (IBCSG). Because some breast cancer adjuvant treatments for premenopausal patients who have undergone surgery cause the interruption of menses, or amenorrhoea, it is of interest to describe the process by which menses discontinue and resume after treatment is completed. The process is complicated by the fact that natural menopause also occurs in the patient population, and that treatment-induced amenorrhoea is not distinguishable from menopause unless menses are observed to resume after treatment completion. We discuss a parametric model for the time to amenorrhoea and for the time to the recovery of menses, also accounting for the presence of censoring and for the possibility that treatment causes an anticipation of natural menopause.

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Year:  2006        PMID: 16345025     DOI: 10.1002/sim.2445

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


  3 in total

1.  An accelerated failure time mixture cure model with masked event.

Authors:  Jenny J Zhang; Molin Wang
Journal:  Biom J       Date:  2009-12       Impact factor: 2.207

2.  Randomized trial using gonadotropin-releasing hormone agonist triptorelin for the preservation of ovarian function during (neo)adjuvant chemotherapy for breast cancer.

Authors:  Pamela N Munster; Amy P Moore; Roohi Ismail-Khan; Charles E Cox; Mensura Lacevic; Margaret Gross-King; Ping Xu; W Bradford Carter; Susan E Minton
Journal:  J Clin Oncol       Date:  2012-01-09       Impact factor: 44.544

3.  Latent class joint model of ovarian function suppression and DFS for premenopausal breast cancer patients.

Authors:  Jenny J Zhang; Molin Wang
Journal:  Stat Med       Date:  2010-09-30       Impact factor: 2.373

  3 in total

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