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Activity Number:
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168
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #304196 |
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Title:
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A Stayer-Mover Mixture Markov Model for Disease Transitions in Early-Staged Breast Cancer Treated with Breast-Conserving Therapy (BCT)
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Author(s):
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Wei-Ting Hwang*+ and Neha Vapiwala and Lawrence J. Solin
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Companies:
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University of Pennsylvania and University of Pennsylvania and Albert Einstein Medical Center
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Address:
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Blockley Hall, Room 628, Philadelphia, PA, 19104,
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Keywords:
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breast cancer ; markov model ; population heterogeneity ; transition intensity
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Abstract:
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Despite early detection and active treatment, early-staged breast cancer patients still experience recurrences or deaths after the initial BCT treatment. Common single endpoint analysis does not fully describe the passage of disease progression and also ignores the possibility that a population is a mixture of pts with and without the potential for recurrence and/or spread into other distant locations. We propose a stayer-mover mixture of two independent multi-state Markov processes to model such population heterogeneity. Application to a prospective cohort of 1291 women (median follow-up: 8.5 yrs) showed 24% of pts do not progress. The transition intensity from post BCT to local recurrence (LR) is 0.55/yr (se: 0.12). Five-year transition probability from LR to distant metastasis is 38%, much higher than the probability of 11%% among those without LR.
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