Literature DB >> 21412443

Bayesian Hierarchical Multiresolution Hazard Model for the Study of Time-Dependent Failure Patterns in Early Stage Breast Cancer.

Vanja Dukić1, James Dignam.   

Abstract

The multiresolution estimator, developed originally in engineering applications as a wavelet-based method for density estimation, has been recently extended and adapted for estimation of hazard functions (Bouman et al. 2005, 2007). Using the multiresolution hazard (MRH) estimator in the Bayesian framework, we are able to incorporate any a priori desired shape and amount of smoothness in the hazard function. The MRH method's main appeal is in its relatively simple estimation and inference procedures, making it possible to obtain simultaneous confidence bands on the hazard function over the entire time span of interest. Moreover, these confidence bands properly reflect the multiple sources of uncertainty, such as multiple centers or heterogeneity in the patient population. Also, rather than the commonly employed approach of estimating covariate effects and the hazard function separately, the Bayesian MRH method estimates all of these parameters jointly, thus resulting in properly adjusted inference about any of the quantities.In this paper, we extend the previously proposed MRH methods (Bouman et al. 2005, 2007) into the hierarchical multiresolution hazard setting (HMRH), to accommodate the case of separate hazard rate functions within each of several strata as well as some common covariate effects across all strata while accounting for within-stratum correlation. We apply this method to examine patterns of tumor recurrence after treatment for early stage breast cancer, using data from two large-scale randomized clinical trials that have substantially influenced breast cancer treatment standards. We implement the proposed model to estimate the recurrence hazard and explore how the shape differs between patients grouped by a key tumor characteristic (estrogen receptor status) and treatment types, after adjusting for other important patient characteristics such as age, tumor size and progesterone level. We also comment on whether the hazards exhibit nonmonotonic patterns consistent with recent hypotheses suggesting multiple hazard change-points at specific time landmarks.

Entities:  

Year:  2007        PMID: 21412443      PMCID: PMC3056202          DOI: 10.1214/07-BA223

Source DB:  PubMed          Journal:  Bayesian Anal        ISSN: 1931-6690            Impact factor:   3.728


  20 in total

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2.  A Multiresolution Hazard Model for Multicenter Survival Studies: Application to Tamoxifen Treatment in Early Stage Breast Cancer.

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3.  The analysis of failure times in the presence of competing risks.

Authors:  R L Prentice; J D Kalbfleisch; A V Peterson; N Flournoy; V T Farewell; N E Breslow
Journal:  Biometrics       Date:  1978-12       Impact factor: 2.571

4.  Kinetics of mammary tumor cell growth and implications for therapy.

Authors:  H E Skipper
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5.  Factors influencing short and long term survival of breast cancer patients.

Authors:  J W Berg; G F Robbins
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7.  Time distribution of the recurrence risk for breast cancer patients undergoing mastectomy: further support about the concept of tumor dormancy.

Authors:  R Demicheli; A Abbattista; R Miceli; P Valagussa; G Bonadonna
Journal:  Breast Cancer Res Treat       Date:  1996       Impact factor: 4.872

8.  Sequential methotrexate and fluorouracil for the treatment of node-negative breast cancer patients with estrogen receptor-negative tumors: eight-year results from National Surgical Adjuvant Breast and Bowel Project (NSABP) B-13 and first report of findings from NSABP B-19 comparing methotrexate and fluorouracil with conventional cyclophosphamide, methotrexate, and fluorouracil.

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Journal:  J Clin Oncol       Date:  1996-07       Impact factor: 44.544

9.  A randomized clinical trial evaluating sequential methotrexate and fluorouracil in the treatment of patients with node-negative breast cancer who have estrogen-receptor-negative tumors.

Authors:  B Fisher; C Redmond; N V Dimitrov; D Bowman; S Legault-Poisson; D L Wickerham; N Wolmark; E R Fisher; R Margolese; C Sutherland
Journal:  N Engl J Med       Date:  1989-02-23       Impact factor: 91.245

10.  Does surgery modify growth kinetics of breast cancer micrometastases?

Authors:  R Demicheli; P Valagussa; G Bonadonna
Journal:  Br J Cancer       Date:  2001-08-17       Impact factor: 7.640

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4.  Incidence of Late Relapses in Patients With HER2-Positive Breast Cancer Receiving Adjuvant Trastuzumab: Combined Analysis of NCCTG N9831 (Alliance) and NRG Oncology/NSABP B-31.

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Journal:  J Clin Oncol       Date:  2019-10-17       Impact factor: 44.544

5.  Multimodal hazard rate for relapse in breast cancer: quality of data and calibration of computer simulation.

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