Literature DB >> 29455447

The continuum of breast cancer care and outcomes in the U.S. Military Health System: an analysis by benefit type and care source.

Yvonne L Eaglehouse1,2, Stephanie Shao1, Wenyaw Chan3, Derek Brown1, Janna Manjelievskaia1, Craig D Shriver1,2, Kangmin Zhu4,5.   

Abstract

PURPOSE: This study investigates transition rates between breast cancer diagnosis, recurrence, and death by insurance benefit type and care source in U.S. Military Health System (MHS).
METHODS: The MHS data repository and central cancer registry linked data were used to identify women aged 40-64 with histologically confirmed breast cancer between 2003 and 2007. Three-state continuous time Markov models were used to estimate transition rates and transition rate ratios (TRRs) by TRICARE benefit type (Prime or non-Prime) and care source (direct, purchased, or both), adjusted for demographic, tumor, and treatment variables.
RESULTS: Analyses included 2668 women with transitions from diagnosis to recurrence (n = 832), recurrence to death (n = 79), and diagnosis to death without recurrence (n = 91). Compared to women with Prime within each care source, women with non-Prime using both care sources had higher transition rates (TRR 1.47, 95% CI 1.03, 2.10). Compared to those using direct care within each benefit type, women utilizing both care sources with non-Prime had higher transition rates (TRR 1.86, 95% CI 1.11, 3.13), while women with Prime utilizing purchased care had lower transition rates (TRR 0.82, 95% CI 0.68, 0.98).
CONCLUSIONS: In the MHS, women with non-Prime benefit plans compared to Prime had higher transition rates along the breast cancer continuum among both care source users. Purchased care users had lower transition rates than direct care users among Prime beneficiaries. IMPLICATIONS FOR CANCER SURVIVORS: Benefit plan and care source may be associated with breast cancer progression. Further research is needed to demonstrate differences in survivorship.

Entities:  

Keywords:  Breast cancer; Health services; Insurance; Recurrence; Survival

Mesh:

Year:  2018        PMID: 29455447     DOI: 10.1007/s11764-018-0680-1

Source DB:  PubMed          Journal:  J Cancer Surviv        ISSN: 1932-2259            Impact factor:   4.442


  24 in total

1.  Racial variation in tumor stage at diagnosis among Department of Defense beneficiaries.

Authors:  Lindsey Enewold; Jing Zhou; Katherine A McGlynn; Susan S Devesa; Craig D Shriver; John F Potter; Shelia H Zahm; Kangmin Zhu
Journal:  Cancer       Date:  2011-08-11       Impact factor: 6.860

2.  Analysis of longitudinal multinomial outcome data.

Authors:  Yen-Peng Li; Wenyaw Chan
Journal:  Biom J       Date:  2006-04       Impact factor: 2.207

3.  The impact of radiotherapy costs on clinical outcomes in breast cancer.

Authors:  Isabel J Boero; Anthony J Paravati; Daniel P Triplett; Lindsay Hwang; Rayna K Matsuno; Loren K Mell; James D Murphy
Journal:  Radiother Oncol       Date:  2015-10-20       Impact factor: 6.280

4.  Having Medicaid insurance negatively impacts outcomes in patients with head and neck malignancies.

Authors:  Arash O Naghavi; Michelle I Echevarria; G Daniel Grass; Tobin J Strom; Yazan A Abuodeh; Kamran A Ahmed; Youngchul Kim; Andy M Trotti; Louis B Harrison; Kosj Yamoah; Jimmy J Caudell
Journal:  Cancer       Date:  2016-08-01       Impact factor: 6.860

5.  Survival of older patients with cancer in the Veterans Health Administration versus fee-for-service Medicare.

Authors:  Mary Beth Landrum; Nancy L Keating; Elizabeth B Lamont; Samuel R Bozeman; Steven H Krasnow; Lawrence Shulman; Jennifer R Brown; Craig C Earle; Michael Rabin; Barbara J McNeil
Journal:  J Clin Oncol       Date:  2012-03-05       Impact factor: 44.544

6.  Racial variation in breast cancer treatment among Department of Defense beneficiaries.

Authors:  Lindsey Enewold; Jing Zhou; Katherine A McGlynn; William F Anderson; Craig D Shriver; John F Potter; Shelia H Zahm; Kangmin Zhu
Journal:  Cancer       Date:  2011-07-15       Impact factor: 6.860

7.  Estimation of sojourn time in chronic disease screening without data on interval cases.

Authors:  T H Chen; H S Kuo; M F Yen; M S Lai; L Tabar; S W Duffy
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

8.  Ten-year survival and cost following breast cancer recurrence: estimates from SEER-medicare data.

Authors:  Michael E Stokes; David Thompson; Eduardo L Montoya; Milton C Weinstein; Eric P Winer; Craig C Earle
Journal:  Value Health       Date:  2008 Mar-Apr       Impact factor: 5.725

9.  Breast reconstruction after mastectomy among Department of Defense beneficiaries by race.

Authors:  Lindsey R Enewold; Katherine A McGlynn; Shelia H Zahm; Jill Poudrier; William F Anderson; Craig D Shriver; Kangmin Zhu
Journal:  Cancer       Date:  2014-06-25       Impact factor: 6.860

10.  Widening disparity in survival between white and African-American patients with breast carcinoma treated in the U. S. Department of Defense Healthcare system.

Authors:  Ismail Jatoi; Heiko Becher; Charles R Leake
Journal:  Cancer       Date:  2003-09-01       Impact factor: 6.860

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  1 in total

Review 1.  Breast Cancer Survivorship: the Role of Rehabilitation According to the International Classification of Functioning Disability and Health-a Scoping Review.

Authors:  Monica Pinto; Dario Calafiore; Maria Carmela Piccirillo; Massimo Costa; Ozden Ozyemisci Taskiran; Alessandro de Sire
Journal:  Curr Oncol Rep       Date:  2022-04-11       Impact factor: 5.945

  1 in total

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