scholarly journals Failure Patterns of Luminal B Breast Cancer Following Postoperative Adjuvant Radiation Therapy

2017 ◽  
Vol 99 (2) ◽  
pp. E9-E10
Author(s):  
N. Choi ◽  
S.W. Lee ◽  
Y. Lim ◽  
K.Y. Eom ◽  
E.Y. Kang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Adjuvant Radiation ◽  
Adjuvant Radiation Therapy ◽  
Luminal B ◽  
Failure Patterns

scholarly journals PO-0654: Failure Patterns of Luminal B Breast Cancer Following Postoperative Adjuvant Radiation Therapy

2017 ◽  
Vol 123 ◽  
pp. S341-S342
Author(s):  
N. Choi ◽  
S.W. Lee ◽  
Y. Lim ◽  
K.Y. Eom ◽  
E.Y. Kang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Adjuvant Radiation ◽  
Adjuvant Radiation Therapy ◽  
Luminal B ◽  
Failure Patterns

Fatigue in patients with adjuvant radiation therapy for breast cancer: long-term follow-up

2004 ◽  
Vol 130 (6) ◽  
pp. 327-333 ◽  
Author(s):  
Hans Geinitz ◽  
Frank B. Zimmermann ◽  
Reinhard Thamm ◽  
Monika Keller ◽  
Raymonde Busch ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Adjuvant Radiation ◽  
Adjuvant Radiation Therapy ◽  
Long Term Follow Up

Adjuvant radiation therapy in young breast cancer patients: current state of the art and evidence-based algorithm

The Breast ◽  
2018 ◽  
Vol 41 ◽  
pp. S15
Author(s):  
Icro Meattini ◽  
Matteo Lambertini ◽  
Isacco Desideri ◽  
Alex De Caluwé ◽  
Orit Kaidar-Person ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Cancer Patients ◽  
State Of The Art ◽  
Adjuvant Radiation ◽  
Evidence Based ◽  
Breast Cancer Patients ◽  
Adjuvant Radiation Therapy ◽  
Current State ◽  
Young Breast Cancer

scholarly journals Narrowing Racial Gaps in Breast Cancer: Factors Affecting Probability of Adjuvant Radiation Therapy

2020 ◽  
Vol 5 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Felicia Snead ◽  
Alexander N. Slade ◽  
Bridget A. Oppong ◽  
Arnethea L. Sutton ◽  
Vanessa B. Sheppard
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Adjuvant Radiation ◽  
Factors Affecting ◽  
Adjuvant Radiation Therapy ◽  
Racial Gaps

scholarly journals Investigating confounders of the association between survival and adjuvant radiation therapy after breast conserving surgery in a sample of elderly breast Cancer patients in Appalachia

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Fabian Camacho ◽  
Roger Anderson ◽  
Gretchen Kimmick
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Structural Model ◽  
Failure Time ◽  
Breast Conserving Surgery ◽  
Adjuvant Radiation ◽  
Percentage Increase ◽  
Adjuvant Radiation Therapy ◽  
Percent Change ◽  
Dual Status

Abstract Background To explain the association between adjuvant radiation therapy after breast conserving surgery (BCS RT) and overall survival (OS) by quantifying bias due to confounding in a sample of elderly breast cancer beneficiaries in a multi-state region of Appalachia. Methods We used Medicare claims linked registry data for fee-for-service beneficiaries with AJCC stage I-III, treated with BCS, and diagnosed from 2006 to 2008 in Appalachian counties of Kentucky, Ohio, North Carolina, and Pennsylvania. Confounders of BCS RT included age, rurality, regional SES, access to radiation facilities, marital status, Charlson comorbidity, Medicaid dual status, institutionalization, tumor characteristics, and surgical facility characteristics. Adjusted percent change in expected survival by BCS RT was examined using Accelerated Failure Time (AFT) models. Confounding bias was assessed by comparing effects between adjusted and partially adjusted associations using a fully specified structural model. Results The final sample had 2675 beneficiaries with mean age of 75, with 81% 5-year survival from diagnosis. Unadjusted percentage increase in expected survival was 2.75 times greater in the RT group vs. non-RT group, with 5-year survival of 85% vs 60%; fully adjusted percentage increase was 1.70 times greater, with 5-year rates of 83% vs 71%. Quantification of incremental confounding showed age accounted for 71% of the effect reduction, followed by tumor features (12%), comorbidity (10%), dual status(10%), and institutionalization (8%). Adjusting for age and tumor features only resulted in only 4% bias from fully adjusted percent change (70% change vs 66%). Conclusion Quantification of confounding aids in determining covariates to adjust for and in interpreting raw associations. Substantial confounding was present (60% of total association), with age accounting for the largest share (71%); adjusting for age plus tumor features corrected for most of the confounding (4% bias). The direct effect of BCS RT on OS accounted for 40% of the total association.

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