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A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer
Author(s) -
Sittenfeld Sarah M. C.,
Zabor Emily C.,
Hamilton Sarah N.,
Kuerer Henry M.,
ElTamer Mahmoud,
Naoum George E.,
Truong Pauline T.,
Nichol Alan,
Smith Benjamin D.,
Woodward Wendy A.,
Moo TracyAnn,
Powell Simon N.,
Shah Chirag S.,
Taghian Alphonse G.,
AbuGheida Ibrahim,
Tendulkar Rahul D.
Publication year - 2022
Publication title -
cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.052
H-Index - 304
eISSN - 1097-0142
pISSN - 0008-543X
DOI - 10.1002/cncr.34352
Subject(s) - medicine , breast cancer , interquartile range , hazard ratio , mastectomy , oncology , proportional hazards model , cohort , lymphovascular invasion , cancer , confidence interval , gynecology , surgery , metastasis
Background Post‐mastectomy radiation therapy (PMRT) in women with pathologic stage T1‐2N1M0 breast cancer is controversial. Methods Data from five North American institutions including women undergoing mastectomy without neoadjuvant therapy with pT1‐2N1M0 breast cancer treated from 2006 to 2015 were pooled for analysis. Competing‐risks regression was performed to identify factors associated with locoregional recurrence (LRR), distant metastasis (DM), overall recurrence (OR), and breast cancer mortality (BCM). Results A total of 3532 patients were included for analysis with a median follow‐up time among survivors of 6.8 years (interquartile range [IQR], 4.5–9.5 years). The 2154 (61%) patients who received PMRT had significantly more adverse risk factors than those patients not receiving PMRT: younger age, larger tumors, more positive lymph nodes, lymphovascular invasion, extracapsular extension, and positive margins ( p < .05 for all). On competing risk regression analysis, receipt of PMRT was significantly associated with a decreased risk of LRR (hazard ratio [HR], 0.21; 95% confidence interval [CI], 0.14–0.31; p < .001) and OR (HR, 0.76; 95% CI, 0.62–0.94; p = .011). Model performance metrics for each end point showed good discrimination and calibration. An online prediction model to estimate predicted risks for each outcome based on individual patient and tumor characteristics was created from the model. Conclusions In a large multi‐institutional cohort of patients, PMRT for T1‐2N1 breast cancer was associated with a significant reduction in locoregional and overall recurrence after accounting for known prognostic factors. An online calculator was developed to aid in personalized decision‐making regarding PMRT in this population.