Evidence map›Paper›PMID 42335630›Full record

ArticleThe Journal of surgical research2026

CBCRisk-Mastectomy: A Prediction Tool to Aid Contralateral Prophylactic Mastectomy Decision-Making.

Ibrahim H Sajal, Ruth M Pfeiffer, Ismail Jatoi, Mitchell H Gail, Reena S Cecchini, Pankaj K Choudhary, Swati Biswas

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Article in The Journal of surgical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ibrahim H SajalDepartment of Mathematical Sciences, University of Texas at Dallas, Richardson, Texas.
Ruth M PfeifferDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Ismail JatoiDivision of Surgical Oncology and Endocrine Surgery, University of Texas Health Science Center, San Antonio, Texas.
Mitchell H GailDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Reena S CecchiniDepartment of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, Pennsylvania.
Pankaj K ChoudharyDepartment of Mathematical Sciences, University of Texas at Dallas, Richardson, Texas. Electronic address: pankaj@utdallas.edu.
Swati BiswasDepartment of Mathematical Sciences, University of Texas at Dallas, Richardson, Texas. Electronic address: swati.biswas@utdallas.edu.

Funding

A Model for Individualized Risk Prediction of Contralateral Breast CancerR21CA186086 · NCI · UNIVERSITY OF TEXAS DALLAS · PI BISWAS, SWATI, CHOUDHARY, PANKAJ · 2014 to 2015
$412k
NCI NIH HHS R21 CA186086
6 · The paper itself

Abstract

introductionUnilateral breast cancer (BC) patients scheduled for mastectomy often choose to undergo contralateral prophylactic mastectomy (CPM), despite substantial declines in contralateral breast cancer (CBC) risk in recent decades. Models predicting absolute risk of future CBC can aid informed decision-making about CPM. CBCRisk is an existing CBC absolute risk prediction model trained on unilateral BC patients regardless of whether they had mastectomy. Here, we developed CBCRisk-Mastectomy, tailored specifically to BC patients scheduled for mastectomy and considering CPM.

methodsWe used data on BC patients who underwent mastectomy to treat their first BC from two nationally representative sources: Breast Cancer Surveillance Consortium (BCSC) and Surveillance, Epidemiology, and End Results (SEER) cancer registry. We imputed missing data in the BCSC sample and used conditional logistic regression models, trained on 2660 BC patients (665 CBC cases) from BCSC, to identify predictors and estimate relative risks. These were combined with attributable risks and CBC incidence rates estimated to obtain absolute risk. Cross-validation was used to internally validate CBCRisk-Mastectomy and compare with CBCRisk.

resultsCBCRisk-Mastectomy has nine predictors: first BC type, lobular carcinoma in situ status, estrogen receptor status, tumor stage, breast density, age at BC diagnosis, family history of BC, age at first birth, and body mass index. The areas under the curve and their 95% confidence intervals for five-year predictions for CBCRisk-Mastectomy and CBCRisk were 0.62 (0.59, 0.65) and 0.58 (0.55, 0.61), respectively.

conclusionsCBCRisk-Mastectomy may aid clinicians in counseling BC patients scheduled for mastectomy, enabling improved decision-making regarding CPM.

Indexed as

Breast NeoplasmsDecision Support TechniquesProphylactic MastectomyUnilateral Breast NeoplasmsAdultAgedFemaleHumansMiddle AgedRisk AssessmentSEER ProgramBreast Cancer Surveillance ConsortiumBreast densityCBCRiskEnd Results (SEER)EpidemiologySurveillance

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.