Dataset Information

CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women.

ABSTRACT:

Purpose

Black breast cancer (BC) survivors have a higher risk of developing contralateral breast cancer (CBC) than Whites. Existing CBC risk prediction tools are developed based on mostly White women. To address this racial disparity, it is crucial to develop tools tailored for Black women to help them inform about their actual risk of CBC.

Methods

We propose an absolute risk prediction model, CBCRisk-Black, specifically for Black BC patients. It uses data on Black women from two sources: Breast Cancer Surveillance Consortium (BCSC) and Surveillance, Epidemiology, and End Results (SEER). First, a matched lasso logistic regression model for estimating relative risks (RR) is developed. Then, it is combined with relevant hazard rates and attributable risks to obtain absolute risks. Six-fold cross-validation is used to internally validate CBCRisk-Black. We also compare CBCRisk-Black with CBCRisk, an existing CBC risk prediction model.

Results

The RR model uses data from BCSC on 744 Black women (186 cases). CBCRisk-Black has four risk factors (RR compared to baseline): breast density (2.13 for heterogeneous/extremely dense), family history of BC (2.28 for yes), first BC tumor size (2.14 for T3/T4, 1.56 for TIS), and age at first diagnosis of BC (1.41 for < 40). The area under the receiver operating characteristic curve (AUC) for 3- and 5-year predictions are 0.72 and 0.65 for CBCRisk-Black while those are 0.65 and 0.60 for CBCRisk.

Conclusion

CBCRisk-Black may serve as a useful tool to clinicians in counseling Black BC patients by providing a more accurate and personalized CBC risk estimate.

SUBMITTER: Sajal IH

PROVIDER: S-EPMC9637387 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women.

Sajal Ibrahim Hossain IH Chowdhury Marzana M Wang Tingfang T Euhus David D Choudhary Pankaj K PK Biswas Swati S

Breast cancer research and treatment 20220513 1

<h4>Purpose</h4>Black breast cancer (BC) survivors have a higher risk of developing contralateral breast cancer (CBC) than Whites. Existing CBC risk prediction tools are developed based on mostly White women. To address this racial disparity, it is crucial to develop tools tailored for Black women to help them inform about their actual risk of CBC.<h4>Methods</h4>We propose an absolute risk prediction model, CBCRisk-Black, specifically for Black BC patients. It uses data on Black women from two ...[more]

PMID: 35562619

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Project description:BackgroundBreast cancer survivors are at risk for contralateral breast cancer (CBC), with the consequent burden of further treatment and potentially less favorable prognosis. We aimed to develop and validate a CBC risk prediction model and evaluate its applicability for clinical decision-making.MethodsWe included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4682 CBC events and a median follow-up of 8.8?years. We developed a multivariable Fine and Gray prediction model (PredictCBC-1A) including patient, primary tumor, and treatment characteristics and BRCA1/2 germline mutation status, accounting for the competing risks of death and distant metastasis. We also developed a model without BRCA1/2 mutation status (PredictCBC-1B) since this information was available for only 6% of patients and is routinely unavailable in the general breast cancer population. Prediction performance was evaluated using calibration and discrimination, calculated by a time-dependent area under the curve (AUC) at 5 and 10?years after diagnosis of primary breast cancer, and an internal-external cross-validation procedure. Decision curve analysis was performed to evaluate the net benefit of the model to quantify clinical utility.ResultsIn the multivariable model, BRCA1/2 germline mutation status, family history, and systemic adjuvant treatment showed the strongest associations with CBC risk. The AUC of PredictCBC-1A was 0.63 (95% prediction interval (PI) at 5?years, 0.52-0.74; at 10?years, 0.53-0.72). Calibration-in-the-large was?-0.13 (95% PI:?-1.62-1.37), and the calibration slope was 0.90 (95% PI: 0.73-1.08). The AUC of Predict-1B at 10?years was 0.59 (95% PI: 0.52-0.66); calibration was slightly lower. Decision curve analysis for preventive contralateral mastectomy showed potential clinical utility of PredictCBC-1A between thresholds of 4-10% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.ConclusionsWe developed a reasonably calibrated model to predict the risk of CBC in women of European-descent; however, prediction accuracy was moderate. Our model shows potential for improved risk counseling, but decision-making regarding contralateral preventive mastectomy, especially in the general breast cancer population where limited information of the mutation status in BRCA1/2 is available, remains challenging.

Project description:BackgroundEstimates of contralateral breast cancer (CBC) risk in the modern treatment era by year of diagnosis and characteristics of the first breast cancer are needed to assess the impact of recent advances in breast cancer treatment and inform clinical decision making.MethodsWe examined CBC risk among 419,818 women (age 30-84 years) who were diagnosed with a first unilateral invasive breast cancer and survived ≥ 1 year in the US Surveillance, Epidemiology, and End Results program cancer registries from 1992 to 2015 (follow-up through 2016). CBC was defined as a second invasive breast cancer in the contralateral breast ≥ 12 months after the first breast cancer. We estimated standardized incidence ratios (SIRs) of CBC by year of diagnosis, age at diagnosis, and tumor characteristics for the first breast cancer. Cumulative incidence of CBC was calculated for women diagnosed with a first breast cancer in the recent treatment era (2004-2015, follow-up through 2016).ResultsOver a median follow-up of 8 years (range 1-25 years), 12,986 breast cancer patients developed CBC. Overall, breast cancer patients had approximately twice the risk of developing cancer in the contralateral breast when compared to that expected in the general population (SIR = 2.21, 95% CI = 2.17-2.25). SIRs for CBC declined by year of first diagnosis, irrespective of age at diagnosis and estrogen receptor (ER) status (p-trends < 0.001), but the strongest decline was after an ER-positive tumor. The 5-year cumulative incidence of CBC ranged from 1.01% (95% CI = 0.90-1.14%) in younger women (age < 50 years) with a first ER-positive tumor to 1.89% (95% CI = 1.61-2.21%) in younger women with a first ER-negative tumor.ConclusionDeclines in CBC risk are consistent with continued advances in breast cancer treatment. The updated estimates of cumulative incidence inform breast cancer patients and clinicians on the risk of CBC and may help guide treatment decisions.

Dataset Information

CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women.

Purpose

Methods

Results

Conclusion

Publications

CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women.

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