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Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk.

ABSTRACT: Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death.We included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ?57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors) and 7 risk factors for non-breast cancer death (comorbidities, functional dependency) and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women's Health Initiative Extension Study (WHI-ES; all were ?55 years and followed for 5 years).Within 5 years, 1.8 % of NHS participants were diagnosed with breast cancer (vs. 2.0 % in WHI-ES, p = 0.02), and 6.6 % experienced non-breast cancer death (vs. 5.2 % in WHI-ES, p < 0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model's c-statistic was 0.61 (95 % CI [0.60-0.63]) in NHS and 0.57 (0.55-0.58) in WHI-ES. On average, our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88-0.97]).We developed a novel prediction model that factors in postmenopausal women's individualized competing risks of non-breast cancer death when estimating breast cancer risk.

SUBMITTER: Schonberg MA

PROVIDER: S-EPMC5093031 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk.

Schonberg Mara A MA Li Vicky W VW Eliassen A Heather AH Davis Roger B RB LaCroix Andrea Z AZ McCarthy Ellen P EP Rosner Bernard A BA Chlebowski Rowan T RT Hankinson Susan E SE Marcantonio Edward R ER Ngo Long H LH

Breast cancer research and treatment 20161021 3

<h4>Purpose</h4>Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death.<h4>Methods</h4>We included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behavior ...[more]

PMID: 27770283

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Project description:AimTo show a new paradigm of simultaneously testing whether breast cancer therapies impact other causes of death.MethodsMA.14 allocated 667 postmenopausal women to 5 years of tamoxifen 20 mg/daily ± 2 years of octreotide 90 mg, given by depot intramuscular injections monthly. Event-free survival was the primary endpoint of MA.14; at median 7.9 years, the tamoxifen+octreotide and tamoxifen arms had similar event-free survival (P = 0.62). Overall survival was a secondary endpoint, and the two trial arms also had similar overall survival (P = 0.86). We used the median 9.8 years follow-up to examine by intention-to-treat, the multivariate time-to-breast cancer-specific (BrCa) and other cause (OC) mortality with log-normal survival analysis adjusted by treatment and stratification factors. We tested whether baseline factors including Insulin-like growth factor 1 (IGF1), IGF binding protein-3, C-peptide, body mass index, and 25-hydroxy vitamin D were associated with (1) all cause mortality, and if so and (2) cause-specific mortality. We also fit step-wise forward cause-specific adjusted models.ResultsThe analyses were performed on 329 patients allocated tamoxifen and 329 allocated tamoxifen+octreotide. The median age of MA.14 patients was 60.1 years: 447 (82%) < 70 years and 120 (18%) ≥ 70 years. There were 170 deaths: 106 (62.3%) BrCa; 55 (32.4%) OC, of which 24 were other malignancies, 31 other causes of death; 9 (5.3%) patients with unknown cause of death were excluded from competing risk assessments. BrCa and OC deaths were not significantly different by treatment arm (P = 0.40): tamoxifen patients experienced 50 BrCa and 32 OC deaths, while tamoxifen + octreotide patients experienced 56 BrCa and 23 OC deaths. Proportionately more deaths (P = 0.004) were from BrCa for patients < 70 years, where 70% of deaths were due to BrCa, compared to 54% for those ≥ 70 years of age. The proportion of deaths from OC increased with increasing body mass index (BMI) (P = 0.02). Higher pathologic T and N were associated with more BrCa deaths (P < 0.0001 and 0.002, respectively). The cumulative hazard plot for BrCa and OC mortality indicated the concurrent accrual of both types of death throughout follow-up, that is the existence of competing risks of mortality. MA.14 therapy did not impact mortality (P = 0.77). Three baseline patient and tumor characteristics were differentially associated with cause of death: older patients experienced more OC (P = 0.01) mortality; patients with T1 tumors and hormone receptor positive tumors had less BrCa mortality (respectively, P = 0.01, P = 0.06). Additionally, step-wise cause-specific models indicated that patients with node negative disease experienced less BrCa mortality (P = 0.002); there was weak evidence that, lower C-peptide (P = 0.08) was associated with less BrCa mortality, while higher BMI (P = 0.01) was associated with worse OC mortality.ConclusionWe demonstrate here a new paradigm of simultaneous testing of therapeutics directed at multiple diseases for which postmenopausal women are concurrently at risk. Octreotide LAR did not significantly impact breast cancer or other cause mortality, although different baseline factors influenced type of death.

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Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk.

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Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk.

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