Validating a model for predicting breast cancer and nonbreast cancer death in women aged 55 years and older.

BACKGROUND: To support mammography screening decision making, we developed a competing-risk model to estimate 5-year breast cancer risk and 10-year nonbreast cancer death for women aged 55 years and older using Nurses' Health Study data and examined model performance in the Black Women's Health Study (BWHS). Here, we examine model performance in predicting 10-year outcomes in the BWHS, Women's Health Initiative-Extension Study (WHI-ES), and Multiethnic Cohort (MEC) and compare model performance to existing breast cancer prediction models. METHODS: We used competing-risk regression and Royston and Altman methods for validating survival models to calculate our model's calibration and discrimination (C index) in BWHS (n = 17 380), WHI-ES (n = 106 894), and MEC (n = 49 668). The Nurses' Health Study development cohort (n = 48 102) regression coefficients were applied to the validation cohorts. We compared our model's performance with breast cancer risk assessment tool (Gail) and International Breast Cancer Intervention Study (IBIS) models by computing breast cancer risk estimates and C statistics. RESULTS: When predicting 10-year breast cancer risk, our model's C index was 0.569 in BWHS, 0.572 in WHI-ES, and 0.576 in MEC. The Gail model's C statistic was 0.554 in BWHS, 0.564 in WHI-ES, and 0.551 in MEC; IBIS's C statistic was 0.547 in BWHS, 0.552 in WHI-ES, and 0.562 in MEC. The Gail model underpredicted breast cancer risk in WHI-ES; IBIS underpredicted breast cancer risk in WHI-ES and in MEC but overpredicted breast cancer risk in BWHS. Our model calibrated well. Our model's C index for predicting 10-year nonbreast cancer death was 0.760 in WHI-ES and 0.763 in MEC. CONCLUSIONS: Our competing-risk model performs as well as existing breast cancer prediction models in diverse cohorts and predicts nonbreast cancer death. We are developing a website to disseminate our model.

A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old.

BACKGROUND: Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women's breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women's individualized BC risk and life expectancy. METHODS: Using competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses' Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women's Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk. RESULTS: Mean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784-0.796) in NHS and 0.768 (0.757-0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538-0.641) in NHS and 0.573 (0.536-0.611) in BWHS. CONCLUSIONS: We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening.

Association of Cognitive Function and Retinal Neural and Vascular Structure in Type 1 Diabetes.

CONTEXT: Cognitive dysfunction is a growing and understudied public health issue in the aging type 1 diabetic population and is difficult and time-consuming to diagnose. Studies in long duration type 1 diabetes have reported the presence of proliferative diabetic retinopathy was associated with cognitive dysfunction. OBJECTIVE: This study assessed whether structural and vascular abnormalities of the retina, representing an extension of the central nervous system, are associated with cognitive impairment and other complications of type 1 diabetes. METHODS: An observational cross-sectional study of individuals with 50 or more years of type 1 diabetes (Joslin Medalist Study) was conducted at a university hospital in the United States. The study included 129 participants with complete cognitive testing. Validated cognitive testing measures included psychomotor speed, and immediate, and delayed memory. Optical coherence tomography (OCT) and OCT angiography (OCTA) were performed to obtain neural retinal layer thicknesses and vascular density for superficial (SCP) and deep retinal capillary plexus (DCP). Multivariable modeling was adjusted for potential confounders associated with outcomes in unadjusted analyses. RESULTS: Decreased vessel density of the SCP and DCP was associated with worse delayed memory (DCP: P = .002) and dominant hand psychomotor speed (SCP: P = .01). Thinning of the retinal outer nuclear layer was associated with worse psychomotor speed both in nondominant and dominant hands (P = .01 and P = .05, respectively). Outer plexiform layer thickness was associated with delayed memory (P = .04). CONCLUSION: These findings suggest that noninvasive retinal imaging using OCT and OCTA may assist in estimating the risks for cognitive dysfunction in people with type 1 diabetes.

Residual ß cell function and monogenic variants in long-duration type 1 diabetes patients.

BACKGROUNDIn the Joslin Medalist Study (Medalists), we determined whether significant associations exist between ß cell function and pathology and clinical characteristics.METHODSIndividuals with type 1 diabetes (T1D) for 50 or more years underwent evaluation including HLA analysis, basal and longitudinal autoantibody (AAb) status, and ß cell function by a mixed-meal tolerance test (MMTT) and a hyperglycemia/arginine clamp procedure. Postmortem analysis of pancreases from 68 Medalists was performed. Monogenic diabetes genes were screened for the entire cohort.RESULTSOf the 1019 Medalists, 32.4% retained detectable C-peptide levels (>0.05 ng/mL, median: 0.21 ng/mL). In those who underwent a MMTT (n = 516), 5.8% responded with a doubling of baseline C-peptide levels. Longitudinally (n = 181, median: 4 years), C-peptide levels increased in 12.2% (n = 22) and decreased in 37% (n = 67) of the Medalists. Among those with repeated MMTTs, 5.4% (3 of 56) and 16.1% (9 of 56) had waxing and waning responses, respectively. Thirty Medalists with baseline C-peptide levels of 0.1 ng/mL or higher underwent the clamp procedure, with HLA-/AAb- and HLA+/AAb- Medalists being most responsive. Postmortem examination of pancreases from 68 Medalists showed that all had scattered insulin-positive cells; 59 additionally had few insulin-positive cells within a few islets; and 14 additionally had lobes with multiple islets with numerous insulin-positive cells. Genetic analysis revealed that 280 Medalists (27.5%) had monogenic diabetes variants; in 80 (7.9%) of these Medalists, the variants were classified as "likely pathogenic" (rare exome variant ensemble learner [REVEL] >0.75).CONCLUSIONAll Medalists retained insulin-positive ß cells, with many responding to metabolic stimuli even after 50 years of T1D. The Medalists were heterogeneous with respect to ß cell function, and many with HLA+ diabetes risk alleles also had monogenic diabetes variants, indicating the importance of genetic testing for clinically diagnosed T1D.FUNDINGFunding for this work was provided by the Dianne Nunnally Hoppes Fund; the Beatson Pledge Fund; the NIH, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK); and the American Diabetes Association (ADA).