METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.
RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.
CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.
METHODS: This is a meta-analysis of seven prospective cohort studies participating in the CHANCES consortium including 18 668 men and 24 751 women with a mean age of 62 and 63 years, respectively. Harmonised individual participant data from all seven cohorts were analysed separately and alternatively for each anthropometric indicator using multivariable Cox proportional hazards models.
RESULTS: After a median follow-up period of 12 years, 1656 first-incident obesity-related cancers (defined as postmenopausal female breast, colorectum, lower oesophagus, cardia stomach, liver, gallbladder, pancreas, endometrium, ovary, and kidney) had occurred in men and women. In the meta-analysis of all studies, associations between indicators of adiposity, per s.d. increment, and risk for all obesity-related cancers combined yielded the following summary hazard ratios: 1.11 (95% CI 1.02-1.21) for BMI, 1.13 (95% CI 1.04-1.23) for WC, 1.09 (95% CI 0.98-1.21) for HC, and 1.15 (95% CI 1.00-1.32) for WHR. Increases in risk for colorectal cancer were 16%, 21%, 15%, and 20%, respectively per s.d. of BMI, WC, HC, and WHR. Effect modification by hormone therapy (HT) use was observed for postmenopausal breast cancer (Pinteraction<0.001), where never HT users showed an ∼20% increased risk per s.d. of BMI, WC, and HC compared to ever users.
CONCLUSIONS: BMI, WC, HC, and WHR show comparable positive associations with obesity-related cancers combined and with colorectal cancer in older adults. For postmenopausal breast cancer we report evidence for effect modification by HT use.
METHODS: We did a cohort analysis of TB cases in SECOND-LINE. TB cases included any clinical or laboratory-confirmed diagnoses and/or commencement of treatment for TB after randomization. Baseline factors associated with TB were analyzed using Cox regression stratified by site.
RESULTS: TB cases occurred at sites in Argentina, India, Malaysia, Nigeria, South Africa, and Thailand, in a cohort of 355 of the 541 SECOND-LINE participants. Overall, 20 cases of TB occurred, an incidence rate of 3.4 per 100 person-years (95% CI: 2.1 to 5.1). Increased TB risk was associated with a low CD4+-cell count (≤200 cells/μL), high viral load (>200 copies/mL), low platelet count (<150 ×109/L), and low total serum cholesterol (≤4.5 mmol/L) at baseline. An increased risk of death was associated with TB, adjusted for CD4, platelets, and cholesterol. A low CD4+-cell count was significantly associated with incident TB, mortality, other AIDS diagnoses, and virologic failure.
DISCUSSION: The risk of TB remains elevated in PLHIV in the setting of second-line HIV therapy in TB endemic regions. TB was associated with a greater risk of death. Finding that low CD4+ T-cell count was significantly associated with poor outcomes in this population supports the value of CD4+ monitoring in HIV clinical management.