METHODS: EPICOR Asia (NCT01361386) is a prospective study of hospital survivors post-ACS enrolled in 218 hospitals from 8 countries/regions in Asia (06/2011-05/2012). All medically managed NSTE-ACS patients were classified into 3 groups: 1) no coronary angiography (CAG-); 2) non-significant coronary artery disease (CAD) on angiogram (CAG+ CAD-); and 3) significant CAD (CAG+ CAD+). We compared baseline differences between patients medically managed and patients undergoing revascularization, and also between the medically managed groups. Adverse events were reported and compared up to 2years.
RESULTS: Of 6163 NSTE-ACS patients, 2272 (37%) were medically managed, with 1339 (59%), 254 (11%), and 679 (30%) in the CAG-, CAG+ CAD-, and CAG+ CAD+ groups, respectively. There were marked differences in the proportion of medically managed patients among the 8 countries/regions (13-81%). Medically managed patients had higher mortality at 2years compared with revascularization (8.7% vs. 3.0%, p<0.001). Among medically managed patients, CAG- patients were older, more likely to have pre-existing cardiovascular disease, and had the highest 2-year mortality (10.5% vs. 4.3% [CAG+ CAD-] and 6.6% [CAG+ CAD+], p<0.001). Mortality differences persisted after adjusting for other patient risk factors.
CONCLUSIONS: Medically managed NSTE-ACS patients are a heterogeneous group with different risk stratification and variable prognosis. Identification of reasons underlying different management strategies, and key factors adversely influencing long-term prognosis, may improve outcomes.
METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.
RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively.
CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.
METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.
CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.
IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.
RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.
CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
OBJECTIVE: To compare the cancer spectrum and frequencies between male BRCA1 and BRCA2 PV carriers.
DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study of 6902 men, including 3651 BRCA1 and 3251 BRCA2 PV carriers, older than 18 years recruited from cancer genetics clinics from 1966 to 2017 by 53 study groups in 33 countries worldwide collaborating through the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Clinical data and pathologic characteristics were collected.
MAIN OUTCOMES AND MEASURES: BRCA1/2 status was the outcome in a logistic regression, and cancer diagnoses were the independent predictors. All odds ratios (ORs) were adjusted for age, country of origin, and calendar year of the first interview.
RESULTS: Among the 6902 men in the study (median [range] age, 51.6 [18-100] years), 1634 cancers were diagnosed in 1376 men (19.9%), the majority (922 of 1,376 [67%]) being BRCA2 PV carriers. Being affected by any cancer was associated with a higher probability of being a BRCA2, rather than a BRCA1, PV carrier (OR, 3.23; 95% CI, 2.81-3.70; P
METHODS: We included women of European ancestry with a prevalent first primary invasive BC (BRCA1 = 6,591 with 1,402 prevalent CBC cases; BRCA2 = 4,208 with 647 prevalent CBC cases) from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), a large international retrospective series. Cox regression analysis was performed to assess the association between overall and ER-specific PRS313 and CBC risk.
RESULTS: For BRCA1 heterozygotes the estrogen receptor (ER)-negative PRS313 showed the largest association with CBC risk, hazard ratio (HR) per SD = 1.12, 95% confidence interval (CI) (1.06-1.18), C-index = 0.53; for BRCA2 heterozygotes, this was the ER-positive PRS313, HR = 1.15, 95% CI (1.07-1.25), C-index = 0.57. Adjusting for family history, age at diagnosis, treatment, or pathological characteristics for the first BC did not change association effect sizes. For women developing first BC
METHODS: We used data from 3,184 BRCA1 and 2,157 BRCA2 families in the Consortium of Investigators of Modifiers of BRCA1/2 to estimate age-specific relative (RR) and absolute risks for 22 first primary cancer types adjusting for family ascertainment.
RESULTS: BRCA1 PVs were associated with risks of male breast (RR = 4.30; 95% CI, 1.09 to 16.96), pancreatic (RR = 2.36; 95% CI, 1.51 to 3.68), and stomach (RR = 2.17; 95% CI, 1.25 to 3.77) cancers. Associations with colorectal and gallbladder cancers were also suggested. BRCA2 PVs were associated with risks of male breast (RR = 44.0; 95% CI, 21.3 to 90.9), stomach (RR = 3.69; 95% CI, 2.40 to 5.67), pancreatic (RR = 3.34; 95% CI, 2.21 to 5.06), and prostate (RR = 2.22; 95% CI, 1.63 to 3.03) cancers. The stomach cancer RR was higher for females than males (6.89 v 2.76; P = .04). The absolute risks to age 80 years ranged from 0.4% for male breast cancer to approximately 2.5% for pancreatic cancer for BRCA1 carriers and from approximately 2.5% for pancreatic cancer to 27% for prostate cancer for BRCA2 carriers.
CONCLUSION: In addition to female breast and ovarian cancers, BRCA1 and BRCA2 PVs are associated with increased risks of male breast, pancreatic, stomach, and prostate (only BRCA2 PVs) cancers, but not with the risks of other previously suggested cancers. The estimated age-specific risks will refine cancer risk management in men and women with BRCA1/2 PVs.