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C-statistics by tumor histology for variable lag-times since blood donation

Purpose: About 60% of ovarian cancers are diagnosed at late stage, when 5-year survival is less than 30% in contrast to 90% for local disease. This has prompted search for early detection biomarkers. For initial testing, specimens taken months or years before ovarian cancer diagnosis are the best source of information to evaluate early detection biomarkers. Here we evaluate the most promising ovarian cancer screening biomarkers in prospectively collected samples from the European Prospective Investigation into Cancer and Nutrition study.Experimental Design: We measured CA125, HE4, CA72.4, and CA15.3 in 810 invasive epithelial ovarian cancer cases and 1,939 controls. We calculated the sensitivity at 95% and 98% specificity as well as area under the receiver operator curve (C-statistic) for each marker individually and in combination. In addition, we evaluated marker performance by stage at diagnosis and time between blood draw and diagnosis.Results: We observed the best discrimination between cases and controls within 6 months of diagnosis for CA125 (C-statistic = 0.92), then HE4 (0.84), CA72.4 (0.77), and CA15.3 (0.73). Marker performance declined with longer time between blood draw and diagnosis and for earlier staged disease. However, assessment of discriminatory ability at early stage was limited by small numbers. Combinations of markers performed modestly, but significantly better than any single marker.Conclusions: CA125 remains the single best marker for the early detection of invasive epithelial ovarian cancer, but can be slightly improved by combining with other markers. Identifying novel markers for ovarian cancer will require studies including larger numbers of early-stage cases. Clin Cancer Res; 22(18); 4664–75. ©2016 AACR.See related commentary by Skates, p. 4542

Case characteristics (median (min-max) or n (%)) by histologic subtypes in the EPIC cohort

Evaluation of added discriminatory ability of each biomarker using Net Reclassification Improvement (NRI)

Spearman coefficients of correlation between detection markers

There is still a scientific debate on the exact role played by obesity on stroke risk. The aim of the study was to analyze the association between obesity, measured by different indices such as body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and a new one called A Body Shape Index (ABSI) and the risk of total and ischemic stroke. A total of 41,020 subjects (15,490 men and 25,530 women) aged 29–69 years participated in the study. All participants were recruited between 1992 and 1996 and followed up until 2008 to ascertain incident cerebrovascular disease events. Cox proportional hazards models were designed to estimate the relative risk and 95 % CI between obesity and cerebrovascular disease incidence. After 13.8 years of follow-up, a total of 674 stroke cases (55.3 % in men) were registered (531 ischemic, 79 hemorrhagic, 42 subarachnoid hemorrhage and 22 unspecified). WC fourth quartile (HR 1.95; 95 % CI 1.20–3.19) and WHR fourth quartile (HR 1.58; 95 % CI 1.12–2.25) were positively associated with total stroke only in men. BMI was not associated with stroke incidence. The new index, ABSI, was significantly associated with total stroke incidence only in men (HR 1.54; 95 % CI 1.06–2.23). Data from the Spanish EPIC cohort study show a strong association of WC and WHR with the relative risk of suffering a stroke only in men, while no associations were found for BMI. It supports the suggestion of other authors of using more than one obesity index in the study of stroke risk prediction.

Purpose: About 60% of ovarian cancers are diagnosed at late stage, when 5-year survival is less than 30% in contrast to 90% for local disease. This has prompted search for early detection biomarkers. For initial testing, specimens taken months or years before ovarian cancer diagnosis are the best source of information to evaluate early detection biomarkers. Here we evaluate the most promising ovarian cancer screening biomarkers in prospectively collected samples from the European Prospective Investigation into Cancer and Nutrition study. Experimental Design: We measured CA125, HE4, CA72.4, and CA15.3 in 810 invasive epithelial ovarian cancer cases and 1,939 controls. We calculated the sensitivity at 95% and 98% specificity as well as area under the receiver operator curve (C-statistic) for each marker individually and in combination. In addition, we evaluated marker performance by stage at diagnosis and time between blood draw and diagnosis. Results: We observed the best discrimination between cases and controls within 6 months of diagnosis for CA125 (C-statistic = 0.92), then HE4 (0.84), CA72.4 (0.77), and CA15.3 (0.73). Marker performance declined with longer time between blood draw and diagnosis and for earlier staged disease. However, assessment of discriminatory ability at early stage was limited by small numbers. Combinations of markers performed modestly, but significantly better than any single marker. Conclusions: CA125 remains the single best marker for the early detection of invasive epithelial ovarian cancer, but can be slightly improved by combining with other markers. Identifying novel markers for ovarian cancer will require studies including larger numbers of early-stage cases. Clin Cancer Res; 22(18); 4664–75. ©2016 AACR. See related commentary by Skates, p. 4542

ObjectiveTo prospectively assess the associations between lean fish, fatty fish and total fish intakes and risk of stroke in the Spanish cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Spain).DesignFish intake was estimated from a validated dietary questionnaire. Cox proportional hazards regression models were used to assess the association between the intakes of lean fish, fatty fish and total fish and stroke risk. Models were run separately for men and women.SettingFive Spanish regions (Asturias, San Sebastian, Navarra, Granada and Murcia).SubjectsIndividuals (n 41 020; 15 490 men and 25 530 women) aged 20–69 years, recruited from 1992 to 1996 and followed-up until December 2008 (December 2006 in the case of Asturias). Only participants with definite incident stroke were considered as cases.ResultsDuring a mean follow-up of 13·8 years, 674 strokes were identified and subsequently validated by record linkage with hospital discharge databases, primary-care records and regional mortality registries, comprising 531 ischaemic, seventy-nine haemorrhagic, forty-two subarachnoid and twenty-two unspecific strokes. After multiple adjustments, no significant associations were observed between lean fish, fatty fish and total fish consumption and the risk of stroke in men or women. In men, results revealed a non-significant trend towards an inverse association between lean fish (hazard ratio=0·84; 95 % CI 0·55, 1·29, Ptrend=0·06) and total fish consumption (hazard ratio=0·77; 95 % CI 0·51, 1·16, Ptrend=0·06) and risk of total stroke.ConclusionsIn the EPIC-Spain cohort, no association was found between lean fish, fatty fish and total fish consumption and risk of stroke.

Endometrial cancer (EC) is the fourth most frequent cancer in women in Europe, and as its incidence is increasing, prevention strategies gain further pertinence. Risk prediction models can be a useful tool for identifying women likely to benefit from targeted prevention measures. On the basis of data from 201,811 women (mostly aged 30–65 years) including 855 incident EC cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict EC was developed. A step-wise model selection process was used to select confirmed predictive epidemiologic risk factors. Piece-wise constant hazard rates in 5-year age-intervals were estimated in a cause-specific competing risks model, five-fold-cross-validation was applied for internal validation. Risk factors included in the risk prediction model were body-mass index (BMI), menopausal status, age at menarche and at menopause, oral contraceptive use, overall and by different BMI categories and overall duration of use, parity, age at first full-term pregnancy, duration of menopausal hormone therapy and smoking status (specific for pre, peri- and post-menopausal women). These variables improved the discriminating capacity to predict risk over 5 years from 71 % for a model based on age alone to 77 % (overall C statistic), and the model was well-calibrated (ratio of expected to observed cases = 0.99). Our model could be used for the identification of women at increased risk of EC in Western Europe. To achieve an EC-risk model with general validity, a large-scale cohort-consortium approach would be needed to assess and adjust for population variation.

High intakes of unprocessed red or processed meat may increase the risk of stroke. We aimed to examine the association between unprocessed red meat, processed meat and total red meat consumption and risk of total stroke and ischaemic stroke. Cox proportional hazards regression analyses were conducted based on the data for 41,020 men and women aged 29-69 years at baseline. During a mean follow-up of 13.8 years, 674 incident cases of stroke (531 ischaemic strokes, 79 haemorrhagic strokes, 42 subarachnoid haemorrhages and 22 mixed or unspecified events) were identified. After multiple adjustment, unprocessed red meat, processed meat and total red meat consumption were not correlated with incidence of total stroke or ischaemic stroke in either men or women. The hazard ratios (HRs) for unprocessed red meat and processed meat and risk of total stroke comparing the highest with the lowest quintiles were, respectively, 0.81 (95% confidence interval (CI) 0.54-1.21; P-trend=0.15) and 0.92 (95% CI 0.64-1.32; P-trend=0.82) in men and 1.21 (95% CI 0.79-1.85; P-trend=0.10) and 0.81 (95% CI 0.51-1.27; P-trend=0.17) in women. The HRs for unprocessed red meat and processed meat and risk of ischaemic stroke were, respectively, 0.80 (95% CI 0.51-1.25; P-trend=0.51) and 0.86 (95% CI 0.57-1.29; P-trend=0.77) in men and 1.24 (95% CI 0.74-2.05; P-trend=0.13) and 0.82 (95% CI 0.47-1.42; P-trend=0.31) in women. In the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, unprocessed red meat and processed meat consumption were not associated with risk of stroke in men or women.