Exogenous hormone use and cutaneous melanoma risk in women: The European Prospective Investigation into Cancer and Nutrition

Evidence suggests an influence of sex hormones on cutaneous melanoma risk, but epidemiologic findings are conflicting. We examined the associations between use of oral contraceptives (OCs) and menopausal hormone therapy (MHT) and melanoma risk in women participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). EPIC is a prospective cohort study initiated in 1992 in 10 European countries. Information on exogenous hormone use at baseline was derived from country-specific self-administered questionnaires. We used Cox proportional hazards regression models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Over 1992–2015, 1,696 melanoma cases were identified among 334,483 women, whereof 770 cases among 134,758 postmenopausal women. There was a positive, borderline-significant association between OC use and melanoma risk (HR = 1.12, 95% CI = 1.00–1.26), with no detected heterogeneity across countries (p_homogeneity = 0.42). This risk increased linearly with duration of use (p_trend = 0.01). Among postmenopausal women, ever use of MHT was associated with a nonsignificant increase in melanoma risk overall (HR = 1.14, 95% CI = 0.97–1.43), which was heterogeneous across countries (p_homogeneity = 0.05). Our findings do not support a strong and direct association between exogenous hormone use and melanoma risk. In order to better understand these relations, further research should be performed using prospectively collected data including detailed information on types of hormone, and on sun exposure, which may act as an important confounder or effect modifier on these relations.     

International validation and update of the Amsterdam model for prediction of survival after pancreatoduodenectomy for pancreatic cancer

BackgroundThe objective of this study was to validate and update the Amsterdam prediction model including tumor grade, lymph node ratio, margin status and adjuvant therapy, for prediction of overall survival (OS) after pancreatoduodenectomy for pancreatic cancer.MethodsWe included consecutive patients who underwent pancreatoduodenectomy for pancreatic cancer between 2000 and 2017 at 11 tertiary centers in 8 countries (USA, UK, Germany, Italy, Sweden, the Netherlands, Korea, Australia). Model performance for prediction of OS was evaluated by calibration statistics and Uno's C-statistic for discrimination. Validation followed the TRIPOD statement.ResultsOverall, 3081 patients (53% male, median age 66 years) were included with a median OS of 24 months, of whom 38% had N2 disease and 77% received adjuvant chemotherapy. Predictions of 3-year OS were fairly similar to observed OS with a calibration slope of 0.72. Statistical updating of the model resulted in an increase of the C-statistic from 0.63 to 0.65 (95% CI 0.64–0.65), ranging from 0.62 to 0.67 across different countries. The area under the curve for the prediction of 3-year OS was 0.71 after updating. Median OS was 36, 25 and 15 months for the low, intermediate and high risk group, respectively (P < 0.001).ConclusionsThis large international study validated and updated the Amsterdam model for survival prediction after pancreatoduodenectomy for pancreatic cancer. The model incorporates readily available variables with a fairly accurate model performance and robustness across different countries, while novel markers may be added in the future. The risk groups and web-based calculator www.pancreascalculator.com may facilitate use in daily practice and future trials.     

Chronic pelvic pain syndrome: Highlighting medicinal plants toward biomolecules discovery for upcoming drugs formulation

Chronic pelvic pain syndrome (CPPS) can be triggered by a various types of gynecological, gastrointestinal, urological, and musculoskeletal disorders. Recently, the role of the central nervous system has proven to be an integral part on the development of any chronic pain syndrome, including CPPS. However, owing to the complex and heterogeneous etiology and pathophysiology of CPPS, the establishment of effective therapeutic interventions remains challenging for both physicians and patients. Nonetheless, recent studies have pointed that medicinal plants and their secondary metabolites can be effectively used in CPPS therapy, besides contributing to restore the patients' quality of life and potentiate the conventional CPPS management. In this sense, this review aims to provide a careful overview on the biomedical data for the use of medicinal plants use and their secondary metabolites on CPPS management.     

An ode to fetal,infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI,and an introduction to an academic society connecting the field

Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.     

Validation of randomized controlled trial-derived models for the prediction of postintervention outcomes in chronic limb-threatening ischemia

BackgroundChronic limb-threatening ischemia (CLTI) represents the most severe form of peripheral artery disease and has a large impact on quality of life, morbidity, and mortality. Interventions are aimed at improving tissue perfusion and averting amputation and secondary cardiovascular complications with an optimal risk-benefit ratio. Several prediction models regarding postprocedural outcomes in CLTI patients have been developed on the basis of randomized controlled trials to improve clinical decision-making. We aimed to determine model performance in predicting clinical outcomes in selected CLTI cohorts.MethodsThis study validated the Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL), Finland National Vascular registry (FINNVASC), and Prevention of Infrainguinal Vein Graft Failure (PREVENT III) models in data sets from a peripheral artery disease registry study (Athero-Express) and two randomized controlled trials of CLTI in The Netherlands, Rejuvenating Endothelial Progenitor Cells via Transcutaneous Intra-arterial Supplementation (JUVENTAS) and Percutaneous Transluminal Angioplasty and Drug-eluting Stents for Infrapopliteal Lesions in Critical Limb Ischemia (PADI). Receiver operating characteristic (ROC) curve analysis was used to calculate their predictive capacity. The primary outcome was amputation-free survival (AFS); secondary outcomes were all-cause mortality and amputation at 12 months after intervention.ResultsThe BASIL and PREVENT III models showed predictive values regarding postintervention mortality in the JUVENTAS cohort with an area under the ROC curve (AUC) of 81% and 70%, respectively. Prediction of AFS was poor to fair (AUC, 0.60-0.71) for all models in each population, with the highest predictive value of 71% for the BASIL model in the JUVENTAS population. The FINNVASC model showed the highest predictive value regarding amputation risk in the PADI population with AUC of 78% at 12 months.ConclusionsIn general, all models performed poor to fair in predicting mortality and amputation. Because the BASIL model performed best in predicting AFS, we propose use of the BASIL model to aid in the clinical decision-making process in CLTI. However, improvements in performance have to be made for any of these models to be of real additional value in clinical practice.     

Principles of studying low-level neurotoxic exposures in children: using the Seychelles Child Development Study of methyl mercury as a prototype

Epidemiological studies to determine the impact of low level toxic exposure on child development are important in guiding clinical and public health action. However, carrying out such studies and interpreting their findings presents a number of significant challenges to the investigators. First, they must find a cohort with suitable exposure, select a biomarker that will accurately determine the level of exposure and determine the endpoints that are most likely to detect subtle differences in neurodevelopment. Following that, the logistics of the study must be organised and collaboration established with the local population and health authorities. To accurately interpret the data, they must also accurately determine covariates that impact child development. After the data are collected, interpreting the findings presents a further challenge. Throughout this process, the study must adhere to fundamental epidemiological principles and clearly defined statistical approaches. This paper discusses those principles and uses the Seychelles Child Development Study to show how one epidemiological study addressed them.