Probabilistic Approaches to Better Quantifying the Results of Epidemiologic Studies

Typical statistical analysis of epidemiologic data captures uncertainty due to random sampling variation, but ignores more systematic sources of variation such as selection bias, measurement error, and unobserved confounding. Such sources are often only mentioned via qualitative caveats, perhaps under the heading of ‘study limitations.’ Recently, however, there has been considerable interest and advancement in probabilistic methodologies for more integrated statistical analysis. Such techniques hold the promise of replacing a confidence interval reflecting only random sampling variation with an interval reflecting all, or at least more, sources of uncertainty. We survey and appraise the recent literature in this area, giving some prominence to the use of Bayesian statistical methodology

Accreditation of The Hydrographic Surveying Course at UCL and The PLA

In September 1999, the Department of Geomatic Engineering at University College London (UCL) introduced a new MSc in Hydrographic Surveying, in partnership with the Port of London Authority (PLA). In May 2001 this degree programme was approved by the courses board of the International Hydrographic Organisation and the International Federation of Surveyors as a Category A course. The aim of this article is to explain the background to the partnership between UCL and the PLA, and to describe how the course has been designed to meet the IHO/FIG criteria

Causal inference based on counterfactuals

BACKGROUND: The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. DISCUSSION: This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. SUMMARY: Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept

Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation

Machine learning methods play increasingly important roles in pre-procedural planning for complex surgeries and interventions. Very often, however, researchers find the historical records of emerging surgical techniques, such as the transcatheter aortic valve replacement (TAVR), are highly scarce in quantity. In this paper, we address this challenge by proposing novel generative invertible networks (GIN) to select features and generate high-quality virtual patients that may potentially serve as an additional data source for machine learning. Combining a convolutional neural network (CNN) and generative adversarial networks (GAN), GIN discovers the pathophysiologic meaning of the feature space. Moreover, a test of predicting the surgical outcome directly using the selected features results in a high accuracy of 81.55%, which suggests little pathophysiologic information has been lost while conducting the feature selection. This demonstrates GIN can generate virtual patients not only visually authentic but also pathophysiologically interpretable

Intrauterine exposure to mild analgesics during pregnancy and the occurrence of cryptorchidism and hypospadia in the offspring: The Generation R Study

This article is available open access through the publisher’s website. Copyright @ 2012 The Authors.BACKGROUND - Recently, over-the-counter mild analgesic use during pregnancy has been suggested to influence the risk of reproductive disorders in the offspring. We examined the influence of maternal exposure to mild analgesics during pregnancy on the occurrence of cryptorchidism and hypospadia in their offspring. METHODS - Associations between maternal exposure to mild analgesics during pregnancy and cryptorchidism or hypospadia in the offspring were studied in 3184 women participating in a large population-based prospective birth cohort study from early pregnancy onwards in the Netherlands (2002–2006), the Generation R Study. Cryptorchidism and hypospadia were identified during routine screening assessments performed in child health care centres by trained physicians. The use of mild analgesics was assessed in three prenatal questionnaires in pregnancy, resulting in four periods of use, namely, periconception period, first 14 weeks of gestation, 14–22 weeks of gestation and 20–32 weeks of gestation. Logistic regression analyses were used to study the associations between maternal exposure to mild analgesics and cryptorchidism and hypospadia. RESULTS - The cumulative prevalence over 30 months of follow up was 2.1% for cryptorchidism and 0.7% for hypospadia. Use of mild analgesics in the second period of pregnancy (14–22 weeks) increased the risk of congenital cryptorchidism [adjusted odds ratio (OR) 2.12; 95% confidence interval (CI) 1.17–3.83], primarily due to the use of acetaminophen (paracetamol) (adjusted OR 1.89; 95% CI 1.01–3.51). Among mothers of cryptorchid sons, 33.8% reported (23 of 68) the use of mild analgesics during pregnancy, compared with 31.8% (7 of 22) of mothers with a boy with hypospadia and 29.9% (926 of 3094) of mothers with healthy boys. CONCLUSIONS - Our results suggest that intrauterine exposure to mild analgesics, primarily paracetamol, during the period in pregnancy when male sexual differentiation takes place, increases the risk of cryptorchidism.Erasmus University Rotterdam, School of Law and Faculty of Social Sciences, the Municipal Health Service Rotterdam area, Rotterdam, the Rotterdam Homecare Foundation, Rotterdam and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR), Rotterdam

Re-interpreting conventional interval estimates taking into account bias and extra-variation

BACKGROUND: The study design with the smallest bias for causal inference is a perfect randomized clinical trial. Since this design is often not feasible in epidemiologic studies, an important challenge is to model bias properly and take random and systematic variation properly into account. A value for a target parameter might be said to be "incompatible" with the data (under the model used) if the parameter's confidence interval excludes it. However, this "incompatibility" may be due to bias and/or extra-variation. DISCUSSION: We propose the following way of re-interpreting conventional results. Given a specified focal value for a target parameter (typically the null value, but possibly a non-null value like that representing a twofold risk), the difference between the focal value and the nearest boundary of the confidence interval for the parameter is calculated. This represents the maximum correction of the interval boundary, for bias and extra-variation, that would still leave the focal value outside the interval, so that the focal value remained "incompatible" with the data. We describe a short example application concerning a meta analysis of air versus pure oxygen resuscitation treatment in newborn infants. Some general guidelines are provided for how to assess the probability that the appropriate correction for a particular study would be greater than this maximum (e.g. using knowledge of the general effects of bias and extra-variation from published bias-adjusted results). SUMMARY: Although this approach does not yet provide a method, because the latter probability can not be objectively assessed, this paper aims to stimulate the re-interpretation of conventional confidence intervals, and more and better studies of the effects of different biases

The various power decays of the survival probability at long times for free quantum particle

The long time behaviour of the survival probability of initial state and its dependence on the initial states are considered, for the one dimensional free quantum particle. We derive the asymptotic expansion of the time evolution operator at long times, in terms of the integral operators. This enables us to obtain the asymptotic formula for the survival probability of the initial state $\psi (x)$, which is assumed to decrease sufficiently rapidly at large $|x|$. We then show that the behaviour of the survival probability at long times is determined by that of the initial state $\psi$ at zero momentum $k=0$. Indeed, it is proved that the survival probability can exhibit the various power-decays like $t^{-2m-1}$ for an arbitrary non-negative integers $m$ as $t \to \infty$, corresponding to the initial states with the condition $\hat{\psi} (k) = O(k^m)$ as $k\to 0$.Comment: 15 pages, to appear in J. Phys.

Stressful life events and cancer risk

In a prospective cohort study in Denmark of 8736 randomly selected people, no evidence was found among 1011 subjects who developed cancer that self-reported stressful major life events had increased their risk for cancer

High-Density Lipoprotein Cholesterol and Particle Concentrations, Carotid Atherosclerosis, and Coronary Events MESA (Multi-Ethnic Study of Atherosclerosis)

ObjectivesThe purpose of this study was to evaluate independent associations of high-density lipoprotein cholesterol (HDL-C) and particle (HDL-P) concentrations with carotid intima-media thickness (cIMT) and incident coronary heart disease (CHD).BackgroundHDL-C is inversely related to CHD, and also to triglycerides, low-density lipoprotein particles (LDL-P), and related metabolic risk. HDL-P associations with CHD may be partially independent of these factors.MethodsIn a multiethnic study of 5,598 men and women ages 45 to 84 years old, without baseline CHD, excluding subjects on lipid-lowering medications, triglycerides >400 mg/dl, or missing values, we evaluated associations of HDL-C and nuclear magnetic resonance spectroscopy-measured HDL-P with cIMT and incident CHD (myocardial infarction, CHD death, and angina, n = 227 events; mean 6.0 years follow-up). All models were adjusted for age, sex, ethnicity, hypertension, and smoking.ResultsHDL-C and HDL-P correlated with each other (ρ = 0.69) and LDL-P (ρ = −0.38, −0.25, respectively, p < 0.05 for all). For (1 SD) higher HDL-C (15 mg/dl) or HDL-P (6.64 μmol/l), cIMT differences were − 26.1 (95% confidence interval [CI]: −34.7 to −17.4) μm and −30.1 (95% CI: −38.8 to − 21.4) μm, and CHD hazard ratios were 0.74 (95% CI: 0.63 to 0.88) and 0.70 (95% CI: 0.59 to 0.82), respectively. Adjusted for each other and LDL-P, HDL-C was no longer associated with cIMT (2.3; 95% CI: − 9.5 to 14.2 μm) or CHD (0.97; 95% CI: 0.77 to 1.22), but HDL-P remained independently associated with cIMT (−22.2; 95% CI: − 33.8 to −10.6 μm) and CHD (0.75; 95% CI: 0.61 to 0.93). Interactions by sex, ethnicity, diabetes, and high-sensitivity C-reactive protein were not significant.ConclusionsAdjusting for each other and LDL-P substantially attenuated associations of HDL-C, but not HDL-P, with cIMT and CHD. Potential confounding by related lipids or lipoproteins should be carefully considered when evaluating HDL-related risk

Antiretroviral Therapy outcomes among adolescents and youth in rural Zimbabwe

Around 2 million adolescents and 3 million youth are estimated to be living with HIV worldwide. Antiretroviral outcomes for this group appear to be worse compared to adults. We report antiretroviral therapy outcomes from a rural setting in Zimbabwe among patients aged 10-30 years who were initiated on ART between 2005 and 2008. The cohort was stratified into four age groups: 10-15 (young adolescents) 15.1-19 years (adolescents), 19.1-24 years (young adults) and 24.1-29.9 years (older adults). Survival analysis was used to estimate rates of deaths and loss to follow-up stratified by age group. Endpoints were time from ART initiation to death or loss to follow-up. Follow-up of patients on continuous therapy was censored at date of transfer, or study end (31 December 2008). Sex-adjusted Cox proportional hazards models were used to estimate hazard ratios for different age groups. 898 patients were included in the analysis; median duration on ART was 468 days. The risk of death were highest in adults compared to young adolescents (aHR 2.25, 95%CI 1.17-4.35). Young adults and adolescents had a 2-3 times higher risk of loss to follow-up compared to young adolescents. When estimating the risk of attrition combining loss to follow-up and death, young adults had the highest risk (aHR 2.70, 95%CI 1.62-4.52). This study highlights the need for adapted adherence support and service delivery models for both adolescents and young adults