Toeval en vertekening

Oratie uitgesproken door Prof.dr. S. le Cessie bij de aanvaarding van het ambt van hoogleraar in de Statistische Methoden in Observationeel (klinisch) Epidemiologisch Onderzoek aan de Universiteit Leiden op vrijdag 22 september 2017LUMC / Geneeskund

Low birth weight and fetal anaemia as risk factors for infant morbidity in rural Malawi

Low birth weight (LBW) and fetal anaemia (FA) are common in malaria endemic areas. To investigate the incidence of infectious morbidity in infants in rural Malawi in relation to birth weight and fetal anaemia, a cohort of babies was followed for a year on the basis of LBW

Using unstructured profile information for gender classification of Portuguese and English

This paper reports experiments on automatically detecting the gender of Twitter users, based on unstructured information found on their Twitter profile. A set of features previously proposed is evaluated on two datasets of English and Portuguese users, and their performance is assessed using several supervised and unsupervised approaches, including Naive Bayes variants, Logistic Regression, Support Vector Machines, Fuzzy c-Means clustering, and k-means. Results show that features perform well in both languages separately, but even best results were achieved when combining both languages. Supervised approaches reached 97.9 % accuracy, but Fuzzy c-Means also proved suitable for this task achieving 96.4 % accuracy.info:eu-repo/semantics/acceptedVersio

How measurements affected by medication use are reported and handled in observational research: a literature review

Purpose In epidemiological research, measurements affected by medication, for example, blood pressure lowered by antihypertensives, are common. Different ways of handling medication are required depending on the research questions and whether the affected measurement is the exposure, the outcome, or a confounder. This study aimed to review handling of medication use in observational research. Methods PubMed was searched for etiological studies published between 2015 and 2019 in 15 high-ranked journals from cardiology, diabetes, and epidemiology. We selected studies that analyzed blood pressure, glucose, or lipid measurements (whether exposure, outcome or confounder) by linear or logistic regression. Two reviewers independently recorded how medication use was handled and assessed whether the methods used were in accordance with the research aim. We reported the methods used per variable category (exposure, outcome, confounder). Results A total of 127 articles were included. Most studies did not perform any method to account for medication use (exposure 58%, outcome 53%, and confounder 45%). Restriction (exposure 22%, outcome 23%, and confounders 10%), or adjusting for medication use using a binary indicator were also used frequently (exposure: 18%, outcome: 19%, confounder: 45%). No advanced methods were applied. In 60% of studies, the methods' validity could not be judged due to ambiguous reporting of the research aim. Invalid approaches were used in 28% of the studies, mostly when the affected variable was the outcome (36%). Conclusion Many studies ambiguously stated the research aim and used invalid methods to handle medication use. Researchers should consider a valid methodological approach based on their research question.Clinical epidemiolog

A Bayesian (meta-)regression model for treatment effects on the risk difference scale

In clinical settings, the absolute risk reduction due to treatment that can be expected in a particular patient is of key interest. However, logistic regression, the default regression model for trials with a binary outcome, produces estimates of the effect of treatment measured as a difference in log odds. We explored options to estimate treatment effects directly as a difference in risk, specifically in the network meta-analysis setting. We propose a novel Bayesian (meta-)regression model for binary outcomes on the additive risk scale. The model allows treatment effects, covariate effects, interactions and variance parameters to be estimated directly on the linear scale of clinical interest. We compared effect estimates from this model to (1) a previously proposed additive risk model by Warn, Thompson and Spiegelhalter ( "WTS model ") and (2) backtransforming the predictions from a logistic model to the natural scale after regression. The models were compared in a network meta-analysis of 20 hepatitis C trials, as well as in the analysis of simulated single trial settings. The resulting estimates diverged, in particular for small sample sizes or true risks close to 0% or 100%. Researchers should be aware that modelling untransformed risk can yield very different results from default logistic models. The treatment effect in participants with such extreme predicted risks weighed more heavily on the overall treatment effect estimate from our proposed model compared to the WTS model. In our network meta-analysis, this sensitivity of our proposed model was needed to detect all information in the data.Clinical epidemiolog

Diet-derived circulating antioxidants and risk of coronary heart disease a Mendelian randomization study

BACKGROUND Previously, observational studies have identified associations between higher levels of dietary-derived antioxidants and lower risk of coronary heart disease (CHD), whereas randomized clinical trials showed no reduction in CHD risk following antioxidant supplementation.OBJECTIVES The purpose of this study was to investigate possible causal associations between dietary-derived circulating antioxidants and primary CHD risk using 2-sample Mendelian randomization (MR).METHODS Single-nucleotide polymorphisms for circulating antioxidants (vitamins E and C, retinol, 13-carotene, and lycopene), assessed as absolute levels and metabolites, were retrieved from the published data and were used as genetic instrumental variables. Summary statistics for gene-CHD associations were obtained from 3 databases: the CARDIoGRAMplusC4D consortium (60,801 cases; 123,504 control subjects), UK Biobank (25,306 cases; 462,011 control subjects), and FinnGen study (7,123 cases; 89,376 control subjects). For each exposure, MR analyses were performed per outcome database and were subsequently meta-analyzed.RESULTS Among an analytic sample of 768,121 individuals (93,230 cases), genetically predicted circulating antioxidants were not causally associated with CHD risk. For absolute antioxidants, the odds ratio for CHD ranged between 0.94 (95% confidence interval [CI]: 0.63 to 1.41) for retinol and 1.03 (95% CI: 0.97 to 1.10) for 13-carotene per unit increase in ln-transformed antioxidant values. For metabolites, the odds ratio ranged between 0.93 (95% CI: 0.82 to 1.06) for g-tocopherol and 1.01 (95% CI: 0.95 to 1.08) for ascorbate per 10-fold increase in metabolite levels.CONCLUSIONS Evidence from our study did not support a protective effect of genetic predisposition to high dietaryderived antioxidant levels on CHD risk. Therefore, it is unlikely that taking antioxidants to increase blood antioxidants levels will have a clinical benefit for the prevention of primary CHD. (C) 2021 by the American College of Cardiology Foundation.Clinical epidemiolog

Flemish population-based cancer screening programs: impact of COVID-19 related shutdown on short-term key performance indicators

Background Many breast, colorectal, and cervical cancer screening programs were disrupted due to the COVID-19 pandemic. This study aimed to estimate the short-term impact of the temporary shutdown (from March until May- June) of the cancer screening programs invitations in Flanders (Belgium) by looking at invitation coverage, percentage of people screened after invitation and the screening interval. Methods Yearly invitation coverage was calculated as the number of people who received an invitation, as a proportion of the people who should have received an invitation that year. Weekly response to the invitation was calculated as the number of people who were screened within 40 days of their date of invitation, as a percentage of the people who received an invitation that week (as a proxy for willingness to screen). Weekly screening interval was calculated as the mean number of months between the current screening and the previous screening of all the people who screened that week. The two last indicators were calculated for each week in 2019 and 2020, after which the difference between that week's value in 2020 and 2019 with 95% confidence intervals. Results of these two indicators were also analysed after stratification for gender, age and participation history. Results Invitation coverage was not impacted in the colorectal and cervical cancer screening program. In the breast cancer screening program invitation coverage went down from 97.5% (2019) to 88.7% (2020), and the backlog of invitations was largely resolved in the first six months of 2021. The willingness to screen was minimally influenced by COVID-19. The breast cancer screening program had a temporary increase in screening interval in the first months following the restart after COVID-19 related shutdown, when it was on average 2.1 months longer than in 2019. Conclusions Willingness to screen was minimally influenced by COVID-19, but there may be an influence on screening coverage because of lower invitation coverage, mainly for the for breast Cancer Screening Program. The increases in screening intervals for the three Cancer Screening Program seem reasonable and would probably not significantly increase the risk of delayed screening cancer diagnoses. When restarting a Cancer Screening Program after a COVID-19 related shutdown, monitoring is crucial.Clinical epidemiolog

Multiple testing: when 's many too much?

In almost all medical research, more than a single hypothesis is being tested or more than a single relation is being estimated. Testing multiple hypotheses increases the risk of drawing a false-positive conclusion. We briefly discuss this phenomenon, which is often called multiple testing. Also, methods to mitigate the risk of false-positive conclusions are discussed.Clinical epidemiolog

Systematic approach towards reliable estimation of abdominal aortic aneurysm size by ultrasound imaging and CT

Background: The management of abdominal aortic aneurysm (AAA) is fully dictated by AAA size, but there are no uniform measurement guidelines, and systematic differences exist between ultrasound- and CT-based size estimation. The aim of this study was to devise a uniform ultrasound acquisition and measurement protocol, and to test whether harmonization of ultrasound and CT readings is feasible. Methods: A literature review was undertaken to evaluate evidence for ultrasound-based measurement of AAA. A protocol for measuring AAA was then developed, and intraobserver and interobserver reproducibility was tested. Finally, agreement between ultrasound readings and CT-based AAA diameters was evaluated. This was an observational study of patients with a small AAA who participated in two pharmaceutical intervention trials. Results: Based on a literature review, an ultrasound acquisition and reading protocol was devised. Evaluation of the protocol showed an intraobserver repeatability of 1.6 mm (2s.d.) and an interobserver intraclass correlation coefficient (ICC) of 0.97. Comparison of protocolled ultrasound readings and local CT readings indicated a good correlation (r = 0.81), but a systematic +4.1-mm difference for CT. Harmonized size readings for ultrasound imaging and CT increased the correlation (r = 0.91) and reduced the systematic difference to +1.8 mm by CT. Interobserver reproducibility of protocolized CT measurements showed an ICC of 0.94 for the inner-to-inner method and 0.96 for the outer-to-outer method. Conclusion: The absence of harmonized size acquisition and reading guidelines results in overtreatment and undertreatment of patients with AAA. This can be avoided by the implementation of standardized ultrasound acquisition and a harmonized reading protocol for ultrasound- and CT-based readings