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Causal analyses of existing databases: no power calculations required

A key misunderstanding is the belief that the goal of a causal analysis is to “detect” an effect. Causal effects are not binary signals that are either detected or undetected; causal effects are numerical quantities that need to be estimated. Read the paper at https://www.sciencedirect.com/science/article/abs/pii/S0895435621002730

https://www.lupop.lu.se/article/causal-analyses-existing-databases-no-power-calculations-required - 2025-10-03

Agenda 2030: Postdoctoral researcher in Biodiversity and health

I ramverket kommer vi använda kunskap om biologisk mångfald, ekologiska processer, miljöpsykologi, och epidemiologi för att hitta en gemensam väg framåt för att bemöta dessa globala utmaningar i praktiken. Vi rekryterar nu tre postdoktorer som tillsammans kommer att koordinera forskningen i projektet. Läs mer och sök tjänsterna på https://lu.varbi.com/what:job/jobID:422401/

https://www.lupop.lu.se/article/agenda-2030-postdoctoral-researcher-biodiversity-and-health - 2025-10-03

Big data registries in spine surgery research: the lurking dangers

Spine surgery research has improved considerably over the last few decades. Its’ most recent growth is in large part due to the mounting increase in studies conducted using national databases and registries. With easy access to a large number of patients, the benefit of these registries has become evident. However, as with any research, this type of data must be used responsibly with the appropria

https://www.lupop.lu.se/article/big-data-registries-spine-surgery-research-lurking-dangers - 2025-10-03

Available positions at the Department of Public Health, Aarhus University

The Department of Public Health contributes to teaching in medicine, public health science, sport science and nursing. At the department, you will have approx. 200 colleagues, including 90 academic staff members and a corresponding number of PhD students. Available positions: Tenure Track Assistant Professor at the Department of Public Health Professor at the Department of Public Health

https://www.lupop.lu.se/article/available-positions-department-public-health-aarhus-university - 2025-10-03

A Real-World Rheumatology Registry and Research Consortium: The German RheumaDatenRhePort (RHADAR) Registry

The German RheumaDatenRhePort (RHADAR) registry encompasses a network of rheumatologists and researchers in Germany providing pseudonymized real-world patient data and allowing timely and continuous improvement in the care of RMD patients. Read the paper at https://www.jmir.org/2021/5/e28164

https://www.lupop.lu.se/article/real-world-rheumatology-registry-and-research-consortium-german-rheumadatenrheport-rhadar-registry - 2025-10-03

The role of kidney registries in expediting large-scale collection of patient-reported outcome measures for people with chronic kidney disease

In this editorial, we discuss the current state-of-play of PROMs collection by kidney registries and provide an overview of what is (un)known about the feasibility and effectiveness of PROMs in CKD and other conditions. Read the paper at https://academic.oup.com/ckj/article/14/6/1495/6173985

https://www.lupop.lu.se/article/role-kidney-registries-expediting-large-scale-collection-patient-reported-outcome-measures-people - 2025-10-03

SWEDEGENE—a Swedish nation-wide DNA sample collection for pharmacogenomic studies of serious adverse drug reactions

SWEDEGENE was established in 2008 and currently contains DNA and information from about 2550 adults who have experienced specific ADRs, and from 580 drug exposed controls. Read the paper at https://www.nature.com/articles/s41397-020-0148-3

https://www.lupop.lu.se/article/swedegene-swedish-nation-wide-dna-sample-collection-pharmacogenomic-studies-serious-adverse-drug - 2025-10-03

Bias Analysis Gone Bad

We identified 3 examples of suboptimal bias analysis, one for each common bias. For each, we describe the original research and its bias analysis, compare the bias analysis with good practices, and describe how the bias analysis and research findings might have been improved. Read the paper at https://academic.oup.com/aje/article/190/8/1604/6189735

https://www.lupop.lu.se/article/bias-analysis-gone-bad - 2025-10-03

Propensity Score Weighting and Trimming Strategies for Reducing Variance and Bias of Treatment Effect Estimates: A Simulation Study

To extend previous simulations on the performance of propensity score (PS) weighting and trimming methods to settings without and with unmeasured confounding, Poisson outcomes, and various strengths of treatment prediction (PS c statistic), we simulated studies with a binary intended treatment T as a function of 4 measured covariates. Read the paper at https://academic.oup.com/aje/article/190/8/16

https://www.lupop.lu.se/article/propensity-score-weighting-and-trimming-strategies-reducing-variance-and-bias-treatment-effect - 2025-10-03

Data from national health registers as endpoints for the Tromsø Study: Correctness and completeness of stroke diagnoses

The benefits of using data from national registers as endpoints in epidemiological studies must be weighed against the impact of potentially decreased data quality. Read the paper at https://journals.sagepub.com/doi/full/10.1177/14034948211021191

https://www.lupop.lu.se/article/data-national-health-registers-endpoints-tromso-study-correctness-and-completeness-stroke-diagnoses - 2025-10-03

A cautionary note on a recently proposed sensitivity analysis for unmeasured confounding

Unmeasured confounding is a common threat to the validity of observational studies. In practice, confounding bias may arise from both confounders that are completely unmeasured and from confounders that are measured with error. Read the paper at https://academic.oup.com/ije/article/50/3/711/6048186

https://www.lupop.lu.se/article/cautionary-note-recently-proposed-sensitivity-analysis-unmeasured-confounding - 2025-10-03

Reflection on modern methods: a common error in the segmented regression parameterization of interrupted time-series analyses

Interrupted time-series (ITS) designs are a robust and increasingly popular non-randomized study design for strong causal inference in the evaluation of public health interventions. Read the paper at https://academic.oup.com/ije/article/50/3/1011/5937253

https://www.lupop.lu.se/article/reflection-modern-methods-common-error-segmented-regression-parameterization-interrupted-time-series - 2025-10-03

A snapshot of European registries on Chronic Kidney Disease patients not on Kidney Replacement Therapy

We report the current status of CKD registries in Europe in relation to their data collection on patients not on KRT so that in the future we may investigate to what extent also their data may be used for similar purposes, like collaborative research on CKD trajectories and patient outcomes. Read the paper at https://academic.oup.com/ndt/advance-article/doi/10.1093/ndt/gfab252/63…

https://www.lupop.lu.se/article/snapshot-european-registries-chronic-kidney-disease-patients-not-kidney-replacement-therapy - 2025-10-03