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Analyses were based on Swedish case–control data comprising incident cases of LADA (n = 465) and T2D (n = 1528) with matched, population-based controls (n = 1789; n = 1553 in genetic analyses). Multivariable-adjusted ORs in relation to self-reported processed and unprocessed red meat intake were estimated by conditional logistic regression models. Attributable proportion (AP) due to interaction wa

https://www.lupop.lu.se/article/consumption-red-meat-genetic-susceptibility-and-risk-lada-and-type-2-diabetes - 2025-10-03

The authors assessed the effect of incorporating the timing of cancer diagnosis events into the assessment of familial risks of breast cancer in first‐degree and second‐degree relatives in a nationwide cohort study of 5,099,172 women (follow‐up was between 1958‐2015). Family history was assessed using 3 approaches: 1) as a static variable (ever having a relative with breast cancer); 2) as accumula

https://www.lupop.lu.se/article/familial-risk-breast-cancer-dynamic-accumulative-and-static-definitions-family-history - 2025-10-03

Ulnar nerve entrapment at the elbow (UNE) is overrepresented in patients with diabetes, but the outcome of surgery is unknown. We aimed to evaluate patient-reported outcome in patients with and without diabetes, and to assess potential sex differences and compare surgical treatment methods. Data on patients operated for UNE (2010-2016, n = 1354) from the Swedish National Registry for Hand Surgery

https://www.lupop.lu.se/article/ulnar-nerve-entrapment-diabetes-patient-reported-outcome-after-surgery-national-quality-registries - 2025-10-03

Nyhetsbrev från Svensk nationell datatjänst juni 2020. Läs mer här.

https://www.lupop.lu.se/article/snd-natverksnytt-0 - 2025-10-03

The recommendations in the document are aimed at helping policymakers and funders to maximise timely, quality data sharing and appropriate responses in future health emergencies. The Research Data Alliance (RDA) COVID-19 Working Group members bring various, global expertise to develop a body of work that comprises how data from multiple disciplines inform response to a pandemic combined with guide

https://www.lupop.lu.se/article/rda-covid-19-recommendations-and-guidelines-data-sharing - 2025-10-03

In this review, we explain statistical concepts targeted towards patients, clinicians and healthcare professionals that summarize cancer patient survival under the assumption that other causes of death exist. Specifically, we explain the appropriate use, interpretation and assumptions behind statistical methods for competing risks, loss in life expectancy due to cancer and conditional survival. Re

https://www.lupop.lu.se/article/cancer-survival-statistics-patients-and-healthcare-professionals-tutorial-real-world-data-analysis - 2025-10-03

Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. Read more here.

https://www.lupop.lu.se/article/avoiding-dynastic-assortative-mating-and-population-stratification-biases-mendelian-randomization - 2025-10-03

McMaster GRADE Centre researchers developed ‘health outcome descriptors’ for standardizing descriptions of health outcomes and overcoming these problems to support the European Commission Initiative on Breast Cancer (ECIBC) Guideline Development Group (GDG). We aimed to determine which aspects of the development, content, and use of health outcome descriptors were valuable to guideline developers.

https://www.lupop.lu.se/article/development-and-use-health-outcome-descriptors-guideline-development-case-study - 2025-10-03

Objectives: To investigate use of data from a clinical quality registry for cardiac rehabilitation in Denmark, considering the extent to which data are used for local quality improvement and what facilitates the use of these data, with a particular focus on whether there are differences between frontline staff and managers. Read more here.

https://www.lupop.lu.se/article/facilitators-using-data-quality-registry-local-quality-improvement-work-cross-sectional-survey-0 - 2025-10-03

Combining National Quality Registries (NQRs) with existing National Health Registries (NHRs) might make it possible to get a wider picture of older adults health situation. The aim was to examine the feasibility of aggregating data across different NQRs and existing NHRs to explore the possibility to investigate trajectories and patterns of disease and care, specifically for the most ill older adu

https://www.lupop.lu.se/article/using-aggregated-data-swedish-national-quality-registries-tools-describe-health-conditions-older - 2025-10-03

Forte har påbörjat en översyn av ett antal mindre bidragsformer. Under 2020 sker därför ingen utlysning av nätverksbidrag, tidskriftsbidrag, konferensbidrag och gästforskarbidrag. Läs mer på https://forte.se/nyhet/ingen-utlysning-av-natverksbidrag-gastforskarbid….

https://www.lupop.lu.se/article/forte-ingen-utlysning-av-natverksbidrag-gastforskarbidrag-tidskriftsbidrag-och-konferensbidrag-2020 - 2025-10-03

Whether you’re starting a review article or your dissertation, embarking on a literature review can feel daunting. Not sure where to start? Join our webinar to learn how to tackle literature reviews with confidence. Read more here.

https://www.lupop.lu.se/article/web-science-webinar-your-essential-guide-literature-reviews - 2025-10-03

Med anledning av coronakrisen deltar Forte i Formas akututlysning för 2020. Utlysningen ska ge möjlighet att samla in forskningsmaterial av akut karaktär för att säkerställa framtida tillgänglighet för forskning. Forskare inom Fortes områden kan ansöka om medel för datainsamling med koppling till coronapandemin. Läs mer på https://forte.se/utlysning/akututlysning-2020.

https://www.lupop.lu.se/article/corona-akut-utlysning-2020 - 2025-10-03

Generalized linear models (GLMs) are often used with binary outcomes to estimate odds ratios. Though not as widely appreciated, GLMs can also be used to quantify risk differences, risk ratios, and their appropriate standard errors (1). Here, we illustrate how GLMs can be used to quantify these latter effect measures, and we demonstrate how to obtain valid standard errors. Read more at https://doi.

https://www.lupop.lu.se/article/estimating-risk-ratios-and-risk-differences-using-regression - 2025-10-03

There has been much debate about the relative emphasis of the field of epidemiology on causal inference. We believe this debate does short shrift to the breadth of the field. Epidemiologists answer myriad questions that are not causal and hypothesize about and investigate causal relationships without estimating causal effects. Descriptive studies face significant and often overlooked inferential a

https://www.lupop.lu.se/article/epidemiologic-toolbox-identifying-honing-and-using-right-tools-job - 2025-10-03

Read more at https://journals.plos.org/plosone/article?id=10.1371/journal.pone.02340….

https://www.lupop.lu.se/article/disentangling-contribution-hospitals-and-municipalities-understanding-patient-level-differences-one - 2025-10-03

Read more at https://pubmed.ncbi.nlm.nih.gov/32639513/.

https://www.lupop.lu.se/article/probabilistic-quantification-bias-combine-strengths-population-based-register-data-and-clinical - 2025-10-03

Read more at https://doi.org/10.1002/sim.8672.

https://www.lupop.lu.se/article/sensitivity-analysis-treatment-effect-unmeasured-confounding-observational-studies-survival-and - 2025-10-03

Breastfeeding in public continues to be contentious with qualitative evidence confirming that women face many challenges. It is therefore important to gain understanding of not only the challenges but also what women perceive is helpful to breastfeed in public. Read more at https://doi.org/10.1186/s13006-020-00281-0.

https://www.lupop.lu.se/article/helpful-and-challenging-aspects-breastfeeding-public-women-living-australia-ireland-and-sweden-cross - 2025-10-03

The main categories of data collected include: demographics, care visits, other encounters, clinical data, visit-level costs, resources and occupancy. Clinical images, patient-generated data, genetics and visits outside Halland are not included in the platform. Read more at https://doi.org/10.1093/ije/dyz262.

https://www.lupop.lu.se/article/data-resource-profile-regional-healthcare-information-platform-halland-sweden - 2025-10-03