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Objectives: we aim to present an in-depth report of the incidence and prevalence of systemic sclerosis (SSc) in Sweden in a nation-wide register-based study covering the entire Swedish population METHODS: each individual residing in Sweden is given a unique personal identity number. We linked the National Patient Register and the Total Population Register to identify 1) patients with prevalent SSc on 2015-12-31 and 2) patients with incident SSc during the time period 2004-2015 based on ICD-10 codes. We estimated prevalence and incidence overall and stratified on age, sex, and county., Results: we identified 1774 prevalent cases, median age was 65 years (IQR 19.2) and 84% were women. The point prevalence estimate was 22.7 per 100,000 (95%CI 13.3-32.0). 1139 individuals were newly diagnosed with SSc during 2004-2015 with a median age of 60 years (IQR 20.6) and 80% were women. The mean standardized incidence was 11.9 per 1,000,000 person-years (95%CI 5.1-18.7). The annual incidence remained stable over the study period. Women had five times higher incidence and prevalence than men. The highest prevalence stratified by age strata was observed in the group aged 70-79., Conclusion: SSc incidence and prevalence in Sweden are comparable to estimates from southern Europe, as opposed to the previous assumption of lower occurrence in northern Europe. We further observe that SSc incidence has been rather constant throughout recent years in Sweden with no obvious increase., Competing Interests: Declaration of competing interest RH reports non-promotional speaker and consultation fees from Janssen-Cilag AB, Boehringer-Ingelheim, Thermo-Fisher Scientific Inc, Ana Mar, Gesynta, and CSL Behring LLC, outside the submitted work. Other co-authors declare no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: We aimed to conduct a systematic review and meta-analysis on the incidence and prevalence of SSc covering the entire literature., Methods: This study followed the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement of 2009. We conducted a systematic search in MEDLINE, Web of Science and Embase to identify articles reporting incidence and/or prevalence of SSc. Two authors conducted the search, reviewed articles for inclusion and extracted relevant data. We used random-effects models to estimate the pooled prevalence and incidence of SSc and performed subgroup analyses by sex, case definition and region to investigate heterogeneity. We explored the association between calendar period and reported estimates using meta-regression., Results: Among 6983 unique records identified, we included 61 studies of prevalence and 39 studies of incidence in the systematic review. The overall pooled prevalence of SSc was 17.6 (95% CI 15.1, 20.5) per 100 000 and the overall pooled incidence rate of SSc was 1.4 (95% CI 1.1, 1.9) per 100 000 person-years. We observed significant regional variations in reported estimates; studies conducted in North America reported considerably higher estimates than other regions. The pooled incidence and prevalence in women were five times higher than in men. More recent studies reported higher estimates than older ones., Conclusion: In this comprehensive review of the incidence and prevalence of SSc across the world, there was large heterogeneity among estimates, which should be taken into consideration when interpreting the results., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Understanding the genetic background of complex diseases requires the expansion of studies beyond univariate associations. Therefore, it is important to use interaction assessments of risk factors in order to discover whether, and how genetic risk variants act together on disease development. The principle of interaction analysis is to explore the magnitude of the combined effect of risk factors on disease causation. In this study, we use simulations to investigate different scenarios of causation to show how the magnitude of the effect of two risk factors interact. We mainly focus on the two most commonly used interaction models, the additive and multiplicative risk scales, since there is often confusion regarding their use and interpretation. Our results show that the combined effect is multiplicative when two risk factors are involved in the same chain of events, an interaction called synergism. Synergism is often described as a deviation from additivity, which is a broader term. Our results also confirm that it is often relevant to estimate additive effect relationships, because they correspond to independent risk factors at low disease prevalence. Importantly, we evaluate the threshold of more than two required risk factors for disease causation, called the multifactorial threshold model. We found a simple mathematical relationship (square root) between the threshold and an additive-to-multiplicative linear effect scale (AMLES), where 0 corresponds to an additive effect and 1 to a multiplicative. We propose AMLES as a metric that could be used to test different effects relationships at the same time, given that it can simultaneously reveal additive, multiplicative and intermediate risk effects relationships. Finally, the utility of our simulation study was demonstrated using real data by analyzing and interpreting gene-gene interaction odds ratios from a rheumatoid arthritis case-control cohort., Competing Interests: The authors have declared that no competing interests exist.