Increased risk of death from COVID-19 in multiple sclerosis: a pooled analysis of observational studies

8524 Background: Management of ARL evolved in the last 2 decades. We previously reported prognostic factors in a pooled analysis of 1,546 patients with ARL, and here present analysis of these factors over time to determine if their prognostic significance has changed. Methods: Following a systematic review, we assembled individual patient data from 19 prospective phase 2/3 clinical trials (published 1993-2010) for ARL (n=1,546). Factors analyzed include age, sex, histology, CD4 count, prior history of (h/o) AIDS, & age-adjusted (aa) IPI. The endpoint was overall survival (OS) expressed as the hazard ratio (HR) for death. We used separate Cox proportional hazard models adjusted for the other covariates to determine the significance of each variable in the following time periods: pre-cART [combination antiretroviral therapy] (<1996; n=388), early cART (‘96-‘00; n=694), modern cART (‘01-‘04; n=282) & current era (‘05-‘10; n=182). We also combined all enrollments in one Cox model to test for difference in association with OS over enrollment periods. Results: Rituximab use was limited in the early cART (20%) compared with the modern cART (83%) and current (93%) eras. Histology & sex were not significantly associated with OS in any time period. Increasing age was associated with worse OS in the pre-cART (HR 1.02; p<0.01) and current (HR 1.05, p=0.04) eras. A prior h/o AIDS increased risk of death during early cART (HR 1.31, p=0.047) but was not significant after 2000. Meanwhile, baseline CD4 count <50 was a poor prognostic factor during early (HR 1.78, p<0.01) and modern cART (HR 2.76, p=0.001) eras, but not in the current era. The aaIPI predicted worse OS in each time period (pre-cART: HR 1.54, p<0.0001; early cART: HR 1.49, p<0.0001; modern cART: HR 1.52, p<0.01; current era: HR 2.34, p<0.0001). No significant interaction between each prognostic factor with enrollment was found. Conclusions: In this pooled analysis of 1,546 patients with ARL, aaIPI was the only consistently significant prognostic factor and its effect was magnified in the current era. HIV-related factors gained prognostic relevance in the early and modern cART era but may not be as relevant with current treatment strategies.

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Excess Body Weight during Childhood and Adolescence Is Associated with the Risk of Multiple Sclerosis: A Meta-Analysis

Neuroepidemiology ◽

10.1159/000450854 ◽

2016 ◽

Vol 47 (2) ◽

pp. 103-108 ◽

Cited By ~ 11

Author(s):

Zhen Liu ◽

Ting-Ting Zhang ◽

Jie Yu ◽

Ying-Li Liu ◽

Su-Fen Qi ◽

...

Keyword(s):

Multiple Sclerosis ◽

Body Weight ◽

Observational Studies ◽

Overweight And Obesity ◽

Excess Body Weight ◽

Female Group ◽

Childhood And Adolescence ◽

Case Control Studies ◽

Male Group ◽

Increased Risk

Background and Aim: Several epidemiological studies have reported the association between obesity and multiple sclerosis (MS). Methods: A literature search of the observational studies, published as original articles in English before December 2015, was performed using electronic databases. Results: Five observational studies were included, of which 3 were case-control studies and 2 were cohort studies. The pooled relative risk (RR) for overweight and obesity during childhood and adolescence compared with normal weight (body mass index = 18.5-24.9 kg/m2) was 1.44 (95% CI 1.22-1.70) and 2.01 (95% CI 1.63-2.48), respectively. In subgroup analyses, we found that excess body weight during childhood and adolescence increased the risk of MS in the female group (overweight: pooled RR = 1.62, 95% CI 1.35-1.94; obesity: pooled RR = 2.25, 95% CI 1.77-2.85), but not in the male group (overweight: pooled RR = 1.19, 95% CI 0.91-1.55; obesity: pooled RR = 1.22, 95% CI 0.79-1.90). Conclusions: Excess body weight during childhood and adolescence was associated with an increased risk of MS; severe obesity demonstrated a stronger risk. A statistically significant association was found in the female group, but not in the male group.

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Mortality in ANCA-associated vasculitis: ameta-analysis of observational studies

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2016-210942 ◽

2017 ◽

Vol 76 (9) ◽

pp. 1566-1574 ◽

Cited By ~ 42

Author(s):

Ju Ann Tan ◽

Natasha Dehghan ◽

Wenjia Chen ◽

Hui Xie ◽

John M Esdaile ◽

...

Keyword(s):

General Population ◽

Publication Bias ◽

Mortality Risk ◽

Observational Studies ◽

Consensus Conference ◽

Antineutrophil Cytoplasmic Antibodies ◽

Published Data ◽

Risk Of Death ◽

Increased Risk ◽

All Cause Mortality

ObjectiveTo determine the magnitude of all-cause mortality risk in patients with antineutrophil cytoplasmic antibodies-associated vasculitis (AAV) compared with the general population through a meta-analysis of observational studies.MethodsWe searched Medline and Embase databases from their inception to April 2015. Observational studies that met the following criteria were assessed by two researchers: (1) clearly defined AAV identified by either the American College of Rheumatology 1990 classification criteria or the 2012 Chapel Hill Consensus Conference disease definitions, and (2) reported standardised mortality ratios (SMR) and 95% CI. We calculated weighted-pooled summary estimates of SMRs (meta-SMRs) for all-cause mortality using random-effects model, tested for publication bias and heterogeneity.ResultsTen studies met the inclusion criteria, comprising 3338 patients with AAV enrolled from 1966 to 2009, and a total of 1091 observed deaths. Overall, we found a 2.7-fold increased risk of death in patients with AAV when compared with the general population (meta-SMR: 2.71 (95% CI 2.26 to 3.24)). Analysis on studies that included only granulomatosis with polyangiitis cases also indicated a similar mortality risk (meta-SMR: 2.63 (95% CI 2.02 to 3.43)). There was no significant publication bias or small-study effect. Subgroup analyses showed that mortality risks were higher in older cohorts, with a trend towards improvement over time (ie, those with their midpoint of enrolment periods that were between 1980–1993 and 1994–1999, vs 2000–2005).ConclusionPublished data indicate there is a 2.7-fold increase in mortality among patients with AAV compared with the general population.

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Evaluation of Frailty as an Unmeasured Confounder in Observational Studies of Antidiabetic Medications

The Journals of Gerontology Series A ◽

10.1093/gerona/gly224 ◽

2018 ◽

Vol 74 (8) ◽

pp. 1282-1288 ◽

Cited By ~ 2

Author(s):

Caroline A Presley ◽

Jonathan Chipman ◽

Jea Young Min ◽

Carlos G Grijalva ◽

Robert A Greevy ◽

...

Keyword(s):

Observational Studies ◽

Proportional Hazards ◽

Cox Proportional Hazards ◽

Health Administration ◽

Medication Regimen ◽

Antidiabetic Medication ◽

Time To Death ◽

Risk Of Death ◽

C Statistic ◽

Increased Risk

Abstract Background It is unknown whether observational studies evaluating the association between antidiabetic medications and mortality adequately account for frailty. Our objectives were to evaluate if frailty was a potential confounder in the relationship between antidiabetic medication regimen and mortality and how well administrative and clinical electronic health record (EHR) data account for frailty. Methods We conducted a retrospective cohort study in a single Veterans Health Administration (VHA) healthcare system of 500 hospitalizations—the majority due to heart failure—of Veterans who received regular VHA care and initiated type 2 diabetes treatment from 2001 to 2008. We measured frailty using a modified frailty index (FI, >0.21 frail). We obtained antidiabetic medication regimen and time-to-death from administrative sources. We compared FI among patients on different antidiabetic regimens. Stepwise Cox proportional hazards regression estimated time-to-death by demographic, administrative, clinical EHR, and FI data. Results Median FI was 0.22 (interquartile range 0.18, 0.27). Frailty differed across antidiabetic regimens (p < .001). An FI increase of 0.05 was associated with an increased risk of death (hazard ratio 1.45, 95% confidence interval 1.32, 1.60). Cox proportional hazards model for time-to-death including demographic, administrative, and clinical EHR data had a c-statistic of 0.70; adding FI showed marginal improvement (c-statistic 0.72). Conclusions Frailty was associated with antidiabetic regimen and death, and may confound that relationship. Demographic, administrative, and clinical EHR data, commonly used to balance differences among exposure groups, performed moderately well in assessing risk of death, with minimal gain from adding frailty. Study design and analytic techniques can help minimize potential confounding by frailty in observational studies.

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Negative interaction between smoking and EBV in the risk of multiple sclerosis: The EnvIMS study

Multiple Sclerosis Journal ◽

10.1177/1352458516671028 ◽

2016 ◽

Vol 23 (7) ◽

pp. 1018-1024 ◽

Cited By ~ 11

Author(s):

Kjetil Bjørnevik ◽

Trond Riise ◽

Inger Bostrom ◽

Ilaria Casetta ◽

Marianna Cortese ◽

...

Keyword(s):

Multiple Sclerosis ◽

Population Based ◽

Pooled Analysis ◽

Negative Interaction ◽

Barr Virus ◽

Increased Risk ◽

History Of ◽

Epstein Barr ◽

Control Study ◽

Additive Scale

Background: Results from previous studies on a possible interaction between smoking and Epstein–Barr virus (EBV) in the risk of multiple sclerosis (MS) are conflicting. Objectives: To examine the interaction between smoking and infectious mononucleosis (IM) in the risk of MS. Methods: Within the case–control study on Environmental Factors In Multiple Sclerosis (EnvIMS), 1904 MS patients and 3694 population-based frequency-matched healthy controls from Norway, Italy, and Sweden reported on prior exposure to smoking and history of IM. We examined the interaction between the two exposures on the additive and multiplicative scale. Results: Smoking and IM were each found to be associated with an increased MS risk in all three countries, and there was a negative multiplicative interaction between the two exposures in each country separately as well as in the pooled analysis ( p = 0.001). Among those who reported IM, there was no increased risk associated with smoking (odds ratio (OR): 0.95, 95% confidence interval (CI): 0.66–1.37). The direction of the estimated interactions on the additive scale was consistent with a negative interaction in all three countries (relative excess risk due to interaction (RERI): −0.98, 95% CI: −2.05–0.15, p = 0.09). Conclusion: Our findings indicate competing antagonism, where the two exposures compete to affect the outcome.

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Smoking and multiple sclerosis risk: a Mendelian randomization study

Journal of Neurology ◽

10.1007/s00415-020-09980-4 ◽

2020 ◽

Vol 267 (10) ◽

pp. 3083-3091

Author(s):

Marijne Vandebergh ◽

An Goris

Keyword(s):

Multiple Sclerosis ◽

Observational Studies ◽

Genome Wide Association Study ◽

Human Genetics ◽

Mendelian Randomization ◽

Meta Analysis ◽

Standard Deviation Increase ◽

Genome Wide ◽

Increased Risk ◽

The Many

Abstract Background Striking changes in the demographic pattern of multiple sclerosis (MS) strongly indicate an influence of modifiable exposures, which lend themselves well to intervention. It is important to pinpoint which of the many environmental, lifestyle, and sociodemographic changes that have occurred over the past decades, such as higher smoking and obesity rates, are responsible. Mendelian randomization (MR) is an elegant tool to overcome limitations inherent to observational studies and leverage human genetics to inform prevention strategies in MS. Methods We use genetic variants from the largest genome-wide association study for smoking phenotypes (initiation: N = 378, heaviness: N = 55, lifetime smoking: N = 126) and body mass index (BMI, N = 656) and apply these as instrumental variables in a two-sample MR analysis to the most recent meta-analysis for MS. We adjust for the genetic correlation between smoking and BMI in a multivariable MR. Results In univariable and multivariable MR, smoking does not have an effect on MS risk nor explains part of the association between BMI and MS risk. In contrast, in both analyses each standard deviation increase in BMI, corresponding to roughly 5 kg/m2 units, confers a 30% increase in MS risk. Conclusion Despite observational studies repeatedly reporting an association between smoking and increased risk for MS, MR analyses on smoking phenotypes and MS risk could not confirm a causal relationship. This is in contrast with BMI, where observational studies and MR agree on a causal contribution. The reasons for the discrepancy between observational studies and our MR study concerning smoking and MS require further investigation.

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