Background Various observations have suggested that the course of COVID-19 might be less favourable in patients with inflammatory rheumatic and musculoskeletal diseases receiving rituximab compared with those not receiving rituximab. We aimed to investigate whether treatment with rituximab is associated with severe COVID-19 outcomes in patients with inflammatory rheumatic and musculoskeletal diseases.Methods In this cohort study, we analysed data from the French RMD COVID-19 cohort, which included patients aged 18 years or older with inflammatory rheumatic and musculoskeletal diseases and highly suspected or confirmed COVID-19. The primary endpoint was the severity of COVID-19 in patients treated with rituximab (rituximab group) compared with patients who did not receive rituximab (no rituximab group). Severe disease was defined as that requiring admission to an intensive care unit or leading to death. Secondary objectives were to analyse deaths and duration of hospital stay. The inverse probability of treatment weighting propensity score method was used to adjust for potential confounding factors (age, sex, arterial hypertension, diabetes, smoking status, body-mass index, interstitial lung disease, cardiovascular diseases, cancer, corticosteroid use, chronic renal failure, and the underlying disease [rheumatoid arthritis vs others]). Odds ratios and hazard ratios and their 95% CIs were calculated as effect size, by dividing the two population mean differences by their SD. This study is registered with ClinicalTrials.gov, NCT04353609.

Introduction We compared histological and clinical profiles of primary Sjögren syndrome (pSS) small fiber neuropathy (SFN; pSS‐SFN) with idiopathic SFN (i‐SFN) and hereditary transthyretin amyloidosis SFN (hATTR‐SFN) and described the evolution of pSS‐SFN. Methods All patients with pSS‐SFN, i‐SFN, and hATTR‐SFN confirmed by reduced intraepidermal nerve fiber density on skin biopsy were retrospectively included, and their characteristics were compared. To analyze prognosis of pSS‐SFN, patients prospectively underwent a second evaluation. Results Fifteen pSS‐SFN, 17 hATTR‐SFN, and 11 i‐SFN were included. Time to diagnosis SFN was longer in pSS‐SFN and i‐SFN than in hATTR‐SFN. Painful and non–length‐dependent patterns were more frequent in pSS‐SFN than in hATTR‐SFN. Twelve (80%) patients with pSS‐SFN had a non–length‐dependent pattern. Ten patients with pSS were reassessed after 3.1 years (1.7–4.7); none developed large fiber neuropathy linked to pSS. Discussion Primary Sjögren syndrome SFN is characterized by a more frequent non–length‐dependent pattern compared with i‐SFN and hATTR‐SFN. Primary Sjögren syndrome SFN did not evolve through large fiber neuropathy.

ObjectivesThe French E3N-EPIC (Etude Epidémiologique auprès des femmes de la Mutuelle générale de l’Education Nationale-European Prospective Investigation into Cancer and Nutrition) cohort enrolled 98 995 women aged 40 to 65 years at inclusion since 1990 to study the main risk factors for cancer and severe chronic conditions in women. They were prospectively followed with biennially self-administered questionnaires collecting self-reported medical, environmental and lifestyle data. Our objective was to assess the accuracy of self-reported diagnoses of rheumatoid arthritis (RA) and to devise algorithms to improve the ascertainment of RA cases in our cohort.DesignA validation study.ParticipantsWomen who self-reported an inflammatory rheumatic disease (IRD) were asked to provide access to their medical record, and to answer an IRD questionnaire. Medical records were independently reviewed.Primary and secondary outcome measuresPositive predictive values (PPV) of self-reported RA alone, then coupled with the IRD questionnaire, and with a medication reimbursement database were assessed. These algorithms were then applied to the whole cohort to ascertain RA cases.ResultsOf the 98 995 participants, 2692 self-reported RA. Medical records were available for a sample of 399 participants, including 305 who self-reported RA. Self-reported RA was accurate only for 42% participants. Combining self-reported diagnoses to answers to a specific IRD questionnaire or to the medication reimbursement database improved the PPV (75.6% and 90.1%, respectively). Using the devised algorithms, we could identify 964 RA cases in our cohort.ConclusionAccuracy of self-reported RA is poor but adding answers to a specific questionnaire or data from a medication reimbursement database performed satisfactorily to identify RA cases in our cohort. It will subsequently allow investigating many potential risk factors of RA in women.