What does ‘leave no one behind’ mean for humanitarian crises-affected populations in the Covid-19 pandemic

Datos Bibliográficos

ID21881365
AutoresLucy Singh (0000-0003-0671-0137, London Women's Clinic, autor de correspondencia), Neha Singh (0000-0003-0057-121X, London School of Hygiene & Tropical Medicine), Behrouz M Nezafat Maldonado (0000-0002-7488-5564, Oxford University Hospitals NHS Trust), Behrouz Nezafat Maldonado (Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK), Sam Tweed (0000-0002-6395-8422, London School of Hygiene & Tropical Medicine), Karl Blanchet (0000-0003-0498-8020, University of Geneva), Warren Graham (0000-0003-1473-5342, London School of Hygiene & Tropical Medicine)
Año2020
Volumen5
Número4
Páginase002540
Fecha de publicación2020-04-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaBMJ Global Health (JOURNAL)
Identificadores de la revistaISSN: 2059-7908 • E-ISSN: 2059-7908
EditorialBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2020-002540
OpenAlexW3016664435
IdiomaEN
Citas recibidas10
Referencias citadas6

Background Risks of hospitalized infections associated with newer biologic agents have not been well characterized in relation to risks with anti-TNF therapy, especially in rheumatoid arthritis (RA) patients with high comorbidity burdens. Objectives To compare the risk of hospitalized infections among RA patients switching from anti-TNF therapy to rituximab (RTX), abatacept (ABA) or another anti-TNF. Methods Using data from 2002-10 from the U.S. Veteran’s Health Administration, we identified a cohort of 38453 RA patients. Eligible patients started RTX, ABA, or anti-TNF therapy after prior exposure to another anti-TNF agent. To minimize confounding from channeling of cancer patients to certain biologics, patients with a history of cancer were excluded to form 2 cohorts: Exclusion for any type of prior cancer using all available data (3257 episodes, 2559 patients) or exclusion only for hematologic cancer in the prior 12 months (3848 episodes, 3018 patients). Baseline characteristics defined in 1 year prior to treatment initiation. Exposure was as-treated based upon days supply (injections) or usual dosing intervals (infusions), with 12 months assumed for RTX exposure. Current exposure was extended by 90 days for all biologics. The outcome was hospitalization with primary diagnosis code for bacterial infection. The hazard ratio (HR, 95% CI) for infection for RTX and ABA vs. anti-TNFs was calculated, adjusting for multiple potential confounders. Results 523 RTX, 366 ABA and 2959 anti-TNF switcher episodes were identified in RA patients without hematologic cancers; 15% of treatment episodes were further excluded with the more restrictive cancer exclusion to form a 2nd cohort. This cohort’s mean overall age was 60.8±10.7 years, 87% male, 25% diabetes, 15% COPD, 3% heart failure, and 66% used glucocorticoids. 2/3rd of the anti-TNF exposure was adalimumab. The most common types of hospitalized infections were pneumonia (36%), skin/soft tissue infections (26%), gastroenteritis (7%) and urinary tract infections (6%). In the less restrictive RA cohort, crude hospitalized infection rates/100person years were RTX: 15.9, ABA: 10.2 and anti-TNF: 12.7. In the less restrictive RA cohort, adjusted HRs for infection were comparable to or lower than for anti-TNF therapy: RTX: 0.85 (0.62-1.12) and ABA: 0.72 (0.50-1.10). In the more restrictive RA cohort, results were similar: adjusted HR for RTX: 0.76 (0.50-1.15) and ABA: 0.58 (0.36-0.93) compared to anti-TNF therapy. Multiple comorbidities and medications were associated with infections (diabetes HR=1.4, 95% CI 1.1-1.7; chronic lung disease HR=1.5, 1.1–1.9; prednisone >7.5mg/day HR=2.1, 1.6-2.7). Conclusions In older, predominantly male, US veterans with RA and high comorbidities, risks of hospitalized bacterial infections for patients treated with RTX or ABA were comparable to or lower than for patients switching to a different anti-TNF therapy (mostly ADA). Ongoing work is characterizing the comparative risks of opportunistic infections. Disclosure of Interest J. Curtis Consultant for: Roche/Genetech, UCB, Centocor CORRONA, Amgen, Pfizer, BMS, Crescendo, Abbott, S. Yang: None Declared, N. Patkar: None Declared, L. Chen: None Declared, J. Singh Grant/Research support from: Takeda, Savient, Consultant for: URL pharmaceuticals, Takeda, Ardea, Savient, Allergan, Novartis, G. Cannon: None Declared, T. Mikuls: None Declared, E. Delzell Grant/Research support from: Amgen, K. Saag Consultant for: Amgen; Lilly; Merck; Novartis; Savient; Ardea; Regeneron; URL, Abbott; DSMB – BioCryst; Roche; Lilly, M. Safford: None Declared, S. Duvall Grant/Research support from: Anolinx, LLC, Genentech, Roche, Amgen, Shire, K. Alexander Employee of: Genetech, P. Napalkov Employee of: Genetech, A. Kamauu Employee of: President- Anolinx LLC, J. Baddley Consultant for: Abbott, Merck

Abatacept · Cancer · Comorbidity · Confidence interval · Confounding · Hazard ratio · Lymphoma · Rheumatoid arthritis · Rituximab · COVID-19 Clinical Research Studies · Medicine · SARS-CoV-2 and COVID-19 Research · Viral Infections and Outbreaks Research · Internal Medicine