COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients
et al., PLoS ONE, doi:10.1371/journal.pone.0248128
, COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without.., PLoS ONE, doi:10.1371/journal.pone.0248128
Collection of seven retrospective database analyses in the USA, showing higher mortality with treatment (not statistically significant).Results contradict strong evidence from the RECOVERY/SOLIDARITY trials, suggesting substantial confounding by indication.Time based confounding is very likely because HCQ became highly controversial and usage dramatically declined over the time covered, while overall treatment protocols during this period improved dramatically, i.e., more control patients likely come later in the period when treatment protocols were greatly improved.This study includes anyone PCR+ during or prior to their visit, and anyone with ICD-10 COVID-19 codes which includes asymptomatic PCR+ patients, therefore some patients in the control groups may be asymptomatic with regards to SARS-CoV-2, but in the hospital for another reason.Authors do not mention the possibility of any of these likely confounding factors.
This study is excluded in the after exclusion results of meta
analysis:
substantial unadjusted confounding by indication likely; substantial confounding by time likely due to declining usage over the early stages of the pandemic when overall treatment protocols improved dramatically; includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons.
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risk of death, 18.0% higher, RR 1.18, p = 0.27, treatment 90 of 429 (21.0%), control 141 of 737 (19.1%), adjusted per study, VA, HCQ+AZ.
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risk of death, 1.0% lower, RR 0.99, p = 0.95, treatment 66 of 578 (11.4%), control 188 of 1,243 (15.1%), adjusted per study, TriNetX, HCQ+AZ.
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risk of death, 129.9% higher, RR 2.30, p < 0.001, treatment 32 of 108 (29.6%), control 33 of 256 (12.9%), Synapse, HCQ+AZ.
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risk of death, 9.0% higher, RR 1.09, p = 0.65, treatment 212 of 1,157 (18.3%), control 203 of 1,101 (18.4%), NNT 873, adjusted per study, Health Catalyst, HCQ+AZ.
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risk of death, 90.0% higher, RR 1.90, p = 0.09, treatment 46 of 208 (22.1%), control 47 of 1,334 (3.5%), adjusted per study, Dascena, HCQ+AZ.
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risk of death, 16.0% higher, RR 1.16, p = 0.26, treatment 428 of 1,711 (25.0%), control 123 of 688 (17.9%), adjusted per study, COTA/HMH, HCQ+AZ.
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risk of mechanical ventilation, 29.0% higher, RR 1.29, p = 0.09, treatment 48 of 305 (15.7%), control 95 of 1,302 (7.3%), adjusted per study, Aetion, HCQ.
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| Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates |
Stewart et al., 17 Mar 2021, retrospective, USA, peer-reviewed, 37 authors.
Abstract: PLOS ONE
RESEARCH ARTICLE
COVID-19 Evidence Accelerator: A parallel
analysis to describe the use of
Hydroxychloroquine with or without
Azithromycin among hospitalized COVID-19
patients
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OPEN ACCESS
Citation: Stewart M, Rodriguez-Watson C,
Albayrak A, Asubonteng J, Belli A, Brown T, et al.
(2021) COVID-19 Evidence Accelerator: A parallel
analysis to describe the use of Hydroxychloroquine
with or without Azithromycin among hospitalized
COVID-19 patients. PLoS ONE 16(3): e0248128.
https://doi.org/10.1371/journal.pone.0248128
Editor: Francesco Di Gennaro, National Institute for
Infectious Diseases Lazzaro Spallanzani-IRCCS,
ITALY
Received: December 10, 2020
Accepted: February 20, 2021
Published: March 17, 2021
Copyright: This is an open access article, free of all
copyright, and may be freely reproduced,
distributed, transmitted, modified, built upon, or
otherwise used by anyone for any lawful purpose.
The work is made available under the Creative
Commons CC0 public domain dedication.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: Health catalyst provided support for this
study in the form of salary for AA, EE, AG, and JJ.
Gilead Sciences provided support for this study in
the form of salary for JA and RM. COTA, Inc
provided support for this study in the form of
salary for AB, EH, and SG. Sypase provided
Mark Stewart1‡, Carla Rodriguez-Watson2‡, Adem Albayrak ID3☯, Julius Asubonteng ID4☯,
Andrew Belli5☯, Thomas Brown6☯, Kelly Cho7,8☯, Ritankar Das9☯, Elizabeth Eldridge3☯,
Nicolle Gatto10☯, Alice Gelman3☯, Hanna Gerlovin ID7☯, Stuart L. Goldberg11☯,
Eric Hansen5☯, Jonathan Hirsch6☯, Yuk-Lam Ho7☯, Andrew Ip ID11☯, Monika Izano ID6☯,
Jason Jones3☯, Amy C. Justice12,13☯, Reyna Klesh ID14☯, Seth Kuranz15☯, Carson Lam9☯,
Qingqing Mao ID9☯, Samson Mataraso ID9☯, Robertino Mera4☯, Daniel C. Posner7☯, Jeremy
A. Rassen ID10☯, Anna Siefkas9☯, Andrew Schrag6☯, Georgia Tourassi16☯,
Andrew Weckstein ID10☯, Frank Wolf6☯, Amar Bhat2☯, Susan Winckler2☯, Ellen V. Sigal1,2☯,
Jeff Allen1*
1 Friends of Cancer Research, Washington, District of Columbia, United States of America, 2 Reagan-Udall
Foundation for the FDA, Washington, District of Columbia, United States of America, 3 Health Catalyst, Salt
Lake City, Utah, United States of America, 4 Gilead Science, Inc. Foster City, California, United States of
America, 5 COTA, Inc., Boston, Massachusetts, United States of America, 6 Syapse, San Francisco,
California, United States of America, 7 Massachusetts Veterans Epidemiology Research and Information
Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America,
8 Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston,
Massachusetts, United States of America, 9 Dascena, Oakland, California, United States of America,
10 Aetion, New York, New York, United States of America, 11 Division of Outcomes and Value Research,
John Theurer Cancer Center at Hackensack University Medical Center, Hackensack, New Jersey, United
States of America, 12 VA Connecticut Healthcare System, West Haven, Connecticut, United States of
America, 13 Yale University Schools of Medicine and Public Health, New Haven, Connecticut, United States
of America, 14 HealthVerity, Philadelphia, Pennsylvania, United States of America, 15 TriNetX, Cambridge,
Massachusetts, United States of America, 16 National Center..
Late treatment
is less effective
is less effective
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