\documentclass[10pt]{article}
\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}
\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
linkcolor = blue,
urlcolor = blue,
citecolor = blue,
anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
\errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother
\usepackage{natbib}
\renewenvironment{abstract}
{{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
{\bigskip}
\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}
\usepackage{authblk}
\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%
\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}
\usepackage[utf8]{inputenc}
\usepackage[T2A]{fontenc}
\usepackage[polish,ngerman,english]{babel}
\usepackage{float}
\begin{document}
\title{Fluvoxamine for COVID-19 outpatients: for the time being, we might
prefer to curb our optimism}
\author[1]{Vladimir Trkulja}%
\affil[1]{Department of Pharmacology, School of Medicine, University of Zagreb}%
\vspace{-1em}
\date{\today}
\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup
\sloppy
\textbf{Fluvoxamine for COVID-19 outpatients: for the time being, we
might prefer to curb our optimism}
Vladimir Trkulja
\textbf{Running head} : Fluvoxamin and COVID-19 outpatients
\textbf{Key words} : fluvoxamine, COVID-19, outpatients,
hospitalizations
Vladimir Trkulja, MD, PhD
Department of Pharmacology
Zagreb University School of Medicine
\selectlanguage{polish}Š\selectlanguage{english}alata 11
10000 Zagreb, Croatia
e-mail: vladimir.trkulja@mef.hr
Number of words: 613
Number of figures/tables: 1
To the Editor,
A rather elaborate pharmacodynmics rationale \textsuperscript{1} and
sound pharmacokinetic reasoning \textsuperscript{2} support the use of
fluvoxamin in early phases of the COVID-19 disease. Two recent
meta-analyses, \textsuperscript{3, 4} both based on the same three
randomized placebo-controlled trials, emphasized the benefit of early
fluvoxamine treatment in non-vaccinated adult symptomatic mild COVID-19
outpatients in terms of a reduced risk of disease deterioration over
subsequent days. In the first of the meta-analyzed trials, Stop COVID
1\textsuperscript{5}, primary outcome was hospitalization or incident
hypoxemia needing oxygen treatment within 15 days. The trial was rather
small, particularly for a binary outcome (fluvoxamine 2x100 to 3x100
mg/day over 15 days, n=80; placebo n=72) and recorded only 6 events (all
with placebo) \textsuperscript{5}. Stop COVID 2
\textsuperscript{6}followed the same design/outcome, and was stopped at
an advanced stage for operational reasons but did not indicate any
benefit {[}incidence 11/272 (4.0\%) fluvoxamin vs. 12/275 (4.4\%)
placebo){]}. The meta-analytical pooled estimates \textsuperscript{3, 4}
were dominated by the results of the TOGETHER trial \textsuperscript{7}
(fluvoxamine 2x100 mg/day, 10 days) that reported a marked relative
reduction in the risk of the primary outcome (emergency room stay of at
least 6 hours or hospitalization; over 28 days): 79/741 (11.0\%) vs.
119/756 (16.0\%), RR=0.69 (95\% CrI 0.53-0.90) \textsuperscript{7}. By
far the most events were hospitalizations, but no clear-cut benefit was
obvious in this respect {[}75/741 (10.0\%) vs. 97/756 (13.0\%), OR=0.77
(0.55-1.05)\textsuperscript{7}{]}. The meta-analysis by Lee et
al.\textsuperscript{3} focused on hospitalizations and reported a 25\%
relative risk reduction by a frequentist method (RR=0.75, 95\%CI
0.58-0.97), while the Bayesian analysis (weakly informative neutral
prior) indicated somewhat more uncertainty (RR=0.78, 95\%CrI 0.58-1.08;
81.6\% probability of RR [?]0.90) \textsuperscript{3}. Guo et
al.\textsuperscript{4} employed only frequentist pooling to indicate a
marked benefit regarding ``study-defined outcomes'' (RR=0.69 95\%CI
0.54-0.88) and somewhat more uncertainty regarding ``hospitalizations''
(RR=0.79, 95\%CI 0.60-1.03) \textsuperscript{4}. In the meantime, a
report was pubslihed of a randomized placebo-controlled trial conducted
in 2020 in Korean outpatients (~10 days of fluvoxamine 2x100
mg/day)\textsuperscript{8}. It was stopped early for operational
reasons\textsuperscript{8}, and the primary outcome (as in Stop COVID
trials) was observed in 2/26 treated and 2/26 placebo
patients\textsuperscript{8}. Figure 1 depicts meta-analysis of
``study-defined primary outcomes'' and of ``hospitalizations'' that uses
the same frequentist and Bayesian methodology as used by Lee et
al.\textsuperscript{3} except that (i) it includes the Korean
data\textsuperscript{8} and (ii) employs Hartung-Knapp-Sidik-Jonkman
correction shown to yield the least biased confidence interval coverage
with small number of trials considerably varying in
size\textsuperscript{9}: (a) uncertainty about the benefit regarding
``study-defined outcomes'' (Figure 1A) is indicated by both the
frequentist and Bayesian intervals extending to \textgreater{}1.0 and
prediction intervals extending well \textgreater{}1.0. Probability of at
least 10\% relative risk reduction is 90.0\%; (b) uncertainty about the
benefit regarding ``hospitalizations'' (Figure 1B) is even more obvious,
with estimate intervals exceding \textgreater{}1.10 (and further
extended predictions intervals), with only 73.8\% probability of at
least 10\% relative risk reduction. If one were to disregard two small
trials with a few events (and, hence, fragile estimates that could have
been by chance, at least in part) \textsuperscript{5, 8}, for the time
being one would be looking at Stop COVID 2 and TOGETHER trial. This
means 86/1013 hospitalization events with fluvoxamine vs. 109/1031
events with placebo, and a considerable uncertainty about any
practically relevant effect: (i) frequentist RR=0.803 (95\%CI
0.422-1.530); (ii) Bayesian RR=0.840 (95\%CrI 0.613-1.170) and only
67.4\% probablity of at least 10\% relative risk reduction. Hopefully,
the on-going trials (depicted in ref. 3) will resolve this uncertainty,
but presently we might prefer to be cautios rather than overtly
optimistic about the actual extent of benefit conveyed by early
fluvoxamine treatment in COVID-19 outpatients.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}
\end{center}
\end{figure}
\textbf{Figure 1} . Meta-analysis of placebo-controlled randomized
trials of fluvoxamine (2x100 or 3x100 mg/day over 10 to 15 days) in
adult, non-vaccinated symptomatic mild COVID-19 outpatients evaluating
the effects on disease progression. Implemented are frequentist and
Bayesian random-effects pooling methods used also in the meta-analysis
by Lee et al. \textsuperscript{3} {[}restricted maximum likelihood
estimator of across study variance in the frequentist analysis, and
weakly informative neutral prior for the effect -- 0 for ln(RR) and
0.355 for its standard deviation -- and half-cauchy with scale 0.10 for
the heterogeneity parameter{]}. The differences vs. the published
meta-analyses \textsuperscript{3, 4} are in that: (i) it includes data
from the Korean trial (Seo et al. \textsuperscript{8}) and (ii) uses
Hartung-Knapp-Sidik-Jonkman correction to calculated frequentist
confidence intervals, as recommended \textsuperscript{9}.
\textbf{A.}Meta-analysis of study-defined primary outcomes (explained in
the text). Data for Stop COVID 1 \textsuperscript{5}, TOGETHER
\textsuperscript{7}and the Korean trial (Seo et al. \textsuperscript{8})
are taken from the respective publications. Data for Stop COVID 2 are
not publicly available and were taken from the meta-analysis by Lee et
al.\textsuperscript{3}. \textbf{B} . Meta-analysis of hospitalizations.
Data for TOGETHER trial \textsuperscript{7} and the Korean
trial\textsuperscript{8} are taken from the respective publications.
Data for Stop COVID 1 and 2 trials are taken from the meta-analysis by
Lee et al.\textsuperscript{3} -- the principal investigator of the Stop
COVID trials is one of the co-authors, hence data should be considered
accurrate.
Bayesian analysis was performed using package
\emph{bayesmeta}\textsuperscript{10} in R (as in the published
meta-analysis\textsuperscript{3}), frequentist analysis was performed
using package\emph{meta} (11) in R.
\textbf{Conflict of interest statement}
The author has no conflict of interest to declare.
References
\begin{enumerate}
\tightlist
\item
Sukhatme VP, Reiersen AM, Vayttaden SJ, Sukhatme VV. Fluvoxiamine: a
review of its mechanism of action and its role in
COVID-19.\emph{Frontiers Pharmacol} . 2021; 12:652688. Doi:
10.3389/fphar.2021.652688
\item
Dodds MG, Doyle EB, Reiersen AM, Brown F, Rayner CR. Fluvoxamine for
the treatment of COVID-19. \emph{Lancet Glob Health} . 2022;
10(3):e332. Doi: 10.1016/S2214-109X(22)00006-7.
\item
Lee TC, Vigod S, Bortolussi-COurval E, Hanula R, Boulware DR, Lenze
EJ, Reiersen AM, McDonald EG. Fluvoxamine for outpatient management of
COVID-19 to prevent hospitalization. A systematic review and
meta-analysis. \emph{JAMA Network Open.} 2022; 5(4):e226269.
Doi:10.1001/jamanetworkopen.2022.6269
\item
Guo CM, Harari O, Chernecki C, THorlund K, Forrest JI. Fluvoxamine for
the early treatment of COVID-19: a meta-analysis of randomized
clinical trials. \emph{Am J Trop Med Hyg} . 2022; 106(5):1315-1320.
\item
Lenze EJ, Mattar C, Zorumski CF, Stevens A, Schweiger J, Nicol GE,
Miller JP, Yang L, Yingling M, Avidan MS, Reiersen AM. Fluvoxamine vs
placebo and clinical deterioration in outpatients with symptomatic
COVID-19. \emph{JAMA} . 2020; 324(22):2292-2300.
\item
Lenze E. Fluvoxamine for early treatment of COVID-19: a fully-remote,
randomized placebo controlled trial. \emph{ClinicalTrials.gov} .
Accessed May 26, 2022. https://clinicaltrials.gov/ct2/show/NCT04668950
\item
Reis G, dos Santos Moreira-Silva EA, Medeiros Silva DC, Thabane L,
Cruz Milagres A, Santiago Ferreira T, Quirino dos Santos CV et al.
Effect of early treatment with fluvoxamine on risk of emergeny care
and hospitalizations among patients with COVID-19: the TOGETHER
randomized platform trial. \emph{Lancet Glob Health} . 2022; 10:
e42-51.
\item
Seo H, Kim H, Bae S, Park S, Chung H, Sung H, Jung J et al.
Fluvoxamine treatment of patients with symptomatic COVID-19 in a
community treatment center: a preliminary result of randomized
controlled trial. \emph{Infect Chemother} . 2022; 54(1):102-113.
\item
Langan D, Higgins JPT, Jakson D, Bowden J. Veroniki AA, Kontopantelis
E, Viechtbauer W, Simmonds M. A comparison of heterogeneity variance
estimators in simulated random-effects meta-analyses. \emph{Res Synth
Methods} . 2019; 10(1):83-98.
\item
R\selectlanguage{ngerman}över C. Bayesian random-effects meta-analysis using the bayesmeta R
Package. \emph{J Stat Softw} . 2020;1(6). doi:10. 18637/jss.v093.i06
\item
Balduzzi S, Rucker G, Schwarzer G. How to perform a meta-analysis with
R: a practical tutorial. \emph{Evid Based Ment Health} . 2019;
22(4):153-160.
\end{enumerate}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Trkulja-HiResFig01/Trkulja-HiResFig01}
\end{center}
\end{figure}
\selectlanguage{english}
\FloatBarrier
\end{document}