\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[greek,ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{Fetal and maternal outcomes after maternal biologic use during
conception and pregnancy: a systematic review and meta-analysis.}



\author[1]{Laura O'Byrne}%
\author[2]{Safi Alqatari}%
\author[3]{Gillian Maher}%
\author[2]{Aoife  O'Sullivan}%
\author[4]{Ali Khashan}%
\author[2]{Grainne Murphy}%
\author[5]{Fergus Mccarthy}%
\affil[1]{Affiliation not available}%
\affil[2]{Cork University Hospital}%
\affil[3]{INFANT Centre}%
\affil[4]{University College Cork}%
\affil[5]{University College Cork and Kings College London}%


\vspace{-1em}



  
  \date{June 09, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Background: Biologic medications, specifically the TNF-\selectlanguage{greek}α \selectlanguage{english}inhibitors,
have become increasingly prevalent in the treatment of chronic
inflammatory disease (CID) in pregnancy. Objective: To determine
pregnancy outcomes in women with CID exposed to biologics during
pregnancy. Search strategy: PubMed and EMBASE databases were searched
through January 1998-July 2021. Selection criteria: Peer reviewed,
English language cohort, case-control, cross-sectional studies, and case
series which contained original data. Data collection and analysis: Two
authors independently conducted data extraction and assessed study
quality. A meta-analysis of proportions using a random-effects model was
used to pool outcomes. Linear regression analysis was used to compare
the mean of proportions of outcomes across exposure groups using the
`treated' group as the reference category. All studies were evaluated
using an appropriate quality assessment tool described by McDonald et
al. Main Results: 35 studies, 11172 pregnancies, were eligible for
inclusion. Analysis showed pooled proportions for congenital
malformations: treated 4\%(95\% CI 0.03-0.4) vs disease matched
4\%(0.03-0.05).Preterm delivery treated 12\%(0.10-0.14) vs disease
matched 10\%(0.09-0.12) Severe neonatal infection: treated
5\%(0.03-0.07) vs disease matched 5\%(0.02-0.07) Low birth weight:
treated 10\%(0.07-0.12) vs disease matched 8\%(0.07-0.09) The pooled
Miscarriage: treated 13\%(0.10-0.15) vs disease matched 8\%(0.04-0.11)
Pre-eclampsia; treated 1\%(0.01-0.02) vs disease matched 1\%(0.00-0.01).
No statistical differences in proportions were observed. Conclusion: We
demonstrated comparable pregnancy outcomes in pregnancies exposed to
biologics, disease matched controls and CID free pregnancies. Overall,
women receiving biologics in pregnancy may be reassured regarding their
safety.%
\end{abstract}%



\sloppy


\textbf{Fetal and maternal outcomes after maternal biologic use during
conception and pregnancy: a systematic review and meta-analysis.}

Dr Laura J O'BYRNE MBBS MSc\textsuperscript{1,2}, Dr Safi G ALQATARI
MBBS\textsuperscript{3}, Dr Gillian M MAHER PhD \textsuperscript{1,4},
Dr Aoife M O'SULLIVAN MB BAO BCh\textsuperscript{3}, Dr Ali S KHASHAN
PhD \textsuperscript{1,4}, Dr Grainne P MURPHY MD*\textsuperscript{3},
Dr Fergus P MCCARTHY PhD *\textsuperscript{1,2}

1 INFANT Research Centre, University College Cork, Cork, Ireland.

2 Department of Obstetrics and Gynaecology, Cork University Maternity
Hospital, Cork Ireland

3 Department of Rheumatology, Cork University Hospital, Cork, Ireland

4 School of Public Health, Western Gateway Building, University College
Cork, Cork, Ireland.

*Contributed equally.

\emph{Conflicts of Interest:} The authors report no conflicts of
interest.

\emph{Source of Funding:} This project was~funded~via an education
bursary awarded to Dr Grainne Murphy by UCB pharma. The funder had no
role in the design, analysis or interpretation of the research and
manuscript and had no part in the research process following~funding.

\emph{Correspondence:} Laura O'Byrne, Department of Obstetrics and
Gynaecology, 5\textsuperscript{th} Floor, Cork University Maternity
Hospital, Wilton, Cork, Ireland.

E-Mail: lobyrne@ucc.ie

\textbf{Running title: Biologics in pregnancy}

\textbf{Abstract}

\textbf{Background:} Biologic medications, specifically the TNF-\selectlanguage{greek}α
\selectlanguage{english}inhibitors, have become increasingly prevalent in the treatment of
chronic inflammatory disease (CID) in pregnancy.

\textbf{Objective:} To determine pregnancy outcomes in women with CID
exposed to biologics during pregnancy.

\textbf{Search strategy:} PubMed and EMBASE databases were searched
through January 1998-July 2021.

\textbf{Selection criteria:} Peer reviewed, English language cohort,
case-control, cross-sectional studies, and case series which contained
original data.

\textbf{Data collection and analysis:} Two authors independently
conducted data extraction and assessed study quality.~ A meta-analysis
of proportions using a random-effects model was used to pool outcomes.
Linear regression analysis was used to compare the mean of proportions
of outcomes across exposure groups using the `treated' group as the
reference category.~~All studies were evaluated using an appropriate
quality assessment tool described by McDonald et al.

\textbf{Main Results:} 35 studies, 11172 pregnancies, were eligible for
inclusion. Analysis showed pooled proportions for congenital
malformations: treated 4\%(95\% CI 0.03-0.4) vs disease matched
4\%(0.03-0.05).Preterm delivery treated 12\%(0.10-0.14) vs disease
matched 10\%(0.09-0.12) Severe neonatal infection: treated
5\%(0.03-0.07) vs disease matched 5\%(0.02-0.07) Low birth weight:
treated 10\%(0.07-0.12) vs disease matched 8\%(0.07-0.09) The pooled
Miscarriage: treated 13\%(0.10-0.15) vs disease matched 8\%(0.04-0.11)
Pre-eclampsia; treated 1\%(0.01-0.02) vs disease matched 1\%(0.00-0.01).
No statistical differences in proportions were observed.

\textbf{Conclusion:} We demonstrated comparable pregnancy outcomes in
pregnancies exposed to biologics, disease matched controls and CID free
pregnancies. Overall, women receiving biologics in pregnancy may be
reassured regarding their safety.

\textbf{Tweetable Abstract:}

Meta-analysis of 11172 pregnancies exposed to biologics shows these
medications are predominantly safe for the fetus and mother.

\textbf{Main Text}

\textbf{Introduction:}

Chronic inflammatory diseases (CIDs) are a group of autoimmune diseases
which affect between 5-7\% of the population and include rheumatoid
arthritis (RA), psoriatic arthritis and inflammatory bowel disease
(IBD).\textsuperscript{1,2} Many CIDs have a female preponderance and
are often associated with activity during reproductive
years.\textsuperscript{3--5} They share a similar pathophysiology
centring on dysregulation of the systemic immune response mediated by
cytokines including tumour necrosis factor (TNF), interleukin 1 (IL-1),
and interleukin 6 (IL-6) which are known to affect pregnancy and
embryogenesis.\textsuperscript{6,7} Modulation of these cytokines with
the introduction of biologic agents over two decades ago was a
revolution in the care for these patients and are increasingly used to
manage chronic autoimmune diseases during pregnancy.

CID activity is inherently associated with an increased risk of a range
of adverse pregnancy outcomes.\textsuperscript{8--10} Women with active
IBD during pregnancy have higher rates of miscarriage, preterm delivery,
low birth weight, congenital anomalies and Caesarean section compared to
a general population.\textsuperscript{8} Likewise, there is a strong
correlation with activity in RA and adverse outcomes such as
miscarriage, low birth weight, pre-eclampsia and Caesarean
section.\textsuperscript{9} Disease flares are associated with a greater
magnitude of risk for both women and their pregnancy with balancing the
risk of disease flare with fears regarding adverse effects of biologic
medications.\textsuperscript{10}

Randomised control trials on biologic medications during pregnancy are
lacking and the majority of data regarding safety in pregnancy arises
from case series, population data review and cohort studies. One of the
most recent meta-analysis by Tsao et al\textsuperscript{11} focused
solely on studies that had a disease matched control group thus limiting
their review to 24 studies including 10 published as abstracts only. The
other most recent meta-analysis by Komaki et al included 13 studies and
compared outcomes in the treatment group to the general population only,
with no disease matched cohort included.\textsuperscript{12}

The primary aim of this systematic review and meta-analysis was to
examine a range of maternal and neonatal adverse pregnancy outcomes in
pregnant women exposed to biologics for the management of underlying CID
compared with disease matched cohorts and women without CID.

\textbf{Methods}

This review was performed according to an \emph{a-priori} -designed
protocol recommended for systematic reviews and
meta-analysis.\textsuperscript{13} Maternal and fetal systematic review
protocols were prospectively registered on PROSPERO CRD4201707072 and
CRD42020185926. The systematic review was based on the following PICO
requirements; Population: Pregnant women with a diagnosis of CID.
Intervention/Exposure: Treatment with Biologic medication. Comparison:
Pregnant women with a diagnosis of CID without treatment with biologics
and a CID free population. Outcomes: fetal outcomes included congenital
malformations, preterm delivery, severe neonatal infection, low birth
weight and small for gestational age. Maternal outcomes included severe
maternal infection, miscarriage and pre-eclampsia.

\textbf{Search methodology}

The search strategy was developed with librarian assistance and was
carried out through PubMed and EMBASE search engines to identify peer
reviewed published papers relating to the association between biologics
use for CID in pregnancy and the risk of maternal and neonatal outcomes.
Searches were conducted in accordance with the PRISMA guidelines
(Preferred Reporting Items for Systematic Review and
Meta-analysis).\textsuperscript{14} PubMed and EMBASE searches were
conducted through January 1998 - April 2020 by two reviewers (LOB, SA),
and updated again July 2021. Full search terms can be found in the
Appendix. Bibliographies of included studies were also searched for
additional studies eligible for inclusion. Titles and abstracts of
studies retrieved from each database were stored and managed in Endnote
reference manager. Three review authors (LOB, SA, AOS) reviewed titles
and abstracts, obtaining full text as required.

\textbf{Study Inclusion and exclusion criteria}

English language cohort, case-control, cross-sectional studies and case
series with a minimum n=30 were eligible for inclusion. Studies must
have been peer-reviewed and contain original data. A diagnosis of a CID
requiring treatment with biologics had to be described for women treated
during pregnancy/or the three months prior to pregnancy (as early
cessation of these medications is common).

Ineligible studies were those who did not specify maternal underlying
medical condition or a condition that was not a chronic inflammatory
disease e.g.: neoplasia. Studies that were not published in English,
those that did not address maternal or fetal outcomes, non-peer reviewed
studies, commentaries, reviews, and conference abstracts were excluded.

\textbf{Data extraction}

Three reviewers (LOB, SA, AOS) independently extracted data using a
standardised collection form for all eligible studies, including study
characteristics and reported outcomes for analysis. Where multiple
publications using the same data existed, we included the most recent
study, provided the earlier publication did not contain reported
information not available in the most recent study. In studies in which
adequate data was not reported, an effort was made to contact authors to
provide us with additional information to allow us to compute effect
estimates. Risk of bias assessment was undertaken by three reviewers
(LOB, SA, AOS) using an appropriate quality assessment tool described by
McDonald et al\textsuperscript{15}, with all included studies classified
as low to moderate risk of bias.

\textbf{Statistical analysis}

Where data permitted, Stata 14 was used to conduct meta-analyses of
proportions using a random-effects model. We analysed the available data
from three main population groups. The `treated' group were women with
CID who required treatment with biologic medications throughout their
pregnancy. The `disease matched' group were the group of women with CID
not prescribed biologics in pregnancy. The `disease free' group was a
group representative of the general population, (i.e. women who were
pregnant and did not have a diagnosis of CID). We modelled data using
the program \emph{metaprop} which augments the metan program. This
allowed for computation of 95\% confidence
intervals\textsuperscript{16}and pooling of proportions, presenting a
weighted sub-group and overall pooled estimates with inverse-variance
weights from a random effects model. The primary analysis was performed
on all eligible studies, with subgroup analyses by biologic type and by
chronic inflammatory disease subtype where appropriate. We used linear
regression analysis to compare the mean of proportions of outcomes
across exposure groups using the `treated' group as the reference
category.

\textbf{Results}

The search for fetal outcomes produced 1887 titles, after exclusion for
duplicates and ineligible studies, 35 studies were eligible and 33 were
included in the meta-analysis (Figure S1). The initial search for
maternal outcomes produced 2104 results after exclusion for duplicates
and ineligible studies, 34 were suitable for inclusion and 25 studies
were included in the maternal outcome meta-analysis (Figure S2).

Overall, there were 35 individual observational studies included in the
meta-analysis, 24 cohort studies and 11 case series fulfilling the
inclusion criteria. This review contains a total of 11172 pregnancies
exposed to biologics, 39290 disease matched controls and 2892933 chronic
inflammatory disease free pregnancies used for the meta-analysis. The
addition of the peer reviewed case series added 2653 women exposed to
biologics in this meta-analysis.

\textbf{Congenital malformations}

There were 28 eligible studies in the congenital malformation
meta-analysis. There were 1288762 infants in this cohort, (7811 born to
women using biologics in pregnancy, 29171 infants born to women with CID
who were not treated with biologics in pregnancy and 1251780 infants
born to women who were CID free) (Table 1). The proportion of congenital
malformations in the treated group was 4\% (95\% CI 0.03-0.04), the
disease matched group was 4\% (0.03 to 0.05) and the disease free group
4\% (0.03 to 0.05). No differences were observed in proportions between
disease matched compared with disease treated women (p=0.238, nor in
disease free compared with disease treated women (p=0.579 Figure 1 and
Table S1).

Sub analysis by chronic inflammatory disease type did not significantly
change results. Those women with IBD treated with biologics had a
proportion of congenital malformations of 4\% (95\% CI 0.02 to 0.05)
compared to CID overall having 4\% (0.02 to 0.06) and RA alone of 4\%
(0.02 to 0.05) (Figure S5).

\textbf{Preterm delivery}

There were 26 studies included in the preterm birth (PTB) meta-analysis.
This included 7728 pregnancies exposed to biologics and 18574 disease
matched controls (Table 1). The proportion of PTB in the treated group
was 12\% (95\% CI 0.10 to 0.14), 10\% (0.09 to 0.012) in the disease
matched and 6\% (0.04 to 0.07) in the disease free group (Figure S4).
There was no statistical difference in the treated group vs the disease
matched group (p=0.250), there was a statistical difference when
comparing disease free with disease treated women (p= 0.008 Table S1).

Subgroup analysis examining anti-TNF-\selectlanguage{greek}α \selectlanguage{english}only revealed a change in the PTB
rate for the treated group to 11\% (95\% CI 0.09 to 0.13) (Figure 2).
Subgroup analysis by disease classification showed anti-TNF-\selectlanguage{greek}α \selectlanguage{english}treated
IBD had a PTB rate of 9\% (0.07 to 0.11) with the disease matched IBD
group having a PTB rate of 9\% (0.08 to 0.010) (Figure S5). Only one
study focused on anti-TNF-\selectlanguage{greek}α \selectlanguage{english}use and RA\textsuperscript{17} with a
treated PTB rate of 18\% (0.14 to 0.24) and disease matched of 14\%
(0.12 to 0.15). The remaining studies focused on mixed CID with a
preterm birth rate of 12\% (0.09 to 0.15).

\textbf{Neonatal infection}

The pooled data on severe neonatal infection included 9 studies with
22368 neonates. This was divided into 7569 neonates born to women with
CID, 3554 neonates born to women requiring biologics treatment during
pregnancy and 4015 disease matched controls (Table 1).

The proportion of severe neonatal infections requiring hospitalisations
in the treated group was 5\% (95\% CI 0.03 to 0.07), the proportion in
the disease matched group was 5\% (0.02 to 0.07) and the disease free
was 2\% (0.02 to 0.02) (Figure S6). No differences were observed in
proportions between disease matched compared with disease treated women
(p=0.970), nor in disease free compared with disease treated women
comparison (p=0.225; Table S1).~ Subgroup analysis by disease diagnosis
revealed no statistical difference between groups (results not shown).

\textbf{Birth weight}

We examined both small for gestational age (SGA) and low birth weight
(LBW) because reports on biologics use during pregnancy and neonatal
birth weight varied. LBW was defined as less than 2.5kg at birth
regardless of gestation while SGA was defined as
\textless{}10\textsuperscript{th} centile for weight at birth by
gestation. In the LBW group there were 17 studies included with a total
of 11474 infants, 5112 exposed to maternal biologic use, 3046 disease
matched and 3316 CID free pregnancies (Table 1).

The overall proportion of LBW in the treated group was 10\% (95\% CI
0.07 to 0.12) the disease matched 8\% (0.07 to 0.09) and the disease
free group 4\% (0.01 to 0.08) (Figure S7). No statistical differences
were observed between disease matched and disease treated women
(p=0.241), nor in disease free (p=0.079; Table S1).~ Sub group analysis
on anti-TNF-\selectlanguage{greek}α \selectlanguage{english}use alone revealed no difference between groups outcomes
(results not shown).

The SGA group included seven studies with 1638595 infants, 3342 born to
women medicated with biologics during pregnancy and 10720 disease
matched controls(Table 1). All of the SGA studies focused on anti-TNF-\selectlanguage{greek}α
\selectlanguage{english}biologics only. The proportion of SGA in the treated group was 6\% (95\%
CI 0.02 to 0.10), the disease matched control 7\% (0.02 to 0.11) and the
disease free population 10\% (0.10 to 0.10) (Figure S8). No differences
were observed in proportions between disease matched compared with
disease treated women (p=0.753), nor in comparison with disease free
(p=0.170; Table S1).

\textbf{Maternal infection}

The data available on maternal serious infection requiring
hospitalisation included two studies both of which focused on anti-TNF-\selectlanguage{greek}α
\selectlanguage{english}use in pregnancy. There was a total of 1685 pregnant women in this
cohort.\textsuperscript{18,19} There were 916 women who were treated
with biologics during their pregnancy (Table 2) and 453 disease matched
control. The studies included in this analysis were
Chaparro\textsuperscript{19} who focused on anti-TNF-\selectlanguage{greek}α \selectlanguage{english}use in IBD and
pregnancy and Clowse\textsuperscript{18} on certolizumab pegol use in
CID in pregnancy.

Overall the pooled analysis showed that the treated group had a
proportion of serious infection of 4\% (95\% CI 0.03 to 0.05), while the
disease matched group had a proportion of serious infections of 1\%
(0.00 to 0.02) (Figure S9). There were only 2 studies included in this
analysis with a statistical difference in proportions between disease
matched compared with disease treated women (p \textless{}0.001.; Table
S2).

\textbf{Miscarriage}

The data available on miscarriage included 15 studies with 9368
pregnancies. There were 2708 pregnancies in women treated with biologics
in pregnancy (Table 2). The proportion of miscarriage in the biologics
treated group was 13\% (95\% CI 0.10 to 0.15), the proportion of
miscarriage in the disease matched group was 8\% (0.04 to 0.11) and in
the disease free group 11\% (0.03 to 0.19) (Figure S10). There was no
significant difference in proportions between disease matched compared
with disease treated women (p=0.078), or in disease free compared with
disease treated women comparison (p=0.631; Table S2). One study was
excluded from the analysis, they had no difference in their miscarriage
rate across their treated and untreated groups of 3\%, but a rate much
lower than all other included studies\textsuperscript{20}. Subgroup
analysis revealed no difference in groups when focusing on anti-TNF-\selectlanguage{greek}α
\selectlanguage{english}studies only (results not shown).

\textbf{Pre-eclampsia:}

There were 5 eligible studies for inclusion in the meta-analysis for
pre-eclampsia. This included data on 1175 pregnant women treated with
biologics and 1017 disease matched controls (Table 2). In the treated
group the percentage of pre-eclampsia was 1\% (95\% CI 0.01 to 0.02) and
the disease matched control 1\% (0.00 to 0.01) (Figure S11). No
differences were observed in proportions between disease matched
compared with disease treated women (p=0.193; Table S2).

\textbf{Discussion}

\textbf{Main findings}

We detected no difference in the rates of congenital malformations,
neonatal infection, low birth weight, small for gestational age,
miscarriage or pre-eclampsia with the use of biologics in pregnancy. The
rates of preterm delivery were not statistically different between the
treated and the disease matched groups but there was a statistical
difference noted between the treated and disease free group, possibly
pointing towards the disease process being a factor. Too few studies
examined serious maternal infection as an outcome to be concluded upon.
These findings may offer significant reassurance to both clinicians and
patients alike in continuing these targeted agents during pregnancy.

\textbf{Strengths and limitations}

Studies examining the use of biologics in pregnancy have been limited
due to small sample size and the rare outcomes of interest. To our
knowledge this is the largest cohort of pregnancies exposed to biologics
collated to date. This review was based on a pre-published protocol on
PROSPERO and followed the PRISMA guidelines. This review allows areas of
future research to be highlighted that are currently lacking, primarily
elucidating the links with preterm birth, maternal infection risk as
well as exploring likely protective effects of these medications against
uncontrolled disease activity. There are several limitations to this
study, our search included English only literature. Disparities in the
measurement criteria e.g.: birth weight, infection criteria and even the
diagnostic criteria for congenital malformation make meta-analysis on
this topic difficult with an already small sample being made smaller by
misusing the appropriate definition and criteria. Additionally, the
recording of concomitant medications, particularly corticosteroids,
dosing and pregnancy outcomes which can differ between studies is
imprecise at best. Pregnancy outcomes in this population can be
influenced by the activity of the underlying disease state
peri-conceptually and during pregnancy which can be difficult to
accurately collate in these observational studies and difficult to
control for by using a ``disease matched cohort'' when matched by
diagnosis only.

We have expanded on the previous reviews by increasing the pool of data
to include peer reviewed cohort studies and case
series\textsuperscript{11,12,21} with statistical analysis of
proportions rather than odds ratio. Another novel approach that we have
taken was allowing comparisons across three populations; the treated,
disease matched and disease free. We also performed sub analysis by
biologic type and disease type where appropriate.

\textbf{Interpretation}

We found no evidence to suggest biologics, with the strongest evidence
for the TNF\selectlanguage{greek}α \selectlanguage{english}inhibitor class, increase the risk of congenital anomalies.
This further expands on the evidence provided from previous
meta-analyses that found no difference in congenital anomalies such as
reported by Tsao et al (OR 1.18, 95\% CI 0.88 to
1.5)\textsuperscript{11}, Komaki et al\textsuperscript{12} and
Neilsen\textsuperscript{21}.This is the largest preterm birth
meta-analysis to date, with twenty-six studies included in the preterm
birth meta-analysis with 7728 pregnancies exposed to biologics. As
expected, a higher rate of PTB was observed in the treated group (12\%
compared with 6\% in the disease-free group (p=0.008), with no
difference in the rates observed between the treated and disease matched
groups. The disease free group rates of 6\% compare with WHO PTB rates
for Europe and North America of 9\% and 11\%
respectively.\textsuperscript{22} The lower rate of PTB in our disease
free population likely reflects the inclusion of a large study by Broms
et al\textsuperscript{4} which encompasses population registry data from
Denmark, Finland and Sweden.

One of the primary factors which may impact PTB rates is disease
activity. Geldhof concluded that women with active or flaring disease
during pregnancy were at a much higher risk of complications
irrespective of exposure to biologics with their exposure group having a
PTB rate of 9.2\% (n=143) and their corticosteroid group a PTB rate of
14.7\% (n=36).\textsuperscript{23} Of concern, maternal disease may
flare when biologic agents are discontinued and this itself may impact
on PTB rates; this was reported with discontinuation of biologics prior
to 24 weeks and a higher incidence of preterm delivery in a number of
studies included in this analysis. \textsuperscript{4,23,24}

Our meta-analysis revealed no statistical difference in severe neonatal
infection between groups. This was similar to the findings of two
studies which were eligible but could not be included in the
metanalysis, Tsao \emph{et al} 2019 (due to a data sharing agreement)
and Luu \emph{et al} . Tsao \emph{et al} 2019 found no increased risk of
serious infections in the first year postpartum for either the mothers
or the neonates\textsuperscript{3}. Similarly, Luu \emph{et al} found no
difference in community or hospital acquired infections in the biologic
treated group compared to a disease matched
population.\textsuperscript{24} Interestingly studies specifically
examining biologic use during the third trimester found no alteration in
the neonatal infection rate during the first 12 months of life for the
neonate.\textsuperscript{19,20,25--27} The only variable associated with
an increased incidence of neonatal infection in multiple studies was
PTB.\textsuperscript{19,20,24}

Our meta-analysis found no statistical difference in birth weight with
biologic use. Literature around this topic has been controversial with
previous studies highlighting the greater prevalence of growth
restriction/low birth weight babies in women with chronic inflammatory
conditions\textsuperscript{4,17}. Of the eligible studies included in
this meta-analysis, Moens had the largest treated group and found no
difference between their treated and untreated
groups.\textsuperscript{28} Tsao \emph{et al} found an OR for the
association between biologic exposure and SGA was 0.91 (95\% CI 0.46 to
1.78).\textsuperscript{29} The PIANO trial found no difference in LBW in
those exposed to biologics after controlling for PTB and disease
activity\textsuperscript{20}.

Our analysis included only two studies examining severe maternal
infection. The recent large Canadian 10 year retrospective cohort study
by Tsao \emph{et al} data could not be
obtained.\textsuperscript{3}However in published work they reported the
occurrence of serious maternal infections to be rare with an incidence
of 0-5\% which is similar to the proportions found in our meta-analysis.
Luu \emph{et al}found no difference in infection rates (community or
hospital treated) in women treated with biologic agents in their third
trimester but echoing findings above, those who discontinued were more
likely to have a flare of their inflammatory
disease.\textsuperscript{24} There was no greater likelihood of
miscarriage for biologic treated patients compared to the comparator
populations. This mirrors previous data
reported\textsuperscript{18,30--32} which did not find an increased risk
of miscarriage with biologics. Assimilating the data on pre-eclampsia,
which is a less studied outcome of interest, we found no data to suggest
that TNF inhibitors increase the risk. This data reflects information
obtained from a small number of studies. Notably, no pre-eclampsia cases
were reported with CZP use in Clowse et al.\textsuperscript{18}
Chaparro\emph{et al} found pre-eclampsia equally distributed across both
the biologics exposed group and the disease matched
cohort.\textsuperscript{19} Julsgaard \emph{et al} specifically found no
difference in the pre-eclampsia rates between women who ceased their
medication prior to 30 weeks' gestation or
continued.\textsuperscript{33}

\textbf{Conclusion}

With the data that is available in the published literature shows no
increased risk with biologics over disease matched cohorts with respect
to congenital malformations, preterm delivery, neonatal infection, small
for gestational age, low birth weight, miscarriage and pre-eclampsia.
There is a suggestion of an increased risk of maternal infections in the
treated group but this is likely due to the lack of studies examining
this outcome.

With over 11172 pregnancies exposed to biologics, our study shows these
medications are predominantly safe for the fetus and the mother. More
evidence is required to prove the likely protective effects of these
medications from unwanted outcomes that disease flare may cause in CID
affected pregnancies. This is important for gastroenterologists,
rheumatologists and obstetricians alike when reassuring women regarding
continuation of treatment throughout pregnancy and for refractory
disease during childbearing years.

\textbf{Disclosure of interests}

None Declared.

\textbf{Contribution to Authorship}

FMcC, AK, GMurphy conceived the study and FMcC, AK, GMurphy, SA, LOB,
GMaher designed the protocol. LOB, SA performed the literature search.
LOB, SA, AOS selected the studies and extracted the relevant
information. LOB, GMaher synthesised the data. LOB wrote the first draft
of the paper. FMcC, AK~, GMurphy, GMaher critically revised successive
drafts of the paper. LOB is the guarantor of the review.

\textbf{References}

1. Maniadakis N, Toth E, Schiff M, et al. A Targeted Literature Review
Examining Biologic Therapy Compliance and Persistence in Chronic
Inflammatory Diseases to Identify the Associated Unmet Needs, Driving
Factors, and Consequences. \emph{Adv Ther} . 2018;35(9):1333-1355.
doi:10.1007/s12325-018-0759-0

2. Jacobs P, Bissonnette R, Guenther LC. Socioeconomic burden of
immune-mediated inflammatory diseases - Focusing on work productivity
and disability. \emph{J Rheumatol} . 2011;38(SUPPL. 88):55-61.
doi:10.3899/jrheum.110901

3. Tsao NW, Lynd LD, Sayre EC, Sadatsafavi M, Hanley G, De Vera MA. Use
of biologics during pregnancy and risk of serious infections in the
mother and baby: A Canadian population-based cohort study. \emph{BMJ
Open} . 2019;9(2):1-9. doi:10.1136/bmjopen-2018-023714

4. Br\selectlanguage{ngerman}öms G, Kieler H, Ekbom A, et al. Anti-TNF treatment during
pregnancy and birth outcomes: Apopulation-based study from Denmark,
Finland, and Sweden. \emph{Pharmacoepidemiol Drug Saf} . 2020;(September
2019):1-12. doi:10.1002/pds.4930

5. Kvien TK, Uhlig T, Ødegård S, Heiberg MS. Epidemiological aspects of
rheumatoid arthritis: The sex ratio. \emph{Ann N Y Acad Sci} .
2006;1069:212-222. doi:10.1196/annals.1351.019

6. De Lorenzo R, Ramirez GA, Punzo D, et al. Neonatal outcomes of
children born to mothers on biological agents during pregnancy: State of
the art and perspectives. \emph{Pharmacol Res} . 2020;152(September
2019):104583. doi:10.1016/j.phrs.2019.104583

7. Yockey LJ, Iwasaki A. Interferons and Proinflammatory Cytokines in
Pregnancy and Fetal Development. \emph{Immunity} . 2018;49(3):397-412.
doi:10.1016/j.immuni.2018.07.017

8. Cornish J, Tan E, Teare J, et al. A meta-analysis on the influence of
inflammatory bowel disease on pregnancy. \emph{Gut} .
2007;56(6):830-837. doi:10.1136/gut.2006.108324

9. Genest G, Spitzer KA, Laskin CA. Maternal and fetal outcomes in a
cohort of patients exposed to tumor necrosis factor inhibitors
throughout pregnancy. \emph{J Rheumatol} . 2018;45(8):1109-1115.
doi:10.3899/jrheum.171152

10. Selinger CP, Nelson-Piercy C, Fraser A, et al. IBD in pregnancy:
Recent advances, practical management. \emph{Frontline Gastroenterol} .
Published online 2020:1-11. doi:10.1136/flgastro-2019-101371

11. Tsao NW, Rebic N, Lynd LD, De Vera MA. Maternal and neonatal
outcomes associated with biologic exposure before and during pregnancy
in women with inflammatory systemic diseases: a systematic review and
meta-analysis of observational studies. \emph{Rheumatology} .
2020;59(8):1808-1817. doi:10.1093/rheumatology/keaa064

12. Komaki F, Komaki Y, Micic D, Ido A, Sakuraba A. Outcome of pregnancy
and neonatal complications with anti-tumor necrosis factor-\selectlanguage{greek}α \selectlanguage{english}use in
females with immune mediated diseases; a systematic review and
meta-analysis. \emph{J Autoimmun} . 2017;76:38-52.
doi:10.1016/j.jaut.2016.11.004

13. NHS Centre for Reviews and Dissemination. Systematic reviews: CRD's
guidance for undertaking reviews in health care. \emph{Univ York York,
UK,} . Published online 2009.
https://www.york.ac.uk/media/crd/Systematic\_Reviews.pdf

14. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting
items for systematic reviews and meta-analyses: the PRISMA
statement.\emph{PLoS Med} . 2009;6(7):e1000097.
doi:10.1371/journal.pmed.1000097

15. McDonald SD, Han Z, Mulla S, Murphy KE, Beyene J, Ohlsson A. Preterm
birth and low birth weight among in vitro fertilization singletons: A
systematic review and meta-analyses. \emph{Eur J Obstet Gynecol Reprod
Biol} . 2009;146(2):138-148. doi:10.1016/j.ejogrb.2009.05.035

16. Nyaga VN, Arbyn M, Aerts M. Metaprop: A Stata command to perform
meta-analysis of binomial data. \emph{Arch Public Heal} .
2014;72(1):1-10. doi:10.1186/2049-3258-72-39

17. Carman WJ, Accortt NA, Anthony MS, Iles J, Enger C. Pregnancy and
infant outcomes including major congenital malformations among women
with chronic inflammatory arthritis or psoriasis, with and without
etanercept use. \emph{Pharmacoepidemiol Drug Saf} .
2017;26(9):1109-1118. doi:10.1002/pds.4261

18. Clowse MEB, Scheuerle AE, Chambers C, et al. Pregnancy Outcomes
After Exposure to Certolizumab Pegol: Updated Results From a
Pharmacovigilance Safety Database. \emph{Arthritis Rheumatol} .
2018;70(9):1399-1407. doi:10.1002/art.40508

19. Chaparro M, Verreth A, Lobaton T, et al. Long-term safety of in
utero exposure to anti-TNF\selectlanguage{greek}α \selectlanguage{english}drugs for the treatment of inflammatory
bowel disease: Results from the multicenter European TEDDY
study.\emph{Am J Gastroenterol} . 2018;113(3):396-403.
doi:10.1038/ajg.2017.501

20. Mahadevan U, Long MD, Kane S V., et al. Pregnancy and Neonatal
Outcomes After Fetal Exposure to Biologics and Thiopurines Among Women
With Inflammatory Bowel Disease. \emph{Gastroenterology} .
2021;160(4):1131-1139. doi:10.1053/j.gastro.2020.11.038

21. Nielsen OH, Gubatan JM, Juhl CB, Streett SE, Maxwell C. Biologics
for Inflammatory Bowel Disease and Their Safety in Pregnancy: A
Systematic Review and Meta-analysis. \emph{Clin Gastroenterol Hepatol} .
Published online 2021. doi:10.1016/j.cgh.2020.09.021

22. Chawanpaiboon S, Vogel JP, Moller AB, et al. Global, regional, and
national estimates of levels of preterm birth in 2014: a systematic
review and modelling analysis. \emph{Lancet Glob Heal} .
2019;7(1):e37-e46. doi:10.1016/S2214-109X(18)30451-0

23. Geldhof A, Slater J, Clark M, Chandran U, Coppola D. Exposure to In
iximab During Pregnancy : Post-Marketing Experience. 2019;(0123456789).

24. Luu M, Benzenine E, Doret M, et al. Continuous Anti-TNF\selectlanguage{greek}α \selectlanguage{english}Use
Throughout Pregnancy: Possible Complications For the Mother But Not for
the Fetus. A Retrospective Cohort on the French National Health
Insurance Database (EVASION). \emph{Am J Gastroenterol} .
2018;113(11):1669-1677. doi:10.1038/s41395-018-0176-7

25. De Lima A, Zelinkova Z, Van Der Ent C, Steegers EAP, Van Der Woude
CJ. Tailored anti-TNF therapy during pregnancy in patients with IBD:
Maternal and fetal safety. \emph{Gut} . 2016;65(8):1261-1268.
doi:10.1136/gutjnl-2015-309321

26. Kanis SL, Modderman S, Escher JC, et al. Health outcomes of 1000
children born to mothers with inflammatory bowel disease in their first
5 years of life. \emph{Gut} . 2021;70(7):1266-1274.
doi:10.1136/gutjnl-2019-319129

27. U. M, D.C. B, M.C. D, et al. Pregnancy outcomes in the tofacitinib
ulcerative colitis octave studies. \emph{Am J Gastroenterol} .
2017;112:S410-S411. doi:10.1038/ajg.2017.303

28. Moens A, van der Woude CJ, Julsgaard M, et al. Pregnancy outcomes in
inflammatory bowel disease patients treated with vedolizumab, anti-TNF
or conventional therapy: results of the European CONCEIVE
study.\emph{Aliment Pharmacol Ther} . 2020;51(1):129-138.
doi:10.1111/apt.15539

29. Tsao NW, Sayre EC, Hanley G, et al. Risk of preterm delivery and
small-for-gestational-age births in women with autoimmune disease using
biologics before or during pregnancy: A population-based cohort
study.\emph{Ann Rheum Dis} . 2018;77(6):869-874.
doi:10.1136/annrheumdis-2018-213023

30. Chambers CD, Johnson DL, Xu R, et al. Birth outcomes in women who
have taken adalimumab in pregnancy: A prospective cohort
study.\emph{PLoS One} . 2019;14(10):1-17.
doi:10.1371/journal.pone.0223603

31. Kawai Y, Tsuchiya T, Aoki S. Pregnancy Outcomes of Patients Exposed
to Adalimumab in Japan. \emph{Dig Dis} . 2019;37(2):123-130.
doi:10.1159/000493462

32. Lichtenstein GR, Feagan BG, Mahadevan U, et al. Pregnancy Outcomes
Reported During the 13-Year TREAT Registry: A Descriptive
Report.\emph{Am J Gastroenterol} . 2018;113(11):1678-1688.
doi:10.1038/s41395-018-0202-9

33. Julsgaard M, Hvas CL, Gearry RB, et al. Anti-TNF Therapy in Pregnant
Women with Inflammatory Bowel Disease: Effects of Therapeutic Strategies
on Disease Behavior and Birth Outcomes. \emph{Inflamm Bowel Dis} .
2020;26(1):93-102. doi:10.1093/ibd/izz110

\emph{Tables and Figures:}

\textbf{Table 1:} Fetal outcomes with the use of biologics in pregnancy.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Fetal outcomes & Number of studies & Number of patients & Proportion of
event & 95\% CI\tabularnewline
\midrule
\endhead
\textbf{Congenital malformations} & & & &\tabularnewline
Treated group & 28 & 7811 & 4\% & 0.03-0.04\tabularnewline
Disease matched & 10 & 29171 & 4\% & 0.03-0.05\tabularnewline
Disease free & 5 & 1251780 & 4\% & 0.03-0.05\tabularnewline
\textbf{Preterm Delivery} & & & &\tabularnewline
Treated group & 26 & 7728 & 12\% & 0.10-0.14\tabularnewline
Disease matched & 11 & 18574 & 10\% & 0.09-0.12\tabularnewline
Disease free & 6 & 1626254 & 6\% & 0.04-0.07\tabularnewline
General population WHO & - & - & 9\% & 0.09-0.09\tabularnewline
\textbf{Neonatal Infection} & & & &\tabularnewline
Treated group & 9 & 3554 & 5\% & 0.03-0.07\tabularnewline
Disease matched & 6 & 4015 & 5\% & 0.02-0.07\tabularnewline
Disease free & 2 & 14799 & 2\% & 0.02-0.02\tabularnewline
\textbf{Low Birth weight} & & & &\tabularnewline
Treated group & 17 & 5112 & 10\% & 0.07-0.12\tabularnewline
Disease matched & 5 & 3046 & 8\% & 0.07-0.09\tabularnewline
Disease free & 4 & 3316 & 4\% & 0.01-0.08\tabularnewline
\textbf{Small for Gestational Age} & & & &\tabularnewline
Treated group & 8 & 3342 & 6\% & 0.02-0.10\tabularnewline
Disease matched & 4 & 10720 & 7\% & 0.02-0.11\tabularnewline
Disease free & 4 & 1624533 & 10\% & 0.10-0.10\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2:} Maternal pregnancy outcomes with the use of biologics
in pregnancy.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Maternal outcomes & Number of studies & Number of patients & Proportion
of event & 95\% CI\tabularnewline
\midrule
\endhead
\textbf{Maternal severe infection} & & & &\tabularnewline
Treated group & 2 & 916 & 4\% & 0.03-0.05\tabularnewline
Disease matched & 1 & 453 & 1\% & 0.00-0.02\tabularnewline
Disease free & 0 & - & - & -\tabularnewline
\textbf{Miscarriage} & & & &\tabularnewline
Treated group & 16 & 3348 & 12\% & 0.09-0.15\tabularnewline
Disease matched & 4 & 3424 & 6\% & 0.01-0.11\tabularnewline
Disease free & 4 & 3641 & 11\% & 0.03-0.19\tabularnewline
\textbf{Pre eclampsia} & & & &\tabularnewline
Treated group & 5 & 1175 & 1\% & 0.01-0.02\tabularnewline
Disease matched & 2 & 1017 & 1\% & 0.00-0.01\tabularnewline
Disease free & 0 & - & - & -\tabularnewline
\bottomrule
\end{longtable}

Figure 1: Metaprop proportions for congenital malformations.

Figure 2: Metaprop proportions of preterm delivery with anti TNF \selectlanguage{greek}α \selectlanguage{english}use
only.

\textbf{Hosted file}

\verb`Figure 1 Metaprop proportions for congenital malformations..docx`  available at \url{https://authorea.com/users/430154/articles/533691-fetal-and-maternal-outcomes-after-maternal-biologic-use-during-conception-and-pregnancy-a-systematic-review-and-meta-analysis}

\textbf{Hosted file}

\verb`Figure 2 Metaprop proportions of preterm delivery with anti TNF \selectlanguage{greek}α \selectlanguage{english}use only..docx`  available at \url{https://authorea.com/users/430154/articles/533691-fetal-and-maternal-outcomes-after-maternal-biologic-use-during-conception-and-pregnancy-a-systematic-review-and-meta-analysis}

\selectlanguage{english}
\FloatBarrier
\end{document}

