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\begin{document}

\title{Recruitment failure in randomised controlled trials: a conundrum}



\author[1]{Rikken JFW}%
\author[1]{Casteleijn RN}%
\author[1]{van der Weide MC}%
\author[1]{Ruben Duijnhoven}%
\author[1]{Mariëtte Goddijn}%
\author[2]{Ben Mol}%
\author[1]{van der Veen F}%
\author[1]{Madelon van Wely}%
\affil[1]{Amsterdam UMC Locatie AMC}%
\affil[2]{Monash University Monash eResearch Centre}%


\vspace{-1em}



  
  \date{May 21, 2024}


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\selectlanguage{english}
\begin{abstract}
\textbf{Objective:} We aim to assess which variables are associated with
recruitment failure of RCTs, leading to an extension of the study
period.. \textbf{Design:} Nationwide cohort study. \textbf{Setting:} A
cohort of RCTs supported by the trial centre of the Dutch Consortium of
Obstetrics and Gynaecology. \textbf{Population:} We included 83 RCTs
that recruited patients between March 1 \textsuperscript{st} 2003 and
December 1 \textsuperscript{st} 2023. \textbf{Main outcome measures:}
Primary outcome was recruitment target not achieved within six months
after the pre-planned recruitment period. Secondary outcomes were
recruitment target not achieved within an extension period of at least
twelve months and premature termination of the trial. \textbf{Results:}
In total, 46 of 83 RCTs (55\%) did not achieve their targeted
recruitment within the pre-planned study period with a maximal extension
period of 6 months. The most relevant indicators for recruitment failure
in multivariable risk prediction modelling were presence of a
no-treatment arm, a compensation fee of less than 200 euros per included
patient, funding of less than 350.000 euros, while a preceding pilot
study lowered this risk. \textbf{Conclusions:} We identified that the
presence of a no-treatment arm, low funding and a low compensation fee
per included patient were the most relevant risk factors for recruitment
failure within the pre-planned period, while a preceding pilot study
lowered this risk. Awareness of these indicators is important when
designing future studies.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Randomised controlled trials (RCTs) are considered to be the best
strategy in evaluating the effectiveness of medical interventions and
they maintain a dominant position in the hierarchy of medical
evidence(1). RCT outcomes are most often adopted into (inter) national
clinical guidelines and have great influence on daily routine clinical
practice. Unfortunately, obtaining evidence from RCTs is often hampered
by failure to recruit enough patients within the pre-planned study
period, leading to premature termination of the trial or extension of
the study period(2).

Premature termination due to poor recruitment has been estimated to
occur in 9-10\% of all

RCTs(3-5). Variables that have been associated with poor recruitment are
an overestimation of the number of eligible patients, a preference for
one of the interventions by the patients, a high burden of the tested
intervention for the patients, an unclear trial design, strict
eligibility criteria, a lack of logistic support or a lack of
funding(6-9).

While the variables that may result in poor recruitment leading to
premature termination of the trial are well known, much less is known on
variables related to recruitment failure within the pre-planned study
period, leading to extension of the study period.

The one study to investigate this matter, explored factors associated
with recruitment in a cohort of 114 multicentre RCTs in more than nine
clinical areas, including cancer, cardiology and obstetrics \&
gynaecology (18 RCTs had a clinical area classified as `other'), and
funded by two public bodies in the United Kingdom; the UK Medical
Research Council (MRC) and the Health Technology Assessment (HTA)
Programme(5). RCTs that were funded by the MRC (as compared with the
HTA) and were in the clinical area `cancer', had better chances of good
recruitment, which was a marginally statistically significant
association. The vast heterogeneity of RCTs included in that study
hampered the identification of other indicators associated with poor
recruitment and did not allow the authors to provide useful advice for
improvement.

A longer recruitment period may result in a shortage of resources
possibly impacting the quality of the trial, limit the institutional
capacity to start new RCTs, result in a trial that tries to answer a
question that is no longer relevant, or result in premature termination
of the study, thus hindering a conclusion with sufficient statistical
power(10).

To assess factors that are associated with recruitment failure within
the pre-planned study period, we performed a nationwide cohort study of
RCTs within the setting of the Dutch Consortium of Obstetrics \&
Gynaecology in the Netherlands. Such knowledge may be instrumental in
helping researchers, trial centres and funding agencies to prevent this
type of recruitment failure.

\textbf{Methods}

\emph{Study design}

This study was designed as a nationwide cohort study and included all
multicentre RCTs carried out within the Dutch Consortium for Women's
Health Research, embedded within the professional society, i.e. Dutch
Society of Obstetrics and Gynaecology (NVOG)(11). The Dutch Consortium
for Women's Health Research facilitated studies in obstetrics,
gynaecology and reproductive medicine.

Within the consortium, participating clinical centres are both academic
and non-academic hospitals. RCTs conducted within the Consortium are
supported by a clinical trial centre
(https://zorgevaluatienederland.nl/), a multidisciplinary trial bureau
with methodologists,~data managers,~contract managers~and trial
managers. The trial centre staff supports research groups by advising on
the budget, logistics, methods, and ethics approval, developing
electronic case record forms, performing contract management and
monitoring, creating the interim reports for the data safety and
monitoring board and providing advice on the statistical analyses. We
constructed the manuscript according to the STROBE guideline(12).

\emph{Study population}

We included finalized multicentre RCTs supported by the clinical trial
centre and performed within the Dutch Consortium for Women's Health
Research, between March 1\textsuperscript{st} 2003 and December
1\textsuperscript{st} 2023. We excluded studies with an observational
design, single centre RCTs, RCTs initiated outside the Netherlands, RCTs
with a cluster or parallel study design, RCTs that never actually
started, RCTs in which inclusion of patients was still ongoing and RCTs
prematurely discontinued for other reasons than poor recruitment, for
example due to safety issues after an interim analysis.

\emph{Outcome measures}

Primary outcome was recruitment target not achieved within 6 months
after the pre-planned recruitment period. These RCTs were defined as
RCTs with recruitment failure. The pre-planned recruitment period was
documented by the principal investigator before the start of the trial.
Secondary outcomes included recruitment target not achieved within an
extension period of at least 12 months and premature termination of the
trial (defined as stopping with including patients before the
recruitment target was achieved). All studies that recruited during the
COVID-19 pandemic received 6 months extension of their recruitment
period.

In all RCTs, we collected information on variables with a potential
effect on recruitment failure, identified after a scoping review. We
recorded variables at five levels; patient, doctor, participating
centre, study organisation and study design (Appendix 1).

\emph{Statistical analysis}

For the primary outcome, we used the planned recruitment period as
documented in the General Assessment and Registration form, a form that
needs to be submitted to the ethical committee before actual start of
the study. If we could not get access to this form, we retrieved this
information from the main investigator and/or used the data mentioned in
the protocol of the study. The actual recruitment period was calculated
as the time between the first and last inclusion date.

We checked the continuous potential indicators with spline curve
analysis. We dichotomised on basis of the spline curve and used the
median when the spline suggested a straight line. We used logistic
regression to evaluate the association between potential indicators of
recruitment failure and expressed these as odds ratios (OR) with
corresponding 95\% confidence intervals (CI).

To further explore the most relevant risk factors for recruitment
failure multivariable risk prediction modelling was done by using both
forward and backward stepwise logistic regression (entry p=0.2 and
exclusion p=0.1).

We used SPSS\textsuperscript{?} (IBM 2019, USA) software for all
statistical analyses (version 25).

\emph{Ethics approval}

Our study focussed on logistics and design issues and did not include
patients as study participants. Consequently, we did not need ethical
approval for this study.

\emph{Transparency statement}

All authors had full access to all the data in the study and the
corresponding author had final responsibility for the decision to submit
for publication. The manuscript is an honest, accurate and transparent
account of the study being reported, no important aspects of the study
have been omitted, and any discrepancies from the study as originally
planned have been explained.

\emph{Role of the funding source}

This study was supported by a small departmental grant of the Centre for
Reproductive Medicine, Amsterdam University Medical Centres, location
AMC.

\emph{Public and patient involvement}

No patients or members of the public were involved in this study since
the study did not concern patients directly.

\textbf{Results}

Between March 1\textsuperscript{st} 2003 and December
1\textsuperscript{st} 2023 189 studies started recruitment and were
assessed for eligibility. Of these, 106 studies did not fulfil our
inclusion criteria, such that in total 83 RCTs were included in the
analyses (Figure 1). Characteristics of the included studies are
summarized in Table 1. Fifteen RCTs did not have funding at all (18\%).
A more detailed list of all RCTs can be found as supplementary file
Appendix 2(13-89).

\emph{Primary and secondary outcomes}

In total, 46 of 83 RCTs (55\%) did not achieve their targeted
recruitment within the pre-planned study period with a maximal extension
period of 6 months (Table 2). Recruitment was not achieved within the
pre-planned study period with a maximal extension period of 12 months in
41 RCTs (49\%). Of these 41 RCTs, 29 studies had a total recruitment
period of up to five years, and 12 RCTs finished their recruitment
within five to ten years.

Nineteen RCTs (23\%) stopped prematurely due to recruitment issues. Of
these 19 RCTs, four studies reached 0 to 10\% of their recruitment
target, six studies 10 to 20\%, two studies 20 to 30\%, five studies 30
to 60\% and two studies reached 70 to 80\% of their planned recruitment
target.

The mean recruitment period was 50 months (range 12-96 months) for RCTs
with recruitment failure versus 31 months (range 12-91 months) for RCTs
without recruitment failure. Twenty-two RCTs had a recruitment period of
over 48 months. The actual absolute recruitment rate was 4.5 inclusions
per month in RCTs with recruitment failure compared to 18.5 inclusions
per month in RCTs without recruitment failure (p\textless{}0.001).

\emph{Potential indicators of recruitment failure}

The association of the potential indicators with RCTs with recruitment
failure i.e. RCTs that did not achieve their recruitment target within
the pre-planned study period with a maximal extension period of 6
months, is shown in Table 3.

Indicators associated with higher chances on recruitment failure were
presence of a no-treatment arm, having a design with more than two arms,
funding, a compensation fee of less than 200 euros per included patient,
funding of less than 350.000 euros and having more than four inclusion
criteria. An indicator associated with lower chances on recruitment
failure was a preceding pilot study. The most relevant indicators for
recruitment failure in multivariable risk prediction modelling were
presence of a no-treatment arm (OR 4.95, 95\% CI 1.18 to 20.80), a
compensation fee of less than 200 euros per included patient (OR 2.90,
95\% CI 1.02 to 8.25)), funding of less than 350.000 euros (OR 2.99,
95\% CI 1.05 to 8.51), while a preceding pilot study lowered the risk
for treatment failure (OR 0.21, 95\% CI 0.05 to 0.83).

When we compared the 41 RCTs that did not achieve their recruitment
target within the pre-planned study period with a maximal extension
period of 12 months, with the 42 RCTs that completed recruitment within
that period, the described associations with treatment failure remained
comparable in direction and size.

The most relevant indicators for stopping prematurely were the absence
of a preceding pilot study and having a no-treatment arm. None of the 19
RCTs that stopped prematurely had performed a pilot study (0\%),
compared to 17 of the 62 RCTs that completed recruitment (27\%). Ten of
the 19 RCTs that stopped prematurely had a no-treatment arm (52\%),
compared to eight of the 64 RCTs that completed recruitment (12.5\%) (OR
6.13, 95\% CI 1.98 to 19.06).

\textbf{Discussion}

\emph{Main findings}

In this nationwide cohort study, 46 of 83 included RCTs (55\%) did not
achieve their recruitment target within the pre-planned study period
with a maximal extension period of six months. RCTs that had a
no-treatment arm, low funding and low financial compensation per
included patient were at risk to experience this type of recruitment
failure, while a preceding pilot study lowered this risk. Upon extension
of the pre-planned study period from six to twelve months, 41 RCTs
(49\%) still did not achieve the pre-planned recruitment target.
Nineteen RCTs (23\%) were stopped prematurely because of recruitment
issues.

\emph{Strenghts and limitations}

Our study has a number of strengths. First, we investigated recruitment
failure in 83 RCTs embedded within the Dutch Consortium for Women's
Health Research -- and thus within one discipline - with support and
monitoring by the clinical trial centre. This allowed us to standardize
several important aspects, like trial management and logistics, data
collection and data monitoring. Second, we were able to assess all
indicators with a potential association with poor recruitment as
described in literature; type of investigation, placebo-controlled
study, treatment versus no treatment, whether the intervention was new
or only available in the trial, whether the study was blinded or if
there were any competing RCTs, number of study arms, number of inclusion
and exclusion criteria, whether a pilot study was performed, number of
participating centres and funding and compensation per included patient.

The main limitation of our study is the number of trials. Obviously, if
we could have accessed an even larger cohort of trials, we might have
been able to identify more potential indicators for recruitment failure.
A further limitation may be that within our study we focussed on
objective indicators, such as trial logistics and design issues. Other
aspects, like patients' or practitioners' perspectives, which may affect
recruitment as well were beyond the scope of our study.

\emph{Interpretation}

The design of a no-treatment arm where treatment is standard clinical
practice was associated with recruitment failure. This design is
particularly relevant, since we may be over-treating patients while we
are actually in equipoise on whether the intervention is effective at
all. Possibly, in this design specifically, the preference of the doctor
or patient might play a role in the laborious recruitment. A no
treatment arm was also associated with stopping prematurely, supporting
its relevance as a risk factor. In our study ten (52\%) of 19 RCTs that
stopped prematurely had a no-treatment arm where in current clinical
practice treatment is expected.

Two typical examples of RCTs with such a design that stopped prematurely
were a trial that compared intrauterine insemination (IUI) with
expectant management in couples with unexplained subfertility, and a
trial that compared immediate delivery with temporizing management in
women between 27+5 and 33+5 weeks of gestation admitted for early-onset
severe preeclampsia with or without HELLP syndrome(33, 81).

Not very surprisingly, the lack of funding and compensation fee per
included patient was associated with recruitment failure. Twelve studies
with recruitment failure had no funding at all, compared with three
studies without recruitment failure. In combination with our outcome
that extending the recruitment period from six to twelve months did not
increase the numbers of RCTs that reached their pre-planned sample size,
this has important clinical, logistic and financial consequences. RCTs
may reach their recruitment target, but in 12 RCTs in our study,
recruitment took up to ten years. It implies that when recruitment is
doomed to fail, it may reach its required sample size in the end, but at
the expense of a lot of endurance and extra funding by a willing
sponsor. On the other hand, RCTs can still be of extreme clinical
importance if the research question is -- and remains -- relevant. This
is shown by a trial that investigated low-molecular-weight heparin in
women with recurrent pregnancy loss and inherited thrombophilia, which
took 7,5 years to recruit, but results were eagerly awaited and
eventually published in a high impact journal(15).

A preceding pilot study lowers recruitment failure, while a study design
with more than two arms or more than four inclusion criteria might
increase the chance of recruitment failure, although with a wide
confidence interval due to small numbers. We think that a preceding
pilot study helps to notice and resolve potential issues before start of
the actual study, while a study design with more than two arms or more
than four inclusion criteria could result in an overly complex
recruitment process. In a review of the literature on factors limiting
the quality and progress of RCTs not hampered by recruitment failure, a
straightforward study protocol and data collection as well as careful
planning were also identified as key factors for completion(90).

A competing study was not associated with a lower chance on recruitment
failure, which is the opposite of what we expected. We hypothesize that
when more RCTs in the same field are recruiting patients at the same
time, clinicians are more aware of the possibility of including patients
in a particular RCT, or when one RCT recruits rapidly, this might be
``contagious'' for the other RCTs.

It is important to note that our results should not withhold clinicians
from conducting RCTs on these research questions. Investigating the
efficacy and safety of treatments and providing robust evidence can be
of the utmost importance. Although it is known that the results of
randomized and nonrandomized studies have a good correlation,
nonrandomized studies tend to show larger treatment effects, and thus
observational studies can be good adjunct to RCTs, but they cannot
replace them(91, 92). More importantly, our study shows that also RCTs
with recruitment that takes many years answer highly relevant clinical
questions and can truly make a big difference in the clinical field.
Principal investigators, sponsors and all who are participating in an
RCT should be aware of the indicators associated with poor recruitment,
and that with dedication and persistence the RCT could be successfully
completed and published.

\textbf{Conclusion}

To conclude, RCTs with a no-treatment arm, low funding, low financial
compensation per included patient are more likely to experience
recruitment failure, while a preceding pilot study lowers this chance.
We propose that investigators and grant providers consider these issues
before the actual start of the study, to improve the chances of
recruitment success. If a relevant trial is destined to have a suspected
long recruitment period, it seems wise to ponder on the question whether
to start the trial, or to accept a longer recruitment period with all
its consequences.

\textbf{Acknowledgements:}

The authors would like to thank all the clinical and principal
investigators of the included RCTs for cooperating in data collection,
and Maya Kruijt, policy advisor Zorgevaluatie Nederland, for her advice.

\textbf{Disclosure of interest:}

MG reports department research and educational grants from Guerbet and
Ferring (location VUmc) outside the submitted work. BWM reports grants
from NHMRC, personal fees from ObsEva, personal fees from Merck KGaA,
personal fees from Guerbet, personal fees from iGenomix, outside the
submitted work.

\textbf{Contribution to Authorship:}

JFWR, MvW, MCW and RGD conceived the study. JFWR and RC did the scope
review, selected the potential indicators, and collected the data.
Differences of opinion and questions regarding the data were resolved
with MvW. JFWR was responsible for the data. JFWR, RC and MvW analysed
the data. JFWR, MvW, MG and FvdV drafted the manuscript, supported by
BWM. All authors contributed to the critical revision of the paper and
approved the final manuscript.

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