Operational Determinants of Recruitment and Biospecimen Collection in Translational Observational Studies: A Multi-Site Comparative Analysis

Operational Determinants of Recruitment and Biospecimen Collection in Translational Observational Studies: A Multi-Site Comparative Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Operational Determinants of Recruitment and Biospecimen Collection in Translational Observational Studies: A Multi-Site Comparative Analysis Ciaran Devoy, Ciarán Devoy, Ronan Andrew McLaughlin, Christopher Cronin, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6939667/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Oct, 2025 Read the published version in Journal of Translational Medicine → Version 1 posted 5 You are reading this latest preprint version Abstract Background Biospecimen collection from study participants is essential for translational research, but operational challenges in study setup and conduct often impede successful delivery. This study uses a comparative approach to identify key logistical and staffing determinants influencing setup duration, recruitment efficiency, sample acquisition, and data completeness across three investigator-led microbiome-wide association studies (MWAS) conducted at cancer centres in Ireland. Methods Three academic observational MWAS enrolling participants with cancers of the breast, gastrointestinal tract, lung, biliary system, kidney, and skin were compared. Data from three cancer centres were analysed. Key variables included study team composition, administrative infrastructure, and full-time equivalent (FTE) research staffing. Metrics assessed included setup duration, recruitment rates, sample acquisition, and data completeness. Descriptive statistics, correlation analyses, and regression models were used to evaluate relationships between staffing and study performance. Results Setup duration ranged from 30 days (Site B, with a pre-established trials unit) to 390 days (Site A, with no dedicated setup personnel). At Site C, the addition of an Academic Clinical Trials Coordinator reduced the remaining setup timeline from 274 to 185 days. Recruitment rates ranged from 1.1 to 1.3 participants/month, with the highest rates at sites with dedicated research nurses (RN+). Sample acquisition was 100% at RN + sites and 70.5% at the RN − site. Site C achieved full data completeness, defined as comprehensive documentation of screening, exclusions, and follow-up outcomes. Statistical modelling indicated that dedicated staffing (both administrative and clinical) was strongly associated with improvements across all metrics, although sample size limited statistical significance. Conclusions Dedicated administrative and clinical trial personnel significantly enhance study efficiency, participant recruitment, and biospecimen collection in academic translational research. This study provides practical insights for improving study design and infrastructure planning in future observational studies. To our knowledge, this is the first multi-site comparative evaluation of operational determinants in academic MWAS, and it offers actionable strategies to streamline translational study delivery, improve biospecimen quality, and strengthen real-world research infrastructure. Translational research Study setup Research nurse Recruitment efficiency Biospecimen collection Operational determinants Observational studies Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION High quality translational research is defined by its relevance to urgent health problems, pragmatic study designs, participant centred approaches, cost effectiveness, and transparency. However, many translational studies fall short of these standards, limiting their real-world impact and generalisability (Ioannidis, 2016; Concato et al., 2000). Observational studies, although less resource intensive than randomised trials, face similar challenges in design, regulatory setup, and participant recruitment. Despite growing awareness of these logistical barriers, evidence guiding best practices in trial management remains sparse, particularly outside of large-scale industry funded trials or U.S. based networks. This lack of operational guidance undermines the efficiency of translational research, leading to delayed starts, incomplete data, or trial discontinuation. Participant recruitment challenges are frequently cited as the most common cause of delays and trial failure, with difficulties contributing to bias, reduced power, and early closure (Cullati et al., 2016; Galea and Tracy, 2007). Factors such as emotional burden, perceived benefit, and clear communication influence consent, with studies showing that participants are more likely to enrol when supported by dedicated staff and transparent information (Trauth et al., 2000; Jones et al., 2016). However, beyond participant motivation, critical but often overlooked stages include the trial startup phase defined by regulatory and administrative processes and participant and sample management during trial conduct. These stages are especially vulnerable to inefficiencies when trials lack dedicated clinical trials staff and streamlined communication between academic and clinical teams (Donovan et al., 2014; Spilsbury et al., 2008). In this report, we analysed three microbiome-wide association studies (MWAS) that were concurrently ongoing at separate cancer centres in Ireland. While the studies shared a common biospecimen based design, they differed in organisational structure, staffing models, and study logistics. By retrospectively comparing these real-world implementations, we sought to identify operational factors that influenced study setup timelines, participant recruitment, and sample acquisition. This analysis builds on the Study Within A Trial (SWAT) concept, which embeds methodological evaluations into real world research to improve trial processes (Treweek et al., 2018). Identifying these determinants offers critical insights for optimising biospecimen related study logistics and enhancing the reliability of future translational research. METHODS This analysis follows the STROBE checklist guidelines for reporting observational studies, as it is a report covering three studies at separate sites (Vandenbroucke et al., 2007). The methodology included measuring the time from the initial setup of the translational microbiome wide association study (MWAS) to obtaining the consent of the first patient while analysing all the stages and obstacles encountered throughout the process. Furthermore, we examined all the individuals, systems, and institutions involved in this process hierarchically. The study conduct stage of the study involved measuring the rates and total number of participants and sample uptake. Since this analysis compares three studies, a basic understanding of the study design and methodology is also necessary. Descriptive statistics were used to summarise setup times, recruitment rates, sample acquisition, and data completeness across sites. Correlation analyses (Pearson and Spearman) and regression models (negative binomial and linear regression) were applied to explore associations between staffing levels, study setup duration, and participant recruitment. The Kruskal-Wallis test was used to compare setup times across different staffing configurations. Translational MWAS design Translational MWAS explore the links between gut microbial communities and cancer progression, including treatment outcomes (Aggarwal et al., 2023). Key elements of the MWAS design were common across all three studies, and important differences will be addressed in the discussion. The primary endpoint was to sequence the gut microbiome (GM) at three time points in the treatment regime of a patient with cancer and to correlate these findings with the efficacy of the treatment. At the time of consent, participants received three OMNIgene®•GUT (OMR-200) home testing kits to collect a stool sample, each labelled with their unique study identifier number. Participants received three stamped addressed envelopes in the appropriate packaging to send stool samples directly to our laboratory for analysis. At each time point, approximately 500 mg of stool sample was to be collected using the kit. The lab for analysis is common to all three studies. Sites All study sites involved cancer centres in the Republic of Ireland. Site A was a public hospital, recruitment to the MWAS commenced after a study amendment to an existing translational study. Therefore, all that was required for the initial setup was an amendment to the original ethical approval. The setup began in March 2020, and the study ended in October 2022, due to lack of recruitment. Site B, the second public hospital, began initial study set up in 2021 and is still recruiting at time of writing. Site C, a private cancer centre, also began the initial proceedings in November 2021 and is still recruiting at time of writing. Participants eligibility criteria are shown in supplementary Table 1. Site A had a study target of 200 participants, Site B 120 participants, while Site C had a goal of 50 participants. Study Setup and Participant Management Team Composition Each study required the same core tasks. Each team included a consultant medical oncologist (clinical investigator), a scientific principal investigator (PI), and a university-based researcher responsible for coordinating sample logistics and processing across all sites. The number of additional personnel involved varied. Table 1 summarises the study team composition at each site, organised by study phase (setup and conduct), with roles and task distribution described. Full-Time Equivalent (FTE) staffing levels are noted in the text. Site A (Existing Study) Smallest setup team (3 members), 0 dedicated FTE. No full-time equivalent staff were dedicated solely to study setup activities. The study conduct team consisted of a single research nurse, available for only a four-month period. Site B (New Study) Largest setup team (5 members), with 4 dedicated FTEs in a pre-established clinical trials unit. The study conduct team consisted of one specialist registrar (SpR) at any given time (0 FTE). The SpR was not in a dedicated research role and maintained full clinical responsibilities. Site C (New Study) Initial setup team (3 members), 0 dedicated FTEs. An Academic Clinical Trials Coordinator (AC) and a biostatistician supporting the Castor electronic data capture platform joined the team 270 days into setup, contributing 1 FTE to expedite academic and clinical processes. The study conduct phase had the largest team, with two consultants and two research nurses working on rotation. Table 1 Study team composition by site, organised by study phase (setup and conduct). Site Study Setup Study Conduct Site A Consultant Medical Oncologist Clinical Research Nurse Scientific Principal Investigator University Researcher Site B Consultant Medical Oncologist Specialist Registrar (SpR, not dedicated research role) Biostatistician Programme Manager, Cancer Clinical Trials Unit Medical Oncology Specialist Registrar (SpR) Research Contracts Officer University Researcher Site C Consultant Medical Oncologist Scientific Principal Investigator University Researcher Consultant Medical Oncologist Data Manager Senior Clinical Research Nurse Senior Dietitian Clinical Research Nurses Biostatistician Academic Clinical Trials Coordinator (joined later) Castor Biostatistician (joined later) At Site C, roles added partway through the setup phase (Academic Clinical Trials Coordinator and Castor Biostatistician) are indicated (light blue shading). Full-Time Equivalent (FTE) staffing contributions are described in the Methods. Participant flow through study Following regulatory approvals at each cancer centre, patients with cancer undergoing treatment were assessed for eligibility and invited to participate. Upon providing informed consent, participants agreed to provide up to three stool samples at defined time points relative to their treatment schedule (Fig. 1 ). Participant eligibility was determined by the consultant medical oncologist. Discontinuation points existed throughout the study period due to factors such as psychological burden, discomfort with stool collection, and advanced disease progression. RESULTS Study Setup Times Dedicated trial administrative staff were a major factor influencing study setup time. The key milestones and delays are summarised in Table 2, while detailed timelines are provided in Supplementary Figure 1. Table 2. Length of time for key milestones and delays. All studies required approvals for ethics from their respective Clinical Research Ethics Committee (CREC), data protection and participant consent. Sites B and C additionally required a material transfer agreement (MTA). Site A had the longest setup phase (390 days for ethics approval, 263 days to first sample) partially due to external factors (COVID-19) and the absence of a dedicated clinical trials team. Site B achieved the fastest ethical approval (<1 month) but faced a 329 day delay for MTA approval on the university side. The first participant sample was collected 51 days post approval. Site C had the slowest setup timeline among new studies (459 days total, 135 days to first sample) due to a delayed setup team formation. However, with the intervention of the AC, setup was completed in 185 days. Figure 2 highlights the relationship between dedicated administrative support and setup efficiency. Site A lacked a dedicated trials team, leading to the longest setup phase. Site B benefitted from a well-established trials team, achieving the fastest ethical approval but facing delays in MTA due to external university level processes. Site C initially featured fragmented stakeholder communication, before the AC intervention reduced MTA approval time from 329 days to 25 days compared with Site B for which the MTA was the biggest contributing factor to delay the study starting. Figure 3 plots Study setup duration against Full-Time Equivalent (FTE) staffing. Site C is represented in two distinct phases, 274 days without the AC and 185 days with, resulting in four data points across the three sites. Although the Kruskal-Wallis test yielded a p-value of 0.2592, indicating no statistically significant difference in setup time across FTE levels, this result is likely influenced by the small sample size (n=4). Despite the lack of significance, the trend remains clear: increased FTE staffing is associated with shorter setup duration, supported by a strong negative Pearson correlation of -0.92 Participant recruitment The potential pool of participants were screened for suitability to go on the trial in accordance with the inclusion and exclusion criteria. Eligible patients were approached and informed about the study before starting treatment. Following consent, participants were provided with stool collection kits for at home sampling, with samples mailed directly to the university laboratory. Study design included for participants to be followed up by study conduct team members and reminded to collect samples at predefined time points. Figure 4a details participant recruitment across the three sites from their respective starting month M1. Site A recruited 4 participants in 3 months before ceasing enrolment due to the departure of its only study nurse. Site B recruited 21 participants over 20 months. Site C with 2 dedicated trial nurses recruited 20 participants over 16 months, maintaining recruitment until it paused in M13 following one of the trial nurse’s departure. Comparing Site B (RN-) and Site C (RN+), statistical analyses consistently indicate that research nurse presence was the primary driver of participant recruitment. A negative binomial regression model estimates that the presence of dedicated research nurses increased participant recruitment by 41% (Estimate = 0.4102, p = 0.0557), a trend approaching statistical significance. Importantly, after adjusting for nurse presence, there was no significant difference in recruitment rates between Site B (RN-) and Site C (RN+) (p = 0.7169), confirming that staffing levels, not site-specific factors, were the key determinant of success. A critical observation was that recruitment at Site C (RN+) paused after M13 when a lead research nurse left, despite the trial continuing. Site B (RN-), without research nurses, demonstrated slow but steady recruitment throughout. This aligns with correlation analyses (Spearman’s rho = 0.3999, p = 0.08; Pearson’s r = 0.4182, p = 0.066) and linear regression models (Estimate = 1.01, p = 0.066), all of which indicate a strong positive relationship between nurse presence and participant recruitment. While just outside the standard statistical significance threshold, the consistency of results across methods suggests that additional data could confirm this effect with greater certainty. In terms of participant category numbers, Figure 4b details participant flow at Site B. Potential participant numbers were estimated based on a 20% screening rate. However, no data were recorded for participants who were excluded, declined, or missed screening, limiting retrospective insight into enrolment efficiency and missed opportunities. Six consented participants missed their first sample, and 15 missed a follow-up sample. At Site C, participant flow was recorded more comprehensively (Figure 4c). Of 45 potential participants, six did not meet the inclusion criteria, 11 missed the screening opportunity (yielding a 75% screening rate), and five declined participation. Three participants discontinued prior to providing a sample. No follow-up timepoints were missed. Site C therefore demonstrated the highest level of data completeness, defined here as the extent to which participant screening, exclusions, declines, missed samples, and follow-up status were documented. This enabled more accurate evaluation of recruitment and retention. By contrast, Site B’s limited screening and exclusion records impeded retrospective analysis. Sample acquisition rates Percentage sample acquisition is taken to be a primary measure of success and refers to the % of potential samples from consented participants successfully collected. This takes into account missed follow-up participant sample numbers, while reducing bias due to differences in treatment regimen kinetics. Figure 6d details sample accumulation across all timepoints. Site A (RN+) % sample acquisition = 100. Figure 5a displays cumulative sample numbers at Site A. 10 samples were collected before trial discontinuation with zero missed follow-up samples. The T2 and T3 samples were technically not missed for participant #4, as the study was terminated before they were due to be collected. Site B (RN-) % sample acquisition = 70.5. Figure 5b displays cumulative sample numbers at Site B which accumulated 36 total samples over 20 months, with gaps in T2 and T3 because of missed follow-ups due to staffing limitations. 21 T1 samples, 10 T2 samples, and 5 T3 samples were collected. Sample collection was staggered, with long intervals between T1 and T2 (119 days avg, SD = 58.3) and T2 and T3 (183 days avg, SD = 16), which corelates with the longer treatment regimens of this site relative to the others with 14 missed follow-up samples. Site C (RN+) % sample acquisition = 100. Figure 5c shows cumulative sample collection at Site C where 54 total samples were collected in 16 months. The shorter treatment regimen facilitated faster completion of the three sampling timepoints. 20 T1 samples, 18 T2 samples, 16 T3 samples were collected, with a continuous collection pattern with shorter T1–T2 (23.7 days avg, SD = 5.2) and T2–T3 (59.6 days avg, SD = 10.4) intervals. There were no missed follow-up samples. The only discrepancies between participant T1, T2 and T3 sample collection were because of morbidity. Site Participant and Sample Temporal Rates By analysing cumulative participant and sample numbers, monthly accrual rates were calculated (Figure 6). Site C (RN+)) displayed the highest accrual rates (participants: 1.3/month, samples: 3.6/month). Despite a three-month gap in participant recruitment (M7–M10), sample collection never dropped to zero. Site A (RN+)): Although only briefly in operation, participant recruitment matched Site C (participants: 1.3/month, samples: 2.5/month). Site B (RN-)): shows the lowest rates (participants: 1.1/month, samples: 1.8/month). Six months of zero growth represented 33% of its operational period. DISCUSSION Our findings demonstrate that the availability of dedicated staff for study setup and study conduct played a pivotal role in successful delivery, including improved participant recruitment, sample acquisition, and reduced delays. In contrast, poor recruitment and missed follow-up points were often associated with understaffing or administrative bottlenecks. A strong negative correlation (r = -0.92) between full-time equivalent (FTE) staffing and setup time supports the value of dedicated personnel, though statistical significance was not reached due to the small sample size (p = 0.26). Site B, with four FTE staff, completed ethical approval in just 30 days. In contrast, sites with no dedicated setup personnel required 274 to 390 days. Site B's progress was later hindered by university legal office delays in securing a material transfer agreement, demonstrating the need for simplified regulatory frameworks, an issue echoed across European research settings (Mills et al., 2006). At all sites, clinical investigators contributed to protocol development, ethics submissions, and data protection assessments outside of protected time, often during personal hours. This structural under-resourcing is common in academic-led research and may have contributed to early delays in study activation. Study team composition and structure were key to managing workload and ensuring continuity. Site C’s addition of an AC notably accelerated study setup, illustrating the impact of specialised administrative roles. During study conduct, teams with dedicated clinical research nurses (e.g., Site C) achieved higher recruitment, retention, and sample completeness compared to sites reliant on rotating or non-research dedicated staff. Site C demonstrated complete sample collection and record keeping, reflecting high data completeness. Defined as the extent to which screening, exclusions, missed follow-ups, and other participant metrics were captured, this allowed for more robust retrospective analysis. Site B’s lack of such data limited its evaluability. Follow-up adherence also varied by staffing model: Site C missed no follow-up samples, while Site B missed 15. At Site B, annual handovers and the absence of structured study conduct processes disrupted continuity. These challenges are consistent with broader findings about the need for sustainable staffing models and institutional support for clinical research delivery (Ward and Kennelly, 2019). Participant involvement was influenced by emotional, logistical, and disease-related factors. The psychological burden of a cancer diagnosis and discomfort with stool sampling may have deterred some from consenting (Thompson et al., 2017). At Site C, early contact and structured follow-up, led by research nurses, contributed to consistent accrual. Site B, relying on a single specialist registrar (SpR) not in a dedicated research role, experienced intermittent recruitment. While some institutions may have SpRs with protected research time, this was not the case at Site B. The absence of dedicated research staff contributed to missed opportunities and sample loss; a challenge not frequently cited in literature but evident in our analysis. Despite systemic constraints in public hospitals, committed individuals such as SpRs supported recruitment efforts. However, this reliance demands high personal investment and is rarely sustainable. Irish research reports confirm that while many hospital-based clinicians view research as essential, most lack protected time to participate meaningfully (Leddy et al., 2020; Kyung Ha et al., 2022). Participant attrition, particularly in elderly cohorts, posed a limitation. Progressive illness often resulted in withdrawal before all samples were collected. This underscores the importance of flexible trial designs that accommodate disease trajectories (Campbell et al., 2007). While some assumptions about attrition can be made based on clinical context, we did not collect participant-reported outcomes or survey data to directly capture reasons for missed samples or study withdrawal. This limits our ability to fully understand participant experiences and decision making, particularly regarding sample collection challenges. Timing of consent also emerged as a key factor; at Site C, participants were approached within one week of multidisciplinary team (MDT) discussions, facilitating enrolment. Missed windows at other sites were often due to competing clinical responsibilities or communication gaps, challenges previously identified as key causes of trial inefficiency (Donovan et al., 2014). At Site C, the decision to implement a bespoke clinical database (Castor) was influenced by earlier difficulties with Excel-based tracking in prior biomarker studies. Although this change contributed to early delays, the platform significantly improved data entry, oversight, and team workflow. Support from clinical data specialists helped to optimise procedures and allowed staff to keep pace with participant accrual. This experience highlights the value of early investment in expert clinical data management systems in investigator-led trials. Funding limitations remain a barrier for investigator-initiated studies. Inadequate budgeting and resource planning can lead to premature termination or underperformance (Briel et al., 2021). Site C’s pre-agreed cost neutral model where per-participant fees were approved by hospital management, may not yet be transferable to public hospitals, but showed promise. Had similar financial structures been available at other sites, recruitment and sample acquisition rates may have been higher. Logistical planning also affected performance. The OMNIgene-GUT kit enabled ambient stool sample storage, reducing return barriers (Bolte et al., 2021). However, over-ordering at Site A, where 80% of kits expired unused, highlighted the need for adaptive procurement strategies, again enabled by dedicated staff. A further source of delay involved the requirement for site specific ethics and data protection approvals at each hospital, despite the existence of national research ethics approval (NREC). This duplication is a well-recognised obstacle in the Irish clinical research system. Cancer Trials Ireland and other stakeholders have called for harmonisation of these processes to support timely trial activation. This analysis was not intended to critique any individual or institution, but to highlight the collaborative effort, time, and resources required to deliver academic translational studies. The opportunity to compare three independently implemented MWAS provided a rare and valuable perspective on the operational factors that contribute to study success or failure. These findings offer a foundation for identifying practical strategies to improve future trial setup, recruitment, and biospecimen collection in similar investigator led settings. CONCLUSION This study highlights key factors critical to the success of translational observational studies, including timely recruitment, structured participant management, dedicated clinical research staff, and strategic financial planning. Implementing SWAT methodologies within biospecimen studies could further enhance trial efficiency, optimise participant retention, and improve data quality. These findings offer practical insights to guide the design and delivery of future investigator initiated trials. Abbreviations AC – Academic Clinical Trials Coordinator CREC – Clinical Research Ethics Committee FTE – Full-Time Equivalent GM – Gut Microbiome MDT – Multidisciplinary Team MWAS – Microbiome-Wide Association Study NREC – National Research Ethics Approval PI – Principal Investigator PM – Patient Management RN – Research Nurse SpR – Specialist Registrar SWAT – Study Within A Trial Declarations Ethics approval and consent to participate Ethics approval for each study was obtained from the relevant institutional Clinical Research Ethics Committees (CRECs). Written informed consent was obtained from all participants prior to enrolment. Consent for publication Not applicable. This manuscript does not contain individual person’s data in any form. Availability of data and materials The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The authors wish to acknowledge support relevant to this manuscript from Research Ireland (18/SP/3522) and Breakthrough Cancer Research, as part of the Precision Oncology Ireland consortium. Authors' contributions CD: Data collection, analysis, writing, original draft, revision, project administration RM: Site B clinical leadership, participant recruitment oversight, data interpretation, critical manuscript review CC, RC: Participant recruitment at Site B, trial implementation, manuscript review and input RC (Roisin Connolly): Strategic guidance, manuscript review and editing EC, LR: Regulatory support, academic coordination, manuscript review DC, BB, BH: Site principal investigators, oversight of participant enrolment and ethics submissions, manuscript review MT: Conceptualisation Scientific supervision, project leadership, critical review and final approval of manuscript All authors read and approved the final manuscript. Acknowledgements The authors would like to thank the clinical and administrative staff at the participating study sites for their support, and in particular acknowledge the contribution of the specialist registrars and research nurses who facilitated participant recruitment and follow-up. Authors’ information CD is a postdoctoral researcher at Cancer Research @UCC with experience in translational microbiome and clinical trial logistics research. References AGGARWAL, N., KITANO, S., PUAH, G. R. Y., KITTELMANN, S., HWANG, I. Y. & CHANG, M. W. 2023. Microbiome and Human Health: Current Understanding, Engineering, and Enabling Technologies. Chem Rev, 123 , 31-72. BOLTE, L. A., KLAASSEN, M. A. Y., COLLIJ, V., VICH VILA, A., FU, J., VAN DER MEULEN, T. A., DE HAAN, J. J., VERSTEEGEN, G. J., DOTINGA, A., ZHERNAKOVA, A., WIJMENGA, C., WEERSMA, R. K. & IMHANN, F. 2021. 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Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Annals of internal medicine, 147 , W-163-W-194. WARD, O. & KENNELLY, H. 2019. Review of clinical research infrastructure in Ireland. Supplementary Files Supplementary.docx strobechecklist.docx Cite Share Download PDF Status: Published Journal Publication published 10 Oct, 2025 Read the published version in Journal of Translational Medicine → Version 1 posted Editorial decision: Major revision 10 Jul, 2025 Reviewers agreed at journal 26 Jun, 2025 Reviewers invited by journal 26 Jun, 2025 Editor assigned by journal 21 Jun, 2025 First submitted to journal 20 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6939667","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476846882,"identity":"104396a5-f526-4122-8005-eb4252b40c9a","order_by":0,"name":"Ciaran Devoy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYHACAxAhByIOPAALMDYQpcUYrCWBFC2JYGUJxLiKv4F542OeisPpG64dfgi05bA8UKTxAT4tEgfYio15zhzO3XA7zQCkxXDGAcZmA/yu4jGTnNkG0pIA1pJgwMDYJkFAi/lPoJZ0g9vpH2Ba2n8QsoXhYxtQ5e0chC34dDBIHGYrlvhwJt1w5u2cggMJBumGMw4zNuN1GH9788YPCRXW8ny30zd/+ABk8Le3P/yA1xpmMNkMdydMhCCoI07ZKBgFo2AUjEwAAKtcSxipyFh/AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-3916-2387","institution":"University College Cork College of Medicine and Health","correspondingAuthor":true,"prefix":"","firstName":"Ciaran","middleName":"","lastName":"Devoy","suffix":""},{"id":476846883,"identity":"49644775-d325-45a6-8dfb-55c92d7e9bf0","order_by":1,"name":"Ciarán Devoy","email":"","orcid":"","institution":"University College Cork College of Medicine and Health","correspondingAuthor":false,"prefix":"","firstName":"Ciarán","middleName":"","lastName":"Devoy","suffix":""},{"id":476846884,"identity":"4d38098c-7544-4fff-911e-e9059ef89e82","order_by":2,"name":"Ronan Andrew McLaughlin","email":"","orcid":"","institution":"RCSI: RCSI Dublin","correspondingAuthor":false,"prefix":"","firstName":"Ronan","middleName":"Andrew","lastName":"McLaughlin","suffix":""},{"id":476846885,"identity":"1a0cc07a-c6c1-4f5b-9408-4427101687fc","order_by":3,"name":"Christopher Cronin","email":"","orcid":"","institution":"Cork University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Cronin","suffix":""},{"id":476846886,"identity":"ef3bc89e-6c6a-4930-be1c-9d08ca427716","order_by":4,"name":"Rachel Clarke","email":"","orcid":"","institution":"RCSI: RCSI Dublin","correspondingAuthor":false,"prefix":"","firstName":"Rachel","middleName":"","lastName":"Clarke","suffix":""},{"id":476846887,"identity":"a0f58ee1-c85f-4fe4-a8ae-a69591ba393a","order_by":5,"name":"Roisin M Connolly","email":"","orcid":"","institution":"University College Cork College of Medicine and Health","correspondingAuthor":false,"prefix":"","firstName":"Roisin","middleName":"M","lastName":"Connolly","suffix":""},{"id":476846888,"identity":"f4df29d4-7515-4a46-b45a-d523a99a5f0c","order_by":6,"name":"Erin Crowley","email":"","orcid":"","institution":"University College Cork College of Medicine and Health","correspondingAuthor":false,"prefix":"","firstName":"Erin","middleName":"","lastName":"Crowley","suffix":""},{"id":476846889,"identity":"aac11cbb-eaf3-4020-9c0b-0bcc8398085b","order_by":7,"name":"Laia Raigal","email":"","orcid":"","institution":"University College Cork College of Medicine and Health","correspondingAuthor":false,"prefix":"","firstName":"Laia","middleName":"","lastName":"Raigal","suffix":""},{"id":476846890,"identity":"83655b4c-6b92-4f54-b574-8f7c639f4ed6","order_by":8,"name":"Dearbhaile Collins","email":"","orcid":"","institution":"Cork University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Dearbhaile","middleName":"","lastName":"Collins","suffix":""},{"id":476846891,"identity":"1a36b1a7-95bb-4390-b722-4eef58d11069","order_by":9,"name":"Brian Bird","email":"","orcid":"","institution":"Bon Secours Hospital Cork","correspondingAuthor":false,"prefix":"","firstName":"Brian","middleName":"","lastName":"Bird","suffix":""},{"id":476846892,"identity":"026b0a34-b097-4be3-a670-32f73133baf9","order_by":10,"name":"Bryan T Hennessy","email":"","orcid":"","institution":"RCSI Dublin","correspondingAuthor":false,"prefix":"","firstName":"Bryan","middleName":"T","lastName":"Hennessy","suffix":""},{"id":476846893,"identity":"1e5a81a8-b1b9-4278-b910-d0b5c3cd01ee","order_by":11,"name":"Mark Tangney","email":"","orcid":"","institution":"University College Cork College of Medicine and Health","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Tangney","suffix":""}],"badges":[],"createdAt":"2025-06-20 14:19:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6939667/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6939667/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12967-025-07074-1","type":"published","date":"2025-10-10T15:57:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85746965,"identity":"fbf184c2-8106-49ad-872a-1ef8256df7d3","added_by":"auto","created_at":"2025-07-01 09:36:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":80121,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eParticipant Flow Diagram. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eDetailing the participant’s journey through the various stages from patients with cancer screening after diagnosis to final reporting. The diagram details the sample collection points relative to the course of treatment. For this type of study, discontinuation points can occur at any time, up to the last sample collection point. The time between sample collection points varied between studies, depending on the treatment regime.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/181e0323fb8e6561b6e9c302.jpg"},{"id":85746961,"identity":"baed3f37-5f69-4f5b-98fd-6481793b9610","added_by":"auto","created_at":"2025-07-01 09:36:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38464,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSetup phase breakdown by site.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Study setup phase breakdown by site, highlighting the contribution of dedicated Cancer Trial Administrative staff to setup time efficiency\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/b04a6d26f2b56c2b6f15b0fb.jpg"},{"id":85746962,"identity":"f0e93174-35ff-4d00-b82c-49d68d3c1614","added_by":"auto","created_at":"2025-07-01 09:36:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":47949,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSetup time related to FTE.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Study setup time in days plotted against Full-Time Equivalent (FTE) staffing. Site C is represented in two distinct phases: before (AC−, 274 days) and after (AC+, 185 days) the addition of an Academic Clinical Trials Coordinator, resulting in four data points across the three sites. The Kruskal-Wallis test (p = 0.2592) indicated no statistically significant difference in setup time across staffing levels, but a strong negative Pearson correlation was observed (r = -0.92).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/b2b104eb014e2f40366437f4.jpg"},{"id":85746963,"identity":"3bb08725-5852-4096-aadc-2a55813f44d5","added_by":"auto","created_at":"2025-07-01 09:36:57","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":55401,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTotal number of participants. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003ea) Cumulative participants over time by Site b) Site B broken down by category from screened to having provided a sample. c) Site C broken down by category from screened to having provided a sample.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/8502e3964c1932dfd307daa6.jpg"},{"id":85749037,"identity":"10a93512-421c-43e9-962c-495eb8b6d66c","added_by":"auto","created_at":"2025-07-01 09:52:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79857,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTotal sample numbers. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003ea. b. and c.) Cumulative sample numbers over time broken down by sampling number (1\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e, 2\u003c/em\u003e\u003csup\u003e\u003cem\u003end\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e, 3\u003c/em\u003e\u003csup\u003e\u003cem\u003erd\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e) for each site. d) Illustrates cumulative sample collection for all sampling time points relative to each study from M1, the starting month of each study.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/21a73935ea118c56a88a9084.jpg"},{"id":85746967,"identity":"0a58a6a5-f273-4543-bb6c-8520342f214e","added_by":"auto","created_at":"2025-07-01 09:36:57","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":28358,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAccrual rates.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Rates of participants, and samples per month by study site.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/a9566342e030b2e62468f3c3.jpg"},{"id":93597585,"identity":"e79ad215-2540-43fd-ab92-f056db57ff8c","added_by":"auto","created_at":"2025-10-15 14:16:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1200126,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/e1ca18d9-a4c1-47ac-9176-d60abb0f4b33.pdf"},{"id":85748202,"identity":"05e84781-cff9-479b-9963-6a69c1ffb1ff","added_by":"auto","created_at":"2025-07-01 09:44:57","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":131215,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/c7343e22157ceae7915ce35c.docx"},{"id":85746974,"identity":"5aea1546-0412-4b54-ae51-a694f6d0d68a","added_by":"auto","created_at":"2025-07-01 09:36:57","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":155370,"visible":true,"origin":"","legend":"","description":"","filename":"strobechecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-6939667/v1/785f8db9198fe216c2c2baac.docx"}],"financialInterests":"","formattedTitle":"Operational Determinants of Recruitment and Biospecimen Collection in Translational Observational Studies: A Multi-Site Comparative Analysis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHigh quality translational research is defined by its relevance to urgent health problems, pragmatic study designs, participant centred approaches, cost effectiveness, and transparency. However, many translational studies fall short of these standards, limiting their real-world impact and generalisability (Ioannidis, 2016; Concato et al., 2000). Observational studies, although less resource intensive than randomised trials, face similar challenges in design, regulatory setup, and participant recruitment. Despite growing awareness of these logistical barriers, evidence guiding best practices in trial management remains sparse, particularly outside of large-scale industry funded trials or U.S. based networks. This lack of operational guidance undermines the efficiency of translational research, leading to delayed starts, incomplete data, or trial discontinuation.\u003c/p\u003e \u003cp\u003eParticipant recruitment challenges are frequently cited as the most common cause of delays and trial failure, with difficulties contributing to bias, reduced power, and early closure (Cullati et al., 2016; Galea and Tracy, 2007). Factors such as emotional burden, perceived benefit, and clear communication influence consent, with studies showing that participants are more likely to enrol when supported by dedicated staff and transparent information (Trauth et al., 2000; Jones et al., 2016). However, beyond participant motivation, critical but often overlooked stages include the trial startup phase defined by regulatory and administrative processes and participant and sample management during trial conduct. These stages are especially vulnerable to inefficiencies when trials lack dedicated clinical trials staff and streamlined communication between academic and clinical teams (Donovan et al., 2014; Spilsbury et al., 2008).\u003c/p\u003e \u003cp\u003eIn this report, we analysed three microbiome-wide association studies (MWAS) that were concurrently ongoing at separate cancer centres in Ireland. While the studies shared a common biospecimen based design, they differed in organisational structure, staffing models, and study logistics. By retrospectively comparing these real-world implementations, we sought to identify operational factors that influenced study setup timelines, participant recruitment, and sample acquisition. This analysis builds on the Study Within A Trial (SWAT) concept, which embeds methodological evaluations into real world research to improve trial processes (Treweek et al., 2018). Identifying these determinants offers critical insights for optimising biospecimen related study logistics and enhancing the reliability of future translational research.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e This analysis follows the STROBE checklist guidelines for reporting observational studies, as it is a report covering three studies at separate sites (Vandenbroucke et al., 2007). The methodology included measuring the time from the initial setup of the translational microbiome wide association study (MWAS) to obtaining the consent of the first patient while analysing all the stages and obstacles encountered throughout the process. Furthermore, we examined all the individuals, systems, and institutions involved in this process hierarchically. The study conduct stage of the study involved measuring the rates and total number of participants and sample uptake. Since this analysis compares three studies, a basic understanding of the study design and methodology is also necessary. Descriptive statistics were used to summarise setup times, recruitment rates, sample acquisition, and data completeness across sites. Correlation analyses (Pearson and Spearman) and regression models (negative binomial and linear regression) were applied to explore associations between staffing levels, study setup duration, and participant recruitment. The Kruskal-Wallis test was used to compare setup times across different staffing configurations.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTranslational MWAS design\u003c/h2\u003e \u003cp\u003eTranslational MWAS explore the links between gut microbial communities and cancer progression, including treatment outcomes (Aggarwal et al., 2023). Key elements of the MWAS design were common across all three studies, and important differences will be addressed in the discussion. The primary endpoint was to sequence the gut microbiome (GM) at three time points in the treatment regime of a patient with cancer and to correlate these findings with the efficacy of the treatment. At the time of consent, participants received three OMNIgene\u0026reg;\u0026bull;GUT (OMR-200) home testing kits to collect a stool sample, each labelled with their unique study identifier number. Participants received three stamped addressed envelopes in the appropriate packaging to send stool samples directly to our laboratory for analysis. At each time point, approximately 500 mg of stool sample was to be collected using the kit. The lab for analysis is common to all three studies.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSites\u003c/h3\u003e\n\u003cp\u003eAll study sites involved cancer centres in the Republic of Ireland. Site A was a public hospital, recruitment to the MWAS commenced after a study amendment to an existing translational study. Therefore, all that was required for the initial setup was an amendment to the original ethical approval. The setup began in March 2020, and the study ended in October 2022, due to lack of recruitment. Site B, the second public hospital, began initial study set up in 2021 and is still recruiting at time of writing. Site C, a private cancer centre, also began the initial proceedings in November 2021 and is still recruiting at time of writing. Participants eligibility criteria are shown in supplementary Table\u0026nbsp;1. Site A had a study target of 200 participants, Site B 120 participants, while Site C had a goal of 50 participants.\u003c/p\u003e\n\u003ch3\u003eStudy Setup and Participant Management Team Composition\u003c/h3\u003e\n\u003cp\u003eEach study required the same core tasks. Each team included a consultant medical oncologist (clinical investigator), a scientific principal investigator (PI), and a university-based researcher responsible for coordinating sample logistics and processing across all sites. The number of additional personnel involved varied. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarises the study team composition at each site, organised by study phase (setup and conduct), with roles and task distribution described. Full-Time Equivalent (FTE) staffing levels are noted in the text.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSite A (Existing Study)\u003c/strong\u003e \u003cp\u003eSmallest setup team (3 members), 0 dedicated FTE. No full-time equivalent staff were dedicated solely to study setup activities. The study conduct team consisted of a single research nurse, available for only a four-month period.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSite B (New Study)\u003c/strong\u003e \u003cp\u003eLargest setup team (5 members), with 4 dedicated FTEs in a pre-established clinical trials unit. The study conduct team consisted of one specialist registrar (SpR) at any given time (0 FTE). The SpR was not in a dedicated research role and maintained full clinical responsibilities.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSite C (New Study)\u003c/strong\u003e \u003cp\u003eInitial setup team (3 members), 0 dedicated FTEs. An Academic Clinical Trials Coordinator (AC) and a biostatistician supporting the Castor electronic data capture platform joined the team 270 days into setup, contributing 1 FTE to expedite academic and clinical processes. The study conduct phase had the largest team, with two consultants and two research nurses working on rotation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStudy team composition by site, organised by study phase (setup and conduct).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy Setup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy Conduct\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSite A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsultant Medical Oncologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eClinical Research Nurse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScientific Principal Investigator\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity Researcher\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eSite B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsultant Medical Oncologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eSpecialist Registrar (SpR, not dedicated research role)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBiostatistician\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProgramme Manager, Cancer Clinical Trials Unit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedical Oncology Specialist Registrar (SpR)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResearch Contracts Officer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity Researcher\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eSite C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsultant Medical Oncologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScientific Principal Investigator\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity Researcher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConsultant Medical Oncologist\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData Manager\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior Clinical Research Nurse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior Dietitian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClinical Research Nurses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBiostatistician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcademic Clinical Trials Coordinator (joined later)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCastor Biostatistician (joined later)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eAt Site C, roles added partway through the setup phase (Academic Clinical Trials Coordinator and Castor Biostatistician) are indicated (light blue shading). Full-Time Equivalent (FTE) staffing contributions are described in the Methods.\u003c/em\u003e \u003c/p\u003e\n\u003ch3\u003eParticipant flow through study\u003c/h3\u003e\n\u003cp\u003eFollowing regulatory approvals at each cancer centre, patients with cancer undergoing treatment were assessed for eligibility and invited to participate. Upon providing informed consent, participants agreed to provide up to three stool samples at defined time points relative to their treatment schedule (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Participant eligibility was determined by the consultant medical oncologist. Discontinuation points existed throughout the study period due to factors such as psychological burden, discomfort with stool collection, and advanced disease progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eStudy Setup Times\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDedicated trial administrative staff were a major factor influencing study setup time. The key milestones and delays are summarised in Table 2, while detailed timelines are provided in Supplementary Figure 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 2. Length of time for key milestones and delays.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003cimg width=\"601\" height=\"97\" 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\" alt=\"image\"\u003e\u003c/p\u003e\n\u003cp\u003eAll studies required approvals for ethics from their respective Clinical Research Ethics Committee (CREC), data protection and participant consent. Sites B and C additionally required a material transfer agreement (MTA). Site A had the longest setup phase (390 days for ethics approval, 263 days to first sample) partially due to external factors (COVID-19) and the absence of a dedicated clinical trials team. Site B achieved the fastest ethical approval (\u0026lt;1 month) but faced a 329 day delay for MTA approval on the university side. The first participant sample was collected 51 days post approval. Site C had the slowest setup timeline among new studies (459 days total, 135 days to first sample) due to a delayed setup team formation. However, with the intervention of the AC, setup was completed in 185 days.\u003c/p\u003e\n\u003cp\u003eFigure 2 highlights the relationship between dedicated administrative support and setup efficiency. Site A lacked a dedicated trials team, leading to the longest setup phase. Site B benefitted from a well-established trials team, achieving the fastest ethical approval but facing delays in MTA due to external university level processes. Site C initially featured fragmented stakeholder communication, before the AC intervention reduced MTA approval time from 329 days to 25 days compared with Site B for which the MTA was the biggest contributing factor to delay the study starting.\u003c/p\u003e\n\u003cp\u003eFigure 3 plots Study setup duration against Full-Time Equivalent (FTE) staffing. Site C is represented in two distinct phases, 274 days without the AC and 185 days with, resulting in four data points across the three sites. Although the Kruskal-Wallis test yielded a p-value of 0.2592, indicating no statistically significant difference in setup time across FTE levels, this result is likely influenced by the small sample size (n=4). Despite the lack of significance, the trend remains clear: increased FTE staffing is associated with shorter setup duration, supported by a strong negative Pearson correlation of -0.92\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipant\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003erecruitment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe potential pool of participants were screened for suitability to go on the trial in accordance with the inclusion and exclusion criteria. Eligible patients were approached and informed about the study before starting treatment. Following consent, participants were provided with stool collection kits for at home sampling, with samples mailed directly to the university laboratory. Study design included for participants to be followed up by study conduct team members and reminded to collect samples at predefined time points.\u003c/p\u003e\n\u003cp\u003eFigure 4a details participant recruitment across the three sites from their respective starting month M1. Site A recruited 4 participants in 3\u0026nbsp;months before ceasing enrolment due to the departure of its only study nurse. Site B recruited 21 participants over 20 months. Site C with 2 dedicated trial nurses recruited 20 participants over 16 months, maintaining recruitment until it paused in M13 following one of the trial nurse\u0026rsquo;s departure.\u003c/p\u003e\n\u003cp\u003eComparing Site B (RN-) and Site C (RN+), statistical analyses consistently indicate that research nurse presence was the primary driver of participant recruitment. A negative binomial regression model estimates that the presence of dedicated research nurses increased participant recruitment by 41% (Estimate = 0.4102, p = 0.0557), a trend approaching statistical significance. Importantly, after adjusting for nurse presence, there was no significant difference in recruitment rates between Site B (RN-) and Site C (RN+) (p = 0.7169), confirming that staffing levels, not site-specific factors, were the key determinant of success.\u003c/p\u003e\n\u003cp\u003eA critical observation was that recruitment at Site C (RN+) paused after M13 when a lead research nurse left, despite the trial continuing. Site B (RN-), without research nurses, demonstrated slow but steady recruitment throughout. This aligns with correlation analyses (Spearman\u0026rsquo;s rho = 0.3999, p = 0.08; Pearson\u0026rsquo;s r = 0.4182, p = 0.066) and linear regression models (Estimate = 1.01, p = 0.066), all of which indicate a strong positive relationship between nurse presence and participant recruitment. While just outside the standard statistical significance threshold, the consistency of results across methods suggests that additional data could confirm this effect with greater certainty.\u003c/p\u003e\n\u003cp\u003eIn terms of participant category numbers, Figure 4b details participant flow at Site B. Potential participant numbers were estimated based on a 20% screening rate. However, no data were recorded for participants who were excluded, declined, or missed screening, limiting retrospective insight into enrolment efficiency and missed opportunities. Six consented participants missed their first sample, and 15 missed a follow-up sample.\u003c/p\u003e\n\u003cp\u003eAt Site C, participant flow was recorded more comprehensively (Figure 4c). Of 45 potential participants, six did not meet the inclusion criteria, 11 missed the screening opportunity (yielding a 75% screening rate), and five declined participation. Three participants discontinued prior to providing a sample. No follow-up timepoints were missed.\u003c/p\u003e\n\u003cp\u003eSite C therefore demonstrated the highest level of data completeness, defined here as the extent to which participant screening, exclusions, declines, missed samples, and follow-up status were documented. This enabled more accurate evaluation of recruitment and retention. By contrast, Site B\u0026rsquo;s limited screening and exclusion records impeded retrospective analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample acquisition rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePercentage sample acquisition is taken to be a primary measure of success and refers to the % of potential samples from consented participants successfully collected. This takes into account missed follow-up participant sample numbers, while reducing bias due to differences in treatment regimen kinetics. Figure 6d details sample accumulation across all timepoints.\u003c/p\u003e\n\u003cp\u003eSite A (RN+) % sample acquisition = 100. Figure 5a displays cumulative sample numbers at Site A. 10 samples were collected before trial discontinuation with zero missed follow-up samples. The T2 and T3 samples were technically not missed for participant #4, as the study was terminated before they were due to be collected.\u003c/p\u003e\n\u003cp\u003eSite B (RN-) % sample acquisition = 70.5. Figure 5b displays cumulative sample numbers at Site B which accumulated 36 total samples over 20 months, with gaps in T2 and T3 because of missed follow-ups due to staffing limitations. 21 T1 samples, 10 T2 samples, and 5 T3 samples were collected. Sample collection was staggered, with long intervals between T1 and T2 (119 days avg, SD = 58.3) and T2 and T3 (183 days avg, SD = 16), which corelates with the longer treatment regimens of this site relative to the others with 14 missed follow-up samples.\u003c/p\u003e\n\u003cp\u003eSite C (RN+) % sample acquisition = 100. Figure 5c shows cumulative sample collection at Site C where 54 total samples were collected in 16 months. The shorter treatment regimen facilitated faster completion of the three sampling timepoints. 20 T1 samples, 18 T2 samples, 16 T3 samples were collected, with a continuous collection pattern with shorter T1\u0026ndash;T2 (23.7 days avg, SD = 5.2) and T2\u0026ndash;T3 (59.6 days avg, SD = 10.4) intervals. There were no missed follow-up samples. The only discrepancies between participant T1, T2 and T3 sample collection were because of morbidity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSite Participant and Sample Temporal Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBy analysing cumulative participant and sample numbers, monthly accrual rates were calculated (Figure 6). Site C (RN+)) displayed the highest accrual rates (participants: 1.3/month, samples: 3.6/month). Despite a three-month gap in participant recruitment (M7\u0026ndash;M10), sample collection never dropped to zero. Site A (RN+)): Although only briefly in operation, participant recruitment matched Site C (participants: 1.3/month, samples: 2.5/month). Site B (RN-)): shows the lowest rates (participants: 1.1/month, samples: 1.8/month). Six months of zero growth represented 33% of its operational period.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003e Our findings demonstrate that the availability of dedicated staff for study setup and study conduct played a pivotal role in successful delivery, including improved participant recruitment, sample acquisition, and reduced delays. In contrast, poor recruitment and missed follow-up points were often associated with understaffing or administrative bottlenecks. A strong negative correlation (r = -0.92) between full-time equivalent (FTE) staffing and setup time supports the value of dedicated personnel, though statistical significance was not reached due to the small sample size (p\u0026thinsp;=\u0026thinsp;0.26). Site B, with four FTE staff, completed ethical approval in just 30 days. In contrast, sites with no dedicated setup personnel required 274 to 390 days. Site B's progress was later hindered by university legal office delays in securing a material transfer agreement, demonstrating the need for simplified regulatory frameworks, an issue echoed across European research settings (Mills et al., 2006). At all sites, clinical investigators contributed to protocol development, ethics submissions, and data protection assessments outside of protected time, often during personal hours. This structural under-resourcing is common in academic-led research and may have contributed to early delays in study activation.\u003c/p\u003e \u003cp\u003eStudy team composition and structure were key to managing workload and ensuring continuity. Site C\u0026rsquo;s addition of an AC notably accelerated study setup, illustrating the impact of specialised administrative roles. During study conduct, teams with dedicated clinical research nurses (e.g., Site C) achieved higher recruitment, retention, and sample completeness compared to sites reliant on rotating or non-research dedicated staff. Site C demonstrated complete sample collection and record keeping, reflecting high data completeness. Defined as the extent to which screening, exclusions, missed follow-ups, and other participant metrics were captured, this allowed for more robust retrospective analysis. Site B\u0026rsquo;s lack of such data limited its evaluability. Follow-up adherence also varied by staffing model: Site C missed no follow-up samples, while Site B missed 15. At Site B, annual handovers and the absence of structured study conduct processes disrupted continuity. These challenges are consistent with broader findings about the need for sustainable staffing models and institutional support for clinical research delivery (Ward and Kennelly, 2019).\u003c/p\u003e \u003cp\u003e Participant involvement was influenced by emotional, logistical, and disease-related factors. The psychological burden of a cancer diagnosis and discomfort with stool sampling may have deterred some from consenting (Thompson et al., 2017). At Site C, early contact and structured follow-up, led by research nurses, contributed to consistent accrual. Site B, relying on a single specialist registrar (SpR) not in a dedicated research role, experienced intermittent recruitment. While some institutions may have SpRs with protected research time, this was not the case at Site B. The absence of dedicated research staff contributed to missed opportunities and sample loss; a challenge not frequently cited in literature but evident in our analysis. Despite systemic constraints in public hospitals, committed individuals such as SpRs supported recruitment efforts. However, this reliance demands high personal investment and is rarely sustainable. Irish research reports confirm that while many hospital-based clinicians view research as essential, most lack protected time to participate meaningfully (Leddy et al., 2020; Kyung Ha et al., 2022).\u003c/p\u003e \u003cp\u003eParticipant attrition, particularly in elderly cohorts, posed a limitation. Progressive illness often resulted in withdrawal before all samples were collected. This underscores the importance of flexible trial designs that accommodate disease trajectories (Campbell et al., 2007). While some assumptions about attrition can be made based on clinical context, we did not collect participant-reported outcomes or survey data to directly capture reasons for missed samples or study withdrawal. This limits our ability to fully understand participant experiences and decision making, particularly regarding sample collection challenges. Timing of consent also emerged as a key factor; at Site C, participants were approached within one week of multidisciplinary team (MDT) discussions, facilitating enrolment. Missed windows at other sites were often due to competing clinical responsibilities or communication gaps, challenges previously identified as key causes of trial inefficiency (Donovan et al., 2014). At Site C, the decision to implement a bespoke clinical database (Castor) was influenced by earlier difficulties with Excel-based tracking in prior biomarker studies. Although this change contributed to early delays, the platform significantly improved data entry, oversight, and team workflow. Support from clinical data specialists helped to optimise procedures and allowed staff to keep pace with participant accrual. This experience highlights the value of early investment in expert clinical data management systems in investigator-led trials.\u003c/p\u003e \u003cp\u003eFunding limitations remain a barrier for investigator-initiated studies. Inadequate budgeting and resource planning can lead to premature termination or underperformance (Briel et al., 2021). Site C\u0026rsquo;s pre-agreed cost neutral model where per-participant fees were approved by hospital management, may not yet be transferable to public hospitals, but showed promise. Had similar financial structures been available at other sites, recruitment and sample acquisition rates may have been higher. Logistical planning also affected performance. The OMNIgene-GUT kit enabled ambient stool sample storage, reducing return barriers (Bolte et al., 2021). However, over-ordering at Site A, where 80% of kits expired unused, highlighted the need for adaptive procurement strategies, again enabled by dedicated staff. A further source of delay involved the requirement for site specific ethics and data protection approvals at each hospital, despite the existence of national research ethics approval (NREC). This duplication is a well-recognised obstacle in the Irish clinical research system. Cancer Trials Ireland and other stakeholders have called for harmonisation of these processes to support timely trial activation.\u003c/p\u003e \u003cp\u003eThis analysis was not intended to critique any individual or institution, but to highlight the collaborative effort, time, and resources required to deliver academic translational studies. The opportunity to compare three independently implemented MWAS provided a rare and valuable perspective on the operational factors that contribute to study success or failure. These findings offer a foundation for identifying practical strategies to improve future trial setup, recruitment, and biospecimen collection in similar investigator led settings.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study highlights key factors critical to the success of translational observational studies, including timely recruitment, structured participant management, dedicated clinical research staff, and strategic financial planning. Implementing SWAT methodologies within biospecimen studies could further enhance trial efficiency, optimise participant retention, and improve data quality. These findings offer practical insights to guide the design and delivery of future investigator initiated trials.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eAC\u003c/strong\u003e \u0026ndash; Academic Clinical Trials Coordinator\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCREC\u003c/strong\u003e \u0026ndash; Clinical Research Ethics Committee\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFTE\u003c/strong\u003e \u0026ndash; Full-Time Equivalent\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eGM\u0026nbsp;\u003c/strong\u003e\u0026ndash; Gut Microbiome\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMDT\u003c/strong\u003e \u0026ndash; Multidisciplinary Team\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMWAS\u003c/strong\u003e \u0026ndash; Microbiome-Wide Association Study\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNREC\u0026nbsp;\u003c/strong\u003e\u0026ndash; National Research Ethics Approval\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePI\u0026nbsp;\u003c/strong\u003e\u0026ndash; Principal Investigator\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePM\u003c/strong\u003e \u0026ndash; Patient Management\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eRN\u003c/strong\u003e \u0026ndash; Research Nurse\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSpR\u003c/strong\u003e \u0026ndash; Specialist Registrar\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSWAT\u003c/strong\u003e \u0026ndash; Study Within A Trial\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval for each study was obtained from the relevant institutional Clinical Research Ethics Committees (CRECs). Written informed consent was obtained from all participants prior to enrolment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This manuscript does not contain individual person\u0026rsquo;s data in any form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to acknowledge support relevant to this manuscript from Research Ireland (18/SP/3522) and Breakthrough Cancer Research, as part of the Precision Oncology Ireland consortium.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;CD: Data collection, analysis, writing, original draft, revision, project administration\u003cbr\u003e\u0026nbsp;RM: Site B clinical leadership, participant recruitment oversight, data interpretation, critical manuscript review\u003cbr\u003e\u0026nbsp;CC, RC: Participant recruitment at Site B, trial implementation, manuscript review and input\u003cbr\u003e\u0026nbsp;RC (Roisin Connolly): Strategic guidance, manuscript review and editing\u003cbr\u003e\u0026nbsp;EC, LR: Regulatory support, academic coordination, manuscript review\u003cbr\u003e\u0026nbsp;DC, BB, BH: Site principal investigators, oversight of participant enrolment and ethics submissions, manuscript review\u003cbr\u003e\u0026nbsp;MT: Conceptualisation Scientific supervision, project leadership, critical review and final approval of manuscript\u003cbr\u003e\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors would like to thank the clinical and administrative staff at the participating study sites for their support, and in particular acknowledge the contribution of the specialist registrars and research nurses who facilitated participant recruitment and follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;CD is a postdoctoral researcher at Cancer Research @UCC with experience in translational microbiome and clinical trial logistics research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAGGARWAL, N., KITANO, S., PUAH, G. 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Review of clinical research infrastructure in Ireland.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Translational research, Study setup, Research nurse, Recruitment efficiency, Biospecimen collection, Operational determinants, Observational studies","lastPublishedDoi":"10.21203/rs.3.rs-6939667/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6939667/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBiospecimen collection from study participants is essential for translational research, but operational challenges in study setup and conduct often impede successful delivery. This study uses a comparative approach to identify key logistical and staffing determinants influencing setup duration, recruitment efficiency, sample acquisition, and data completeness across three investigator-led microbiome-wide association studies (MWAS) conducted at cancer centres in Ireland.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThree academic observational MWAS enrolling participants with cancers of the breast, gastrointestinal tract, lung, biliary system, kidney, and skin were compared. Data from three cancer centres were analysed. Key variables included study team composition, administrative infrastructure, and full-time equivalent (FTE) research staffing. Metrics assessed included setup duration, recruitment rates, sample acquisition, and data completeness. Descriptive statistics, correlation analyses, and regression models were used to evaluate relationships between staffing and study performance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSetup duration ranged from 30 days (Site B, with a pre-established trials unit) to 390 days (Site A, with no dedicated setup personnel). At Site C, the addition of an Academic Clinical Trials Coordinator reduced the remaining setup timeline from 274 to 185 days. Recruitment rates ranged from 1.1 to 1.3 participants/month, with the highest rates at sites with dedicated research nurses (RN+). Sample acquisition was 100% at RN\u0026thinsp;+\u0026thinsp;sites and 70.5% at the RN\u0026thinsp;\u0026minus;\u0026thinsp;site. Site C achieved full data completeness, defined as comprehensive documentation of screening, exclusions, and follow-up outcomes. Statistical modelling indicated that dedicated staffing (both administrative and clinical) was strongly associated with improvements across all metrics, although sample size limited statistical significance.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eDedicated administrative and clinical trial personnel significantly enhance study efficiency, participant recruitment, and biospecimen collection in academic translational research. This study provides practical insights for improving study design and infrastructure planning in future observational studies. To our knowledge, this is the first multi-site comparative evaluation of operational determinants in academic MWAS, and it offers actionable strategies to streamline translational study delivery, improve biospecimen quality, and strengthen real-world research infrastructure.\u003c/p\u003e","manuscriptTitle":"Operational Determinants of Recruitment and Biospecimen Collection in Translational Observational Studies: A Multi-Site Comparative Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 09:36:52","doi":"10.21203/rs.3.rs-6939667/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2025-07-10T08:26:22+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-06-26T12:33:33+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-26T11:47:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-21T12:25:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Translational Medicine","date":"2025-06-20T10:19:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a8d877c1-a5dc-47a4-9a67-b2fba3c163c1","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-13T16:03:11+00:00","versionOfRecord":{"articleIdentity":"rs-6939667","link":"https://doi.org/10.1186/s12967-025-07074-1","journal":{"identity":"journal-of-translational-medicine","isVorOnly":false,"title":"Journal of Translational Medicine"},"publishedOn":"2025-10-10 15:57:24","publishedOnDateReadable":"October 10th, 2025"},"versionCreatedAt":"2025-07-01 09:36:52","video":"","vorDoi":"10.1186/s12967-025-07074-1","vorDoiUrl":"https://doi.org/10.1186/s12967-025-07074-1","workflowStages":[]},"version":"v1","identity":"rs-6939667","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6939667","identity":"rs-6939667","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}