O-EGS06 Trials and Tribulations: Educational Impact and Recommendations from the Implementation of Student-Led Recruitment in a Clinical Trial

Abstract Background Medical students have an essential role in medical research, yet often feel unprepared and lack opportunities for involvement as recruiters within research studies. This study aimed to understand the educational effect of involvement in clinical trial recruitment on medical students, and to derive generalisable future recommendations. Methods Tracking wound infection with smartphone technology (TWIST) was a randomised controlled trial enrolling adult emergency abdominal surgery patients across two university teaching hospitals. All recruiters underwent pre-recruitment training based on “Generating Student Recruiters for Randomised Trials” (GRANULE) principles, and completed pre-and post-recruitment surveys. Respondent agreement with statements were assessed using 5-point Likert scales (from 1 [“strongly disagree”] to 5 [“strongly agree”]). Quantitative data were analysed using paired t-tests to compare differences pre- and post-involvement, and a thematic analysis approach adopted for anonymised free-text answers. Results Of 492 patients recruited to TWIST from 2016 to 2020, 86.0% (n = 423) were recruited by medical students. Following student involvement, the monthly recruitment rate tripled (4.8 to 15.7 patients). Thirty student recruiters (96.8%), completed both surveys, reporting significant improvements in clinical and academic competencies. This included increased confidence in gaining and documenting consent, as well as interest in pursuing a clinical-academic career. Over half (58.2%) felt the undergraduate curriculum had not prepared them for involvement in clinical trials (mean:2.47, SD: 0.94). There were three emergent themes regarding recommendations for involvement of students, based on their engagement, preparation, and support during recruitment. Conclusions Student recruitment in clinical trials is feasible and provides a route to developing a research-active medical workforce. It also accelerates recruitment to clinical trials, as well as benefiting students through development of clinical competencies and provision of additional exposure to research. Adequate training, support, and selection of suitable trials are essential for successful student engagement.

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A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data

Applied Clinical Informatics ◽

10.1055/s-0041-1733846 ◽

2021 ◽

Vol 12 (04) ◽

pp. 816-825

Author(s):

Yingcheng Sun ◽

Alex Butler ◽

Ibrahim Diallo ◽

Jae Hyun Kim ◽

Casey Ta ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Electronic Health Records ◽

The United States ◽

Design Stage ◽

Common Data Model ◽

Free Text ◽

Eligibility Criteria ◽

Health Records ◽

Electronic Health

Abstract Background Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population. Objectives This research aims to estimate the population representativeness of clinical trials systematically using EHR data during the early design stage. Methods We present an end-to-end analytical framework for transforming free-text clinical trial eligibility criteria into executable database queries conformant with the Observational Medical Outcomes Partnership Common Data Model and for systematically quantifying the population representativeness for each clinical trial. Results We calculated the population representativeness of 782 novel coronavirus disease 2019 (COVID-19) trials and 3,827 type 2 diabetes mellitus (T2DM) trials in the United States respectively using this framework. With the use of overly restrictive eligibility criteria, 85.7% of the COVID-19 trials and 30.1% of T2DM trials had poor population representativeness. Conclusion This research demonstrates the potential of using the EHR data to assess the clinical trials population representativeness, providing data-driven metrics to inform the selection and optimization of eligibility criteria.

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2166

Journal of Clinical and Translational Science ◽

10.1017/cts.2017.59 ◽

2017 ◽

Vol 1 (S1) ◽

pp. 12-12

Author(s):

Jianyin Shao ◽

Ram Gouripeddi ◽

Julio C. Facelli

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Power Distribution ◽

Large Scale ◽

Search Space ◽

Free Text ◽

Eligibility Criteria ◽

Clinical Notes ◽

Semantic Concepts ◽

Mimic Iii

OBJECTIVES/SPECIFIC AIMS: This poster presents a detailed characterization of the distribution of semantic concepts used in the text describing eligibility criteria of clinical trials reported to ClincalTrials.gov and patient notes from MIMIC-III. The final goal of this study is to find a minimal set of semantic concepts that can describe clinical trials and patients for efficient computational matching of clinical trial descriptions to potential participants at large scale. METHODS/STUDY POPULATION: We downloaded the free text describing the eligibility criteria of all clinical trials reported to ClinicalTrials.gov as of July 28, 2015, ~195,000 trials and ~2,000,000 clinical notes from MIMIC-III. Using MetaMap 2014 we extracted UMLS concepts (CUIs) from the collected text. We calculated the frequency of presence of the semantic concepts in the texts describing the clinical trials eligibility criteria and patient notes. RESULTS/ANTICIPATED RESULTS: The results show a classical power distribution, Y=210X(−2.043), R2=0.9599, for clinical trial eligibility criteria and Y=513X(−2.684), R2=0.9477 for MIMIC patient notes, where Y represents the number of documents in which a concept appears and X is the cardinal order the concept ordered from more to less frequent. From this distribution, it is possible to realize that from the over, 100,000 concepts in UMLS, there are only ~60,000 and 50,000 concepts that appear in less than 10 clinical trial eligibility descriptions and MIMIC-III patient clinical notes, respectively. This indicates that it would be possible to describe clinical trials and patient notes with a relatively small number of concepts, making the search space for matching patients to clinical trials a relatively small sub-space of the overall UMLS search space. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results showing that the concepts used to describe clinical trial eligibility criteria and patient clinical notes follow a power distribution can lead to tractable computational approaches to automatically match patients to clinical trials at large scale by considerably reducing the search space. While automatic patient matching is not the panacea for improving clinical trial recruitment, better low cost computational preselection processes can allow the limited human resources assigned to patient recruitment to be redirected to the most promising targets for recruitment.

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Barriers to participation in breast cancer trials

Journal of Clinical Oncology ◽

10.1200/jco.2007.25.18_suppl.6593 ◽

2007 ◽

Vol 25 (18_suppl) ◽

pp. 6593-6593

Author(s):

O. Herasme ◽

J. Goldberg ◽

R. Sandoval ◽

C. Harris ◽

Y. Ortiz-Pride ◽

...

Keyword(s):

Breast Cancer ◽

Clinical Trial ◽

Clinical Trials ◽

Child Care ◽

Cancer Patients ◽

Controlled Trial ◽

Demographic Factors ◽

Trial Participation ◽

Barriers To Participation ◽

Cancer Trials

6593 Background: Clinical cancer trials allow investigators to test the effectiveness and safety of new cancer drugs and treatments. Historically, fewer that 5% of cancer patients have participated in clinical trials. The purpose of this study was to assess attitudes, beliefs, and practical barriers to clinical trial recruitment. Methods: Women were recruited in the Herbert Irving Comprehensive Cancer Center while waiting for routine breast screening or for oncology care in connection with a diagnosis of breast cancer. The 29-item survey questionnaire covered demographic factors, prior cancer diagnosis or risk factors, past experience with clinical trials if any, willingness to participate in different types of trials, and attitudinal and practical barriers to participation. Results: Of 329 respondents, 48.9% were non- Hispanic white, 10.9% non-Hispanic black, 34.9% Hispanic, and 5.30% other/unknown. The mean age of participants was 52.5 (SD=12.1). Of 131 (39.8%) participants reporting that they had been asked to participate in clinical trial, 82 were white, 17 black and 32 Hispanic. Of those who enrolled, 64 were white, 14 were black, and 19 Hispanic. Of those asked to participate 56/63 breast cancer patients (88.9%) and 44/68 others (64.7%) enrolled (P=0.002). Of 48 who reported that they had child care responsibilities, 33 enrolled (68.8) compared to 67/83 (80.7%) of those without such responsibilities (P=0.07). Of the total sample, 88/220 (40.0%) of those without childcare responsibilities but only 32/109 (29.4) said they would be willing to participate in a placebo-controlled trial. Respondents were twice as likely to say they would participate in a trial comparing two active agents as a placebo-controlled trial. Conclusion: Our findings suggest that being asked to participate in a clinical trial may be associated with demographic factors, and that specific circumstances, such as child care responsibilities, may also affect trial participation. Awareness of these barriers may help investigators to develop effective strategies for overcoming them and for improving trial participation overall. No significant financial relationships to disclose.

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Feasibility of cancer clinical trial enrollment goals based on cancer incidence.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.30_suppl.20 ◽

2018 ◽

Vol 36 (30_suppl) ◽

pp. 20-20

Author(s):

George Nhat Tran ◽

Matthew Harker ◽

Karen Chiswell ◽

Joseph M. Unger ◽

Mark Fleury ◽

...

Keyword(s):

Clinical Trial ◽

Cancer Diagnosis ◽

Cancer Incidence ◽

Recruitment Rate ◽

Free Text ◽

Medical Subject Headings ◽

Cancer Society ◽

The Us ◽

Clinical Trial Enrollment ◽

Suboptimal Design

20 Background: More than 20% of US clinical trials fail to accrue sufficient patients and terminate prematurely, impeding innovation and negating the valuable contributions of participating patients. The aim of this study is to estimate availability of patients for each trial opening in the national oncology clinical research portfolio to provide a benchmark for better understanding feasibility of clinical trial enrollment goals. Methods: The Database for Aggregate Analysis of ClinicalTrials.gov, up-to-date as of September 3, 2017, was used to identify actively-recruiting, interventional oncology trials at US sites. Observational studies were excluded as not all are registered. Trials were categorized via Medical Subject Headings or free text condition terms and sorted by cancer diagnosis. Trial slot availability was estimated between September 1, 2017, to August 31, 2018. Availability was estimated from total anticipated enrollment, assuming a constant recruitment rate. Estimates for studies with both foreign and US sites were pro-rated to calculate available enrollment in the US alone. The 2017 American Cancer Society cancer incidence estimates were used to approximate total US cancer diagnoses. Results: 4598 oncology trials were identified. Overall, an estimated 12.6 cancer patients are available for each clinical trial slot. The estimates by cancer diagnosis were: colorectal: 24.7 patients per trial slot; lung & bronchus: 20.1; prostate: 17.6; breast (female): 13.8; leukemia 11.6; and brain & other nervous system: 6.0. Conclusions: Across all diagnoses, 1 in 13 patients must enroll to meet accrual demands. This ratio varies by diagnosis. If cancer incidence is too low, trials with unrealistic accrual goals may be doomed at inception. In diagnoses with high disease burden, trial failure may be due to poor patient access or suboptimal design. [Table: see text]

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Trifluoperazine (“Stelazine”) a Controlled Clinical Trial in Chronic Schizophrenia

Journal of Mental Science ◽

10.1192/bjp.107.447.250 ◽

1961 ◽

Vol 107 (447) ◽

pp. 250-257 ◽

Cited By ~ 7

Author(s):

W. J. Stanley ◽

D. Walton

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Controlled Trial ◽

Pernicious Anaemia ◽

Chronic Schizophrenia ◽

Mental Illnesses ◽

Controlled Clinical Trial ◽

Vitamin B ◽

Uncontrolled Trial ◽

New Compounds

So many new compounds are now being introduced for the treatment of psychiatric disorders that it is difficult for the clinician to assess the accuracy of the claims made for them. If a form of therapy is one hundred per cent. effective in a disease which was previously one hundred per cent. fatal, for example vitamin B12 in pernicious anaemia, the question of a controlled trial does not arise. But even the manufacturers do not claim such a degree of effectiveness for drugs advocated for the treatment of mental illnesses, and in addition the natural course of such illnesses is very variable, so that it is essential that clinical trials of these drugs should be controlled. Foulds (1958) has reviewed British and American clinical trials of drugs in psychiatry during the years 1951 to 1956, and has shown that the less controlled a trial, the more likely it is to result in a favourable report on the drug being tested, presumably because of bias on the part of the clinician. Forrester (1958), however, on the basis of a completely uncontrolled trial of Stelazine on only twenty-five patients, concluded that “the amount of improvement in a few cases was not sufficient to encourage the further use of the drug”.

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Knowledge of medical students on clinical trials

International Journal of Basic & Clinical Pharmacology ◽

10.18203/2319-2003.ijbcp20192584 ◽

2019 ◽

Vol 8 (7) ◽

pp. 1484

Author(s):

Ravi Shankar Kanna ◽

Jagadeesh Alla ◽

Krishnakanth K.

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Medical Students ◽

Basic Research ◽

Thinking Skills ◽

Cross Sectional Study ◽

Critical Thinking Skills ◽

School Students ◽

Cross Sectional ◽

Institutional Ethics

Background: Basic research can help medical school students improve critical thinking skills required by medical practice. In this era of evidence-based medicine, the combination of medical education with clinical research is the key to ensure scientific discoveries are translated into clinical practice. This study’s objective was to know the awareness about clinical trials among undergraduate medical students.Methods: After obtaining approval from the Institutional Ethics Committee of NRI Academy of Medical Sciences, Guntur, India, this cross sectional study was conducted in second year medical students after taking their consent. A sample of 90was considered for statistical analysis. A structured questionnaire was used to measure the objective of this study, which had general, regulatory and ethical questions related to clinical trials. Qualitative data variables were expressed by using frequency and Percentage (%).Results: Out of 90 students, it was observed that in the general questions category, 70% of students were aware of the purpose of conducting clinical trials, 50% were aware of the pre-requisites for a participant before participating in a clinical trial and 50% were aware of the parameters evaluated in a clinical trial. 95% of students did not know the response for regulatory questions. The students’ awareness regarding ethics related to clinical trials was better than the other two categories.Conclusions: The overall awareness of clinical trials was low among students though they demonstrated good awareness regarding few aspects of clinical trials.

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Using A Behavioral Model to Assess The Barriers And Facilitators to Engaging Local Healthcare Providers In Conducting Interventional Cancer Trials In Nigeria

10.21203/rs.3.rs-122162/v1 ◽

2020 ◽

Author(s):

Abiola Ibraheem ◽

Mojisola Oluwasanu ◽

Akinsegun Akinbami ◽

Akinyimika Sowunmi ◽

Stella Odedina ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Healthcare Providers ◽

Behavioral Model ◽

University Teaching ◽

Cancer Clinical Trials ◽

Structured Interviews ◽

Low Middle Income Countries ◽

Baseline Knowledge ◽

Local Healthcare

Abstract BACKGROUND: Globalization of cancer clinical trials is now involving low middle income countries such as Nigeria as a rationale for global equity. With this ongoing clinical trial globalization, it is important to engage stakeholders such as local providers at the institutions where these trials are conducted by improving knowledge and perception of local providers concerning clinical trials.METHODS: This is a qualitative focused group study consisting of ten groups conducted at Lagos State University Teaching Hospital between November 2019 and January 2020 using locally developed probe questions to engage local providers according to departments. Transcripts of semi-structured interviews was analyzed using direct content analysis and was mapped against the implementation theory of capability, opportunity and motivation for behavior change(COM-B) to access the challenges and barriers reported by local providers. RESULTS: 239 local providers participated in this study, the challenges identified by providers were low knowledge about clinical trials, poor attitudes and systemic barriers. The opportunities suggested by local providers to improve the conduct of clinical trial in that environ included clinical trial workshops to improve baseline knowledge and perception and team collaboration between providers. CONCLUSION: As cancer clinical trials are being globalized, the local healthcare community should be brought to par with this new intervention and not be left behind. Training about clinical trials should not be limited to providers actively involved in the clinical trials but all the providers in that region should be empowered by improving the baseline knowledge and perception of clinical trials.

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Rate of patient’s Recruitment and Recruitment Derivatives from the Perspectives of Internal factors - Protocol Study Nosology, Experience of Investigators and Potential Patient’s Pool of Sites

10.54026/cjct/1007 ◽

2021 ◽

Vol 2 (2) ◽

pp. 1-6

Author(s):

Svyatoslav Milovanov

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Statistical Analysis ◽

Retrospective Analysis ◽

Analysis Data ◽

Recruitment Rate ◽

Internal Factor ◽

Internal Factors ◽

Study Recruitment ◽

Protocol Study

The recruitment as a process found by many authors to be undergoing of many factors. There is a factors which are decreasing the recruitment and last data is reporting up to 80% trials failed due to law or even absence of recruitment on level of sites. But the factors are differently changing the recruitment. The final number of recruitment is static figure very well known, there is also known speed of recruitment which is calculating in the start of the study and these parameters along with others is quantitative evaluation of recruitment. We investigated the rate of recruitment in the light of some factors using parameters reflecting the recruitment progress of recruitment. Materials and Methods: Retrospective analysis of data of four clinical trials II-III phases in oncology and hematology, conducted since 2007 to 2017 years. Study objectives: to investigate the study recruitment rate using different parameters and its changes along with acting of internal factors; to develop new parameters which could be sensitive for evaluation of factor’s action. Statistical analysis: data had been collected from feasibility questionnaires, open statistical sources. Results: It was determined rate of recruitment and its derivatives where was acting an internal factor. Discussion: Recruitment been undergone the internal factors. The way of action is multidirectional and could boost the recruitment and in opposite to decrease one and knowing it is important in success of recruitment and clinical trial itself eventually

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Challenges for funders in monitoring compliance with policies on clinical trials registration and reporting: analysis of funding and registry data in the UK

BMJ Open ◽

10.1136/bmjopen-2019-035283 ◽

2020 ◽

Vol 10 (2) ◽

pp. e035283 ◽

Cited By ~ 1

Author(s):

Rachel L Knowles ◽

Kam Pou Ha ◽

Julia Mueller ◽

Frances Rawle ◽

Rosa Parker

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Medical Research ◽

Research Funding ◽

Controlled Trial ◽

Monitoring Systems ◽

Clinical Trial Registry ◽

Funding Body ◽

The Uk ◽

Research Funding Body

ObjectivesTo evaluate compliance by researchers with funder requirements on clinical trial transparency, including identifying key areas for improvement; to assess the completeness, accuracy and suitability for annual compliance monitoring of the data routinely collected by a research funding body.DesignDescriptive analysis of clinical trials funded between February 2011 and January 2017 against funder policy requirements.SettingPublic medical research funding body in the UK.Data sourcesRelevant clinical trials were identified from grant application details, post-award grant monitoring systems and the International Standard Randomised Controlled Trial Number (ISRCTN) registry.Main outcome measureThe proportion of all Medical Research Council (MRC)-funded clinical trials that were (a) registered in a clinical trial registry and (b) publicly reported summary results within 2 years of completion.ResultsThere were 175 grants awarded that included a clinical trial and all trials were registered in a public trials registry. Of 62 trials completed for over 24 months, 42 (68%) had publicly reported the main findings by 24 months after trial completion; 18 of these achieved this within 12 months of completion. 11 (18%) trials took >24 months to report and 9 (15%) completed trials had not yet reported findings. Five datasets were shared with other researchers.ConclusionsCompliance with the funder policy requirements on trial registration was excellent. Reporting of the main findings was achieved for most trials within 24 months of completion; however, the number of unreported trials remains a concern and should be a focus for future funder policy initiatives. Identifying trials from grant management and grant monitoring systems was challenging therefore funders should ensure investigators reliably provide trial registries with information and regularly update entries with details of trial publications and protocols.

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A natural language processing tool for automatic identification of new disease and disease progression: Parsing text in multi-institutional radiology reports to facilitate clinical trial eligibility screening.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.1555 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 1555-1555

Author(s):

Eric J. Clayton ◽

Imon Banerjee ◽

Patrick J. Ward ◽

Maggie D Howell ◽

Beth Lohmueller ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Natural Language Processing ◽

Natural Language ◽

Disease Progression ◽

Language Processing ◽

Free Text ◽

New Disease ◽

Radiology Reports ◽

Precision And Accuracy

1555 Background: Screening every patient for clinical trials is time-consuming, costly and inefficient. Developing an automated method for identifying patients who have potential disease progression, at the point where the practice first receives their radiology reports, but prior to the patient’s office visit, would greatly increase the efficiency of clinical trial operations and likely result in more patients being offered trial opportunities. Methods: Using Natural Language Processing (NLP) methodology, we developed a text parsing algorithm to automatically extract information about potential new disease or disease progression from multi-institutional, free-text radiology reports (CT, PET, bone scan, MRI or x-ray). We combined semantic dictionary mapping and machine learning techniques to normalize the linguistic and formatting variations in the text, training the XGBoost model particularly to achieve a high precision and accuracy to satisfy clinical trial screening requirements. In order to be comprehensive, we enhanced the model vocabulary using a multi-institutional dataset which includes reports from two academic institutions. Results: A dataset of 732 de-identified radiology reports were curated (two MDs agreed on potential new disease/dz progression vs stable) and the model was repeatedly re-trained for each fold where the folds were randomly selected. The final model achieved consistent precision (>0.87 precision) and accuracy (>0.87 accuracy). See the table for a summary of the results, by radiology report type. We are continuing work on the model to validate accuracy and precision using a new and unique set of reports. Conclusions: NLP systems can be used to identify patients who potentially have suffered new disease or disease progression and reduce the human effort in screening or clinical trials. Efforts are ongoing to integrate the NLP process into existing EHR reporting. New imaging reports sent via interface to the EHR will be extracted daily using a database query and will be provided via secure electronic transport to the NLP system. Patients with higher likelihood of disease progression will be automatically identified, and their reports routed to the clinical trials office for clinical trial screening parallel to physician EHR mailbox reporting. The over-arching goal of the project is to increase clinical trial enrollment. 5-fold cross-validation performance of the NLP model in terms of accuracy, precision and recall averaged across all the folds.[Table: see text]

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