Barriers and facilitators to oncology clinical trial accrual: Comparing perceptions of community and academic oncologists.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18131-e18131
Author(s):  
Andrew R. Wong ◽  
Arti Hurria ◽  
Virginia Sun ◽  
Daneng Li ◽  
Kevin George ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Barriers And Facilitators ◽  
Structured Interviews ◽  
Eligibility Criteria ◽  
Patients With Cancer ◽  
Oncology Clinical Trial ◽  
Medical Oncologists ◽  
Academic Practices ◽  
Clinical Trial Accrual

e18131 Background: Multiple studies have described the barriers and facilitators to oncology clinical trial accrual in academic practices. However, few studies have been done in community settings, even though the majority of patients with cancer receive their care in the community. We examined and compared community and academic oncologists’ perceptions of the barriers and facilitators to cancer clinical trial accrual. Methods: Semi-structured interviews were conducted from March to June 2018 with 44 medical oncologists at City of Hope (24 in academia; 20 in community sites). Purposive sampling was used to ensure participant diversity. Primary measures were oncologists’ self-reported perceptions of the barriers and facilitators to clinical trial accrual. Responses were recorded digitally, transcribed, and de-identified. Data was managed using NVivo v12. Two analysts coded the interview data using thematic content analysis (kappa = 0.74). A third analyst adjudicated discrepancies. Results: Of the 44 participants, 36% were women, and 68% had > 10 years of experience. Compared to academic oncologists, community oncologists more often cited barriers due to the lack of protocols suitable for community patients’ histology and stage (13% vs. 6%) and insufficient trial personnel support (13% vs. 9%). Compared to community oncologists, academic oncologists more often cited barriers due to limited time (14% vs. 8%) and overly stringent eligibility criteria (14% vs. 9%). Community oncologists more commonly reported extrinsic facilitators (e.g. reminders of available protocols from trial support staff) (91% vs. 76%) while academic oncologists more commonly reported intrinsic facilitators for offering clinical trials (e.g. self-motivation to prioritize clinical trials) (24% vs. 9%). Conclusions: Community oncologists more often reported facing barriers to accrual due to limited suitable trials and insufficient personnel support compared to academic oncologists. Additionally, community oncologists cite the need for more infrastructure to support accrual. Interventions to increase trial accrual must be tailored to address the unique needs of both community and academic practices.

Barriers to clinical trial accrual: Clinical trialists' perspectives.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18156-e18156
Author(s):  
Edward S. Kim ◽  
Dax Kurbegov ◽  
Patricia A. Hurley ◽  
David Michael Waterhouse
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Cost Benefit ◽  
Trial Participation ◽  
Clinical Trial Participation ◽  
Eligibility Criteria ◽  
Contract Research Organization ◽  
The Public ◽  
Community Forum ◽  
Clinical Trial Accrual

e18156 Background: Oncology clinical trial participation rates remain at historic lows. There are many barriers that impede participation. Understanding those barriers, from the perspective of cancer clinical trialists, will help develop solutions to increase physician and site engagement, with the goal of improving accrual rates and advancing cancer treatment. Methods: Physician investigators and research staff from community-based and academic-based research sites were surveyed during ASCO’s Research Community Forum (RCF) Annual Meeting (N = 159) and through a pre-meeting survey (N = 124) in 2018. Findings and potential solutions were discussed during the meeting. Results: 84% of respondents (n = 84) reported that it took 6-8 months to open a trial and 86% (n = 81) reported that trials had unnecessary delays 70% of the time. The top 10 barriers to accrual identified were: insufficient staffing resources, restrictive eligibility criteria, physician buy-in, site access to trials, burdensome regulatory requirements, difficulty identifying patients, lack of suitable trials, sponsor and contract research organization requirements, patient barriers, and site cost-benefit. Respondents shared strategies to address these barriers. Conclusions: The current state of conducting clinical trials is not sustainable and hinders clinical trial participation. New strategies are needed to ensure patients and practices have access to trials, standardize and streamline processes, reduce inefficiencies, simplify trial activation, reduce regulatory burden, provide sufficient compensation to sites, engage the community and patients, educate the public, and increase collaborations. The ASCO RCF offers resources, available to the public, that offer practical strategies to overcome barriers to clinical trial accrual and has ongoing efforts to facilitate oncology practice participation in clinical trials.

Transforming Clinical Trial Eligibility Criteria to Reflect Practical Clinical Application

2016 ◽  
pp. 83-90 ◽  
Author(s):  
Edward S. Kim ◽  
Jennifer Atlas ◽  
Gwynn Ison ◽  
Jennifer L. Ersek
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Diagnostic Testing ◽  
Standard Of Care ◽  
Trial Participation ◽  
Eligibility Criteria ◽  
Number Of Patients ◽  
Oncology Clinical Trials ◽  
Clinical Trial Accrual ◽  
Clinical Trial Results

Historically, oncology clinical trials have focused on comparing a new drug’s efficacy to the standard of care. However, as our understanding of molecular pathways in oncology has evolved, so has our ability to predict how patients will respond to a particular drug, and thus comparison with a standard therapy has become less important. Biomarkers and corresponding diagnostic testing are becoming more and more important to drug development but also limit the type of patient who may benefit from the therapy. Newer clinical trial designs have been developed to assess clinically meaningful endpoints in biomarker-enriched populations, and the number of modern, molecularly driven clinical trials are steadily increasing. At the same time, barriers to clinical trial enrollment have also grown. Many barriers contribute to nonenrollment in clinical trials, including patient, physician, institution, protocol, and regulatory barriers. At the protocol level, eligibility criteria have become a large roadblock to clinical trial accrual. Over time, eligibility criteria have become more and more restrictive. To accrue an adequate number of patients to molecularly driven trials, we should consider eligibility criteria carefully and attempt to reduce restrictive criteria. Reducing restrictive eligibility criteria will allow more patients to be eligible for clinical trial participation, will likely increase the speed of drug approvals, and will result in clinical trial results that more accurately reflect treatment of the population in the clinical setting.

Use of a clinical trials screening tool in the NCI Community Oncology Research Program (NCORP) to enhance accrual and promote disparities research.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14587-e14587
Author(s):  
Diane C. St. Germain ◽  
Troy Budd ◽  
Worta J. McCaskill-Stevens
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Screening Tool ◽  
Social Issues ◽  
Demographic Data ◽  
Specific Information ◽  
Eligibility Criteria ◽  
Oncology Patient ◽  
Oncology Research ◽  
Clinical Trial Accrual

e14587 Background: Despite the identification of multiple patient, clinician, and health systems barriers, accrual to a new generation of cancer clinical trials continues to present challenges. It may be that barrier data is not sufficiently granular. A clinical trial screening tool was developed for use in NCORP to collect trial- and site-specific information as well as broadened demographic data to determine factors that may impact accrual. Methods: The tool was developed with stakeholder input and the NCI Oncology Patient Enrollment Network was used for data input and analyses. Results: From February 2016 to December 2019, 14,340 entries were made in the screening tool. Eighty-two percent of participants consented to participate. Participants screened were female (77%), married (64%) and Caucasian (85%). Fourteen percent of the participants were racial minorities (1% not reported) and 5% were Hispanic or Latino. The mean age was 60 (range 1-95). Thirty-six percent were employed, ≥ 32 hours per week followed by 35% retirees. Income did not vary significantly ( < $25,000(16%), $25,000 - $50,00 (20%), $51,000 - $10,000 (26%), and > $100,000 (19%), and 19% of participants refused to provide income data. Four percent of the participants were uninsured at diagnosis. Seventy-two percent (8,501) of participants screened enrolled in a clinical trial. Of those not enrolled, 49% were ineligible and 48% were eligible but declined to participate. The most common reasons for ineligibility included concurrent disease, abnormal lab or other tests, and patient could not comply with eligibility criteria. The most common reasons eligible participants declined to participate were perception that toxicities were too great and social issues (child care, transportation). Further analysis of the data will include correlation of race/ethnicity, age, income and co-morbidities with enrollment status. Conclusions: The majority of participants approached agreed to participate in the screening tool protocol. Approximately half of the participants were eligible for a trial but declined to participate. These issues will be addressed within the network to enhance accrual. The data collected will also provide opportunities for investigators within the network to develop research questions focused on disparities and clinical trial accrual.

Prospective Evaluation of Cancer Clinical Trial Accrual Patterns: Identifying Potential Barriers to Enrollment

2001 ◽  
Vol 19 (6) ◽  
pp. 1728-1733 ◽  
Author(s):  
Primo N. Lara ◽  
Roger Higdon ◽  
Nelson Lim ◽  
Karen Kwan ◽  
Michael Tanaka ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Private Insurance ◽  
Cancer Clinical Trial ◽  
Cancer Center ◽  
Trial Participation ◽  
Cancer Clinical Trials ◽  
Eligibility Criteria ◽  
Clinical Trial Accrual ◽  
Patient Accrual

PURPOSE: Well-conducted cancer clinical trials are essential for improving patient outcomes. Unfortunately, only 3% of new cancer patients participate in clinical trials. Barriers to patient accrual in cancer clinical trials must be identified and overcome to increase patient participation. MATERIALS AND METHODS: We prospectively tracked factors that potentially affected patient accrual into cancer clinical trials at the University of California Davis Cancer Center. Oncologists seeing new outpatients were asked to complete questionnaires regarding patient characteristics and the physician’s decision-making on patient eligibility, protocol availability, and patient opinions on participation. Statistical analysis was performed to correlate these parameters with subsequent protocol accrual. RESULTS: There were 276 assessable patients. At the initial visits, physicians did not consider clinical trials in 38% (105/276) of patients principally because of a perception of protocol unavailability and poor performance status. Physicians considered 62% (171/276) of patients for participation in clinical trials. Of these, only 53% (91/171) had an appropriate protocol available for site and stage of disease. Seventy-six of 90 patients (84%) with available protocols met eligibility criteria for a particular study. Only 39 of 76 patients (51%) agreed to participate in cancer clinical trials, for an overall accrual rate of 14% (39/276). The remainder (37/76, 49%) declined trial participation despite meeting eligibility criteria. The most common reasons were a desire for other treatment (34%), distance from the cancer center (13%), patient refusal to disclose reason (11%), and insurance denial (8%). Patients with private insurance were less likely to enroll in clinical trials compared to those with government-funded insurance (OR, 0.34; P = .03; 95% CI, 0.13 to 0.9). CONCLUSION: Barriers to cancer clinical trial accrual can be prospectively identified and addressed in the development and conduct of future studies, which may potentially lead to more robust clinical trials enrollment. Investigation of patient perceptions regarding the clinical trials process and the role of third party–payers is warranted.

Overcoming Barriers to Clinical Trial Enrollment

2019 ◽  
pp. 105-114 ◽  
Author(s):  
Ryan D. Nipp ◽  
Kessely Hong ◽  
Electra D. Paskett
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Treatment Strategies ◽  
Trial Participation ◽  
Routine Practice ◽  
Clinical Trial Participation ◽  
Eligibility Criteria ◽  
Financial Barriers ◽  
Patients With Cancer ◽  
Clinical Trial Enrollment

Clinical trials are imperative for testing novel cancer therapies, advancing the science of cancer care, and determining the best treatment strategies to enhance outcomes for patients with cancer. However, barriers to clinical trial enrollment contribute to low participation in cancer clinical trials. Many factors play a role in the persistently low rates of trial participation, including financial barriers, logistical concerns, and the lack of resources for patients and clinicians to support clinical trial enrollment and retention. Furthermore, restrictive eligibility criteria often result in the exclusion of certain patient populations, which thus adds to the widening disparities seen between patients who enroll in trials and those treated in routine practice. Moreover, additional factors, such as difficulty by patients and clinicians in coping with the uncertainty inherent to clinical trial participation, contribute to low trial enrollment and represent key components of the decision-making process. Specifically, patients and clinicians may struggle to assess the risk-benefit ratio and may incorrectly estimate the probability and severity of challenges associated with clinical trial participation, thus complicating the informed consent process. Importantly, research has increasingly focused on overcoming barriers to clinical trial enrollment. A promising solution involves the use of patient navigators to help enhance clinical trial recruitment, enrollment, and retention. Although clinical trials are essential for improving and prolonging the lives of patients with cancer, barriers exist that can impede trial enrollment; yet, efforts to recognize and address these barriers and enhance trial enrollment are being investigated.

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

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.

scholarly journals Are clinical trial eligibility criteria an accurate reflection of a real-world population of advanced non-small-cell lung cancer patients?

2018 ◽  
Vol 25 (4) ◽  
Author(s):  
K. Al-Baimani ◽  
H. Jonker ◽  
T. Zhang ◽  
G.D. Goss ◽  
S.A. Laurie ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Advanced Nsclc ◽  
Small Cell ◽  
Small Cell Lung ◽  
Eligibility Criteria ◽  
Ecog Ps

Background Advanced non-small-cell lung cancer (nsclc) represents a major health issue globally. Systemic treatment decisions are informed by clinical trials, which, over years, have improved the survival of patients with advanced nsclc. The applicability of clinical trial results to the broad lung cancer population is unclear because strict eligibility criteria in trials generally select for optimal patients.Methods We performed a retrospective chart review of all consecutive patients with advanced nsclc seen in outpatient consultation at our academic institution between September 2009 and September 2012, collecting data about patient demographics and cancer characteristics, treatment, and survival from hospital and pharmacy records. Two sets of arbitrary trial eligibility criteria were applied to the cohort. Scenario A stipulated Eastern Cooperative Oncology Group performance status (ecog ps) 0–1, no brain metastasis, creatinine less than 120 μmol/L, and no second malignancy. Less-strict scenario B stipulated ecog ps 0–2 and creatinine less than 120 μmol/L. We then used the two scenarios to analyze treatment and survival of patients by trial eligibility status.Results The 528 included patients had a median age of 67 years, with 55% being men and 58% having adenocarcinoma. Of those 528 patients, 291 received at least 1 line of palliative systemic therapy. Using the scenario A eligibility criteria, 73% were trial-ineligible. However, 46% of “ineligible” patients actually received therapy and experienced survival similar to that of the “eligible” treated patients (10.2 months vs. 11.6 months, p = 0.10). Using the scenario B criteria, only 35% were ineligible, but again, the survival of treated patients was similar in the ineligible and eligible groups (10.1 months vs. 10.9 months, p = 0.57).Conclusions Current trial eligibility criteria are often strict and limit the enrolment of patients in clinical trials. Our results suggest that, depending on the chosen drug, its toxicities and tolerability, eligibility criteria could be carefully reviewed and relaxed.

scholarly journals Safety and Effectiveness of Favipiravir for Novel Coronavirus (COVID-19): A Rapid Review of Available Evidence

2021 ◽  
Author(s):  
Mohammadreza Mobinizadeh ◽  
Morteza Arab-Zozani
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Therapeutic Potential ◽  
Data Extraction ◽  
Rapid Review ◽  
Eligibility Criteria ◽  
Clinical Trial Registration ◽  
Registration System ◽  
Novel Coronavirus ◽  
First Time

Context: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appeared for the first time in December 2019 in Wuhan, China. Due to the lack of unified and integrated evidence for Favipiravir, this study was conducted to rapidly review the existing evidence to help evidence-based decision-making on the therapeutic potential of this drug in the treatment of COVID-19 patients. Evidence Acquisition: This study is a rapid Health Technology Assessment (HTA). By searching pertinent databases, the research team collected relevant articles and tried to create a policy guide through a thematic approach. This rapid review was done in four steps: (1) Searching for evidence through databases; (2) screening the evidence considering eligibility criteria; (3) data extraction; and (4) analyzing the data through thematic analysis. Results: After applying the inclusion criteria, four studies were finally found, including three review studies and a clinical trial that was temporarily removed by its publisher from the journal’s website. After searching the sources mentioned in the articles, two ongoing clinical trials were found in China. Also, by searching the clinical trial website, www.clinicaltrials.gov, five clinical trials were found in the search. The result of the search in the clinical trial registration system in Iran showed a study that is in the process of patient recruitment. A limited number of other articles were found, mostly in the form of reflections from physicians or researchers and letters to editors who have predicted the drug’s performance on SARS-CoV-2, which needs further clinical study to be approved. Conclusions: With the available evidence, it is not possible to make a definite conclusion about the safety and efficacy of Favipiravir in the treatment of patients with COVID-19.

The role of experience and clinical decision support in clinical trial accrual within oncology.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1527-1527
Author(s):  
Waqas Haque ◽  
Ann M. Geiger ◽  
Celette Sugg Skinner ◽  
Rasmi Nair ◽  
Simon Craddock Lee ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Principal Investigator ◽  
Physician Practices ◽  
The Past ◽  
The Future ◽  
Clinical Trial Accrual

1527 Background: Patient accrual for cancer clinical trials is suboptimal. The complexity of applying eligibility criteria and enrolling patients may deter oncologists from recommending patients for a trial. As such, there is a need to understand how experience, training, and clinical decision support impact physician practices and intentions related to trial accrual. Methods: From May to September 2017, we conducted a survey on clinical trial accrual in a national sample of medical, surgical, and radiation oncologists. The 20-minute survey assessed barriers and facilitators to clinical trial accrual, including experience (e.g., “In the past 5 years, have you been a study or site PI of a trial?”), training (e.g., “Did you receive training about trial design and recruitment as part of medical school, residency, or fellowship? After fellowship?”), and clinical decision support (e.g., “What kind of clinical decision support has your practice implemented?). We used logistic regression to identify factors associated with frequency of discussing trials (with ≥25% of patients) and likelihood of recommending a trial to a patient (likely or very likely) in the future. Results: Survey respondents (n = 1,030) were mostly medical oncologists (59%), age 35-54 years (67%), male (74%), and not in academic practice (58%). About 18% of respondents (n = 183) reported discussing trials with ≥25% of their patients, and 80% reported being likely or very likely to recommend a trial to a patient in the future. Prior experience as principal investigator of a trial was associated with both frequency of discussing trials (OR 3.27, 95% CI 2.25, 4.75) and likelihood of recommending a trial in the future (OR 5.22, 95% CI 3.71, 7.34), as was receiving additional training in clinical trials after fellowship (discussion with patients: OR 2.48, 95% CI 1.80, 3.42; recommend in future: OR 1.92, 95% CI 1.37, 2.69). Implementing clinical decision support was not associated with discussing trials with ≥25% of patients (OR 1.12, 95% CI 0.76, 1.67), but was associated with being likely to recommend a trial in the future (OR 1.73, 95% CI 1.11, 2.71). Conclusions: In a national survey of oncologists, we observed differences in physician practices and intention related to clinical trial accrual. Whereas the vast majority (80%) reported being likely or very likely to recommend trials in the future, far fewer (20%) reported discussing trials with their patients within the past 5 years. Implementation of clinical decision support – electronic tools intended to optimize patient care and identification of patient eligibility – was not associated with frequency of past discussion of clinical trials but was associated with recommending a trial in the future. Given the stronger association between experience as a site Principal Investigator and recommending a trial, future research should explore how improving opportunities to lead a clinical trial impact trial accrual.

Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center

2020 ◽  
pp. 50-59 ◽  
Author(s):  
J. Thaddeus Beck ◽  
Melissa Rammage ◽  
Gretchen P. Jackson ◽  
Anita M. Preininger ◽  
Irene Dankwa-Mullan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Language Processing ◽  
Medical Records ◽  
Cancer Center ◽  
Patients With Cancer ◽  
Attribute Extraction ◽  
Time Required ◽  
Manual Review

PURPOSE Less than 5% of patients with cancer enroll in clinical trials, and 1 in 5 trials are stopped for poor accrual. We evaluated an automated clinical trial matching system that uses natural language processing to extract patient and trial characteristics from unstructured sources and machine learning to match patients to clinical trials. PATIENTS AND METHODS Medical records from 997 patients with breast cancer were assessed for trial eligibility at Highlands Oncology Group between May and August 2016. System and manual attribute extraction and eligibility determinations were compared using the percentage of agreement for 239 patients and 4 trials. Sensitivity and specificity of system-generated eligibility determinations were measured, and the time required for manual review and system-assisted eligibility determinations were compared. RESULTS Agreement between system and manual attribute extraction ranged from 64.3% to 94.0%. Agreement between system and manual eligibility determinations was 81%-96%. System eligibility determinations demonstrated specificities between 76% and 99%, with sensitivities between 91% and 95% for 3 trials and 46.7% for the 4th. Manual eligibility screening of 90 patients for 3 trials took 110 minutes; system-assisted eligibility determinations of the same patients for the same trials required 24 minutes. CONCLUSION In this study, the clinical trial matching system displayed a promising performance in screening patients with breast cancer for trial eligibility. System-assisted trial eligibility determinations were substantially faster than manual review, and the system reliably excluded ineligible patients for all trials and identified eligible patients for most trials.

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