scholarly journals Screening Intervention to Identify Eligible Patients and Improve Accrual to Phase II-IV Oncology Clinical Trials

2013 ◽  
Vol 9 (4) ◽  
pp. e174-e181 ◽  
Author(s):  
Leo Chen ◽  
Janice Grant ◽  
Winson Y. Cheung ◽  
Hagen F. Kennecke

Manually screening patient records increased enrollment to specific clinical trials. A screening intervention process, involving a dedicated screening coordinator, should be considered to improve clinical trial accrual.

Author(s):  
Edward S. Kim ◽  
Jennifer Atlas ◽  
Gwynn Ison ◽  
Jennifer L. Ersek

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.


2020 ◽  
pp. 614-622 ◽  
Author(s):  
Kristian Stensland ◽  
Samuel Kaffenberger ◽  
David Canes ◽  
Matthew Galsky ◽  
Ted Skolarus ◽  
...  

PURPOSE Clinical trials often fail to reach their anticipated end points, most frequently because of poor accrual. Prior studies have analyzed trial termination, but it has not been easy to assess accrual estimates using international databases such as ClinicalTrials.gov because of limitations in accessing accrual information. Specifically, it is not easy to extract both anticipated and actual accrual of clinical trials. We designed a new algorithmic approach to extracting trial accrual data from ClinicalTrials.gov and used it to estimate the sufficiency of patient accrual onto genitourinary (GU) cancer trials. METHODS We queried ClinicalTrials.gov for completed/terminated phase II and III clinical trials for prostate, bladder, kidney, testicular, and ureteral cancers registered after 2007. We extracted trial characteristics from available XML files. We then used a Python algorithm to access prior trial registrations on the ClinicalTrials.gov archive site and extract both anticipated and actual accrual numbers. We then compared the actual accrual of each trial to its anticipated accrual and defined sufficient accrual as 85% of anticipated accrual. RESULTS The algorithm was 100% accurate compared with hand extraction in a small validation subset. A total of 925 trials were included, of which 840 (91%) had both anticipated and actual accrual. Only 418 (50%) trials had sufficient accrual (≥ 85% of anticipated). Considering only trials marked as successfully completed, 395/597 (66%) reached sufficient accrual. CONCLUSION GU cancer trials often do not meet their anticipated accrual goals. New approaches to trial conduct are direly needed. Our reproducible and scalable approach to extracting accrual information can be applied to analysis of ClinicalTrials.gov in future analyses in the hope of improving the efficiency of the clinical trials enterprise.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1543-1543
Author(s):  
Peter Blankenship ◽  
David DeLaRosa ◽  
Marc Burris ◽  
Steven Cusson ◽  
Kayla Hendricks ◽  
...  

1543 Background: Tissue requirements in oncology clinical trials are increasingly complex due to prescreening protocols for patient selection and serial biopsies to understand molecular-level treatment effects. Novel solutions for tissue processing are necessary for timely tissue procurement. Based on these needs, we developed a Tissue Tracker (TT), a comprehensive database for study-related tissue tasks at our high-volume clinical trial center. Methods: In this Microsoft Access database, patients are assigned an ID within the TT that is associated with their name, medical record number, and study that follows their request to external users: pathology departments, clinical trial coordinators and data team members. To complete tasks in the TT, relevant information is required to update the status. Due to the high number of archival tissue requests from unique pathology labs, the TT has a “Follow-Up Dashboard” that organizes information needed to conduct follow-up on all archival samples with the status “Requested”. This results in an autogenerated email and pdf report sent to necessary teams. The TT also includes a kit inventory system and a real-time read only version formatted for interdepartmental communication, metric reporting, and other data-driven efforts. The primary outcome in this study was to evaluate our average turnaround time (ATAT: average time from request to shipment) for archival and fresh tissue samples before and after TT development. Results: Before implementing the TT, between March 2016 and March 2018, we processed 2676 archival requests from 235 unique source labs resulting in 2040 shipments with an ATAT of 19.29 days. We also processed 1099 fresh biopsies resulting in 944 shipments with an ATAT of 7.72 days. After TT implementation, between April 2018 and April 2020, we processed 2664 archival requests from 204 unique source labs resulting in 2506 shipments (+28.0%) with an ATAT of 14.78 days (-23.4%). During that same period, we processed 1795 fresh biopsies (+63.3%) resulting in 2006 shipments (+112.5%) with an ATAT of 6.85 days (-11.3%). Conclusions: Oncology clinical trials continue to evolve toward more extensive tissue requirements for prescreening and scientific exploration of on-treatment molecular profiling. Timely results are required to optimize patient trial participation. During the intervention period, our tissue sample volume and shipments increased, but the development and implementation of an automated tracking system allowed improvement in ATAT of both archival and fresh tissue. This automation not only improves end-user expectations and experiences for patients and trial sponsors but this allows our team to adapt to the increasing interest in tissue exploration.


2009 ◽  
Vol 32 (3) ◽  
pp. 253-257 ◽  
Author(s):  
Rasmus T. Hoeg ◽  
Jennifer A. Lee ◽  
Michelle A. Mathiason ◽  
Kristina Rokkones ◽  
Stephanie L. Serck ◽  
...  

2000 ◽  
Vol 18 (15) ◽  
pp. 2805-2810 ◽  
Author(s):  
Charles L. Bennett ◽  
Tammy J. Stinson ◽  
Victor Vogel ◽  
Lyn Robertson ◽  
Donald Leedy ◽  
...  

PURPOSE: Medical care for clinical trials is often not reimbursed by insurers, primarily because of concern that medical care as part of clinical trials is expensive and not part of standard medical practice. In June 2000, President Clinton ordered Medicare to reimburse for medical care expenses incurred as part of cancer clinical trials, although many private insurers are concerned about the expense of this effort. To inform this policy debate, the costs and charges of care for patients on clinical trials are being evaluated. In this Association of American Cancer Institutes (AACI) Clinical Trials Costs and Charges pilot study, we describe the results and operational considerations of one of the first completed multisite economic analyses of clinical trials. METHODS: Our pilot effort included assessment of total direct medical charges for 6 months of care for 35 case patients who received care on phase II clinical trials and for 35 matched controls (based on age, sex, disease, stage, and treatment period) at five AACI member cancer centers. Charge data were obtained for hospital and ancillary services from automated claims files at individual study institutions. The analyses were based on the perspective of a third-party payer. RESULTS: The mean age of the phase II clinical trial patients was 58.3 years versus 57.3 years for control patients. The study population included persons with cancer of the breast (n = 24), lung (n = 18), colon (n = 16), prostate (n = 4), and lymphoma (n = 8). The ratio of male-to-female patients was 3:4, with greater than 75% of patients having stage III to IV disease. Total mean charges for treatment from the time of study enrollment through 6 months were similar: $57,542 for clinical trial patients and $63,721 for control patients (1998 US$; P = .4) CONCLUSION: Multisite economic analyses of oncology clinical trials are in progress. Strategies that are not likely to overburden data managers and clinicians are possible to devise. However, these studies require careful planning and coordination among cancer center directors, finance department personnel, economists, and health services researchers.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1527-1527
Author(s):  
Waqas Haque ◽  
Ann M. Geiger ◽  
Celette Sugg Skinner ◽  
Rasmi Nair ◽  
Simon Craddock Lee ◽  
...  

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.


ESMO Open ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. e000469 ◽  
Author(s):  
David Allan Moore ◽  
Marina Kushnir ◽  
Gabriel Mak ◽  
Helen Winter ◽  
Teresa Curiel ◽  
...  

BackgroundThe increasing frequency and complexity of cancer genomic profiling represents a challenge for the oncology community. Results from next-generation sequencing–based clinical tests require expert review to determine their clinical relevance and to ensure patients are stratified appropriately to established therapies or clinical trials.MethodsThe Sarah Cannon Research Institute UK/UCL Genomics Review Board (GRB) was established in 2014 and represents a multidisciplinary team with expertise in molecular oncology, clinical trials, clinical cancer genetics and molecular pathology. Prospective data from this board were collated.ResultsTo date, 895 patients have been reviewed by the GRB, of whom 180 (20%) were referred for clinical trial screening and 62 (7%) received trial therapy. For a further 106, a clinical trial recommendation was given.ConclusionsNumerous challenges are faced in implementing a GRB, including the identification of potential germline variants, the interpretation of variants of uncertain significance and consideration of the technical limitations of pathology material when interpreting results. These challenges are likely to be encountered with increasing frequency in routine practice. This GRB experience provides a model for the multidisciplinary review of molecular profiling data and for the linking of molecular analysis to clinical trial networks.


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