Cancer clinical trials available in the community setting: A 5-year analysis from 1999–2004

6056 Background: Less than 5% of newly diagnosed cancer patients are accrued into clinical trials. In the community setting, the lack of appropriate clinical trials is a major barrier. Our prospective study in 2004 determined that 58% of newly diagnosed adult cancer patients at our community-based cancer center didn’t have a clinical trial available appropriate for their disease stage. Among those with clinical trials, 23% were subsequently found to be ineligible (Go RS, et al. Cancer 2006, in press). However, the availability of clinical trials may vary from year to year. Methods: A retrospective study was conducted to determine what clinical trials were available for newly diagnosed adult cancer patients at our institution from June 1999-July 2004. The study also investigated the proportions of newly diagnosed patients who had a clinical trial available appropriate for type and stage of disease and patients accrued. Results: Over the 5-year period, 207 (82, 87, 99, 102, 117, years 1–5, respectively) trials were available. Most (50.7%) trials were for the following cancers: breast (15.5%), lung (13.5%), head and neck (7.7%), colorectal (7.2%) and lymphoma (6.8%). ECOG (53%), RTOG (26%), and CTSU (9%) provided the majority of the trials. A total of 5,776 new adult cancer patients were seen during this period. Overall, 60% of the patients had a trial available appropriate for type and stage of their cancer, but only 103 (3%) were enrolled. There was a significant upward trend in the proportions of patients with available trials over the years (60.2%, 55.9%, 59.2%, 60.7%, 63.9%, years 1–5, respectively; Mantel-Haenszel P=.008). The proportion of patients with a trial available was highest for prostate (97.3%), lung (90.9%), and breast (73.9%), and lowest for melanoma (17.1%), renal (11.6%), and bladder (7.2%). The majority of patients accrued to trials had the following cancers: breast (32%), lung (17%), lymphoma (9%), colon (7%), and prostate (5%). Conclusions: Nearly half of the newly diagnosed adult patients at our center had no trials available appropriate for type and stage of their cancers. It is likely that if strict clinical trial eligibility criteria were applied, approximately 2/3 of our patients would not be eligible for a clinical trial. No significant financial relationships to disclose.

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Perceptions concerning clinical trials in oncology patients.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.e16533 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. e16533-e16533

Author(s):

Dana Lee ◽

Ju-Hsien Chao ◽

Sandy Stevens ◽

Goetz H. Kloecker

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Cancer Patients ◽

Treatment Option ◽

Phase 1 ◽

Cancer Center ◽

Line Treatment ◽

Newly Diagnosed ◽

First Line ◽

Oncology Patients

e16533 Background: Accrual to clinical trials among adult cancer patients is persistently low. Patient preference plays an important role in enrollment. To identify the reasons why patients decline study participation, it is important, to evaluate the perceptions of newly diagnosed oncology patients about clinical trials. Methods: Patients were given a ten-question survey reflective of their attitudes regarding clinical trials as a treatment option at their initial visit. The self-directed questionnaire was scored on an ordinate scale from strongly agree (1) to strongly disagree (5). Results: Ninety-two new patients were surveyed in the cancer - specific multispecialty clinics in an academic cancer center. The patients expected information relating to eligible clinical trials and privacy protection by university sponsored studies as they strongly concurred with “I expect my doctor to inform me about clinical trials that I am eligible for” (mean score 2.15, p=0.001) followed by “all possible measures to protect my privacy are likely to be taken in a clinical trial that is sponsored by a university” (2.36, p=0.36). The strongest disagreement was “If enrolled in a clinical trial, I am comfortable being assigned by a method such as ‘flipping a coin’ or ‘throwing a dice’” (3.73, p=0.001) and “I would be willing to participate in a clinical trial as a first line treatment option” (3.50, p=0.001). Industry sponsored trials, phase 1 trials, second line treatment trials, privacy concerns and investigator initiated trials and time commitment and altruistic reasons did not significantly deviate from the mean preference (2.5) by a one sample T-test analysis. Conclusions: Patients consider the option of clinical trials as important in their treatment, and expect to be informed by their oncologist about clinical trials. Newly diagnosed cancer patients perceive randomization and first line trials negatively. Since randomized data provides new standards for care and hope for improved treatment, patients and their families must be educated about their importance.

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Improving hematology/oncology clinical research recruitment via universal prescreening: The VA Connecticut (VACT) Cancer Center experience.

Journal of Clinical Oncology ◽

10.1200/jco.2020.39.28_suppl.79 ◽

2021 ◽

Vol 39 (28_suppl) ◽

pp. 79-79

Author(s):

Jenny Jing Xiang ◽

Alicia Roy ◽

Christine Summers ◽

Monica Delvy ◽

Jessica Lee O'Donovan ◽

...

Keyword(s):

Lung Cancer ◽

Clinical Trials ◽

Clinical Research ◽

Cancer Patients ◽

Cancer Center ◽

Cancer Type ◽

Eligibility Criteria ◽

Research Recruitment ◽

Lung Cancer Patients ◽

Study Enrollment

79 Background: Patient-trial matching is a critical step in clinical research recruitment that requires extensive review of clinical data and trial requirements. Prescreening, defined as identifying potentially eligible patients using select eligibility criteria, may streamline the process and increase study enrollment. We describe the real-world experience of implementing a standardized, universal clinical research prescreening protocol within a VA cancer center and its impact on research enrollment. Methods: An IRB approved prescreening protocol was implemented at the VACT Cancer Center in March 2017. All patients with a suspected or confirmed diagnosis of cancer are identified through tumor boards, oncology consults, and clinic lists. Research coordinators perform chart review and manually enter patient demographics, cancer type and stage, and treatment history into a REDCap (Research Electronic Data Capture) database. All clinical trials and their eligibility criteria are also entered into REDCap and updated regularly. REDCap generates real time lists of potential research studies for each patient based on his/her recorded data. The primary oncologist is alerted to a patient’s potential eligibility prior to upcoming clinic visits and thus can plan to discuss clinical research enrollment as appropriate. Results: From March 2017 to December 2020, a total of 2548 unique patients were prescreened into REDCAP. The mean age was 71.5 years, 97.5% were male, and 15.5% were African American. 32.57 % patients had genitourinary cancer, 17.15% had lung cancer, and 46.15% were undergoing malignancy workup. 1412 patients were potentially eligible after prescreening and 556 patients were ultimately enrolled in studies. The number of patients enrolled on therapeutic clinical trials increased after the implementation of the prescreening protocol (35 in 2017, 64 in 2018, 78 in 2019, and 55 in 2020 despite the COVID19 pandemic). Biorepository study enrollment increased from 8 in 2019 to 15 in 2020. The prescreening protocol also enabled 200 patients to be enrolled onto a lung nodule liquid biopsy study from 2017 to 2019. Our prescreening process captured 98.57% of lung cancer patients entered into the cancer registry during the same time period. Conclusions: Universal prescreening streamlined research recruitment operations and was associated with yearly increases in clinical research enrollment at a VA cancer center. Our protocol identified most new lung cancer patients, suggesting that, at least for this malignancy, potential study patients were not missed. The protocol was integral in our program becoming the top accruing VA site for NCI’s National Clinical Trial Network (NCTN) studies since 2019.

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Evaluating the Financial Impact of Clinical Trials in Oncology: Results From a Pilot Study From the Association of American Cancer Institutes/Northwestern University Clinical Trials Costs and Charges Project

Journal of Clinical Oncology ◽

10.1200/jco.2000.18.15.2805 ◽

2000 ◽

Vol 18 (15) ◽

pp. 2805-2810 ◽

Cited By ~ 27

Author(s):

Charles L. Bennett ◽

Tammy J. Stinson ◽

Victor Vogel ◽

Lyn Robertson ◽

Donald Leedy ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Pilot Study ◽

Medical Care ◽

Phase Ii ◽

Third Party ◽

Disease Stage ◽

Cancer Center ◽

Policy Debate ◽

Economic Analyses

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.

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Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach

Cancer Informatics ◽

10.4137/cin.s19454 ◽

2014 ◽

Vol 13 ◽

pp. CIN.S19454 ◽

Cited By ~ 10

Author(s):

Satya S. Sahoo ◽

Shiqiang Tao ◽

Andrew Parchman ◽

Zhihui Luo ◽

Licong Cui ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Survival Rates ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

Dramatic Improvement ◽

Multiple Sources ◽

Eligibility Criteria ◽

Physician Participation ◽

Time Required

Cancer is responsible for approximately 7.6 million deaths per year worldwide. A 2012 survey in the United Kingdom found dramatic improvement in survival rates for childhood cancer because of increased participation in clinical trials. Unfortunately, overall patient participation in cancer clinical studies is low. A key logistical barrier to patient and physician participation is the time required for identification of appropriate clinical trials for individual patients. We introduce the Trial Prospector tool that supports end-to-end management of cancer clinical trial recruitment workflow with (a) structured entry of trial eligibility criteria, (b) automated extraction of patient data from multiple sources, (c) a scalable matching algorithm, and (d) interactive user interface (UI) for physicians with both matching results and a detailed explanation of causes for ineligibility of available trials. We report the results from deployment of Trial Prospector at the National Cancer Institute (NCI)-designated Case Comprehensive Cancer Center (Case CCC) with 1,367 clinical trial eligibility evaluations performed with 100% accuracy.

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Poor access to clinical trials among community cancer patients requiring chemotherapy for recurrent or progressive disease: Limitations of current cancer cooperative groups

Journal of Clinical Oncology ◽

10.1200/jco.2006.24.18_suppl.6076 ◽

2006 ◽

Vol 24 (18_suppl) ◽

pp. 6076-6076 ◽

Cited By ~ 1

Author(s):

L. A. Meyer ◽

J. A. Lee ◽

M. A. Mathiason ◽

K. A. Frisby ◽

K. C. Bruden ◽

...

Keyword(s):

Clinical Trials ◽

Cancer Patients ◽

Progressive Disease ◽

Cancer Center ◽

Cooperative Groups ◽

Newly Diagnosed ◽

Poor Access ◽

Accrual Rate ◽

Clinical Trial Accrual ◽

A Prospective Study

6076 Background: Data on clinical trial accrual among cancer patients treated in the community are limited. In a prospective study at our community-based cancer center, we found that the accrual rate was only 4% for newly diagnosed patients and protocol limitations accounted for 68% of non-accrual (Go RS, et al. Cancer 2006). We would like to determine the availability of trials for adult cancer patients with recurrent or progressive disease treated in the community and the accrual rate. Methods: We retrospectively identified this specific group of patients who received chemotherapy at our institution between November 2004 and October 2005 and collected data on the number, types, and sources of trials that were available. Results: We identified a total of 140 patients. There was an equal number of females (52.9%) and males, with a median age of 66 years (range, 38–89) at the time of chemotherapy. Fifty trials were available, with about half for the following cancers: lung (14%), pancreatic (12%), renal (10%), head and neck (8%), prostate (6%), and breast (6%). No trials were available for bladder, colorectal, and gastroesophageal cancers. The proportions of phase I, II, and III trials were 4%, 62%, and 34%, respectively. The sources of trials were: ECOG (56%), Wisconsin Oncology Network (14%), Intergroup (12%), GOG (10%), RTOG (2%), CTSU (2%), our institution (2%), and pharmaceutical companies (2%). Only 69 (49.3%) patients had trials appropriate for their type and stage of cancers. Among those patients with available trials, 24 (34.8%) were eligible to participate and 6 were enrolled, for an overall accrual rate of 4.3%. There were no differences in age and sex among subgroups in terms of trial availability, eligibility, and accrual. Conclusions: At our institution, enrollment of cancer patients with recurrent or progressive disease in clinical trials is as low as for newly diagnosed patients. Over 80% of the patients were denied access to a trial because of protocol unavailability and ineligibility. Current cancer cooperative groups do not provide adequate trials for patients in the community. No significant financial relationships to disclose.

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Clinical Trial Enrolment In the Adolescent and Young Adult (AYA) Population with Hematologic Malignancies: A South Carolina (SC) Community Practice Perspective

Blood ◽

10.1182/blood.v116.21.2577.2577 ◽

2010 ◽

Vol 116 (21) ◽

pp. 2577-2577

Author(s):

Jill Sullivan ◽

Jamie Jackson ◽

Griffen Kristie ◽

John Eberly ◽

Jennifer Davis ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

South Carolina ◽

Pediatric Patients ◽

Conflicts Of Interest ◽

Cancer Center ◽

Similar Distribution ◽

Community Based ◽

Acute Leukemias ◽

Leukemias And Lymphomas

Abstract Abstract 2577 Background: Leukemias and lymphomas comprise 25% of all cancers in AYA patients age 15–39 years. Survival benefit from treatment advances has been less for AYA patients compared to the pediatric patients (<15 years of age). One reason for this disparity in survival is the relative lack of clinical trial accrual in AYA population. Previous population-based analysis of cooperative group participation between 1992 and 1997 found 71% of children under age 15 participated in clinical trials versus 24% of 15–19 year olds and less than 2% of 20–29 year olds (Liu et al., 2003). The majority of reports on this “AYA Gap” have been from large academic institutions or pooled national databases. We report our 5 year experience of clinical trial enrolment of AYA leukemias and lymphomas (L&L) from a SC community-based practice. Methods: We retrospectively analyzed the data on all patients, age 0–39 years, with newly diagnosed acute leukemias(ALL, AML) and lymphomas (Hodgkin {HL} and non-hodgkin lymphoma{NHL}) between 2005 and 2009 through the Greenville Memorial Hospital (GMH) and BI-LO Charities Children's Cancer Center (BCCCC) registries in Greenville SC. AYA was defined ages 15–39, with the pediatric ages <15 as the control. Demographic comparisons were made with available state-wide and SEER registry data. Clinical trial availability was abstracted from practice clinical research offices and NCI database using www.clinicaltrials.gov. Results: Among 684 total oncology patients 0–39 years of age, 528 were AYA. Median age was 33 for the total AYA population but 26 for the 76 patients with L&L (ALL = 14, AML = 7, HL = 27, NHL = 28); there was no difference between the pediatric and AYA populations in regards to other demographic characteristics (race, gender, insurance, or vital status). Leukemia and lymphoma patients age 15–39 represented a similar distribution (4.7% and 10.4% of total diagnosis, respectively) in comparison to statewide and SEER data. Leukemia accounted for 80% of pediatric diagnoses while lymphoma comprised the bulk (72%) of AYA diagnoses; this is similar to data observed nationally. Statewide clinical trials were available to 72% of pediatric patients and 60% of AYA patients; local clinical trial availability was higher in the pediatric population than the AYA population (94% versus 69%). Sixty-two percent of pediatric patients were actually enrolled on a clinical trial in comparison to only 17% of AYA patients. Only 21% of AYA were treated at a pediatric facility, as compared to 98% of pediatric patients. Clinical trial enrollment of AYA patients treated at a pediatric facility was 75% versus 3% of patients treated at an adult facility. For the 97% of AYA patients treated at an adult facility but not enrolled on a clinical trial, 55% of patients had a trial available to them locally (34%) or statewide (21%). When considering lymphoma alone, as the most prominent AYA diagnosis, the majority of HL (89%) and NHL (82%) patients were not enrolled on clinical trials; of those patients not enrolled on a clinical trial, only 30% and 22% of HL and NHL, respectively, had a clinical trial available to them locally. Conclusion: In a community-based adult and pediatric oncology practice, there is a significant discrepancy in the number of L&L patients enrolled on a clinical trial when comparing pediatric and AYA cohorts. AYA L&L patients fail to be enrolled on clinical trials due to lack of clinical trial availability as compared to the pediatric L&L population. Disclosures: No relevant conflicts of interest to declare.

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Clinical trial accrual among new cancer patients at a community-based cancer center

Cancer ◽

10.1002/cncr.21597 ◽

2006 ◽

Vol 106 (2) ◽

pp. 426-433 ◽

Cited By ~ 78

Author(s):

Ronald S. Go ◽

Kathleen A. Frisby ◽

Jennifer A. Lee ◽

Michelle A. Mathiason ◽

Christine M. Meyer ◽

...

Keyword(s):

Clinical Trial ◽

Cancer Patients ◽

Cancer Center ◽

Community Based ◽

Clinical Trial Accrual

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

Journal of Clinical Oncology ◽

10.1200/jco.2001.19.6.1728 ◽

2001 ◽

Vol 19 (6) ◽

pp. 1728-1733 ◽

Cited By ~ 384

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.

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MatchMiner: An open source computational platform for real-time matching of cancer patients to precision medicine clinical trials using genomic and clinical criteria

10.1101/199489 ◽

2017 ◽

Cited By ~ 2

Author(s):

James Lindsay ◽

Catherine Del Vecchio Fitz ◽

Zachary Zwiesler ◽

Priti Kumari ◽

Bernd Van Der Veen ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Precision Medicine ◽

Open Source ◽

Cancer Patients ◽

Patient Specific ◽

Current Standard ◽

Eligibility Criteria ◽

Clinical Criteria ◽

Cancer Medicine

AbstractBackgroundMolecular profiling of cancers is now routine at many cancer centers, and the number of precision cancer medicine clinical trials, which are informed by profiling, is steadily rising. Additionally, these trials are becoming increasingly complex, often having multiple arms and many genomic eligibility criteria. Currently, it is a challenging for physicians to match patients to relevant clinical trials using the patient’s genomic profile, which can lead to missed opportunities. Automated matching against uniformly structured and encoded genomic eligibility criteria is essential to keep pace with the complex landscape of precision medicine clinical trials.ResultsTo meet these needs, we built and deployed an automated clinical trial matching platform called MatchMiner at the Dana-Farber Cancer Institute (DFCI). The platform has been integrated with Profile, DFCI’s enterprise genomic profiling project, which contains tumor profile data for >20,000 patients, and has been made available to physicians across the Institute. As no current standard exists for encoding clinical trial eligibility criteria, a new language called Clinical Trial Markup Language (CTML) was developed, and over 178 genomically-driven clinical trials were encoded using this language. The platform is open source and freely available for adoption by other institutions.ConclusionMatchMiner is the first open platform developed to enable computational matching of patient-specific genomic profiles to precision cancer medicine clinical trials. Creating MatchMiner required developing clinical trial eligibility standards to support genome-driven matching and developing intuitive interfaces to support practical use-cases. Given the complexity of tumor profiling and the rapidly changing multi-site nature of genome-driven clinical trials, open source software is the most efficient, scalable, and economical option for matching cancer patients to clinical trials.

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Barriers to clinical trial accrual in a community cancer clinic.

Journal of Clinical Oncology ◽

10.1200/jco.2014.32.30_suppl.91 ◽

2014 ◽

Vol 32 (30_suppl) ◽

pp. 91-91

Author(s):

Cheruppolil R. Santhosh-Kumar

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Cancer Patients ◽

Community Setting ◽

Care Quality ◽

Rural Setting ◽

Trial Participation ◽

Trial Process ◽

Clinical Trial Accrual ◽

Cancer Clinic

91 Background: The availability of and enrollment in clinical trials at an institution may be considered cancer care quality measures. Nationally, most cancer patients are initially diagnosed and treated in the community setting. Data regarding clinical trial accrual of new cancer patients from community-based cancer centers and the barriers they encounter are limited. We sought to identify potential barriers to enrollment in clinical trials at a community cancer clinic. Methods: Data on new cancer patients seen at our comprehensive community cancer clinic were prospectively collected from 2007 through 2010. Factors that potentially affected patient accrual in clinical studies were tracked. Results: During the four-year study period, a total of 662 patients were diagnosed with breast, prostate, colon, lung, gynecological, melanoma and renal cell cancers. No studies were available for 42% of the patients (n=278). Of the remaining patients, 49% (190/384) met protocol eligibility. Of the eligible study patients, 45% (85/190) enrolled, for an overall accrual rate of 13% (85/662), and 55% (105/190) declined participation. Patients declined to participate due to stress of diagnosis, refusal of treatment entirely, issues with randomization and placebo, concerns with side effects of the medications, delay of treatment while awaiting the clinical trial process, patient refusal, transportation concerns and length of treatment. Conclusions: This study demonstrates that above average clinical trial participation can be achieved in community cancer clinics in the rural setting. There are modifiable barriers to clinical trial accrual including study availability, patient eligibility and other patient factors. Improvement of patients’ perceptions and perspectives regarding the clinical trial process could be achieved through patient education. Elimination of barriers to trial accrual could be studied as a quality metric.

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