Community and academic partnerships: Moving a new generation of clinical trials in NCI Community Oncology Research Program (NCORP) into community oncology practices.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 2551-2551
Author(s):  
Worta J. McCaskill-Stevens ◽  
Ann M. Geiger
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Cancer Care ◽  
Cost Of Care ◽  
Community Practice ◽  
Effective Strategies ◽  
Oncology Research ◽  
Research Activities ◽  
Community Oncology ◽  
Catchment Areas

2551 Background: NCORP is a model program that bridges academic and community oncology practices and research. Over the past decade, community cancer investigators have adopted new technology, encountered new treatment sequalae, and faced rising cost of care with its financial toxicity imposed upon individuals seeking care. Opportunities are abundant for community investigators to assess feasibility and uptake of research advances into community practice settings, yet these opportunities are met with the challenges of dynamic changes in types of organizations delivering cancer care and diversity of populations within their catchment areas. Little information is shared about how and to what extent the health environment influences this partnership and the implementation of a broad cancer research portfolio. Methods: This abstract reports on the continued interest and participation of community oncologists in research which is demonstrated by 987 practices with over 4000 investigators in NCORP. Since 2014, over 30,000 individuals enrolled in symptom management, screening, surveillance, quality of life, and treatment trials. An additional 4500 patients and clinicians have enrolled in care delivery studies. Results: NCORP has been central in evaluating the most effective strategies for investigators to effectively communicate to patients the science of genomically-driven trials. It has also provided ways of bringing the pediatric and AYA patients access to the most up-to-date treatment strategies and new therapies in their community. This creates the least disruption on family structure/dynamics, diminished traveling requirements/costs, and reduced the financial burden. NCORP promotes involvement of treating oncologists in research activities. This also improves care for patients not enrolled in clinical trials. Therefore, NCORP serves as a laboratory to determine the most effective strategies for co-management of cancer patients and survivors. Conclusions: Several questions however remain to be addressed using this clinical trial model. These include: how to continue to reduce disparities in cancer care and clinical trial participation; and, what are the best strategies for fostering implementation of cancer care models in community practice.

Impact of nontreatment oncology research trials on physician engagement in clinical research in an oncology community practice setting.

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 44-44
Author(s):  
Susan S. Night ◽  
Juston S. Roemisch ◽  
David A. Smith
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Negative Impact ◽  
Rapid Development ◽  
Treatment Options ◽  
Community Practice ◽  
Oncology Research ◽  
Community Oncology ◽  
Physician Engagement

44 Background: The rapid development of new oncology drugs has created a significant increase in the number of clinical research studies. This underscores the need for greater participation in research by physicians as well as patients. Many physicians hesitate to participate in oncology clinical trials that provide treatment options for their patients given the complexity of the protocols. Non-treatment clinical trials may serve as a bridge for engaging physicians in clinical research and enhance the culture of research in community oncology practices. Methods: A large non-treatment oncology clinical trial was opened in a network of community oncology practices with approximately 1,000 physicians. We evaluated the number of physicians who did not enroll a patient onto a clinical trial in Year 1 but did enroll patients onto the non-treatment study. We further examined the number of physicians who enrolled a patient onto the non-treatment study that also enrolled patients onto a treatment clinical trial. Overall physician engagement in clinical research was measured by comparing practices where non-treatment study was offered to locations that did not participate in the non-treatment study. Negative impact on treatment accruals was also evaluated. Results: There were 105 physicians that practice at a site with the non-treatment study who had 0 accruals in Year 1 but enrolled a patient to any clinical trial in Year 2. Ninety-two of those physicians were responsible for enrolling over 900 patients to the non-treatment study in Year 2. Additionally, 46 of the 0 accruing physicians in Year 1, enrolled a patient to the non-treatment study also enrolled a patient to a treatment clinical trial. We also found that 24 physicians who did not did not enroll a patient in Year 1 and did not enroll a patient to the non-treatment study did enroll patients to a treatment clinical trial in Year 2. Conclusions: Participation in oncology treatment clinical trials can be difficult in the community oncology setting. Participation in a non-treatment study may serve as a bridge to engage more physicians in clinical research and enhance the culture of research within a community oncology practice.

Patients’ perceptions of care coordination among NCORP therapeutic clinical trial participants: A matched case-control study.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13504-e13504
Author(s):  
Izumi Okado ◽  
Ian Pagano ◽  
Jessica Rhee ◽  
Jeffrey L. Berenberg ◽  
Randall F. Holcombe
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Care Coordination ◽  
Cancer Care ◽  
Healthcare Delivery ◽  
Cancer Clinical Trials ◽  
Cancer Type ◽  
Oncology Research ◽  
Domain Scores

e13504 Background: Effective coordination of care (CC) is a critical component of high-quality cancer care; however, many patients with cancer continue to receive poorly coordinated care. CC experiences among therapeutic clinical trial (CT) participants are relatively unknown. We examined cancer patients’ perceptions of CC among CT participants using a validated Care Coordination Instrument (CCI). Methods: The study sample (N = 90) consisted of 45 CT participants and 45 matched non-participants from archival data from our prior CC studies. 171 patients who participated in therapeutic cancer clinical trials through the Hawaii Minority/Underserved NCI Community Oncology Research Program (NCORP) between 2015 and 2020 were contacted for study participation, and 26% completed the CCI. The CCI measures overall perceptions of CC and across 3 domains (Communication, Navigation, Operational). Paired t-tests were used to compare overall and domain scores between CT participants and non-participants. The two groups were matched by age, gender, cancer type (breast, GI, other), and clinical stage. Results: Among CT participants, the mean age was 61.7 ( SD = 9.4), and the majority were female (67%) and Asian (56%). The most common cancer types were breast (27%) and GI (16%), with 24% with stage III disease. CT participants reported significantly higher total CC scores than non-participants (62.5 vs. 55.8; p = .0008). Similar trends were found for Navigation ( p = .007) and Operational ( p = .001) domain scores. 29% of CT participants reported receiving high-intensity CC assistance from their clinical research associates (CRAs), and 27% indicated receiving moderate-level CC assistance. Responses to open-ended questions regarding CC revealed that CT participants received assistance with a variety of CC activities from their CRAs, including scheduling appointments and explaining test results and procedures. Conclusions: Patients who participate in therapeutic cancer clinical trials report more positive perceptions of CC compared to non-participants. Qualitative data suggest that significant care coordination support is provided by the clinical research associate. The results underscore the importance of CC support provided by CRAs who may be an unrecognized component of the healthcare delivery team. CC provided by CRAs may contribute to improved quality and value of cancer care for patients enrolled on therapeutic clinical trials.

Practical Aspects of Implementing and Applying Health Care Cloud Computing Services and Informatics to Cancer Clinical Trial Data

2021 ◽  
pp. 826-832
Author(s):  
Jay G. Ronquillo ◽  
William T. Lester
Keyword(s):  
Health Care ◽  
Clinical Trial ◽  
Cancer Research ◽  
Cloud Computing ◽  
Clinical Trials ◽  
Laboratory Tests ◽  
Cancer Clinical Trial ◽  
Cancer Clinical Trials ◽  
Precision Oncology ◽  
Oncology Research

PURPOSE Cloud computing has led to dramatic growth in the volume, variety, and velocity of cancer data. However, cloud platforms and services present new challenges for cancer research, particularly in understanding the practical tradeoffs between cloud performance, cost, and complexity. The goal of this study was to describe the practical challenges when using a cloud-based service to improve the cancer clinical trial matching process. METHODS We collected information for all interventional cancer clinical trials from ClinicalTrials.gov and used the Google Cloud Healthcare Natural Language Application Programming Interface (API) to analyze clinical trial Title and Eligibility Criteria text. An informatics pipeline leveraging interoperability standards summarized the distribution of cancer clinical trials, genes, laboratory tests, and medications extracted from cloud-based entity analysis. RESULTS There were a total of 38,851 cancer-related clinical trials found in this study, with the distribution of cancer categories extracted from Title text significantly different than in ClinicalTrials.gov ( P < .001). Cloud-based entity analysis of clinical trial criteria identified a total of 949 genes, 1,782 laboratory tests, 2,086 medications, and 4,902 National Cancer Institute Thesaurus terms, with estimated detection accuracies ranging from 12.8% to 89.9%. A total of 77,702 API calls processed an estimated 167,179 text records, which took a total of 1,979 processing-minutes (33.0 processing-hours), or approximately 1.5 seconds per API call. CONCLUSION Current general-purpose cloud health care tools—like the Google service in this study—should not be used for automated clinical trial matching unless they can perform effective extraction and classification of the clinical, genetic, and medication concepts central to precision oncology research. A strong understanding of the practical aspects of cloud computing will help researchers effectively navigate the vast data ecosystems in cancer research.

scholarly journals Evolution of Cancer Care Delivery Research in the NCI Community Oncology Research Program

2019 ◽  
Vol 112 (6) ◽  
pp. 557-561 ◽  
Author(s):  
Ann M Geiger ◽  
Ann M O’Mara ◽  
Worta J McCaskill-Stevens ◽  
Brenda Adjei ◽  
Priyanga Tuovenin ◽  
...  
Keyword(s):  
Research Program ◽  
National Cancer Institute ◽  
Cancer Care ◽  
Care Delivery ◽  
Well Being ◽  
Practice Change ◽  
Evidence Based ◽  
Oncology Research ◽  
Community Oncology ◽  
Robust Portfolio

Abstract Research seeking to improve patient engagement with decision-making, use of evidence-based guidelines, and coordination of multi-specialty care has made important contributions to the decades-long effort to improve cancer care. The National Cancer Institute expanded support for these efforts by including cancer care delivery research in the 2014 formation of the National Cancer Institute Community Oncology Research Program (NCORP). Cancer care delivery research is a multi-disciplinary effort to generate evidence-based practice change that improves clinical outcomes and patient well-being. NCORP scientists and community-based clinicians and organizations rapidly embraced the addition of this type of research into the network, resulting in a robust portfolio of observational studies and intervention studies within the first 5 years of funding. This commentary describes the initial considerations in conducting this type of research in a network previously focused on cancer prevention, control, and treatment studies; characterizes the protocols developed to date; and outlines future directions for cancer care delivery research in the second round of NCORP funding.

scholarly journals Current models, challenges and best practices for work conducted between European academic cooperative groups and industry

ESMO Open ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. e000628
Author(s):  
Rolf A Stahel ◽  
Denis Lacombe ◽  
Fatima Cardoso ◽  
Paolo G Casali ◽  
Anastassia Negrouk ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Working Group ◽  
Early Stage ◽  
Data Access ◽  
Cooperative Groups ◽  
Effective Strategies ◽  
Patients With Cancer ◽  
Oncology Research ◽  
Industry Partnerships ◽  
Multi Stakeholder

BackgroundThe academia-industry interface is important, and, despite challenges that inevitably occur, bears the potential for positive synergies to emerge. Perceived barriers to wider collaboration in academia-industry oncology research in Europe need to be addressed, current academic cooperative group and industry models for collaboration need to be discussed, and a common terminology to facilitate understanding of both sectors’ concerns needs to be established with an eye towards improving academia-industry partnerships on clinical trials for the benefit of patients with cancer.MethodologyCAREFOR (Clinical Academic Cancer Research Forum), a multi-stakeholder platform formed to improve the direction for academic clinical trials in the field of oncology in Europe, formed the CAREFOR-Industry Working Group comprised of experienced professionals from European academic cooperative groups joined by industry representatives selected based on their activities in the area of medical oncology. They jointly discussed academic cooperative groups, clinical trials conducted between academic cooperative groups and industry, examples of successful collaborative models, common legal negotiation points in clinical trial contracts, data access, and principles of interaction.ResultsFour principles of interaction between the academia and industry are proposed: (1) clarify the roles and responsibilities of all partners involved in the study, (2) involve legal teams from an early stage; (3) acknowledge that data is an important output of the study, (4) agree on the intent of the trial prior to its start.ConclusionsThe CAREFOR-Industry Working Group describes current models, challenges, and effective strategies for academia-industry research in Europe with an eye towards improving academia-industry partnerships on clinical trials for patients with cancer. Current perceived challenges are explained, and future opportunities/recommendations for improvement are described for the areas of most significant impact. Challenges are addressed from both the academic and industry perspectives, and principles of interaction for the optimal alignment between academia and industry in selected areas are proposed.

Identification of Cancer Care and Protocol Characteristics Associated With Recruitment in Breast Cancer Clinical Trials

2008 ◽  
Vol 26 (27) ◽  
pp. 4458-4465 ◽  
Author(s):  
Julie Lemieux ◽  
Pamela J. Goodwin ◽  
Kathleen I. Pritchard ◽  
Karen A. Gelmon ◽  
Louise J. Bordeleau ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Cancer Care ◽  
Primary Objective ◽  
Cancer Clinical Trials ◽  
Cooperative Groups ◽  
Number Of Patients ◽  
Trial Protocols ◽  
Few Data

Purpose It is estimated that only 5% of patients with cancer participate in a clinical trial. Barriers to participation may relate to available protocols, physicians, and patients, but few data exist on barriers related to cancer care environments and protocol characteristics. Methods The primary objective was to identify characteristics of cancer care environments and clinical trial protocols associated with a low recruitment into breast cancer clinical trials. Secondary objectives were to determine yearly recruitment fraction onto clinical trials from 1997 to 2002 in Ontario, Canada, and to compare recruitment fraction among years. Questionnaires were sent to hospitals requesting characteristics of cancer care environments and to cooperative groups/pharmaceutical companies for information on protocols and the number of patients recruited per hospital/year. Poisson regression was used to estimate the recruitment fraction. Results Questionnaire completion rate varied between 69% and 100%. Recruitment fraction varied between 5.4% and 8.5% according to year. More than 30% of patients were diagnosed in hospitals with no available trials. In multivariate analysis, the following characteristics were associated with recruitment: use of placebo versus not (relative risk [RR] = 0.80; P = .05), nonmetastatic versus metastatic trial (RR = 2.80; P < .01), and for nonmetastatic trials, protocol allowing an interval of 12 weeks or longer versus less than 12 weeks (from diagnosis, surgery, or end of therapy) before enrollment (RR = 1.36; P < .01). Conclusion Allowable interval of 12 weeks or longer to randomly assign patients in clinical trials could help recruitment. In our study, absence of an available clinical trial represented the largest barrier to recruitment.

Paucity of economic analyses of phase III clinical trials conducted by the cooperative oncology groups: A review of the evidence

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 17052-17052
Author(s):  
K. Fitzner ◽  
J. McKoy ◽  
C. L. Bennett
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Cost Effectiveness ◽  
Cancer Care ◽  
Phase Iii ◽  
Economic Data ◽  
Direct Medical Costs ◽  
Phase Iii Clinical Trials ◽  
Need To Evaluate ◽  
Economic Analyses

17052 Background: Cancer care is expensive, accounting for $72 billion in direct medical costs. New oncology drugs are frequently costly, and can be > $100,000 per patient. Hence, assessments of the costs and cost-effectiveness of cancer pharmaceuticals alongside phase III clinical trials conducted by the NCI-sponsored cooperative oncology groups represents an important opportunity to generate relevant economic data. Methods: Review of published cost and cost-effectiveness analyses for cancer drugs conducted alongside phase III clinical trials conducted by the NCI-sponsored cooperative clinical trial groups. Results: See Table . Conclusions: Despite increasing concerns over the high costs of cancer pharmaceuticals and the need to evaluate the costs and cost-effectiveness of these agents, NCI sponsored phase III clinical trials rarely include economic assessments. Future phase III clinical trials with expensive new cancer agents conducted by cooperative clinical trials groups should include prospective economic assessments. [Table: see text] No significant financial relationships to disclose.

Beyond metastatic renal cell carcinoma (mRCC) clinical trials: Targeted therapy use and overall survival in community oncology clinics.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e15061-e15061
Author(s):  
Michael Roger Harrison ◽  
Daniel J. George ◽  
Mark S. Walker ◽  
Lori L. Hudson ◽  
Connie Chen ◽  
...  
Keyword(s):  
Overall Survival ◽  
Clinical Trials ◽  
Cox Regression ◽  
Significant Risk ◽  
Standard Of Care ◽  
Community Practice ◽  
Disease Characteristics ◽  
Differential Outcomes ◽  
Drug Mechanism ◽  
Community Oncology

e15061 Background: Targeted therapies are now the standard of care for mRCC with use and expected outcomes defined by clinical trials. What are "real world" patterns of use and survival outcomes in mRCC patients (pts) treated in community oncology (COMM) settings? Methods: We reviewed a retrospective registry of adult mRCC pts from 11 COMM oncology practices, diagnosed since 1/2007 and not enrolled in a trial. Demographics, disease characteristics, treatment patterns and outcomes were recorded from the EMR and supplemented with chart abstraction.Pts were grouped by treatment sequence reflecting up to 3 exposures based on drug mechanism of action (VEGFR TKI [TKI] or mTOR inhibitor [mTOR]). Other pts received a non-TKI, non-mTOR therapy in the 1st three exposures (e.g., bevacizumab, cytokines, combinations, etc.). No Therapy pts received no systemic therapy as of data analysis. Survival analyses included Kaplan-Meier methods and Cox regression. Results: 255 patient/disease characteristics included: age 65±11 yrs; 68% male; 71% Caucasian; 62% clear cell histology (25% unknown); 1.6 ±0.9 metastatic sites. MSKCC risk was: 28% good, 63% intermediate, 10% poor. Median overall survival (OS) was 12.1 mo (95% CI: 8.7-15.4); median OS by sequence was: No Therapy (n=38; 3.7), mTOR (n=28; 5.2), TKI (n=79; 8.7), mTOR/TKI (n=10; 9.3), TKI/mTOR (n=32; 13.7), TKI/TKI (n=24; 20.7), Other (n=20; 22.5), TKI/mTOR/TKI (N=14; 29.8), TKI/TKI/mTOR (N=10; 33.1). Cox regression identified subgroups with differential outcomes. After significant covariates were controlled, compared with No Therapy, all regimens with TKI as 1st exposure had hazard ratios (HR) <1.0 (range=0.14 – 0.51; all p values ≤ 0.02). Other treatment had HR=0.31 (P=0.001), but when mTOR was the only treatment HR=1.04 (p=0.88). MSKCC scores of intermediate (HR=2.4) or poor (HR=4.5) were a significant risk (p<0.001). Conclusions: Only pts treated with two TKI exposures (≥20.7 mo) approached the best OS seen in trials (26 mo). For mTOR only, 1st line treatment in sicker patients, OS (5.2 mo) was shorter than trials (11 mo). Outcome differences between trial and community practice settings offer insights into opportunities to optimize care.

Capacity to provide specialized care for older adults in community oncology practices: Results of the NCI Community Oncology Research Program (NCORP) Landscape survey.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 6539-6539
Author(s):  
Grant Richard Williams ◽  
Kathryn E. Weaver ◽  
Glenn Jay Lesser ◽  
Emily Van Meter Dressler ◽  
Karen Marie Winkfield ◽  
...  
Keyword(s):  
Care Delivery ◽  
Median Number ◽  
Ancillary Services ◽  
Community Practice ◽  
Patient Portals ◽  
Free Standing ◽  
Oncology Research ◽  
Community Oncology ◽  
Specialized Care ◽  
American Society

6539 Background: American Society of Clinical Oncology guidelines recommend that patients ≥65 years of age starting chemotherapy undergo a geriatric assessment (GA) to inform and guide management; however, little is known about resources available in community oncology practices to facilitate geriatric specialty care and implement these guidelines. Methods: Community oncology practices were electronically surveyed in 2017 regarding the availability of various providers, supportive services, and practice characteristics, as part of a larger survey of cancer care delivery research (CCDR) capacity at NCORP sites. Designated CCDR leads provided information about their site. Descriptive statistics were used to report prevalence of resources available at each community practice. Results: Of the 925 NCORP practice locations, 504 (54%) responded to the survey, representing 227 practice groups. Of respondents, 58% included a free-standing clinic or private/group practice and 82% included inpatient services. The median number of new cancer cases per year ≥65 years of age was 443 (Interquartile range [IQR] 220-903). The median number of medical oncology providers was 5 (IQR 3-11). Only 1.8% of practices had a dual fellowship trained geriatric oncologist on staff. Geriatricians were available for consultation or co-management for 34% of sites, but only 13% of those had availability within the oncology clinic. Among those with access to geriatricians, consultations were primarily outpatient (90%) versus inpatient (54%). Ancillary services that could support GA were variably available onsite: social work (83%), nurse navigators (78%), pharmacist (77%), dietician (69%), supportive caregiver services (62%), rehabilitative medicine (57%), psychologist (41%), and psychiatrist (39%). Most sites utilized electronic health record systems (84%) and patient portals (89%). Conclusions: Availability of geriatric-trained providers is limited in community oncology practices. Use of primarily self-administered GA tools that direct referrals to available ancillary services may be an effective implementation strategy for guideline-based care.

Transforming the site feasibility assessment process for oncology clinical trials.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14092-e14092
Author(s):  
Dax Kurbegov ◽  
Patricia A. Hurley ◽  
David Michael Waterhouse ◽  
Grzegorz S. Nowakowski ◽  
Edward S. Kim
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Task Force ◽  
Assessment Process ◽  
Trial Participation ◽  
Clinical Trial Participation ◽  
Contract Research Organization ◽  
Feasibility Assessment ◽  
Oncology Research ◽  
Start Up

e14092 Background: Current methods to assess trial sites for clinical trial participation are onerous, with unnecessary redundancies and no-value steps that impact research site resources and clinical trial participation. This project sought stakeholder feedback on recommendations to transform industry sponsor and contract research organization (CRO) processes for evaluating sites for trials. Methods: An ASCO task force developed recommendations to improve the feasibility assessment process and standardize and centralize questions and forms. A survey was conducted with sites, industry trial sponsors, and CROs to obtain feedback and assess buy-in for the recommendations. Results: Respondents were from 28 oncology research sites (19 academic, 9 community-based), 8 sponsors, and 4 CROs. All stakeholders agreed that the current process is burdensome (93% sites, 90% sponsors, 100% CROs), standardization will improve the process (86% sites, 87% sponsors, 75% CROs). All agreed a centralized portal will reduce burdens (93% sites, 100% sponsors, 75% CROs) and expedite trial start-up (89% sites, 100% sponsors, 75% CROs). Site certification was a viable option for sites (86%) and CROs (75%), but less so for sponsors (57%). Most respondents preferred a two-tier model: 1) a short site questionnaire followed by a pre-study visit for new interactions, and 2) only a pre-study site visit or a teleconference if there is an existing relationship. The greatest benefits were time savings, expedited start-up, reduction in personnel resources, and cost savings. The greatest barriers to adoption were buy-in and alignment from sponsors/CROs and insufficient information about site or protocol. Top predictors of a site’s success on a trial were physician engagement, available patients, and site experience. Conclusions: Site feasibility assessments are important for all stakeholders to establish trial suitability. However, current methods impose tremendous burdens on site resources (reported by authors elsewhere). While this sample is limited, the proposed process and standardization changes show promise to reduce burdens and costs for all stakeholders and expedite patient enrollment onto clinical trials.

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