Factors Associated With Breast Cancer Clinical Trials Participation and Enrollment at a Large Academic Medical Center

2004 ◽  
Vol 22 (11) ◽  
pp. 2046-2052 ◽  
Author(s):  
Michael S. Simon ◽  
Wei Du ◽  
Lawrence Flaherty ◽  
Philip A. Philip ◽  
Patricia Lorusso ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trials ◽  
Medical Center ◽  
Performance Status ◽  
Academic Medical Center ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Poor Performance Status ◽  
Cancer Clinical Trials ◽  
Factors Associated

Purpose The practice patterns of medical oncologists at a large National Cancer Institute Comprehensive Cancer Center in Detroit, MI were evaluated to better understand factors associated with accrual to breast cancer clinical trials. Patients and Methods From 1996 to 1997, physicians completed surveys on 319 of 344 newly evaluated female breast cancer patients. The 19-item survey included clinical data, whether patients were offered clinical trial (CT) participation and enrollment, and when applicable, reasons why they were not. Multivariate analyses using logistic regression were performed to evaluate predictors of an offer and enrollment. Results The patients were 57% white, 32% black, and 11% other/unknown race. One hundred six (33%) were offered participation and 36 (34%) were enrolled. In multivariate analysis, CTs were less likely offered to older women (mean age, 52 years for those offered v 57 years for those not offered; P = .0005) and black women (21% of blacks offered v 42% of whites; P = .0009). Women with stage 1 disease, poor performance status, and those who were previously diagnosed were also less likely to be offered trials. None of these factors were significant predictors of enrollment. Women were not offered trials because of ineligibility (57%), lack of available trials (41%), and noncompliance (2%). Reasons for failed enrollment included patient refusal (88%) and failed eligibility (12%). Conclusion It is important for cooperative groups to design studies that will accommodate a broader spectrum of patients. Further work is needed to assess ways to improve communication about breast cancer CT participation to all eligible women.

Relationship of age, smoking, alcohol use, and exercise among adults with cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e20582-e20582
Author(s):  
Shani Malia Alston ◽  
Allison Mary Deal ◽  
Brittaney-Belle Elizabeth Gordon ◽  
Trevor Augustus Jolly ◽  
Grant Richard Williams ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Alcohol Use ◽  
Exercise Intervention ◽  
Smoking Status ◽  
Medical Center ◽  
Academic Medical Center ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Vigorous Exercise ◽  
Former Smokers

e20582 Background: Smoking, alcohol use, and exercise among cancer patients (pts) are important health concerns due to their effects on treatment outcomes. Few studies have focused on health behaviors (HB) in this group. The goal of this study was to assess HB in cancer pts seen at an academic medical center. Methods: The Health Behavior Questionnaire (HBQ) is a nine-item survey that assesses smoking, alcohol and exercise behaviors based on the 2006/7 National Health Interview Survey (http://www.cdc.gov/nchs/nhis.htm). Pts completed the HBQ from 2010 to present as part of two breast cancer (BC) trials and a geriatric assessment trial. The Jonckheere-Terpstra test compared differences among groups as age increased (Jonckheere, Biometrika 41:1/2, 1954). Results: Of 371 pts, 66% were age ≥60 (median 66), 81% white, 16% black and 95% were female. BC was most common (92%). 5% were current and 40% former smokers. 43% reported having ≥1 drinks per week (dpw). Alcohol users averaged 5 dpw (range of 1-18). 40% never exercised vigorously (≥10 minutes that causes heavy sweating or large increases in heart rate/breathing). Older pts were less likely to exercise (p <0.001). Pts who exercised vigorously were more likely to drink (p<0.02). Former smokers were more likely to use alcohol (p<0.0004). The frequency of HB by age is tabulated below. Conclusions: The % of current smokers in this sample of cancer pts was lower than the national average (5% vs 19%) as was the % of current drinkers when compared nationally (43% vs 51.5%). There was no association of age with alcohol use or smoking status. Older pts in this cohort were significantly less likely to report vigorous exercise. As exercise is important for older pts, future studies in exercise intervention would be beneficial. Support: Breast Cancer Research Foundation, New York, NY and Lineberger Comprehensive Cancer Center, Chapel Hill, NC. [Table: see text]

scholarly journals Assessment of adherence and relative dose intensity with oral chemotherapy in oncology clinical trials at an academic medical center

2017 ◽  
Vol 24 (5) ◽  
pp. 348-353 ◽  
Author(s):  
Jeff A Engle ◽  
Anne M Traynor ◽  
Toby C Campbell ◽  
Kari B Wisinski ◽  
Noelle LoConte ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Medical Center ◽  
Performance Status ◽  
Academic Medical Center ◽  
Dose Intensity ◽  
Oral Chemotherapy ◽  
Relative Dose Intensity ◽  
Cancer Center ◽  
Related Factors ◽  
Oncology Clinical Trials

Background/Aims Oral chemotherapy is increasingly utilized leaving the patient responsible for self-administering an often complex regimen where adverse effects are common. Non-adherence and reduced relative dose intensity are both associated with poorer outcomes in the community setting but are rarely reported in clinical trials. The purpose of this study is to quantify adherence and relative dose intensity in oncology clinical trials and to determine patient and study related factors that influence adherence and relative dose intensity. Methods Patients were identified from non-industry-funded clinical trials conducted between 1 January 2009 and 31 March 2013 at the University of Wisconsin Carbone Cancer Center. Data were extracted from primary research records. Descriptive statistics and linear regression modeling was performed using SAS 9.4. Results A total of 17 clinical trials and 266 subjects were included. Mean adherence was greater than 97% for the first eight cycles. Mean relative dose intensity was less than 90% for the first cycle and declined over time. Male gender, a performance status of 1 or 2, metastatic disease, and traveling more than 90 miles to reach the cancer center were associated with higher relative dose intensity. Conclusions Patients with cancer enrolled in clinical trials are highly adherent but unlikely to achieve protocol specified relative dose intensity. Given that determining the phase II dose is the primary endpoint of phase I trials, incorporating relative dose intensity into this determination should be considered.

Accelerating the clinical trial start-up process for early-phase cancer studies: A test of process change to support rapid activation in an academic medical center.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e17507-e17507 ◽  
Author(s):  
Sheilah K Hurley ◽  
Therica M Miller ◽  
Rebecca Flores Stella ◽  
Keren Dunn ◽  
Ryan Schroeder ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Medical Center ◽  
Academic Medical Center ◽  
Cancer Center ◽  
Small Series ◽  
Academic Medical ◽  
One Year ◽  
Activation Times ◽  
High Level

e17507 Background: Clinical trial sponsors have strong scientific, financial, and regulatory interests in rapidly activating studies at participating sites. Academic medical centers have difficulty activating trials within a few weeks of sponsor agreement because, among other inefficiencies, they engage the necessary committee reviews, regulatory approvals, contracting, and budgeting in serial fashion. Incremental revisions in such workflows do not result in strong improvements. Methods: We redesigned our institutional workflow to complete clinical trial activation tasks within six weeks. Historical procedures were replaced rather than scrutinized. A high level leadership committee was required to change and integrate procedures across the medical center, and engage sponsors to improve their turnaround times. A web-based collaborative workflow tracking tool was created to help coordinate the necessary tasks and measure performance. Six clinical trials from the Cancer Center portfolio were used to test and improve the new workflow. Results: Clinical trial activation redesign took one year. For the six studies used as tests of change, the activation times were 49, 54, 78, 58, 62, and 32 days. Times in excess of 6 weeks were largely due to sponsor delays. Conclusions: Considerable effort is required to significantly alter a complex workflow like clinical trial activation. Appropriate priorities, leadership, staffing, and tools are required. Markedly shortened study activation for a small series of cancer trials taught our academic medical center lessons that will be useful for improving the process for all clinical trials, and will make us a better partner for pharmaceutical and academic sponsors as well as for investigator initiated research. [Table: see text]

Attrition rates, reasons, and predictive factors in supportive/palliative oncology clinical trials at a comprehensive cancer center.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 9069-9069
Author(s):  
Isabella Claudia Glitza ◽  
David Hui ◽  
Gary B. Chisholm ◽  
Eduardo Bruera
Keyword(s):  
Clinical Trials ◽  
Performance Status ◽  
Multivariate Logistic Regression Analysis ◽  
Symptom Burden ◽  
Attrition Rate ◽  
Comprehensive Cancer Center ◽  
Gastrointestinal Malignancies ◽  
Factors Associated ◽  
Palliative Oncology ◽  
Oncology Clinical Trials

9069 Background: Attrition is common among supportive/palliative oncology clinical trials. Few studies have documented the reasons and predictors for dropout. We aimed to determine the rate, reasons and factors associated with attrition both before reaching the primary endpoint (PE) and the end of study (EOS). Methods: We conducted a review of all prospective interventional supportive/palliative oncology trials by our department between 1999-2010. Patient and study characteristics and attrition data were extracted. We determined factors associated with attrition using multivariate logistic regression analysis. Results: 15 blinded randomized trials and 3 single arm trials were included. 16 of 18 studies did not reach accrual target. Baseline demographics for the 1214 patients were: median age 60 (range 23-93 years), female 56%, Caucasians 69%, ECOG performance status ≥3 41%, gastrointestinal malignancies (23%), median fatigue 7/10, appetite 5/10 and pain 4/10. Attrition rate was 26% (N=311) for PE and 44% (N=535) for EOS. Common reasons for EOS dropout were patient preference (N=93, 17%), symptom burden (N=87, 16%), death (N=45, 8%) and hospital admission (N=43, 8%), and were similar for PE dropouts. No predictors were identified for PE attrition. The Table shows poor performance status, anorexia and dyspnea are associated with EOS attrition in multivariate analysis. Conclusions: We found that attrition rate was high amongsupportive/palliative oncology clinical trials, and was associated with poor function and high baseline symptom burden. These findings have implications for future study designs including eligibility criteria and sample size calculation. [Table: see text]

Characterization of unplanned 30-day medical oncology readmissions after discharge at an academic medical center with a comprehensive cancer center.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 269-269 ◽  
Author(s):  
Inga Tolin Lennes ◽  
Justin Eusebio ◽  
Nie Bohlen ◽  
Margaret Ruddy ◽  
David P. Ryan
Keyword(s):  
Readmission Rate ◽  
Medical Center ◽  
Academic Medical Center ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Unplanned Readmission ◽  
Oncology Patient ◽  
Hematopoietic Stem ◽  
Medical Oncologists ◽  
Increased Risk

269 Background: Hospital readmission rate is increasingly suggested as a quality care metric. Currently there are no standard criteria for an avoidable readmission in oncology. Although patients with cancer have been identified as being at increased risk of readmission, there has been little to examine the reasons for the oncology patient readmission. The aim was to examine the profiles of patients with an unplanned readmission within 30 days after discharge by an oncology provider and to measure the unplanned 30-day readmission rate. Methods: A retrospective review of oncology provider discharge encounters resulting in a 30-day unplanned readmission during the 2012 calendar year at a tertiary hospital with a comprehensive cancer center was conducted. Planned readmissions for chemotherapy, radiation therapy, hematopoietic stem cell transplantation, dialysis, and surgical procedures, as well as readmissions for rehabilitation, hospice, and psychiatry were excluded. Medical oncologists analyzed medical records for the primary reason of readmission and if the readmission was possibly preventable. Results: Of the 2,944 admissions, a final cohort of 441 unplanned readmissions from 321 unique patients for an unplanned 30-day readmission rate of 14.9% was observed. The average age at admission was 59 (SD 15.9). The cohort was mostly male (56.9%) and White/Caucasian (84.4%). Gastrointestinal (24.0%), lymphoma (18.6%), and leukemia (17.5%) were the most common cancer types. Of those with solid tumors types (n = 225), approximately 70% had metastatic disease. The median time to readmission was 10 days and 10.7% died within 30 days of readmission. Oncology reviewers most commonly assessed that readmission was primarily due to treatment-related effects (46.7%) and the progression of disease (42.2%). Approximately 20% of 30-day readmissions were determined to be possibly preventable, representing 3% of all admissions for the year. Conclusions: Oncology patients readmitted within 30-days frequently present with complicated, advanced disease. A review by medical oncologists suggests there is margin for intervention to reduce 30-day unplanned admissions.

Bridging the gaps between tertiary and community care networks: Results from a southern California survey research analysis.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1538-1538
Author(s):  
Alex Chehrazi-Raffle ◽  
Nicholas Salgia ◽  
Joann Hsu ◽  
Zeynep Busra Zengin ◽  
Sabrina Salgia ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Los Angeles ◽  
Southern California ◽  
Medical Center ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Community Practice ◽  
Electronic Data Capture System ◽  
Tertiary Center

1538 Background: Although many tertiary cancer centers offer access to myriad research protocols, the majority of patients nevertheless receive treatment at community practices. We sought to examine the barriers that hamper clinical collaboration between tertiary and community practice environments in Southern California. Methods: A 31-item survey was distributed to community and tertiary oncologists using REDCap, a browser-based electronic data capture system. Survey questions assessed the following attributes: demographics and features of clinical practice, referral patterns, availability and knowledge pertaining to clinical trials, strategies for knowledge acquisition, and integration of community and tertiary practices. Results: The survey was distributed to 98 oncologists, 85 (87%) of whom completed it in full. The most common institutional affiliations were City of Hope Comprehensive Cancer Center (58%), University of California, Los Angeles (10%), and Cedars Sinai Medical Center (8%). In total, 52 (61%) respondents were community practitioners and 33 (38%) were tertiary oncologists. A majority (56%) of community oncologists defined themselves as general oncologists whereas almost all (97%) tertiary oncologists reported a subspecialty. Clinical trial availability was the most common reason for pt referrals to tertiary centers (73%). The most frequent barrier to tertiary referral was financial considerations (59%). Clinical trials were offered by 97% of tertiary practitioners as compared to 67% of community oncologists (p = 0.001). Of note, while a majority of tertiary center providers (52%) described the primary value of community practices to be a source of referrals for clinical trials, most community oncologists (82%) reported only a minimal-to-moderate understanding of clinical trials available at regional tertiary centers. Conclusions: Community oncologists refer patients to tertiary centers primarily with the intent of clinical trial enrollment; however, significant gaps exist in their knowledge of trial availability. Our results identify the need for enhanced communication and collaboration between community and tertiary providers to expand patients’ access to clinical trials.

Increasing Clinical Trials Accrual at a Comprehensive Cancer Center

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1266-1266
Author(s):  
Bayard L. Powell ◽  
Debbie Olson ◽  
Robert M. Morrell ◽  
Terry L. Hales ◽  
Kevin P High ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Clinical Research ◽  
Critical Role ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Point System ◽  
Cancer Clinical Trials ◽  
Treatment Trials ◽  
Academic Year ◽  
Year 2013

Abstract Background: During the academic year 2013 (July 2012-June 2013) our accrual to cancer clinical trials, a critical measure of success for a Comprehensive Cancer Center (CCC), was lower than prior years and below the desired level for CCC core grant renewal. Academic physicians were faced with increasing pressures to meet clinical demands, often at the expense of academic productivity, including clinical research. Methods: Our Dean and clinical leadership committed to support our efforts to increase accrual to clinical trials by providing salary support for our Section on Hematology and Oncology for specific milestones of 5%, 10%, and 15% increases in accrual to all clinical trials and in accrual to treatment (NCI definition) trials. The goal of the faculty was to increase accrual by > 15% to all trials and to treatment trials to maximize the “pool”. To determine how to divide the pool among investigators we developed a point system recognizing clinical investigators for roles as a) PI for trials (with additional points for all accrual to their trials) and b) for entering patients on clinical trials. The point system for both roles (PI and entering patients) was weighted relative to the value of the trial to the CCC, e.g. investigator initiated > cooperative group > industry initiated, and treatment trials >> non-treatment trials. In addition, we awarded points for publications (first and senior author > co-author) and presentations (oral > poster; major national meeting > other meetings). Results: During academic year 2014 (July 2013-June 2014) accrual to all cancer clinical trials increased by 140% (276 to 663) and accrual to treatment trials increased 40% (114 to 160). These increases occurred in both hematologic malignancies (95% all; 16% treatment) where we had a strong track record for accruals, and in solid tumors (200% all; 76% treatment) where our prior record was not as strong. Discussion: Accrual to clinical trials, both treatment and non-treatment improved dramatically. Interpretation of cause and effect is complex. The baseline year (2013) included implementation of a new EMR and the recent year (2014) included recruitment of additional faculty. However, 2014 was complicated by implementation of a new practice plan heavily weighted toward individual RVU production, and a decrease in available co-operative group trials to historically low levels. However, we can conclude that attention to this critical role of clinical investigators is important and can influence behavior. We cannot determine whether financial incentives are needed or whether the funding is one of several potential methods of recognition of the importance of clinical trials. It is possible that the commitment to provide financial support for clinical research demonstrated to clinical investigators that the leadership valued clinical trials activity and this recognition was more important than the actual funds. Future efforts will also need to find ways to recognize/reward clinical trials productivity of groups of investigators for their multidisciplinary contributions to the care of patients on clinical trials, without generating internal competition within the groups. Disclosures No relevant conflicts of interest to declare.

scholarly journals Administrative Support

2021 ◽  
pp. 85-91
Author(s):  
Gabriel Alcantara ◽  
Nelson J. Chao
Keyword(s):  
Operations Management ◽  
Financial Management ◽  
Administrative Support ◽  
Medical Center ◽  
Human Resources Management ◽  
Academic Medical Center ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Administrative Functions ◽  
Strategic Program

AbstractA comprehensive cancer center is supported with an administrative infrastructure that facilitates the overall planning, management, and organization in the delivery of the center’s cancer care. This chapter explores the various administrative functions that are integral to the development and implementation of a comprehensive cancer center. Core administrative functions include, but are not limited to, strategic program planning and development, financial management, human resources management, operations management, space and facilities planning, compliance to regulatory and accreditation standards, and facilitation of access/intake functions for new patients entering the center for care. Depending on size of the cancer center and whether it is a freestanding institution, affiliated with an academic medical center, or part of a hospital or health system, the administrative infrastructure can vary in the extent to which operations are centralized versus decentralized. The optimal framework for administrative management can be scaled incrementally as the cancer center grows.

scholarly journals Accuracy of an Artificial Intelligence System for Cancer Clinical Trial Eligibility Screening (Preprint)

2021 ◽  
Author(s):  
Tufia Haddad ◽  
Jane M. Helgeson ◽  
Katharine E. Pomerleau ◽  
Anita M. Preininger ◽  
M. Christopher Roebuck ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Clinical Trials ◽  
Cancer Patients ◽  
Predictive Value ◽  
Interrater Reliability ◽  
Academic Medical Center ◽  
Cancer Clinical Trials ◽  
Breast Cancer Patients ◽  
Cancer Trial

BACKGROUND Screening patients for eligibility for clinical trials is labor intensive. It requires abstraction of data elements from multiple components of the longitudinal health record and matching them to inclusion and exclusion criteria for each trial. Artificial intelligence (AI) systems have been developed to improve the efficiency and accuracy of this process. OBJECTIVE This study aims to evaluate the ability of an AI clinical decision-support system (CDSS) to identify eligible patients for a set of clinical trials. METHODS This study included the de-identified data from a cohort of breast cancer patients seen at the medical oncology clinic of academic medical center between May and July 2017 and assessed patient eligibility for four breast cancer clinical trials. CDSS eligibility screening performance was validated against manual screening. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for eligibility determinations were calculated. Disagreements between manual screeners and the CDSS were examined to identify sources of discrepancies. Interrater reliability between manual reviewers was analyzed using Fleiss’ kappa, and significance of differences was determined by Wilcoxon signed-rank test. RESULTS Three hundred eighteen breast cancer patients were included. Interrater reliability for manual screening was 0.64, indicating substantial agreement. The overall accuracy of breast cancer trial-eligibility determinations by the CDSS was 87.6%. CDSS sensitivity was 81.1% and specificity was 89%. CONCLUSIONS The AI CDSS in this study demonstrated accuracy, sensitivity, and specificity of greater than 80% in determining eligibility of patients for breast cancer clinical trials. CDSSs can accurately exclude ineligible patients for clinical trials and offers the potential to increase screening efficiency and accuracy. Additional research is needed to explore whether increased efficiency in screening and trial matching translates to improvements in trial enrollment, accruals, feasibility assessments, and cost.

Feasibility of integrating the Outcomes4Me smartphone navigation application into the care of breast cancer patients (FIONA).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1570-1570
Author(s):  
Steven J. Isakoff ◽  
Maya Said ◽  
Agnes H. Kwak ◽  
Eva Glieberman ◽  
Amanda Stroiney ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Pilot Study ◽  
Patient Engagement ◽  
Medical Center ◽  
Treatment Options ◽  
Academic Medical Center ◽  
Patient Reported ◽  
Clinical Trial Information

1570 Background: Patients diagnosed with breast cancer (BC) face complex decisions about their care and many studies have shown that improved patient engagement results in increased satisfaction and better outcomes. Patient engagement includes education, treatment option selection, symptom tracking and reporting, and clinical trial opportunities. We conducted a pilot study to determine the feasibility of introducing the Outcomes4Me patient engagement app into the standard of care experience of BC patients. Methods: This was a pilot study (NCT04262518) conducted at an academic medical center. Eligible patients had any subtype of stage 1-4 BC and were on any type of chemo-, hormonal-, targeted-, or radiation-therapy for BC during the study period. Participants downloaded the app on their smartphone and their app usage was evaluated. Surveys were administered at baseline and end of study. Clinicians caring for patients using the app were surveyed at the end of the study. The primary endpoint was feasibility, defined as at least 40% of patients engaging with the app at least 3 times over the 12-week study period. Additional endpoints included usability, satisfaction, correlation of patient reported data with the EHR, clinical trial matching, and patient experience. Results: Between June 2020 and December 2020, 107 patients enrolled; results are reported for 90 patients with complete data as of 1/24/21. Baseline demographics: median age 53 (range: 27-77); 90% White, 4% Black, 3% Asian; 66% had hormone positive/HER2-, 20% HER2+, and 13% triple negative BC; 31% had stage 4 disease. At study entry, 93% had never used an app to help with their disease or treatment options. Over the 12 week study period, 58% of patients engaged with the app at least 3 times, meeting the primary feasibility endpoint. Patients engaged with the app on average 5.5 days (range: 0-40) with 20% engaging on more than 10 days during the study. The mean System Usability Score was 71 (median = 76) and was similar across age groups. The 5 app features deemed most (‘somewhat’ or ‘very’) helpful were: background about their BC (76%), information about treatment options (74%), newsfeed about their BC (70%), symptom tracking (65%), and clinical trial information (65%). 53% said that the app helped them keep track of symptoms and 33% said they are more likely to explore or enroll in a clinical trial after using the app. Conclusions: Integration of the Outcomes4Me app into the care management of BC patients is feasible with acceptable usability. Our results suggest that use of a patient smartphone app may be helpful for many aspects of patient education and engagement for patients with BC. The results also suggest that this type of intervention can help patients better track their symptoms and make them aware of clinical trials, potentially facilitating the management of side effects and accelerating clinical trials recruitment. Clinical trial information: NCT04262518.

Sign in / Sign up

Export Citation Format

Share Document