Citations

Abstract INTRODUCTION Participating in a clinical trial is a personal choice and an individual experience. Several barriers to recruitment of high risk men and women in chemoprevention trials have been documented; however, to our knowledge, there are no existing reports on participant satisfaction in such trials. Therefore, our aim was to describe and evaluate participants’ perception of their experience with participating in chemoprevention trials conducted by CPN by summarizing the 5-item “Was It Worth It” (WIWI) tool for each trial and across the trials, and according to race/ethnicity, sex, age, site, and organ of primary interest. METHODS Because participants who participate in chemoprevention trials tend to be at increased cancer-risk, but otherwise healthy, the WIWI tool can help answer simple questions about participants’ assessment of whether or not participation in such a trial was worthwhile. The WIWI tool was consistently administered at the end of the intervention period in each trial conducted by CPN; since 2003, 7 trials have completed the study intervention period and are included in the results reported here. RESULTS The scientific focus of the 7 trials targeted 5 organs: breast, colorectum, esophageal, hepatobiliary, and lung. Of the 485 participants registered to these 7 trials, 419 (86.4%) were non-Hispanic white, 19 (3.9%) non-Hispanic black, 32 (6.6%) Hispanic, 14 (2.9%) other race/ethnicity, and 1 (0.2%) unknown race/ethnicity; there were 120 (24.7%) females. In total, 446 (92.0%) participants completed the WIWI questionnaire at the end of their respective intervention period. Across the trials, 93% [95% CI] [90.6%, 95.4%] of the participants indicated that participation was worthwhile and 92% [89.5%, 94.5%] reported that they would participate again. Additionally, 414 (92.8%) participants indicated that they would recommend participating in the current research study to others, while 10 (2.3%) indicated that they would not and 22 (4.9%) were uncertain. Furthermore, several participants provided actionable feedback to the question “If there was one thing that could have been done to improve your experience in this research study, what would it be?” Participant feedback on overall changes in quality of life and on their expectations with participation in the trial was positive but more nuanced, varying according to trial and participant composition. CONCLUSION In this dataset of chemoprevention trial participants enrolled through the CPN consortium, highly favorable feedback was evident with respect to the overall study experience, suggesting that the recruitment and retention methods employed are facilitating success. These data can be used to help advance the NCI accrual quality improvement program in developing/enhancing strategies to improve accrual, retention, and adherence as well as enhance participant diversity in subsequent trials. Citation Format: David Zahrieh, Ryan P. McMurray, Nathan R. Foster, Paul J. Limburg, Sumithra J. Mandrekar. Participant satisfaction with cancer chemoprevention clinical trials: The Mayo Clinic Cancer Prevention Network (CPN) experience [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5092.

e23111 Background: Acupuncture has been shown to reduce aromatase inhibitor-induced arthralgias, as well as possibly hot flashes and fatigue, but research has been limited. The purpose of this study was to evaluate real world perceived benefit of acupuncture for commonly experienced symptoms among breast cancer survivors. Methods: Breast cancer survivors who had used acupuncture for cancer- or treatment-related symptoms were identified using an ongoing prospective Mayo Clinic Breast Disease Registry (MCBDR) cohort. In addition, Mayo Clinic electronic health records (EHR) were queried to identify additional participants. All identified patients were mailed a survey with acupuncture-related questions. Respondents were also asked to recall their severity of arthralgia, myalgia, post-surgical pain, hot flashes, nausea/vomiting, fatigue, depression, anxiety, insomnia, lymphedema, headache, and neuropathy from 1 to 5 (1 = mild, 5 = severe) before and after acupuncture treatment. Results: Acupuncture use was reported among 413 participants in MCBDR (12% of all enrollees) and 73 patients were identified in the Mayo EHR. 241 eligible women returned surveys (median age at diagnosis 50 yrs). Mean symptom severity scores decreased from before to after acupuncture by at least 1 point for all queried symptoms (Table). Conclusions: Acupuncture is frequently used by patients for a variety of breast cancer-related symptoms. Those who do pursue acupuncture usually perceive few toxicities and substantial benefits. Cost may be a barrier to treatment for some. [Table: see text]

Introduction: What if you could only ask one question of the patient during a clinic visit? Further, suppose the patient’s biggest concern can pragmatically be incorporated into routine clinical care and clinical pathways that can address the patient’s single biggest concern can be identified. If the principal concern can be dealt with efficiently at each visit through key stakeholder case management, positive outcomes should result. Therefore, motivated by the need for patient-centered health care visits, the Beacon electronic patient-reported outcomes (PRO) quality of life (QOL) tool was developed. Methods: Central to the tool is that at each health care visit, the patient’s biggest concern is electronically communicated to the health care team. Therefore, the tool can help catalyze important discussions between the health care team and the patient, perhaps on topics that would not have been discussed otherwise at a routine visit. In recognition of the community of resources needed to provide comprehensive care, the tool generates clinical pathways or actions that can be pursued to address the patient’s biggest concern. The concern is efficiently triaged such that members of the health care community with appropriate expertise and resources are identified to address and manage that single biggest concern signaled by the patient. A report, which can be uploaded into the patient’s medical chart, is created and provides a list of resources for a case manager to assist the patient and contains graphical presentations of the patient’s QOL and a history of prior concerns. The report also labels potentially significant changes in QOL. Discussion: The tool, which has been applied successfully in several health conditions, acts as a beacon to health care providers so that a patient’s self-reported concern can be consistently and effectively integrated into their care. Key Points: It is impractical to try to deal with every patient concern in every visit. The key to the Beacon tool is that at each visit the patient’s biggest concern is identified, clinical pathways indicated, and resources efficiently matched to address the patient’s biggest concern.

Motivated by the paucity of high‐quality stillbirth surveillance data and the spatial analysis of such data, we describe the pattern of stillbirth events as a step toward increased understanding of risk factors which can better guide future measures to mitigate these events. A challenge in such an analysis is that some mothers experience stillbirth events from independent pregnancies within a defined study period. To account for these dependencies, we parameterize our model to include a maternal contextual effect and broaden the appeal of Bayesian Poisson point process modeling to quantify excess stillbirth risk while considering a form of a log‐Gaussian Cox process. In the presence of extra unobserved spatial variation in risk, we demonstrate a pragmatic methodologic strategy to model the risk surface in relation to covariates and that there is a variance‐bias trade‐off associated with the use of a maternal contextual effect. We applied our strategy to the spatial distribution of stillbirth in Iowa during the years 2005–2011 using data obtained from an active, statewide public health surveillance program. We identified areas of excess risk for further investigation based on model components that captured important features of the data.