The American Registry for Migraine Research: Research Methods and Baseline Data for an Initial Patient Cohort.

BACKGROUND: The American Registry for Migraine Research (ARMR) is a multicenter, prospective, longitudinal patient registry, biorepository, and neuroimaging repository that collects clinical data, electronic health record (EHR) data, blood samples, and brain imaging data from individuals with migraine or other headache types. In this manuscript, we outline ARMR research methods and report baseline data describing an initial cohort of ARMR participants. METHODS: Adults with any International Classification of Headache Disorders (ICHD) diagnosis were prospectively enrolled from one of the 8 participating headache specialty centers. At baseline, ARMR participants complete web-based questionnaires, clinicians enter the participant's ICHD diagnoses, an optional blood specimen is collected, and neuroimaging data are uploaded to the ARMR neuroimaging repository. Participants maintain the ARMR daily headache diary longitudinally and follow-up questionnaires are completed by participants every 3 months. EHR data are integrated into the ARMR database from a subset of ARMR sites. Herein, we describe the ARMR methodology and report the summary data from ARMR participants who had, from February 2016 to May 2019, completed at least 1 baseline questionnaire from which data are reported in this manuscript. Descriptive statistics are used to provide an overview of patient's sociodemographics, headache diagnoses, headache characteristics, most bothersome symptoms other than headache, headache-related disability, comorbidities, and treatments. RESULTS: Data were available from 996 ARMR participants, enrolled from Mayo Clinic Arizona, Dartmouth-Hitchcock Medical Center, University of Utah, University of Colorado, Thomas Jefferson University, University of Texas Health Science Center at Houston, Georgetown University Medical Center, and DENT Neurological Institute. Among ARMR participants, 86.7% (n = 864) were female and the mean age at the time of enrollment was 48.6 years (±13.9; range 18-84). The most common provider-reported diagnosis was chronic migraine (n = 622), followed by migraine without aura (n = 327), migraine with aura (n = 196), and medication overuse headache (n = 65). Average headache frequency was 19.1 ± 9.2 days per month (n = 751), with 68% reporting at least 15 headache days per month. Sensitivity to light was the most frequent (n = 222) most bothersome symptom overall, other than headache, but when present, cognitive dysfunction was most frequently (n = 157) the most bothersome symptom other than headache. Average migraine disability assessment (MIDAS) score was 52 ± 49 (n = 760), (very severe headache-related disability); however, 17% of the ARMR population had MIDAS scores suggesting "no" or "mild" disability. The most common non-headache health issues were allergies (n = 364), back pain (n = 296), neck pain (n = 296), depression (n = 292), and anxiety (n = 278). Nearly 85% (n = 695) of patients were using preventive medications and 24.7% were using non-medication preventive therapy (eg, vitamins and neuromodulation). The most common preventive medication classes were neurotoxins, anticonvulsants, antidepressants, vitamins/supplements, and anticalcitonin gene-related peptide ligand or receptor-targeted monoclonal antibodies. Nearly 90% (n = 734) of ARMR participants was taking medications to treat migraine attacks, with the most common classes being triptans, non-steroidal anti-inflammatory drugs, antiemetics, acetaminophen, and combination analgesics. CONCLUSIONS: ARMR is a source of real-world patient data, biospecimens, and brain neuroimaging data that provides comprehensive insight into patients with migraine and other headache types being seen in headache specialty clinics in the United States. ARMR data will allow for longitudinal and advanced analytics that are expected to lead to a better characterization of patient heterogeneity, healthcare resource utilization, identification of endophenotypes, factors that predict treatment outcomes and clinical course, and ultimately advance the field toward precision headache medicine.

Decision Support and Shared Decision Making About Active Surveillance Versus Active Treatment Among Men Diagnosed with Low-Risk Prostate Cancer: a Pilot Study.

This study aimed to explore the effects of a decision support intervention (DSI) and shared decision making (SDM) on knowledge, perceptions about treatment, and treatment choice among men diagnosed with localized low-risk prostate cancer (PCa). At a multidisciplinary clinic visit, 30 consenting men with localized low-risk PCa completed a baseline survey, had a nurse-mediated online DS session to clarify preference for active surveillance (AS) or active treatment (AT), and met with clinicians for SDM. Participants also completed a follow-up survey at 30 days. We assessed change in treatment knowledge, decisional conflict, and perceptions and identified predictors of AS. At follow-up, participants exhibited increased knowledge (p < 0.001), decreased decisional conflict (p < 0.001), and more favorable perceptions of AS (p = 0.001). Furthermore, 25 of the 30 participants (83 %) initiated AS. Increased family and clinician support predicted this choice (p < 0.001). DSI/SDM prepared patients to make an informed decision. Perceived support of the decision facilitated patient choice of AS.

Evaluation of a Technology-Based Survivor Care Plan for Breast Cancer Survivors: Pre-Post Pilot Study.

BACKGROUND: As of 2016, almost 16 million individuals were cancer survivors, including over 3.5 million survivors of breast cancer. Because cancer survivors are living longer and have unique health care needs, the Institute of Medicine proposed a survivor care plan as a way to alleviate the many medical, emotional, and care coordination problems of survivors. OBJECTIVE: This pilot study for breast cancer survivors was undertaken to: (1) examine self-reported changes in knowledge, confidence, and activation from before receipt to after receipt of a survivor care plan; and (2) describe survivor preferences for, and satisfaction with, a technology-based survivor care plan. METHODS: A single group pretest-posttest design was used to study breast cancer survivors in an academic cancer center and a community cancer center during their medical visit after they completed chemotherapy. The intervention was a technology-based survivor care plan. Measures were taken before, immediately after, and 1 month after receipt of the survivor care plan. RESULTS: A total of 38 breast cancer survivors agreed to participate in the study. Compared to baseline levels before receipt of the survivor care plan, participants reported increased knowledge both immediately after its receipt at the academic center (P<.001) and the community center (P<.001) as well as one month later at the academic center (P=.002) and the community center (P<.001). Participants also reported increased confidence immediately following receipt of the survivor care plan at the academic center (P=.63) and the community center (P=.003) and one month later at both the academic center (P=.63) and the community center (P<.001). Activation was increased from baseline to post-survivor care plan at both the academic center (P=.05) and community center (P<.001) as well as from baseline to 1-month follow-up at the academic center (P=.56) and the community center (P<.001). Overall, community center participants had lower knowledge, confidence, and activation at baseline compared with academic center participants. Overall, 22/38 (58%) participants chose the fully functional electronic survivor care plan. However, 12/23 (52%) in the community center group chose the paper version compared to 4/15 (27%) in the academic center group. Satisfaction with the format (38/38 participants) and the content (37/38 participants) of the survivor care plan was high for both groups. CONCLUSIONS: This study provides evidence that knowledge, confidence, and activation of survivors were associated with implementation of the survivor care plan. This research agrees with previous research showing that cancer survivors found the technology-based survivor care plan to be acceptable. More research is needed to determine the optimal approach to survivor care planning to ensure that all cancer survivors can benefit from it.