Genome-matched treatments and patient outcomes in the Maine Cancer Genomics Initiative (MCGI).

Genomic tumor testing (GTT) is an emerging technology aimed at identifying variants in tumors that can be targeted with genomically matched drugs. Due to limited resources, rural patients receiving care in community oncology settings may be less likely to benefit from GTT. We analyzed GTT results and observational clinical outcomes data from patients enrolled in the Maine Cancer Genomics Initiative (MCGI), which provided access to GTTs; clinician educational resources; and genomic tumor boards in community practices in a predominantly rural state. 1603 adult cancer patients completed enrollment; 1258 had at least one potentially actionable variant identified. 206 (16.4%) patients received a total of 240 genome matched treatments, of those treatments, 64% were FDA-approved in the tumor type, 27% FDA-approved in a different tumor type and 9% were given on a clinical trial. Using Inverse Probability of Treatment Weighting to adjust for baseline characteristics, a Cox proportional hazards model demonstrated that patients who received genome matched treatment were 31% less likely to die within 1 year compared to those who did not receive genome matched treatment (HR: 0.69; 95% CI: 0.52-0.90; p-value: 0.006). Overall, GTT through this initiative resulted in levels of genome matched treatment that were similar to other initiatives, however, clinical trials represented a smaller share of treatments than previously reported, and "off-label" treatments represented a greater share. Although this was an observational study, we found evidence for a potential 1-year survival benefit for patients who received genome matched treatments. These findings suggest that when disseminated and implemented with a supportive infrastructure, GTT may benefit cancer patients in rural community oncology settings, with further work remaining on providing genome-matched clinical trials.

The Maine Cancer Genomics Initiative: Implementing a Community Cancer Genomics Program Across an Entire Rural State.

PURPOSE: The Maine Cancer Genomics Initiative (MCGI) aimed to overcome patient- and provider-level barriers to using genomic tumor testing (GTT) in rural practices by providing genomic tumor boards (GTBs), clinician education, and access to comprehensive large-panel next-generation sequencing to all patients with cancer in Maine. This paper describes the successful implementation of the initiative and three key services made operative between 2016 and 2020. METHODS: A community-inclusive, hub-and-spoke approach was taken to implement the three program components: (1) a centralized GTB program; (2) a modular online education program, designed using an iterative approach with broad clinical stakeholders; and (3) GTT free of charge to clinicians and patients. Implementation timelines, participation metrics, and survey data were used to describe the rollout. RESULTS: The MCGI was launched over an 18-month period at all 19 oncology practices in the State. Seventy-nine physicians (66 medical oncologists, 5 gynecologic oncologists, 1 neuro-oncologist, and 7 pediatric oncologists) enrolled on the study, representing 100% of all practicing oncologists in Maine. Between July 2017 and September 2020, 1610 patients were enrolled. A total of 515 cases were discussed by 47 (73%) clinicians in 196 GTBs. Clinicians who participated in the GTBs enrolled significantly more patients on the study, stayed in Maine, and reported less time spent in clinical patient care. CONCLUSION: The MCGI was able to engage geographically and culturally disparate cancer care practices in a precision oncology program using a hub-and-spoke model. By facilitating access to GTT, structured education, and GTBs, we narrowed the gap in the implementation of precision oncology in one of the most rural states in the country.

Telemedicine Improves Rate of Successful First Visit to NICU Follow-up Clinic.

OBJECTIVES: NICU graduates require ongoing surveillance in follow-up clinics because of the risk of lower cognitive, motor, and academic performance. We hypothesized that multiple programmatic changes, including availability of telemedicine consultation before hospital discharge, would improve NICU follow-up clinic attendance rates. METHODS: In this retrospective study, we included infants who survived and were premature (≤29 6/7 weeks/<1500 g) or had brain injury (grade III/IV intraventricular hemorrhage, stroke or seizure, hypoxic ischemic encephalopathy). We compared rates of follow-up for the early cohort (January 2018-June 2019; no telemedicine) with the late cohort (May 2020-May 2021; telemedicine available); and performed a mediation analysis to assess other programmatic changes for the late cohort including improved documentation to parents and primary care provider regarding NICU follow-up. RESULTS: The rate of successful 12-month follow-up improved from 26% (early cohort) to 61% (late cohort) (P < .001). After controlling for maternal insurance, the odds of attending a 12-month follow-up visit were 3.7 times higher for infants in the late cohort, for whom telemedicine was available (confidence interval, 1.8-7.9). Approximately 37% of this effect was mediated by including information for NICU follow-up in the discharge documentation for parents (P < .001). CONCLUSIONS: Telemedicine consultation before NICU discharge, in addition to improving communication regarding the timing and importance of NICU follow-up, was effective at improving the rate of attendance to NICU follow-up clinics.

Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative.

OBJECTIVE: In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations. MATERIALS AND METHODS: We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using 4 federated Common Data Models. N3C data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements. RESULTS: Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source Common Data Model conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness, and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback. DISCUSSION: We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for DQ improvement that will support improved research analytics locally and in aggregate. CONCLUSION: By combining rapid, continual assessment of DQ with a large volume of multisite data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.

Feasibility of a Nurse Coached Walking Intervention for Informal Dementia Caregivers.

This study's purpose was to determine the feasibility of a nurse coached walking intervention for informal caregivers of persons with dementia. Participants were randomly assigned to a nurse coached intervention or a control group. Five male and 27 female caregivers (n = 32) participated. Measures included steps, walked well-being, and perceived stress. For steps walked, each group experienced a statistical difference (p = .01 control; p = .02 intervention) and large effect size (0.90). Neither group had a statistical difference in well-being (p = .38 control; p = .08 intervention) or perceived stress (p = .56 control; p = .18 intervention). The intervention group achieved a large effect size in well-being (1.38) and moderate effect size in perceived stress (0.51). A 0.94 pedometer adherence, self-reported user ease with technology and 100% retention rate support feasibility. Many participants described feelings of loneliness and grief, but reported the pedometer motivated them to walk.

Epistemic Beliefs: Relationship to Future Expectancies and Quality of Life in Cancer Patients.

CONTEXT: Expectations about the future (future expectancies) are important determinants of psychological well-being among cancer patients, but the strategies patients use to maintain positive and cope with negative expectancies are incompletely understood. OBJECTIVES: To obtain preliminary evidence on the potential role of one strategy for managing future expectancies: the adoption of "epistemic beliefs" in fundamental limits to medical knowledge. METHODS: A sample of 1307 primarily advanced-stage cancer patients participating in a genomic tumor testing study in community oncology practices completed measures of epistemic beliefs, positive future expectancies, and mental and physical health-related quality of life (HRQOL). Descriptive and linear regression analyses were conducted to assess the relationships between these factors and test two hypotheses: 1) epistemic beliefs affirming fundamental limits to medical knowledge ("fallibilistic epistemic beliefs") are associated with positive future expectancies and mental HRQOL, and 2) positive future expectancies mediate this association. RESULTS: Participants reported relatively high beliefs in limits to medical knowledge (M = 2.94, s.d.=.67) and positive future expectancies (M = 3.01, s.d.=.62) (range 0-4), and relatively low mental and physical HRQOL. Consistent with hypotheses, fallibilistic epistemic beliefs were associated with positive future expectancies (b = 0.11, SE=.03, P< 0.001) and greater mental HRQOL (b = 0.99, SE=.34, P = 0.004); positive expectancies also mediated the association between epistemic beliefs and mental HRQOL (Sobel Z=4.27, P<0.001). CONCLUSIONS: Epistemic beliefs in limits to medical knowledge are associated with positive future expectancies and greater mental HRQOL; positive expectancies mediate the association between epistemic beliefs and HRQOL. More research is needed to confirm these relationships and elucidate their causal mechanisms.

Patients' Expectations of Benefits From Large-Panel Genomic Tumor Testing in Rural Community Oncology Practices.

Large-panel genomic tumor testing (GTT) is an emerging technology that promises to make cancer treatment more precise. Because GTT is novel and complex, patients may have unrealistic expectations and limited knowledge of its benefits. These problems may limit the clinical value of GTT, but their prevalence and associated factors have not been explored. METHODS: Patients with cancer enrolled in a large initiative to disseminate GTT in community oncology practices completed surveys assessing their expectations, knowledge, and attitudes about GTT. The study sample (N = 1,139) consisted of patients with a range of cancer types (22% gynecologic, 14% lung, 10% colon, 10% breast, and 46% other malignancies) and cancer stages (4% stage I, 3% stage II, 15% stage III, and 74% stage IV). Mean age was 64 years (standard deviation = 11); 668 (59%) were women; 71% had no college degree; 57% came from households with less than $50,000 US dollars household income; and 73% lived in a rural area. RESULTS: Generally, patients had high expectations that they would benefit from GTT (M = 2.81 on 0-4 scale) and positive attitudes toward it (M = 2.98 on 0-4 scale). Patients also had relatively poor knowledge about GTT (48% correct answers on an objective test of GTT knowledge). Greater expectations for GTT were associated with lower knowledge (b = -0.46; P < .001), more positive attitudes (b = 0.40; P < .001), and lower education (b = -0.53; P < .001). CONCLUSION: This research suggests patients have high expectations that they will benefit from GTT, which is associated with low knowledge, positive attitudes, and low education. More research is needed to understand the concordance between expectations and actual clinical outcomes.