RESUMO
Cancer health disparities persist across the cancer care continuum despite decades of effort to eliminate them. Among the strategies currently used to address these disparities are multi-institution research initiatives that engage multiple stakeholders and change efforts. Endemic to the theory of change of such programs is the idea that collaboration-across institutions, research disciplines, and academic ranks-is necessary to improve outcomes. Despite this emphasis on collaboration, however, it is not often a focus of evaluation for these programs and others like them. In this paper we describe a method for evaluating collaboration within the Meharry-Vanderbilt-Tennessee State University Cancer Partnership using network analysis. Specifically, we used network analysis of co-authorship on academic publications to visualize the growth and patterns of scientific collaboration across partnership institutions, research disciplines, and academic ranks over time. We presented the results of the network analysis to internal and external advisory groups, creating the opportunity to discuss partnership collaboration, celebrate successes, and identify opportunities for improvement. We propose that basic network analysis of existing data along with network visualizations can foster conversation and feedback and are simple and effective ways to evaluate collaboration initiatives.
Assuntos
Autoria , Pesquisa Interdisciplinar , Humanos , Universidades , Comunicação , Comportamento CooperativoRESUMO
BACKGROUND: Approximately 10% of patients with SCLC develop a paraneoplastic syndrome (PNS). Neurologic PNS are thought to improve prognosis, which we hypothesized is related to increased tumor-infiltrating lymphocytes and immune recognition. METHODS: We queried 2,512,042 medical records from a single institution to identify patients who have SCLC with and without PNS and performed manual, retrospective chart review. We then performed multiplexed fluorescence immunohistochemistry and automated quantitative analysis (AQUA Technology) on tumors to assess CD3, CD4, and CD8 T cell infiltrates and programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) interactions. T cell infiltrates and PD-1/PD-L1 interaction scores were compared among patients with neurologic PNS, endocrinologic PNS, and a control group without PNS. Clinical outcomes were analyzed using the Kaplan-Meier method and Cox proportional hazards models. RESULTS: We evaluated 145 SCLC patients: 55 with PNS (25 neurologic and 30 endocrinologic) and 90 controls. Patients with neurologic PNS experienced improved overall survival compared to patients with endocrinologic PNS and controls (median overall survival of 24 months versus 12 months versus 13 months, respectively). Of the 145 patients, we identified tumor tissue from 34 patients that was adequate for AQUA analysis. Among 37 specimens from these 34 patients, patients with neurologic PNS had increased T cell infiltrates (p = 0.033) and PD-1/PD-L1 interaction (p = 0.014) compared to tumors from patients with endocrinologic PNS or controls. CONCLUSIONS: Tumor tissue from patients with SCLC with neurologic PNS showed increased tumor-infiltrating lymphocytes and PD-1/PD-L1 interaction consistent with an inflamed tumor microenvironment.