David A. Siegel, Eric B. Durbin, Brad H. Pollock, Allison Grimes, Lingyun Ji, Todd A. Alonzo, Sarah L. Vargas, Bin Huang, Jaclyn R. McDowell, Ellen Lycan, Peter Ransdell, Eric Tai, Michael E. Roth, David R. Freyer

Population-Based Data Linkage Describing Patterns of Cancer Clinical Trial Enrollment Among Children and Adolescents

  • Oncology (nursing)
  • Health Policy
  • Oncology

PURPOSE Database linkage between cancer registries and clinical trial consortia has the potential to elucidate referral patterns of children and adolescents with newly diagnosed cancer, including enrollment into cancer clinical trials. This study's primary objective was to assess the feasibility of this linkage approach. METHODS Patients younger than 20 years diagnosed with incident cancer during 2012-2017 in the Kentucky Cancer Registry (KCR) were linked with patients enrolled in a Children's Oncology Group (COG) study. Matched patients between databases were described by sex, age, race and ethnicity, geographical location when diagnosed, and cancer type. Logistic regression modeling identified factors associated with COG study enrollment. Timeliness of patient identification by KCR was reported through the Centers for Disease Control and Prevention's Early Case Capture (ECC) program. RESULTS Of 1,357 patients reported to KCR, 47% were determined by matching to be enrolled in a COG study. Patients had greater odds of enrollment if they were age 0-4 years ( v 15-19 years), reported from a COG-affiliated institution, and had renal cancer, neuroblastoma, or leukemia. Patients had lower odds of enrollment if Hispanic ( v non-Hispanic White) or had epithelial (eg, thyroid, melanoma) cancer. Most (59%) patients were reported to KCR within 10 days of pathologic diagnosis. CONCLUSION Linkage of clinical trial data with cancer registries is a feasible approach for tracking patient referral and clinical trial enrollment patterns. Adolescents had lower enrollment compared with younger age groups, independent of cancer type. Population-based early case capture could guide interventions designed to increase cancer clinical trial enrollment.

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