NCI Data Jamboree (Project Abstract Submission): Submission #31

Submission information
Submission Number: 31
Submission ID: 188930
Submission UUID: 9a96df0d-1901-4a14-9184-dd6c5e7f954f

Created: Fri, 07/24/2026 - 14:17
Completed: Fri, 07/24/2026 - 14:25
Changed: Fri, 07/24/2026 - 14:25

Remote IP address: 10.208.28.116
Submitted by: Anonymous
Language: English

Is draft: No
First Name Xiao
Middle Initial
Last Name Hu
Degree(s) B.S.
Position/Title/Career Status Graduate Student
Organization University of Maryland School of Public Health
Organization Address College Park, MD
Email xhu60@umd.edu
List of Additional Authors
  • First Name: Dylan
    Last Name: Boone
    Affiliation: University of Maryland School of Public Health
  • First Name: Betelihim
    Last Name: Haile
    Affiliation: University of Maryland School of Public Health
  • First Name: Shika
    Last Name: Marur
    Affiliation: University of Maryland School of Public Health
  • First Name: Marco
    Last Name: Negrete
    Affiliation: University of Maryland School of Public Health
Abstract Category Evaluating data quality for reproducibility and AI-readiness
Abstract Keywords NCCR, early-onset cancer, claims data, treatment validation
Abstract Title Comparison of registry treatment data and linked claims in the National Childhood Cancer Registry
Abstract The National Childhood Cancer Registry (NCCR) is a new US-based cancer registry that represents ~75% of all US children and adolescents and young adults (AYAs) diagnosed with cancer. It combines data from multiple cancer registries and links it to pharmacy and medical claims, area based measures, and other data sources. Some treatment information is reported within the cancer registry data; however, previous studies have found significant underreporting of systemic and radiation therapy data in cancer registries (e.g., SEER). Prior studies using SEER-Medicare linked data have evaluated treatment data quality among patients aged 65 and older, but to our knowledge, none have assessed this concordance in younger adults. These analyses are especially needed because AYAs diagnosed with cancer have distinct treatment patterns including more aggressive regimens and fertility preservation concerns. This kind of assessment would also provide valuable information for researchers interested in using NCCR, especially if they do not plan to use the linked claims data.

All patients aged 15-39 diagnosed with breast, colorectal, thyroid, or testicular cancer between 2000-2021 enrolled in a linked insurers plan for at least 12 months after their cancer diagnosis will be included in the analysis. Treatment concordance between the cancer registry and claims (gold standard) will be assessed using Kappa statistics, sensitivity, specificity, positive/negative predictive values, and percent agreement. Analysis will be performed overall and stratified by cancer site, stage, diagnosis year, and patient demographics. Our core in-event analysis will focus on breast cancer, with the remaining cancer types analyzed as time allows during and after the event. Deliverables include concordance metric tables, documentation of systemic discordance patterns, recommendations for NCCR data users regarding treatment variable validity, and reproducible code for cohort creation and analysis.

Experience using medical and pharmacy claims is needed. Analyses will be conducted using SAS.