Improving Precision of Do Not Contact Codes: Results of a Manual Review to Inform Coding and Case Contact Procedures.

Introduction: Central cancer registries are responsible for managing appropriate research contacts and record releases. Do not contact (DNC) flags are used by some registries to indicate patients who should not be contacted or included in research. Longitudinal changes in DNC coding practices and definitions may result in a lack of code standardization and inaccurately include or exclude individuals from research. Purpose: We performed a comprehensive manual review of DNC cases in the Utah Cancer Registry to inform updates to standardization of DNC code definitions, and use of DNC codes for exclusion/inclusion in research. Methods: We identified 858 cases with a current or prior DNC flag in the SEER Data Management System (SEER*DMS) or a research database, with cancers diagnosed from 1957-2021. We reviewed scanned images of correspondence with cases and physicians, incident forms, and comments in SEER*DMS and research databases. We evaluated whether there was evidence to support the current DNC code, a different DNC code, or insufficient evidence for any code. Results: Of the 755 cases that had a current DNC flag and reason code in SEER*DMS, the distribution was as follows: 58%, Patient requested no contact; 20%, Physician denied; 13%, Patient is not aware they have cancer; 4%, Patient is mentally disabled [sic]; 4%, Other; and 1%, Unknown. In 5% of these cases, we found evidence supporting a different DNC reason code. Among cases included because of a prior DNC flag in SEER*DMS (n = 10) or a DNC flag in a research database (ie, cases with no current DNC flag or reason code in SEER*DMS, n = 93), we found evidence supporting the addition of a SEER*DMS DNC flag and reason code in 50% and 40% of cases, respectively. We identified DNC reason codes with outdated terminology (Patient is mentally disabled) and codes that may not accurately reflect patient research preferences (Physician denied without asking the patient). To address this, we identified new reason codes, retired old reason codes, and updated current reason code definitions and research handlings. Conclusion: The time and resource investment in manual review allowed us to identify and, in most cases, resolve discordance in DNC flags and reason codes, adding reason codes when they were missing. This process was valuable because it informed recommended changes to DNC code definitions and research handlings that will ensure more appropriate inclusion and exclusion of cancer cases in research.

Predictors of Response Outcomes for Research Recruitment Through a Central Cancer Registry: Evidence From 17 Recruitment Efforts for Population-Based Studies.

When recruiting research participants through central cancer registries, high response fractions help ensure population-based representation. We conducted multivariable mixed-effects logistic regression to identify case and study characteristics associated with making contact with and obtaining cooperation of Utah cancer cases using data from 17 unique recruitment efforts undertaken by the Utah Cancer Registry (2007-2016) on behalf of the following studies: A Population-Based Childhood Cancer Survivors Cohort Study in Utah, Comparative Effectiveness Analysis of Surgery and Radiation for Prostate Cancer (CEASAR Study), Costs and Benefits of Follow-up Care for Adolescent and Young Adult Cancers, Study of Exome Sequencing for Head and Neck Cancer Susceptibility Genes, Genetic Epidemiology of Chronic Lymphocytic Leukemia, Impact of Remote Familial Colorectal Cancer Risk Assessment and Counseling (Family CARE Project), Massively Parallel Sequencing for Familial Colon Cancer Genes, Medullary Thyroid Carcinoma (MTC) Surveillance Study, Osteosarcoma Surveillance Study, Prostate Cancer Outcomes Study, Risk Education and Assessment for Cancer Heredity Project (REACH Project), Study of Shared Genomic Segment Analysis and Tumor Subtyping in High-Risk Breast-Cancer Gene Pedigrees, Study of Shared Genomic Segment Analysis for Localizing Multiple Myeloma Genes. Characteristics associated with lower odds of contact included Hispanic ethnicity (odds ratio (OR) = 0.34, 95% confidence interval (CI): 0.27, 0.41), nonwhite race (OR = 0.46, 95% CI: 0.35, 0.60), and younger age at contact. Years since diagnosis was inversely associated with making contact. Nonwhite race and age ≥60 years had lower odds of cooperation. Study features with lower odds of cooperation included longitudinal design (OR = 0.50, 95% CI: 0.41, 0.61) and study brochures (OR = 0.70, 95% CI: 0.54, 0.90). Increased odds of cooperation were associated with including a questionnaire (OR = 3.19, 95% CI: 1.54, 6.59), postage stamps (OR = 1.60, 95% CI: 1.21, 2.12), and incentives (OR = 1.62, 95% CI: 1.02, 2.57). Among cases not responding after the first contact, odds of eventual response were lower when >10 days elapsed before subsequent contact (OR = 0.71, 95% CI: 0.59, 0.85). Obtaining high response is challenging, but study features identified in this analysis support better results when recruiting through central cancer registries.