Self-collected biospecimen consent and return rates in a population-based study among women with ovarian cancer: insights from the ORCHiD study.

PURPOSE: The collection of biospecimens in population-based studies enables investigation of molecular mechanisms underlying health outcomes but faces implementation challenges. We describe biospecimen collection outcomes in the Ovarian Cancer Epidemiology, Healthcare Access and Disparities (ORCHiD) study and identify key predictors of consent and return. METHODS: Among 764 ORCHiD participants recruited from seven state cancer registries (March 2021-October 2024), optional participation in a biospecimen sub-study requiring self-collection of saliva and vaginal swabs was offered. We used Poisson regression with robust error variance to estimate relative risks (RRs) and 95% confidence intervals (CIs) for sociodemographic, clinical, geographic, and logistical factors associated with biospecimen consent and return. RESULTS: Overall, 435 (56.9%) consented and 230 (52.9% of consenters) returned samples. In unadjusted analyses, unemployed participants were significantly less likely to consent (RR = 0.72, 95% CI: 0.53-0.98). In adjusted models, participants who were not married (RR = 1.16, 95% CI: 1.00-1.34) and those recruited from California (RR = 1.23, 95% CI: 1.02-1.49) were more likely to consent. Black participants were more likely than White participants to return biospecimens (RR = 1.31, 95% CI: 1.03-1.65), as were retired versus employed participants (RR = 1.28, 95% CI: 0.99-1.65). Return rates were lower from California (0.66, 95% CI: 0.48-0.90) and North Carolina (RR = 0.61, 95% CI: 0.41-0.90) versus New York. CONCLUSIONS: Higher return rates among Black participants suggest that culturally responsive engagement and follow-up strategies may support equitable biospecimen participation in population-based studies.

Duke Scholars

Author Tomi Akinyemiju Population Health Sciences

Author Andrew Berchuck Obstetrics and Gynecology, Gynecologic Oncology

Author April Deveaux Population Health Sciences