Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility
Abstract Background Research on social determinants of genetic testing uptake is limited, particularly among unaffected patients with inherited cancer susceptibility. Methods We conducted a secondary analysis of the Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE) trial at Uni...
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BMC
2025-01-01
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Online Access: | https://doi.org/10.1186/s12885-025-13495-4 |
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author | Jemar R. Bather Melody S. Goodman Adrian Harris Guilherme Del Fiol Rachel Hess David W. Wetter Daniel Chavez-Yenter Lingzi Zhong Lauren Kaiser-Jackson Rachelle Chambers Richard Bradshaw Wendy Kohlmann Sarah Colonna Whitney Espinel Rachel Monahan Saundra S. Buys Ophira Ginsburg Kensaku Kawamoto Kimberly A. Kaphingst on behalf of the BRIDGE research team |
author_facet | Jemar R. Bather Melody S. Goodman Adrian Harris Guilherme Del Fiol Rachel Hess David W. Wetter Daniel Chavez-Yenter Lingzi Zhong Lauren Kaiser-Jackson Rachelle Chambers Richard Bradshaw Wendy Kohlmann Sarah Colonna Whitney Espinel Rachel Monahan Saundra S. Buys Ophira Ginsburg Kensaku Kawamoto Kimberly A. Kaphingst on behalf of the BRIDGE research team |
author_sort | Jemar R. Bather |
collection | DOAJ |
description | Abstract Background Research on social determinants of genetic testing uptake is limited, particularly among unaffected patients with inherited cancer susceptibility. Methods We conducted a secondary analysis of the Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE) trial at University of Utah Health and NYU Langone Health, involving 2,760 unaffected patients meeting genetic testing criteria for inherited cancer susceptibility and who were initially randomized to either an automated chatbot or an enhanced standard of care (SOC) genetic services delivery model. We used encounters from the electronic health record (EHR) to measure the uptake of genetic counseling and testing, including dichotomous measures of (1) whether participants initiated pre-test cancer genetic services, (2) completed pre-test cancer genetic services, (3) had genetic testing ordered, and (4) completed genetic testing. We merged zip codes from the EHR to construct census tract-weighted social measures of the Social Vulnerability Index. Multilevel models estimated associations between social vulnerability and genetic services utilization. We tested whether intervention condition (i.e., chatbot vs. SOC) moderated the association of social vulnerability with genetic service utilization. Covariates included study arm, study site, age, sex, race/ethnicity, language preference, rural residence, having a recorded primary care provider, and number of algorithm criteria met. Results Patients living in areas of medium socioeconomic status (SES) vulnerability had lower odds of initiating pre-test genetic services (adjusted OR [aOR] = 0.81, 95% CI: 0.67, 0.98) compared to patients living in low SES vulnerability areas. Patients in medium household vulnerability areas had a lower likelihood of completing pre-test genetic services (aOR = 0.80, 95% CI: 0.66–0.97) and having genetic testing ordered (aOR = 0.79, 95% CI: 0.63–0.99) relative to patients in low household vulnerability areas. We did not find that social vulnerability associations varied by intervention condition. Conclusions These results underscore the importance of investigating social and structural mechanisms as potential pathways to increasing genetic testing uptake among patients with increased inherited risk of cancer. Census information is publicly available but seldom used to assess social determinants of genetic testing uptake among unaffected populations. Existing and future cohort studies can incorporate census data to derive analytic insights for clinical scientists. Trial registration BRIDGE was registered as NCT03985852 on June 6, 2019 at clinicaltrials.gov. |
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spelling | doaj-art-9c47e0f3897549a490dd0b7a621715e02025-02-02T12:28:59ZengBMCBMC Cancer1471-24072025-01-0125111110.1186/s12885-025-13495-4Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibilityJemar R. Bather0Melody S. Goodman1Adrian Harris2Guilherme Del Fiol3Rachel Hess4David W. Wetter5Daniel Chavez-Yenter6Lingzi Zhong7Lauren Kaiser-Jackson8Rachelle Chambers9Richard Bradshaw10Wendy Kohlmann11Sarah Colonna12Whitney Espinel13Rachel Monahan14Saundra S. Buys15Ophira Ginsburg16Kensaku Kawamoto17Kimberly A. Kaphingst18on behalf of the BRIDGE research teamCenter for Anti-Racism, Social Justice & Public Health, New York University School of Global Public HealthCenter for Anti-Racism, Social Justice & Public Health, New York University School of Global Public HealthCenter for Anti-Racism, Social Justice & Public Health, New York University School of Global Public HealthDepartment of Biomedical Informatics, Spencer Fox Eccles School of Medicine, University of UtahDepartment of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of UtahDepartment of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of UtahDivision of Hematology-Oncology, Perelman School of Medicine at the University of PennsylvaniaDepartment of Communication, University of Minnesota DuluthHuntsman Cancer InstitutePerlmutter Cancer Center, NYU Langone HealthDepartment of Biomedical Informatics, Spencer Fox Eccles School of Medicine, University of UtahHuntsman Cancer InstituteBreast/Gynecologic System of Excellence, VA Medical Center National TeleOncologyHuntsman Cancer InstitutePerlmutter Cancer Center, NYU Langone HealthDivision of Oncology, Huntsman Cancer InstituteCenter for Global Health, National Cancer InstituteDepartment of Biomedical Informatics, Spencer Fox Eccles School of Medicine, University of UtahHuntsman Cancer InstituteAbstract Background Research on social determinants of genetic testing uptake is limited, particularly among unaffected patients with inherited cancer susceptibility. Methods We conducted a secondary analysis of the Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE) trial at University of Utah Health and NYU Langone Health, involving 2,760 unaffected patients meeting genetic testing criteria for inherited cancer susceptibility and who were initially randomized to either an automated chatbot or an enhanced standard of care (SOC) genetic services delivery model. We used encounters from the electronic health record (EHR) to measure the uptake of genetic counseling and testing, including dichotomous measures of (1) whether participants initiated pre-test cancer genetic services, (2) completed pre-test cancer genetic services, (3) had genetic testing ordered, and (4) completed genetic testing. We merged zip codes from the EHR to construct census tract-weighted social measures of the Social Vulnerability Index. Multilevel models estimated associations between social vulnerability and genetic services utilization. We tested whether intervention condition (i.e., chatbot vs. SOC) moderated the association of social vulnerability with genetic service utilization. Covariates included study arm, study site, age, sex, race/ethnicity, language preference, rural residence, having a recorded primary care provider, and number of algorithm criteria met. Results Patients living in areas of medium socioeconomic status (SES) vulnerability had lower odds of initiating pre-test genetic services (adjusted OR [aOR] = 0.81, 95% CI: 0.67, 0.98) compared to patients living in low SES vulnerability areas. Patients in medium household vulnerability areas had a lower likelihood of completing pre-test genetic services (aOR = 0.80, 95% CI: 0.66–0.97) and having genetic testing ordered (aOR = 0.79, 95% CI: 0.63–0.99) relative to patients in low household vulnerability areas. We did not find that social vulnerability associations varied by intervention condition. Conclusions These results underscore the importance of investigating social and structural mechanisms as potential pathways to increasing genetic testing uptake among patients with increased inherited risk of cancer. Census information is publicly available but seldom used to assess social determinants of genetic testing uptake among unaffected populations. Existing and future cohort studies can incorporate census data to derive analytic insights for clinical scientists. Trial registration BRIDGE was registered as NCT03985852 on June 6, 2019 at clinicaltrials.gov.https://doi.org/10.1186/s12885-025-13495-4Health technologyCancer predisposition syndromesDecision makingCancer preventionEarly detectionUser interaction |
spellingShingle | Jemar R. Bather Melody S. Goodman Adrian Harris Guilherme Del Fiol Rachel Hess David W. Wetter Daniel Chavez-Yenter Lingzi Zhong Lauren Kaiser-Jackson Rachelle Chambers Richard Bradshaw Wendy Kohlmann Sarah Colonna Whitney Espinel Rachel Monahan Saundra S. Buys Ophira Ginsburg Kensaku Kawamoto Kimberly A. Kaphingst on behalf of the BRIDGE research team Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility BMC Cancer Health technology Cancer predisposition syndromes Decision making Cancer prevention Early detection User interaction |
title | Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility |
title_full | Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility |
title_fullStr | Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility |
title_full_unstemmed | Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility |
title_short | Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility |
title_sort | social vulnerability and genetic service utilization among unaffected bridge trial patients with inherited cancer susceptibility |
topic | Health technology Cancer predisposition syndromes Decision making Cancer prevention Early detection User interaction |
url | https://doi.org/10.1186/s12885-025-13495-4 |
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