Annual Meeting of the NCI Cohort Consortium (Abstract Submission): Submission #8
Submission information
Submission Number: 8
Submission ID: 150019
Submission UUID: 4fdc7561-b4ba-471f-8a45-e0a4e1775718
Submission URI: /egrp/cohortconsortium/abstracts
Submission Update: /egrp/cohortconsortium/abstracts?token=c9D1XsZf_mnlFfAFvzj2mM9vI4-3kj-3Egu_O93mY4s
Created: Wed, 08/27/2025 - 14:15
Completed: Wed, 08/27/2025 - 14:33
Changed: Wed, 08/27/2025 - 14:33
Remote IP address: 10.208.24.239
Submitted by: Anonymous
Language: English
Is draft: No
Webform: Cohort 2025 (Abstracts Submission)
Lightning Talks Abstract
Isaac
Ergas
Staff Scientist
PhD, MPH
Kaiser Permanente Northern California Division of Research
The Pathways Study data portal: an automated, web-based platform for data sharing in a large cohort of breast cancer survivors
Background: The recent NIH Data Management & Sharing (DMS) policy outlines appropriate sharing of NIH-supported data. The Pathways Study, a prospective cohort of 4,504 breast cancer survivors diagnosed at Kaiser Permanente Northern California from 2005–2013, is developing an online data portal to make study-data and resources accessible while safeguarding privacy.
Methods: The portal includes: (1) study overviews and research team profiles; (2) collaborators, ancillary studies, publications, and dissemination of findings such as news stories and webinars; (3) downloadable questionnaires, data dictionaries, and biospecimen information; (4) interactive visualizations; (5) data explorer and request system; and (6) guidelines for data use, IRB requirements, and quality control prior to manuscript submission.
Data availability will be built-out incrementally, beginning with frequently requested data domains (e.g., demographics, tumor characteristics, outcomes) and later to additional domains. Data will be curated and uploaded into an SQL Server, then transferred daily into Oracle APEX to support the portal’s query and download functions. Future users can search variables, generate custom variable lists, and submit formal requests, which will integrate into internal workflows for review, approval, and delivery.
Results: The general website launched in October 2024, providing study information, dissemination of findings, and administrative resources. The data portal, including the variable explorer and data request system, is anticipated to launch in October 2025.
Conclusion/Discussion: We anticipate that the Pathways Study data portal will streamline data-sharing, facilitate collaboration, and maximize the value of cohort data. This platform also offers a model to meet the expectations of the NIH DMS policy.
Methods: The portal includes: (1) study overviews and research team profiles; (2) collaborators, ancillary studies, publications, and dissemination of findings such as news stories and webinars; (3) downloadable questionnaires, data dictionaries, and biospecimen information; (4) interactive visualizations; (5) data explorer and request system; and (6) guidelines for data use, IRB requirements, and quality control prior to manuscript submission.
Data availability will be built-out incrementally, beginning with frequently requested data domains (e.g., demographics, tumor characteristics, outcomes) and later to additional domains. Data will be curated and uploaded into an SQL Server, then transferred daily into Oracle APEX to support the portal’s query and download functions. Future users can search variables, generate custom variable lists, and submit formal requests, which will integrate into internal workflows for review, approval, and delivery.
Results: The general website launched in October 2024, providing study information, dissemination of findings, and administrative resources. The data portal, including the variable explorer and data request system, is anticipated to launch in October 2025.
Conclusion/Discussion: We anticipate that the Pathways Study data portal will streamline data-sharing, facilitate collaboration, and maximize the value of cohort data. This platform also offers a model to meet the expectations of the NIH DMS policy.