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Identification of Key Elements in Prostate Cancer for Ontology Building via a Multidisciplinary Consensus Agreement.


ABSTRACT:

Background

Clinical data collection related to prostate cancer (PCa) care is often unstructured or heterogeneous among providers, resulting in a high risk for ambiguity in its meaning when sharing or analyzing data. Ontologies, which are shareable formal (i.e., computable) representations of knowledge, can address these challenges by enabling machine-readable semantic interoperability. The purpose of this study was to identify PCa-specific key data elements (KDEs) for standardization in clinic and research.

Methods

A modified Delphi method using iterative online surveys was performed to report a consensus agreement on KDEs by a multidisciplinary panel of 39 PCa specialists. Data elements were divided into three themes in PCa and included (1) treatment-related toxicities (TRT), (2) patient-reported outcome measures (PROM), and (3) disease control metrics (DCM).

Results

The panel reached consensus on a thirty-item, two-tiered list of KDEs focusing mainly on urinary and rectal symptoms. The Expanded Prostate Cancer Index Composite (EPIC-26) questionnaire was considered most robust for PROM multi-domain monitoring, and granular KDEs were defined for DCM.

Conclusions

This expert consensus on PCa-specific KDEs has served as a foundation for a professional society-endorsed, publicly available operational ontology developed by the American Association of Physicists in Medicine (AAPM) Big Data Sub Committee (BDSC).

SUBMITTER: Moreno A 

PROVIDER: S-EPMC10295832 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Identification of Key Elements in Prostate Cancer for Ontology Building via a Multidisciplinary Consensus Agreement.

Moreno Amy A   Solanki Abhishek A AA   Xu Tianlin T   Lin Ruitao R   Palta Jatinder J   Daugherty Emily E   Hong David D   Hong Julian J   Kamran Sophia C SC   Katsoulakis Evangelia E   Brock Kristy K   Feng Mary M   Fuller Clifton C   Mayo Charles C  

Cancers 20230608 12


<h4>Background</h4>Clinical data collection related to prostate cancer (PCa) care is often unstructured or heterogeneous among providers, resulting in a high risk for ambiguity in its meaning when sharing or analyzing data. Ontologies, which are shareable formal (i.e., computable) representations of knowledge, can address these challenges by enabling machine-readable semantic interoperability. The purpose of this study was to identify PCa-specific key data elements (KDEs) for standardization in  ...[more]

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