Prompt Engineering for Eastern Cooperative Oncology Group Status Extraction: Comparing Large Language Model Techniques

Advanced LLM prompting improved ECOG extraction over basic methods. DFT and CoT each showed specific strengths (DFT had higher PPV and user satisfaction; CoT achieved higher sensitivity). These approaches appear to be generalizable across cancer types. Key implementation considerations include computational cost and human oversight. Overall, advanced prompting can standardize ECOG documentation, accelerate patient cohort identification, and inform personalized treatment planning.

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Publication Details

Journal
JCO Clinical Cancer Informatics
Published
2026-02-01
DOI
https://doi.org/10.1200/cci-25-00226
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Prompt Engineering for Eastern Cooperative Oncology Group Status Extraction: Comparing Large Language Model Techniques

Kok Joon Chong, L. Foo, IBUN TAN, Hwee Lin Wee et al.
JCO Clinical Cancer Informatics
Machine Learning in Healthcare
article

Prompt Engineering for Eastern Cooperative Oncology Group Status Extraction: Comparing Large Language Model Techniques

Kok Joon Chong, L. Foo, IBUN TAN, Hwee Lin Wee, Yuba Raj Pun, David Shao Peng Tan, Meenakshi Dubey, Melissa Ooi, Kee Yuan Ngiam
article en

Abstract

Advanced LLM prompting improved ECOG extraction over basic methods. DFT and CoT each showed specific strengths (DFT had higher PPV and user satisfaction; CoT achieved higher sensitivity). These approaches appear to be generalizable across cancer types. Key implementation considerations include computational cost and human oversight. Overall, advanced prompting can standardize ECOG documentation, accelerate patient cohort identification, and inform personalized treatment planning.

JCO Clinical Cancer InformaticsVol. 10(10)
National University of Singapore (SG), National University Cancer Institute, Singapore (SG), National Cancer Centre Singapore (SG), National University Hospital (SG), National University Health System (SG)
Openalex Percentile: Top 59%
Machine Learning in Healthcare
DOISourceOpenAlex
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Prompt Engineering for Eastern Cooperative Oncology Group Status Extraction: Comparing Large Language Model Techniques — Kok Joon Chong, L. Foo, et al. · JCO Clinical Cancer Informatics (2026) | TGRS Research Map | TGRS