Evidence map›Paper›PMID 42169576›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2026

Diagnostic Accuracy and Reproducibility of ChatGPT-4o for HER2 Immunohistochemistry Scoring in Equivocal Breast Cancer Cases.

Cheep Charoenlap, Pakorn Arunsawat, Kittiphan Chienwichai, Tanaporn Prateepchaiboon, Arunchai Chang

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Article in Asian Pacific journal of cancer prevention : APJCP, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Cheep CharoenlapDepartment of Anatomical Pathology, Hatyai Hospital, Songkhla, Thailand.
Pakorn ArunsawatDepartment of Anatomical Pathology, Hatyai Hospital, Songkhla, Thailand.
Kittiphan ChienwichaiDivision of Nephrology, Department of Internal Medicine, Hatyai Hospital, Songkhla, Thailand.
Tanaporn PrateepchaiboonDivision of Medical Oncology, Department of Internal Medicine, Hatyai Hospital, Songkhla, Thailand.
Arunchai ChangDivision of Gastroenterology, Department of Internal Medicine, Hatyai Hospital, Songkhla, Thailand.ORCID 0000-0002-0158-2685

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6 · The paper itself

Abstract

backgroundHER2 immunohistochemistry (IHC) plays a central role in therapeutic decision-making for breast cancer. However, interpretation of equivocal (2+) IHC results remains challenging and is subject to interobserver variability, necessitating reflex in situ hybridization testing. This study evaluated the diagnostic performance and reproducibility of ChatGPT-4o, a general-purpose large language model, in scoring HER2 IHC in breast cancer cases initially classified as IHC 2+.

methodsWe retrospectively analyzed 81 formalin-fixed, paraffin-embedded invasive carcinoma of no special type (NST) cases with prior HER2 IHC 2+ scores and corresponding dual in situ hybridization (DISH) results. Five high-power field images per case were independently analyzed by ChatGPT-4o across three sessions, using a standardized prompt aligned with the ASCO/CAP 2023 guidelines. Cases remaining equivocal after AI-assisted interpretation were excluded from diagnostic performance calculations. HER2 DISH served as the reference standard.

resultsFourteen cases (17.3%) remained equivocal following AI interpretation. Among the 67 reclassified cases, ChatGPT-4o demonstrated an overall diagnostic accuracy of 79% (95% CI: 67-88%), a sensitivity of 30%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 77%. Intra-model reproducibility was good (intraclass correlation coefficient = 0.78), whereas agreement with HER2 DISH was fair (Cohen's κ = 0.375). Misclassification predominantly involved false-negative interpretations among HER2-positive cases.

conclusionChatGPT-4o demonstrated high specificity and reproducibility for identifying HER2 IHC 3+ cases but showed limited sensitivity and only fair concordance with HER2 DISH. These findings indicate that, in its current general-purpose form, ChatGPT-4o is not suitable for independent HER2 assessment and may serve, at best, as an exploratory adjunct to pathologist interpretation.

Indexed as

Biomarkers, TumorBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesImmunohistochemistryFemaleFollow-Up StudiesGenerative Artificial IntelligenceHumansLarge Language ModelsPrognosisReproducibility of ResultsRetrospective StudiesBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesArtificial intelligencebreast cancerChatGPT-4odiagnostic reproducibilityHER2 immunohistochemistry

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.