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Diagnosis of the Novel IASLC Grading System Using Intraoperative Frozen Section (ECTOP-1014): A Prospective,
Fangqiu Fu1, Yan Jin2, Chaoqiang Deng1
1Department of Thoracic Surgery and State Key Laboratory of Genetics and Development of Complex Phenotypes, Fudan University Shanghai Cancer Center, Shanghai, China; Institute of Thoracic Oncology, Fudan University, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Background:
The International Association for the Study of Lung Cancer (IASLC) proposed a novel grading system for invasive nonmucinous adenocarcinoma. This study aimed to evaluate the accuracy of intraoperative frozen section in diagnosing IASLC grades in early-stage lung adenocarcinoma and to identify factors associated with potential misdiagnosis.
Methods:
This was a prospective, multicenter clinical trial from Eastern Cooperative Thoracic Oncology Projects (ECTOP-1014, NCT05794698), conducted from July 2022 to August 2023. Frozen section results were compared with final pathology to assess diagnostic concordance. Logistic regression was used to identify predictors of frozen section misdiagnosis.
Results:
The overall concordance rate between frozen section and final pathology in diagnosing IASLC grades was 79.9%, with a weighted κ of 0.627, indicating good agreement. Lepidic and micropapillary predominant patterns were independently associated with high misdiagnosis rates (P < .001). Interobserver agreement between pathologists was very good (κ = 0.821). With incorporation of frozen section into the model identifying grade 3 tumors, the area under the curve reached 0.907.
Conclusions:
Frozen section demonstrated favorable precision in diagnosing IASLC grades and could provide supplemental information that may aid in surgical decision-making. However, certain histologic patterns, such as lepidic and micropapillary, may lead to higher rates of misdiagnosis. Further studies are required to validate these findings and to explore the impact of frozen section-guided decisions on patient outcomes.
