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Development and internal validation of predictive models for spread through air spaces in clinical stage IA lung adenocarcinoma

  • 0Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuaifuyuan, Beijing, 100730, China.
General Thoracic and Cardiovascular Surgery +

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April 28, 2025

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April 28, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

A new model accurately predicts spread through air spaces (STAS) in lung adenocarcinoma, improving preoperative assessment. This tool aids surgeons in optimizing treatment strategies for early-stage lung cancer patients.

Area Of Science

  • Thoracic Surgery
  • Surgical Oncology
  • Radiology

Background

  • Spread Through Air Spaces (STAS) is a key prognostic factor in lung adenocarcinoma.
  • Accurate preoperative prediction of STAS is crucial for treatment planning but remains challenging.
  • Current methods lack reliability for clinical stage IA lung adenocarcinoma.

Purpose Of The Study

  • To develop and validate predictive models for STAS in clinical stage IA lung adenocarcinoma.
  • To identify key predictors for STAS using demographic, CT, and PET features.
  • To provide an easy-to-use tool for preoperative STAS risk assessment.

Main Methods

  • Analysis of 1212 patients with clinical stage IA lung adenocarcinoma.
  • Development of two logistic regression models: Model 1 (demographics, CT features) and Model 2 (Model 1 + SUVmax).
  • Internal validation using tenfold cross-validation; assessment of discrimination (AUC) and calibration.

Main Results

  • STAS prevalence was 10.6%.
  • Model 1 (tumor diameter, smoking, location, spiculation, lobulation) showed moderate discrimination (AUC=0.700).
  • Model 2 (smoking, SUVmax, spiculation, lobulation) achieved higher discrimination (AUC=0.807) with good calibration, sensitivity 0.857, and specificity 0.652. A nomogram was developed.

Conclusions

  • Two validated models predict STAS in stage IA lung adenocarcinoma.
  • Model 2, incorporating SUVmax, significantly outperformed Model 1.
  • Model 2 aids surgeons in optimizing surgical strategies, potentially alongside frozen section analysis.

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