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Related Experiment Videos

Molecular-Based Risk Prediction Models for Recurrence After Curative Treatment of Early-Stage Lung Cancer: A

Aaron Ling1, Evangeline Samuel1,2,3, Rahini Mahendran4

  • 1Latrobe Regional Hospital, Traralgon, Victoria, Australia.

Thoracic Cancer
|July 15, 2026
PubMed
Summary

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Molecular prediction models show moderate-to-good performance for early-stage non-small cell lung cancer (NSCLC) recurrence and survival. Further external validation and methodological rigor are needed for clinical use.

Area of Science:

  • Oncology
  • Biostatistics
  • Genomics

Background:

  • Recurrence after curative treatment is a significant challenge in early-stage non-small cell lung cancer (NSCLC).
  • Molecular-based prediction models offer potential for improved risk stratification and personalized surveillance.
  • Current models require evaluation for clinical applicability.

Purpose of the Study:

  • To systematically identify and evaluate molecular-based risk prediction models for recurrence and survival in early-stage NSCLC.
  • To assess the performance and methodological quality of existing prediction models.

Main Methods:

  • Systematic review and meta-analysis following PRISMA guidelines.
  • Searched MEDLINE, EMBASE, and Cochrane Library (Jan 2000-Dec 2023).
Keywords:
early stagelocally advancedlung cancermolecular basedprognostic modelsrecurrencerisk prediction modessurveillance

Related Experiment Videos

  • Extracted performance metrics, assessed risk of bias (PROBAST), and pooled data using random-effects meta-analysis.

    • Main Results:

    • Five studies met inclusion criteria, utilizing mRNA expression, long noncoding RNAs, and DNA methylation.
    • Pooled AUC for internal validation was 0.77 (95% CI: 0.66-0.90); for external validation, it was 0.72 (95% CI: 0.68-0.75).
    • Two studies had high risk of bias; methodological rigor and external validation need improvement.

    Conclusions:

    • Molecular-based prediction models show moderate-to-good discriminative performance for recurrence and survival in early-stage NSCLC.
    • Broader external validation is crucial before routine clinical implementation.
    • Improved methodological rigor in model development and reporting is necessary.