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Development, internal validation and calibration of a risk score to predict survival in patients with EGFR-mutant non-small cell lung cancer


Aims EGFR tyrosine kinase inhibitors (TKIs) are first-line molecularly targeted therapies in patients with advanced non-small cell lung cancer (NSCLC) who carry sensitising EGFR mutations, due to its superior survival outcomes compared with conventional chemotherapy regimens. In this study, we sought to identify clinical, immune and biochemical variables with prognostic significance in this patient subgroup and incorporate them into a nomogram-based risk score.

Methods A total of 199 patients with EGFR mutation-positive, advanced NSCLC (defined as stage IV at initial diagnosis or incurable disease recurrence) treated with first-line EGFR TKI therapy were retrospectively profiled. Univariable and multivariable survival analyses were conducted, with variables from the multivariable model with the highest Harrell’s Concordance (C) Index selected for inclusion in the subsequent survival nomogram. Internal validation and internal calibration of our prognostic nomogram were also performed.

Results Serum lactate dehydrogenase (LDH) and lung/pleural metastasis were independent predictors of unfavourable overall survival in all three multivariable models. A survival nomogram was generated based on the multivariable model with the highest Harrell’s C Index, incorporating the following 11 variables: white cell count, haemoglobin, LDH, neutrophil/lymphocyte ratio, ethnicity (Chinese vs non-Chinese), Karnofsky-Performance Status (score of ‘90–100’ or ‘70–80’ vs ‘0–60’), Charlson Comorbidity Index (≥3, or 2, or 1 vs 0), neurological symptoms, brain, lung/pleural and adrenal metastases.

Conclusion We identified serum LDH as an independent predictor of unfavourable clinical outcomes in patients with advanced, EGFR mutation-positive NSCLC. We further developed a robust nomogram-based risk score that incorporates clinical, biochemical and immune variables that can provide more targeted prognostication and management in this patient subgroup.

  • biomarkers, tumour
  • lung neoplasms
  • neoplasm metastasis

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