Practical prognostic tool for personalising first-line alectinib in ALK-positive NSCLC: A real-world model integrating neutrophil-to-lymphocyte ratio, lactate dehydrogenase, and eosinophil count.

e20743 Background: Despite the efficacy of first-line alectinib in anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC), significant interpatient heterogeneity exists. Robust tools for individualized risk stratification using readily available parameters are lacking. Methods: This retrospective study developed and validated a prognostic nomogram for overall survival (OS). The training cohort comprised 127 patients from a Chinese academic center. The external validation cohort included 64 patients from the US Flatiron Health database. All patients received first-line alectinib. Feature selection was performed using the Boruta algorithm among baseline clinical and laboratory variables. A Cox model was used to build a nomogram, which was assessed by concordance index (C-index), calibration curves, and decision curve analysis (DCA). Results: The model identified three independent prognostic factors: neutrophil-to-lymphocyte ratio (NLR), absolute eosinophil count (AEC), and lactate dehydrogenase (LDH). The nomogram demonstrated good discrimination, with a C-index of 0.78 (95% CI: 0.69–0.87) in the training cohort, which was maintained at 0.77 (95% CI: 0.68–0.86) upon external validation. Calibration was excellent across all predicted timepoints (1-5 years). Using an optimal cut-off (57.97 points), patients were stratified into low- and high-risk groups. High-risk patients had significantly inferior median OS (14.7 vs. not reached, P < 0.001) and time to treatment failure (7.7 vs. 62.5 months, P < 0.001) in the training cohort, a finding robustly validated externally. DCA confirmed the clinical utility of the model across a wide range of threshold probabilities. Conclusions: We developed and validated a practical prognostic nomogram based on three routine blood parameters (NLR, AEC, LDH) that effectively stratifies survival in ALK-positive NSCLC patients treated with first-line alectinib. This tool could facilitate personalized risk-adaptive management and enrich future clinical trials.

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Publication Details

Journal
Journal of Clinical Oncology
Published
2026-05-28
DOI
https://doi.org/10.1200/jco.2026.44.16_suppl.e20743
Primary Topic
Lung Cancer Treatments and Mutations
Type
article
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article

Practical prognostic tool for personalising first-line alectinib in ALK-positive NSCLC: A real-world model integrating neutrophil-to-lymphocyte ratio, lactate dehydrogenase, and eosinophil count.

Jianya Zhou, Jiahe Shi, Yufang W, Jing Zheng
Journal of Clinical Oncology
Lung Cancer Treatments and Mutations
article

Practical prognostic tool for personalising first-line alectinib in ALK-positive NSCLC: A real-world model integrating neutrophil-to-lymphocyte ratio, lactate dehydrogenase, and eosinophil count.

Jianya Zhou, Jiahe Shi, Yufang W, Jing Zheng
article en

Abstract

e20743 Background: Despite the efficacy of first-line alectinib in anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC), significant interpatient heterogeneity exists. Robust tools for individualized risk stratification using readily available parameters are lacking. Methods: This retrospective study developed and validated a prognostic nomogram for overall survival (OS). The training cohort comprised 127 patients from a Chinese academic center. The external validation cohort included 64 patients from the US Flatiron Health database. All patients received first-line alectinib. Feature selection was performed using the Boruta algorithm among baseline clinical and laboratory variables. A Cox model was used to build a nomogram, which was assessed by concordance index (C-index), calibration curves, and decision curve analysis (DCA). Results: The model identified three independent prognostic factors: neutrophil-to-lymphocyte ratio (NLR), absolute eosinophil count (AEC), and lactate dehydrogenase (LDH). The nomogram demonstrated good discrimination, with a C-index of 0.78 (95% CI: 0.69–0.87) in the training cohort, which was maintained at 0.77 (95% CI: 0.68–0.86) upon external validation. Calibration was excellent across all predicted timepoints (1-5 years). Using an optimal cut-off (57.97 points), patients were stratified into low- and high-risk groups. High-risk patients had significantly inferior median OS (14.7 vs. not reached, P < 0.001) and time to treatment failure (7.7 vs. 62.5 months, P < 0.001) in the training cohort, a finding robustly validated externally. DCA confirmed the clinical utility of the model across a wide range of threshold probabilities. Conclusions: We developed and validated a practical prognostic nomogram based on three routine blood parameters (NLR, AEC, LDH) that effectively stratifies survival in ALK-positive NSCLC patients treated with first-line alectinib. This tool could facilitate personalized risk-adaptive management and enrich future clinical trials.

Journal of Clinical OncologyVol. 44(16_suppl)
Zhejiang University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 6%
Lung Cancer Treatments and Mutations
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