Development and validation of a nomogram for predicting 90-day mortality in patients with advanced lung cancer based on inflammatory and nutritional biomarkers

This retrospective study of 455 stage III/IV non-small cell lung cancer patients treated at Sanmen People's Hospital from January 2022 to January 2025 aimed to identify prognostic factors for short-term mortality and develop a validated nomogram for risk assessment. Patients were divided into training (n = 318) and validation (n = 137) cohorts, with clinical and laboratory variables - age, body mass index, Eastern Cooperative Oncology Group (ECOG) performance status, chronic obstructive pulmonary disease (COPD), C-reactive protein (CRP), interleukin-6 (IL-6), serum albumin (ALB), and lactate dehydrogenase (LDH) - analyzed using Kolmogorov-Smirnov tests for data distribution, and t-tests, Mann-Whitney U tests, and chi-square tests for comparisons. Logistic regression identified CRP ≥ 24.42 mg/L (odds ratio = 6.285, P = 0.002), IL-6 ≥ 28.705 pg/mL (odds ratio = 38.364, P < 0.001), and LDH ≥ 357 U/L (odds ratio = 10.132, P < 0.001) as predictors of increased mortality risk, while ALB ≥ 32.65 g/L (odds ratio = 0.073, P < 0.001) and ECOG score = 0 (odds ratio = 0.214, P = 0.040) were associated with reduced risk. Cox regression confirmed CRP, IL-6, ALB, LDH, and COPD as significant predictors. A nomogram constructed from these factors showed strong performance, with area under the curve values of 0.932, 0.930, and 0.962 for 30-, 60-, and 90-day mortality in the training cohort, and 0.894, 0.916, and 0.925 in the validation cohort, respectively, alongside concordance indices of 0.922 (training) and 0.877 (validation). Decision curve analysis and calibration plots confirmed robust clinical applicability and prognostic precision, establishing the nomogram as a reliable tool for personalized risk stratification in advanced lung cancer.

Authors

Institutions

Publication Details

Journal
American Journal of Cancer Research
Published
2025-01-01
DOI
https://doi.org/10.62347/rnyp8960
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and validation of a nomogram for predicting 90-day mortality in patients with advanced lung cancer based on inflammatory and nutritional biomarkers

Zhouru Wang
American Journal of Cancer Research
Inflammatory Biomarkers in Disease Prognosis
article

Development and validation of a nomogram for predicting 90-day mortality in patients with advanced lung cancer based on inflammatory and nutritional biomarkers

Zhouru Wang
article en

Abstract

This retrospective study of 455 stage III/IV non-small cell lung cancer patients treated at Sanmen People's Hospital from January 2022 to January 2025 aimed to identify prognostic factors for short-term mortality and develop a validated nomogram for risk assessment. Patients were divided into training (n = 318) and validation (n = 137) cohorts, with clinical and laboratory variables - age, body mass index, Eastern Cooperative Oncology Group (ECOG) performance status, chronic obstructive pulmonary disease (COPD), C-reactive protein (CRP), interleukin-6 (IL-6), serum albumin (ALB), and lactate dehydrogenase (LDH) - analyzed using Kolmogorov-Smirnov tests for data distribution, and t-tests, Mann-Whitney U tests, and chi-square tests for comparisons. Logistic regression identified CRP ≥ 24.42 mg/L (odds ratio = 6.285, P = 0.002), IL-6 ≥ 28.705 pg/mL (odds ratio = 38.364, P < 0.001), and LDH ≥ 357 U/L (odds ratio = 10.132, P < 0.001) as predictors of increased mortality risk, while ALB ≥ 32.65 g/L (odds ratio = 0.073, P < 0.001) and ECOG score = 0 (odds ratio = 0.214, P = 0.040) were associated with reduced risk. Cox regression confirmed CRP, IL-6, ALB, LDH, and COPD as significant predictors. A nomogram constructed from these factors showed strong performance, with area under the curve values of 0.932, 0.930, and 0.962 for 30-, 60-, and 90-day mortality in the training cohort, and 0.894, 0.916, and 0.925 in the validation cohort, respectively, alongside concordance indices of 0.922 (training) and 0.877 (validation). Decision curve analysis and calibration plots confirmed robust clinical applicability and prognostic precision, establishing the nomogram as a reliable tool for personalized risk stratification in advanced lung cancer.

American Journal of Cancer ResearchVol. 15(8)
Wenzhou Medical University (CN), Taizhou First People's Hospital (CN), Zhejiang Taizhou Hospital (CN)
Zero hunger
Openalex Percentile: Top 68%
Inflammatory Biomarkers in Disease Prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development and validation of a nomogram for predicting 90-day mortality in patients with advanced lung cancer based on inflammatory and nutritional biomarkers — Zhouru Wang · American Journal of Cancer Research (2025) | TGRS Research Map | TGRS