A novel prognostic model based on lymph node ratio combined with prognostic nutrition index predicts survival in elderly patients with locally advanced gastrointestinal neoplasms

Lymph node ratio (LNR) is associated with the prognosis of malignant tumours. For elderly patients, the prognostic nutrition index (PNI) is also a vital factor for evaluating long-term survival after radical surgery. We aimed to develop a nomogram to predict the survival of elderly patients with locally advanced gastrointestinal malignancies. Clinical data of elderly patients with locally advanced gastric cancer (GC) or colorectal cancer (CRC) who underwent radical curative surgery at our centre from January 2010 to 2021 were retrospectively reviewed and collected. Using the surv_cutpoint function, we calculated the cut-off values of LNR and prognostic PNI and then divided the GC patients and CRC patients into two groups separately. The method was used to plot cumulative survival curves, and Cox proportional hazards models were used to assess factors influencing disease-free survival (DFS). A survival nomogram was constructed based on the factors screened from the multivariate analysis. We validated the model’s reliability through two approaches: an internal 7:3 random split and a longitudinal external validation, ensuring that the findings were both stable and generalisable. A total of 548 patients—340 with GC and 208 with CRC—with a median age of 69 years were included. The calculated cut-off values for the LNR were 0.21 for GC patients and 0.12 for CRC patients, whereas the PNI thresholds were set at 52.64 and 49.53, respectively. Based on these thresholds, patients were categorised into high-risk (LNR-high and PNI-low), low-risk, and intermediate-risk groups. Multivariate Cox regression analysis revealed that LNR-high status and PNI-low status (high-risk group), vessel carcinoma embolus status, perineural invasion status, abnormal tumour marker levels and incomplete adjuvant chemotherapy were independent risk factors for lowered survival. The constructed nomogram demonstrated robust discriminative power, with AUCs for 1-, 2-, and 3 year DFS consistently exceeding 0.84 in both the internal and temporal validation cohorts. Subgroup analyses further confirmed the model’s stable predictive efficacy across both the GC and CRC cohorts. The LNR combined with the PNI could better predict the prognosis of elderly patients with locally advanced gastrointestinal neoplasms. Trial registration This study was approved and supervised by the Research Ethics Committee of Peking University Cancer Hospital and Institute, Beijing, China (2025KT175). All methods and experimental protocols were carried out in accordance with relevant guidelines and regulations. All patients have signed informed consent to use these experimental data.

Authors

Institutions

Publication Details

Journal
European journal of medical research
Published
2026-05-11
DOI
https://doi.org/10.1186/s40001-026-04563-x
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A novel prognostic model based on lymph node ratio combined with prognostic nutrition index predicts survival in elderly patients with locally advanced gastrointestinal neoplasms

Shun-Yu Deng, Mao‐Xing Liu, Ke Xu, Jiadi Xing et al.
European journal of medical research
Inflammatory Biomarkers in Disease Prognosis
article

A novel prognostic model based on lymph node ratio combined with prognostic nutrition index predicts survival in elderly patients with locally advanced gastrointestinal neoplasms

Shun-Yu Deng, Mao‐Xing Liu, Ke Xu, Jiadi Xing, Xiang-Qian Su, Pin Gao, Fei Tan
article en

Abstract

Lymph node ratio (LNR) is associated with the prognosis of malignant tumours. For elderly patients, the prognostic nutrition index (PNI) is also a vital factor for evaluating long-term survival after radical surgery. We aimed to develop a nomogram to predict the survival of elderly patients with locally advanced gastrointestinal malignancies. Clinical data of elderly patients with locally advanced gastric cancer (GC) or colorectal cancer (CRC) who underwent radical curative surgery at our centre from January 2010 to 2021 were retrospectively reviewed and collected. Using the surv_cutpoint function, we calculated the cut-off values of LNR and prognostic PNI and then divided the GC patients and CRC patients into two groups separately. The method was used to plot cumulative survival curves, and Cox proportional hazards models were used to assess factors influencing disease-free survival (DFS). A survival nomogram was constructed based on the factors screened from the multivariate analysis. We validated the model’s reliability through two approaches: an internal 7:3 random split and a longitudinal external validation, ensuring that the findings were both stable and generalisable. A total of 548 patients—340 with GC and 208 with CRC—with a median age of 69 years were included. The calculated cut-off values for the LNR were 0.21 for GC patients and 0.12 for CRC patients, whereas the PNI thresholds were set at 52.64 and 49.53, respectively. Based on these thresholds, patients were categorised into high-risk (LNR-high and PNI-low), low-risk, and intermediate-risk groups. Multivariate Cox regression analysis revealed that LNR-high status and PNI-low status (high-risk group), vessel carcinoma embolus status, perineural invasion status, abnormal tumour marker levels and incomplete adjuvant chemotherapy were independent risk factors for lowered survival. The constructed nomogram demonstrated robust discriminative power, with AUCs for 1-, 2-, and 3 year DFS consistently exceeding 0.84 in both the internal and temporal validation cohorts. Subgroup analyses further confirmed the model’s stable predictive efficacy across both the GC and CRC cohorts. The LNR combined with the PNI could better predict the prognosis of elderly patients with locally advanced gastrointestinal neoplasms. Trial registration This study was approved and supervised by the Research Ethics Committee of Peking University Cancer Hospital and Institute, Beijing, China (2025KT175). All methods and experimental protocols were carried out in accordance with relevant guidelines and regulations. All patients have signed informed consent to use these experimental data.

European journal of medical research
Peking University (CN), Peking University Cancer Hospital (CN), Ministry of Education (ET)
National Natural Science Foundation of China
Reduced inequalities
Openalex Percentile: Top 7%
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.