Prognostic Nutritional Index Predicts Early Recurrence After Esophagectomy for Esophageal Cancer Following Neoadjuvant Chemotherapy

Background/Aim: Although neoadjuvant chemotherapy (NAC) has improved oncologic outcomes in esophageal cancer, early postoperative recurrence remains a major cause of a poor prognosis. Immune-, inflammation-, and nutrition-based prognostic scores (IINBPS), such as the prognostic nutritional index (PNI), are reported prognostic markers in various malignancies; however, their ability to predict early recurrence after NAC remains unclear. This study aimed to identify the most reliable IINBPS for predicting early recurrence after esophagectomy following NAC. Patients and Methods: We retrospectively analyzed 61 patients with esophageal cancer who underwent curative esophagectomy following NAC between January 2012 and December 2024. Early recurrence was defined as recurrence within six months after surgery. Clinicopathological factors and IINBPS before and after NAC were evaluated. Receiver operating characteristic curve analysis was used to assess predictive performance, and risk factors for early recurrence were analyzed using univariate and multivariate logistic regression analyses. Results: without early recurrence had significantly lower pre-NAC PNI values. Multivariate analysis identified low pre-NAC PNI as an independent predictor of early recurrence. Conclusion: Pre-NAC PNI was the most useful IINBPS predictor of early recurrence after esophagectomy for esophageal cancer.

Authors

Institutions

Publication Details

Journal
Cancer Diagnosis & Prognosis
Published
2026-05-01
DOI
https://doi.org/10.21873/cdp.10557
Primary Topic
Esophageal Cancer Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prognostic Nutritional Index Predicts Early Recurrence After Esophagectomy for Esophageal Cancer Following Neoadjuvant Chemotherapy

Yoshinaga Okugawa, Hiroki Imaoka, Ryo Uratani, Takahito Kitajima et al.
Cancer Diagnosis & Prognosis
Esophageal Cancer Research and Treatment
article

Prognostic Nutritional Index Predicts Early Recurrence After Esophagectomy for Esophageal Cancer Following Neoadjuvant Chemotherapy

Yoshinaga Okugawa, Hiroki Imaoka, Ryo Uratani, Takahito Kitajima, Yuji Toiyama, Mai Shimamura, Mikio Kawamura, Tadanobu Shimura, Shigeyuki Yoshiyama, Hiromi Yasuda, SHINJI YAMASHITA, MASAKI OHI, TAKASHI ICHIKAWA, YOSHIKI OKITA
article en

Abstract

Background/Aim: Although neoadjuvant chemotherapy (NAC) has improved oncologic outcomes in esophageal cancer, early postoperative recurrence remains a major cause of a poor prognosis. Immune-, inflammation-, and nutrition-based prognostic scores (IINBPS), such as the prognostic nutritional index (PNI), are reported prognostic markers in various malignancies; however, their ability to predict early recurrence after NAC remains unclear. This study aimed to identify the most reliable IINBPS for predicting early recurrence after esophagectomy following NAC. Patients and Methods: We retrospectively analyzed 61 patients with esophageal cancer who underwent curative esophagectomy following NAC between January 2012 and December 2024. Early recurrence was defined as recurrence within six months after surgery. Clinicopathological factors and IINBPS before and after NAC were evaluated. Receiver operating characteristic curve analysis was used to assess predictive performance, and risk factors for early recurrence were analyzed using univariate and multivariate logistic regression analyses. Results: without early recurrence had significantly lower pre-NAC PNI values. Multivariate analysis identified low pre-NAC PNI as an independent predictor of early recurrence. Conclusion: Pre-NAC PNI was the most useful IINBPS predictor of early recurrence after esophagectomy for esophageal cancer.

Cancer Diagnosis & PrognosisVol. 6(3)
Mie University (JP), Mie University Hospital (JP)
Zero hunger
Openalex Percentile: Top 14%
Esophageal Cancer Research and Treatment
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.