Evidence map›Paper›PMID 41767901›Full record

ArticleJournal of inflammation research2026

Development and Validation of a Nomogram Based on Advanced Lung Cancer Inflammation Index for Predicting Overall Survival in Non-Surgical Esophageal Squamous Cell Carcinoma.

Changjiang Liu, Huiqing Li, Hua Li, Lei Liu, Jia Liang, Yan Zhao, Supeng Shen

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Article in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Changjiang Liu *Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050011, People's Republic of China.
Huiqing Li *Department of Oncology, People's Hospital of Wei County, Handan, Hebei, 056899, People's Republic of China.
Hua Li *Second Department of Surgery, The Sixth People's Hospital of Hengshui, Hengshui, Hebei, 053203, People's Republic of China.
Lei LiuDepartment of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050011, People's Republic of China.
Jia LiangLaboratory of Pathology, Hebei Cancer Institute, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050011, People's Republic of China.
Yan ZhaoDepartment of Radiotherapy, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050011, People's Republic of China.
Supeng ShenLaboratory of Pathology, Hebei Cancer Institute, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050011, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Despite advancements in multidisciplinary treatment strategies, long-term survival of esophageal squamous cell carcinoma (ESCC) patients remain suboptimal. Identifying novel prognostic biomarkers is essential for individualized treatment and surveillance approaches. The Advanced Lung Cancer Inflammation Index (ALI), an integrative biomarker reflecting nutritional, inflammatory, and immune status, has emerged as a potential predictor of prognosis. However, its association with overall survival (OS) in non-surgical ESCC patients remains poorly understood. This study aims to evaluate the prognostic value of ALI in ESCC patients undergoing radical radiotherapy and to develop a predictive nomogram to support clinical decision-making. Patients and Methods: We retrospectively analyzed pre-radiotherapy ALI values of 266 ESCC patients treated from January 2017 to October 2022. A restricted cubic spline (RCS) model explored the link between continuous ALI levels and survival risk. Univariate and multivariate Cox proportional hazards models were used to identify independent predictors of OS, and a nomogram was constructed to predict 1 - year, 3 - year, and 5 - year OS probabilities. Results: RCS analysis stratified patients into low (≤227.5), medium (227.5-570.4), and high (>570.4) ALI risk groups. Kaplan-Meier curves showed significant differences among the three groups, with lower ALI values associated with poorer prognosis (P = 0.0057). Multivariate analysis confirmed that ALI, radiation dose, T stage, and N stage were independent predictors of OS. A forest plot precisely quantified each variable's prognostic contribution. The developed nomogram exhibited moderate to high predictive accuracy, as reflected by the area under the time-dependent ROC curves. Decision curve analysis (DCA) indicated a net clinical benefit at 1 - year, 3 - year, and 5 - year time points. Conclusion: ALI is an independent prognostic factor for overall survival in non-surgical ESCC patients treated with radical radiotherapy. The ALI-based nomogram demonstrates good predictive performance and may serve as a useful tool for personalized risk stratification and clinical management.

Indexed as

advanced lung cancer inflammation index(ESCC)esophageal squamous cell carcinomaprognosissurvival

Identifiers

PMID41767901
PMCPMC12947655

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.