Evidence map›Paper›PMID 40400988›Full record

ArticleJournal of thoracic disease2025

Computed tomography-based body composition and systemic inflammation for outcome prediction in patients with resectable esophageal squamous cell carcinoma.

Rong Wang, Liyang Zhu, Jiqing Hao, Nathawadee Lerttanatum, Xiangxun Chen, Liming Wu, Yichun Wang

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Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Rong WangDepartment of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Liyang ZhuDepartment of Radiation Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Jiqing HaoDepartment of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Nathawadee LerttanatumDepartment of Pathology, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.
Xiangxun ChenDepartment of Radiation Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Liming WuDepartment of Radiation Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Yichun WangDepartment of Radiation Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Computed tomography (CT) can assess a patient's body composition, thereby reflecting an individual's health status. Currently, there is a scarcity of research on the relationship between body composition and prognosis in patients with esophageal squamous cell carcinoma (ESCC) after esophagectomy. We assessed the independent and combined prognostic value of CT-derived body composition parameters, clinical history, pathologic findings, and inflammatory factors in patients with resected ESCC and established a predictive model. Methods: This retrospective analysis included 142 patients with postoperative ESCC. Sarcopenia was diagnosed by assessing the skeletal muscle index at the third lumbar level of CT components. Survival analysis included the Kaplan-Meier method, and the Cox proportional hazards method was employed for multifactor analysis. The consistency index and calibration curve were used to determine the predictive accuracy and discrimination ability of the nomogram. Results: Sarcopenia prevalence among the 142 patients was 62.0% (88/142). The median overall survival (OS) and the 1-, 3-, and 5-year survival rates of patients with sarcopenia were 54.0 months (95% confidence interval: 37.8-70.2), 79.5%, 59.1%, and 44.5%, respectively. Patients without sarcopenia had a median OS of 93.0 months (95% confidence interval: 70.0-116.0), with 1-, 3-, and 5-year survival rates 90.0%, 73.9%, and 65.1%, respectively (P=0.04 for the comparison of OS between the sarcopenia group and the non-sarcopenia group). In the Cox multivariate model, sarcopenia, smoking, lymphocyte albumin score, and tumor-node-metastasis (TNM) stage significantly correlated with postoperative survival in ESCC. The concordance index of the nomogram and calibration curve indicated good agreement between predicted and observed results. Conclusions: Sarcopenia in ESCC was negatively associated with OS. The combination of sarcopenia, pathological parameters, and inflammatory factors could independently predict the survival of patients undergoing ESCC surgery, demonstrating good prognostic value.

Indexed as

Esophageal squamous cell carcinoma (ESCC)nomogramoverall survival (OS)prognosissarcopenia

Identifiers

PMID40400988
PMCPMC12090184

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