Evidence map›Paper›PMID 40223986›Full record

ArticleJournal of thoracic disease2025

Nomogram for predicting the prognosis of metastatic thymic epithelial tumors.

Caiwen Huang, Hui Liu, Qihua Zou, Liping Kang, Jianliang Mai, Yongbin Lin, Ying Liang

Abstract read
In one paragraph

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. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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.

Caiwen Huang *State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Hui Liu *State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Qihua Zou *State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Liping KangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Jianliang MaiState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Yongbin Lin *State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Ying Liang *State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The majority of patients diagnosed with thymic epithelial tumors (TETs) are often at an advanced stage that precludes cure. This study aimed to develop a nomogram to predict the prognosis of metastatic TETs. Methods: Patients diagnosed as metastatic TETs in Sun Yat-sen University Cancer Center from July 2000 to November 2021 were retrospectively reviewed. A nomogram was developed to predict the prognosis of metastatic TETs. The performance of the nomogram was assessed by the concordance index (C-index), calibration curves, and decision curve analysis curves. Based on the nomogram scores, patients were divided into different prognostic groups. Results: A total of 254 patients were enrolled. The median overall survival (OS) was 53.03 months [95% confidence interval (CI): 40.56-65.51]. Univariate and multivariate analyses showed that World Health Organization (WHO) histologic classification type C, Masaoka-Koga stage IVb, Karnofsky performance status (KPS) score 70-80, and baseline serum albumin level <40 g/L were independent poor prognostic factors of OS. These factors were then taken into the development of nomogram model. The C-index was 0.68 (95% CI: 0.59-0.79), indicating good performance. The risk groups were categorized by nomogram scores with a threshold at 112 score. The median OS in the high-risk group was much shorter than that of the low-risk group [28.60 versus 74.17 months, hazard ratio (HR): 2.44; 95% CI: 1.65-3.62; P<0.001]. Conclusions: WHO histologic classification, Masaoka-Koga stage, KPS score, and baseline serum albumin level were identified as independent prognostic factors of OS in metastatic TETs. This study developed a nomogram model effectively predicting the prognosis of metastatic TETs.

Indexed as

nomogramprediction modelThymic epithelial tumors (TETs)

Identifiers

PMID40223986
PMCPMC11986742

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