ArticleFrontiers in oncology2022
Applying post-neoadjuvant pathologic stage as prognostic tool in esophageal squamous cell carcinoma.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Identification of Prognostic Factors in Esophageal Cancer Using Machine Learning: A Retrospective Study Based on the SEER Database.Journal of clinical medicine · 2026Article
- Article
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Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: It is still uncertain whether the newly released eighth American Joint Committee on Cancer (AJCC) post-neoadjuvant pathologic (yp) tumor-node-metastasis (TNM) stage for esophageal carcinoma can perform well regarding patient stratification. The current study aimed to assess the prognostication ability of the eighth AJCC ypTNM staging system and attempted to explore how to facilitate the staging system for more effective evaluation of prognosis. Materials and methods: A total of 486 patients treated with neoadjuvant radiotherapy/chemoradiotherapy (nRT/CRT) were enrolled. ypN stage was reclassified by recursive partitioning. Prognostic performance, monotonicity, homogeneity, and discriminatory of yp and modified yp (myp) staging systems were assessed by time-dependent receiver operating characteristic (ROC), linear trend log-rank test, likelihood ratio χ2 test, Harrell's c statistic, and Akaike information criterion (AIC). Results: The ypT stage, ypN stage, and pathologic response were significant prognostic factors of overall survival. Survival was not discriminated well using the eighth AJCC ypN stage and ypTNM stage. Recursive partitioning reclassified mypN0-N2 as metastasis in 0, 1-2, and ≥3 regional lymph nodes. Applying the ypT stage, mypN stage, and pathologic response to construct the myp staging system, the myp stage performed better in time-dependent ROC, linear trend log-rank test, likelihood ratio χ2 test, Harrell's c statistic, and AIC. Conclusions: The eighth AJCC ypTNM staging system performed well in differentiating prognosis to some extent. By reclassifying the ypN stage and enrolling pathologic response as a staging element, the myp staging system holds significant potential for prognostic discrimination.
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