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The Prognostic Value of Tumor Length for Cause-Specific Mortality in Resectable Esophageal Cancer.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
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2018 (English)In: Annals of Thoracic Surgery, ISSN 0003-4975, E-ISSN 1552-6259, Vol. 106, no 4, p. 1038-1046Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: The current esophageal cancer AJCC-TNM staging system may not capture the full prognostic implications of the primary tumor. A study is needed to explore the prognostic value of tumor size on esophageal cancer-specific mortality.

METHODS: Patients who underwent surgical resection for non-metastatic esophageal cancer were selected from the Surveillance, Epidemiology and End Results Program database (United States, 1988 - 2014). Using statistics methods - maximally selected rank and two hazard models (Cox model and Fine-Gray model) - the optimum cutoff point for tumor length in each T classification was estimated and the prognostic value of tumor size on esophageal cancer-specific mortality was analyzed.

RESULTS: 4,447 patients were identified. The median tumor size was significantly correlated with T classification, with the correlation coefficient of 0.43 (p < 0.001). Patients in the T1-T3 classifications who had larger tumor size showed a larger probability of cancer-specific mortality. The multivariate Cox model showed that tumor size was significantly associated with an increase in cancer-specific mortality in T1 (2.15, 95% CI [1.72, 2.69]) and T2 (1.31, 95% CI [1.06, 1.62]), but marginally significantly in T3 (1.12, 95% CI [1.00, 1.27]) and insignificantly in T4 classification (p > 0.1). Similar results were found using the multivariate Fine-Gray model.

CONCLUSIONS: We have found that combining T classification with tumor size can increase the precision in identifying the high-risk groups in T1-T2 classification. Based on esophageal cancer-specific mortality our study is the first to explore the prognostic cutoff point of tumor size by T classification.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 106, no 4, p. 1038-1046
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Cancer and Oncology
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URN: urn:nbn:se:umu:diva-150579DOI: 10.1016/j.athoracsur.2018.05.018ISI: 000445116100033PubMedID: 29883640OAI: oai:DiVA.org:umu-150579DiVA, id: diva2:1238266
Available from: 2018-08-13 Created: 2018-08-13 Last updated: 2018-10-05Bibliographically approved

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