Prognostic Value of Tumor Size in Gastric Cancer: A Retrospective Cohort Study Based on SEER Database

Background. Although tumor size is regarded as the “T” stage of the tumor-node-metastasis (TNM) staging system for many solid tumors, its prognostic impact in gastric cancer remains uncertain and conflicting. Methods. We enrolled 6960 eligible patients from the Surveillance, Epidemiology, and End Re...

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Veröffentlicht in:International journal of surgical pathology 2023-10, Vol.31 (7), p.1273-1282
Hauptverfasser: Xiao, Jian, Shen, Kuan, Fan, Hao, Wang, Gang, Liu, Kanghui, Wang, Yuanhang, Ma, Xiang, Ni, Peidong, Xu, Zekuan, Yang, Li
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container_end_page 1282
container_issue 7
container_start_page 1273
container_title International journal of surgical pathology
container_volume 31
creator Xiao, Jian
Shen, Kuan
Fan, Hao
Wang, Gang
Liu, Kanghui
Wang, Yuanhang
Ma, Xiang
Ni, Peidong
Xu, Zekuan
Yang, Li
description Background. Although tumor size is regarded as the “T” stage of the tumor-node-metastasis (TNM) staging system for many solid tumors, its prognostic impact in gastric cancer remains uncertain and conflicting. Methods. We enrolled 6960 eligible patients from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to select the best cut-off value of tumor size. Then, the Kaplan–Meier method and the Cox proportional hazards model were applied to examine the efficacy of tumor size on prognostic prediction for overall survival (OS) and gastric cancer-specific survival (GCSS). The presence of nonlinear association was determined by the restricted cubic spline (RCS) model. Results. Tumor size was divided into 3 groups: small size (≤2.5 cm), medium size (2.6-5.2 cm), and large size (≥5.3 cm). After adjusting by covariates such as depth of tumor infiltration, the large and medium groups showed a worse prognosis than the small group; however, no survival difference in OS was suggested between the medium and large groups. Similarly, although there was a nonlinear relationship between tumor size and survival, increasing tumor size did not show an independent negative effect on prognosis in the RCS analysis. However, the stratified analyses proposed this 3-way cut of tumor size in prognostic prediction for patients with both inadequate lymphadenectomy and negative nodal metastasis. Conclusions. Tumor size as a prognostic predictor may not have good clinical applicability in gastric cancer. Otherwise, it was recommended for patients with both insufficient examinations of lymph nodes and stage N0 disease.
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Although tumor size is regarded as the “T” stage of the tumor-node-metastasis (TNM) staging system for many solid tumors, its prognostic impact in gastric cancer remains uncertain and conflicting. Methods. We enrolled 6960 eligible patients from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to select the best cut-off value of tumor size. Then, the Kaplan–Meier method and the Cox proportional hazards model were applied to examine the efficacy of tumor size on prognostic prediction for overall survival (OS) and gastric cancer-specific survival (GCSS). The presence of nonlinear association was determined by the restricted cubic spline (RCS) model. Results. Tumor size was divided into 3 groups: small size (≤2.5 cm), medium size (2.6-5.2 cm), and large size (≥5.3 cm). After adjusting by covariates such as depth of tumor infiltration, the large and medium groups showed a worse prognosis than the small group; however, no survival difference in OS was suggested between the medium and large groups. Similarly, although there was a nonlinear relationship between tumor size and survival, increasing tumor size did not show an independent negative effect on prognosis in the RCS analysis. However, the stratified analyses proposed this 3-way cut of tumor size in prognostic prediction for patients with both inadequate lymphadenectomy and negative nodal metastasis. Conclusions. Tumor size as a prognostic predictor may not have good clinical applicability in gastric cancer. 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Although tumor size is regarded as the “T” stage of the tumor-node-metastasis (TNM) staging system for many solid tumors, its prognostic impact in gastric cancer remains uncertain and conflicting. Methods. We enrolled 6960 eligible patients from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to select the best cut-off value of tumor size. Then, the Kaplan–Meier method and the Cox proportional hazards model were applied to examine the efficacy of tumor size on prognostic prediction for overall survival (OS) and gastric cancer-specific survival (GCSS). The presence of nonlinear association was determined by the restricted cubic spline (RCS) model. Results. Tumor size was divided into 3 groups: small size (≤2.5 cm), medium size (2.6-5.2 cm), and large size (≥5.3 cm). After adjusting by covariates such as depth of tumor infiltration, the large and medium groups showed a worse prognosis than the small group; however, no survival difference in OS was suggested between the medium and large groups. Similarly, although there was a nonlinear relationship between tumor size and survival, increasing tumor size did not show an independent negative effect on prognosis in the RCS analysis. However, the stratified analyses proposed this 3-way cut of tumor size in prognostic prediction for patients with both inadequate lymphadenectomy and negative nodal metastasis. Conclusions. Tumor size as a prognostic predictor may not have good clinical applicability in gastric cancer. 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Although tumor size is regarded as the “T” stage of the tumor-node-metastasis (TNM) staging system for many solid tumors, its prognostic impact in gastric cancer remains uncertain and conflicting. Methods. We enrolled 6960 eligible patients from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to select the best cut-off value of tumor size. Then, the Kaplan–Meier method and the Cox proportional hazards model were applied to examine the efficacy of tumor size on prognostic prediction for overall survival (OS) and gastric cancer-specific survival (GCSS). The presence of nonlinear association was determined by the restricted cubic spline (RCS) model. Results. Tumor size was divided into 3 groups: small size (≤2.5 cm), medium size (2.6-5.2 cm), and large size (≥5.3 cm). After adjusting by covariates such as depth of tumor infiltration, the large and medium groups showed a worse prognosis than the small group; however, no survival difference in OS was suggested between the medium and large groups. Similarly, although there was a nonlinear relationship between tumor size and survival, increasing tumor size did not show an independent negative effect on prognosis in the RCS analysis. However, the stratified analyses proposed this 3-way cut of tumor size in prognostic prediction for patients with both inadequate lymphadenectomy and negative nodal metastasis. Conclusions. Tumor size as a prognostic predictor may not have good clinical applicability in gastric cancer. 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subjects Cohort analysis
Gastric cancer
Medical prognosis
Metastasis
title Prognostic Value of Tumor Size in Gastric Cancer: A Retrospective Cohort Study Based on SEER Database
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