Annals of surgical oncology · 2021
Optimal Lymph Node Staging System in Evaluating Prognosis of Gallbladder Carcinoma: A Multi-institutional Study.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Chen Chen, Rui Zhang, Yuhan Wu, Yongjie Zhang, Yinghe Qiu, Ning Yang, Tianqiang Song, Jianying Lou, Jiangtao Li, Xianhai Mao, Shengping Li, Shubin Si, Zhiqiang Cai, Zhaohui Tang, Zhimin Geng
Аннотация
BACKGROUND: Lymph node (LN) involvement is a critical prognostic factor in patients with gallbladder carcinoma (GBC). Controversy exists regarding optimal categorization of nodal metastasis status, including anatomical location of positive nodes (AJCC 7th N staging), number of metastatic lymph nodes (NMLN), log odds of metastatic LNs (LODDS), and lymph node ratio (LNR).
METHODS: Patients who underwent curative-intent resection for GBC from six Chinese tertiary hospitals between 2008 and 2013 were analyzed retrospectively. The relative discriminative abilities of the different LN staging systems were assessed by different models including the tree-augmented naïve Bayesian (TAN) model, Cox proportional hazards regression model, and binary logistic regression model.
RESULTS: A total of 226 patients were involved in this cohort. Based on the TAN model and composite importance measures, the most important factor affecting the prognosis in the different LN staging systems was NMLN. Among the four TAN models which were built with 4 metastatic LN markers and baseline variables, the accuracy of the NMLN-based prognostic model was 88.15%, higher than 7th N staging (86.44%), LNR (87.34%), and LODDS (85.19%). The Cox model based on NMLN (C-index: 0.763, AIC: 1371.62) had a higher fitness than the others (7th N staging C-index: 0.756, AIC: 1375.51; LNR C-index: 0.759, AIC: 1378.82; LODDS C-index 0.748, AIC: 1390.99). The AUCs of different staging binary logistic regression models were NMLN (0.872), LNR (0.872), 7th N staging (0.869) and LODDS (0.856), respectively.
CONCLUSIONS: NMLN was the optimal LN staging system in evaluating prognosis of GBC.
METHODS: Patients who underwent curative-intent resection for GBC from six Chinese tertiary hospitals between 2008 and 2013 were analyzed retrospectively. The relative discriminative abilities of the different LN staging systems were assessed by different models including the tree-augmented naïve Bayesian (TAN) model, Cox proportional hazards regression model, and binary logistic regression model.
RESULTS: A total of 226 patients were involved in this cohort. Based on the TAN model and composite importance measures, the most important factor affecting the prognosis in the different LN staging systems was NMLN. Among the four TAN models which were built with 4 metastatic LN markers and baseline variables, the accuracy of the NMLN-based prognostic model was 88.15%, higher than 7th N staging (86.44%), LNR (87.34%), and LODDS (85.19%). The Cox model based on NMLN (C-index: 0.763, AIC: 1371.62) had a higher fitness than the others (7th N staging C-index: 0.756, AIC: 1375.51; LNR C-index: 0.759, AIC: 1378.82; LODDS C-index 0.748, AIC: 1390.99). The AUCs of different staging binary logistic regression models were NMLN (0.872), LNR (0.872), 7th N staging (0.869) and LODDS (0.856), respectively.
CONCLUSIONS: NMLN was the optimal LN staging system in evaluating prognosis of GBC.