Annamaria Agnes1,2, Alberto Biondi1,2, Ferdinando M Cananzi3, Stefano Rausei4, Rossella Reddavid5, Vito Laterza2, Federica Galli4, Vittorio Quagliuolo3, Maurizio Degiuli5, Domenico D'Ugo1,2, Roberto Persiani1,2. 1. Dipartimento Scienze Gastroenterologiche, Endocrino-Metaboliche e Nefro-Urologiche, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy. 2. Department of Surgery, Università Cattolica del Sacro Cuore, Rome, Italy. 3. Department of Surgery, Surgical Oncology Unit, Humanitas Clinical and Research Center, Milan, Italy. 4. Department of Surgery, ASST Settelaghi, Varese, Italy. 5. Department of Oncology, Surgical Oncology, and Digestive Surgery, San Luigi University Hospital (S.L.U.H.), University of Turin, Turin, Italy.
Abstract
BACKGROUND: The current and the previous editions of the tumor-node-metastasis (TNM) system for gastric cancer (GC; TNM8 and TNM7) have a high risk of stage-migration bias when the node count after gastrectomy is suboptimal. Hence, they are possibly not the optimal staging systems for GC patients. This study aims to compare the TNM with two systems less affected by the stage-migration bias, namely, the lymph nodes ratio (LNR) and the log odds of positive lymph nodes (LODDS), to assess which one is the best in stratifying the prognosis of GC patients. METHODS: The sample study included 1221 GC patients. Two 7-cluster staging systems based on the combination of pT categories and LNR and LODDS categories (TLNR and TLODDS) were compared with the two last editions of TNM, using the Akaike information criteria, the Bayesian information criteria, and the receiver operating characteristic (ROC) curve graphs. Further validation on an independent sample of 251 patients was carried out. RESULTS: The univariable and multivariable analyses and the ROC curves detected an advantage of the TLNR and TLODDS systems over the TNM. The TLNR and TLODDS showed the best accuracy both in the subgroup of patients with ≥16 nodes examined. The results were confirmed in the validation analysis. CONCLUSIONS: TLNR and TLODDS staging systems should be considered a valid implementation of the TNM for the prognostic stratification of GC patients. If these results are confirmed in further studies, the future implementation of the TNM should consider the introduction of the LNR or the LODDS along with the number of metastatic nodes.
BACKGROUND: The current and the previous editions of the tumor-node-metastasis (TNM) system for gastric cancer (GC; TNM8 and TNM7) have a high risk of stage-migration bias when the node count after gastrectomy is suboptimal. Hence, they are possibly not the optimal staging systems for GC patients. This study aims to compare the TNM with two systems less affected by the stage-migration bias, namely, the lymph nodes ratio (LNR) and the log odds of positive lymph nodes (LODDS), to assess which one is the best in stratifying the prognosis of GC patients. METHODS: The sample study included 1221 GC patients. Two 7-cluster staging systems based on the combination of pT categories and LNR and LODDS categories (TLNR and TLODDS) were compared with the two last editions of TNM, using the Akaike information criteria, the Bayesian information criteria, and the receiver operating characteristic (ROC) curve graphs. Further validation on an independent sample of 251 patients was carried out. RESULTS: The univariable and multivariable analyses and the ROC curves detected an advantage of the TLNR and TLODDS systems over the TNM. The TLNR and TLODDS showed the best accuracy both in the subgroup of patients with ≥16 nodes examined. The results were confirmed in the validation analysis. CONCLUSIONS: TLNR and TLODDS staging systems should be considered a valid implementation of the TNM for the prognostic stratification of GC patients. If these results are confirmed in further studies, the future implementation of the TNM should consider the introduction of the LNR or the LODDS along with the number of metastatic nodes.
Authors: Dimitrios Prassas; Sami Alexander Safi; Maria Chara Stylianidi; Leila Anne Telan; Sarah Krieg; Christoph Roderburg; Irene Esposito; Tom Luedde; Wolfram Trudo Knoefel; Andreas Krieg Journal: Cancers (Basel) Date: 2022-04-06 Impact factor: 6.639