Advertisement

Development and validation of metabolic scoring to individually predict prognosis and monitor recurrence early in gastric cancer: A large-sample analysis

  • Author Footnotes
    1 Qi-Yue Chen and Si-Jin Que contributed equally to this work and should be considered co-first authors.
    Qi-Yue Chen
    Footnotes
    1 Qi-Yue Chen and Si-Jin Que contributed equally to this work and should be considered co-first authors.
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Author Footnotes
    1 Qi-Yue Chen and Si-Jin Que contributed equally to this work and should be considered co-first authors.
    Si-Jin Que
    Footnotes
    1 Qi-Yue Chen and Si-Jin Que contributed equally to this work and should be considered co-first authors.
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Jun-Yu Chen
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Qing-Zhong
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Zhi-Yu Liu
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Jia-Bin Wang
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Jian-Xian Lin
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Jun Lu
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Long-Long Cao
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Mi Lin
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Ru-Hong Tu
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Ze-Ning Huang
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Ju-Li Lin
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Hua-Long Zheng
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Jian-Wei Xie
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Chao-Hui Zheng
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Ping Li
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Chang-Ming Huang
    Correspondence
    Corresponding author.Department of Gastric Surgery, Fujian Medical University Union Hospital, No.29 Xinquan Road, Fuzhou 350001, Fujian Province, China.
    Affiliations
    Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China

    Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

    Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
    Search for articles by this author
  • Author Footnotes
    1 Qi-Yue Chen and Si-Jin Que contributed equally to this work and should be considered co-first authors.

      Abstract

      Purpose

      To develop and validate a simple metabolic score (Metabolic score, MS) for use in evaluating the prognosis of gastric cancer (GC) patients and dynamically monitor for early recurrence.

      Methods

      We retrospectively collected general clinicopathological data of patients who underwent radical gastrectomy for GC between September 2012 and December 2017 in the Department of Gastric Surgery of the Fujian Medical University Union Hospital. Using a random forest algorithm to screen preoperative blood indicators into the Least absolute shrinkage and selection operator (LASSO) model, we developed a novel MS to predict prognosis.

      Results

      Data of 1974 patients were used to develop and validate the model. Total cholesterol (TCHO), bilirubin (TBIL), direct bilirubin (DBIL), and 15 other metabolic indicators had significant predictive value for the prognosis using the random forest algorithm. In the overall population, 533 patients (27.0%) had high and 1441 (73%) had low MS status. High MS status was related to tumor progression. The KM curves of 3-year OS and RFS for training set patients showed low MS had a better prognosis than high MS (OS: 79.4% vs 59.7%, P < 0.001; RFS: 76.0% vs 56.2%, P < 0.001).

      Conclusions

      We have developed and validated MS to predict the long-term survival of GC patients and allow early monitoring of recurrence. This will provide physicians with simple, economical, and dynamic tumor monitoring information.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to European Journal of Surgical Oncology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Siegel R.L.
        • Miller K.D.
        • Jemal A.
        Cancer statistics, 2020.
        CA A Cancer J Clin. 2020; 70: 7-30
        • Wen J.
        • Wang G.
        • Xie X.
        • Lin G.
        • Yang H.
        • Luo K.
        • et al.
        Prognostic value of a four-miRNA signature in patients with lymph node positive locoregional esophageal squamous cell carcinoma undergoing complete surgical resection.
        Ann Surg. 2021; 273: 523-531
        • Amin M.B.
        • Greene F.L.
        • Edge S.B.
        • Compton C.C.
        • Gershenwald J.E.
        • Brookland R.K.
        • et al.
        The Eighth Edition AJCC Cancer Staging Manual: continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging.
        CA A Cancer J Clin. 2017; 67: 93-99
        • Pita-Fernandez S.
        • Alhayek-Ai M.
        • Gonzalez-Martin C.
        • Lopez-Calvino B.
        • Seoane-Pillado T.
        • Pertega-Diaz S.
        Intensive follow-up strategies improve outcomes in nonmetastatic colorectal cancer patients after curative surgery: a systematic review and meta-analysis.
        Ann Oncol. 2015; 26: 644-656
        • Litvak A.
        • Cercek A.
        • Segal N.
        • Reidy-Lagunes D.
        • Stadler Z.K.
        • Yaeger R.D.
        • et al.
        False-positive elevations of carcinoembryonic antigen in patients with a history of resected colorectal cancer.
        J Natl Compr Cancer Netw. 2014; 12: 907-913
        • Sorbye H.
        • Dahl O.
        Carcinoembryonic antigen surge in metastatic colorectal cancer patients responding to oxaliplatin combination chemotherapy: implications for tumor marker monitoring and guidelines.
        J Clin Oncol. 2003; 21: 4466-4467
        • Lee J.W.
        • Son M.W.
        • Chung I.K.
        • Cho Y.S.
        • Lee M.S.
        • Lee S.M.
        Significance of CT attenuation and F-18 fluorodeoxyglucose uptake of visceral adipose tissue for predicting survival in gastric cancer patients after curative surgical resection.
        Gastric Cancer. 2020; 23: 273-284
        • Selzner M.
        • Hany T.F.
        • Wildbrett P.
        • McCormack L.
        • Kadry Z.
        • Clavien P.A.
        Does the novel PET/CT imaging modality impact on the treatment of patients with metastatic colorectal cancer of the liver?.
        Ann Surg. 2004; 240 (; discussion 35-6): 1027-1034
        • Kim H.D.
        • Ryu M.H.
        • Yoon S.
        • Na Y.S.
        • Moon M.
        • Lee H.
        • et al.
        Clinical implications of neutrophil-to-lymphocyte ratio and MDSC kinetics in gastric cancer patients treated with ramucirumab plus paclitaxel.
        Chin J Cancer Res. 2020; 32: 621-630
        • Golshani-Hebroni S.G.
        • Bessman S.P.
        Hexokinase binding to mitochondria: a basis for proliferative energy metabolism.
        J Bioenerg Biomembr. 1997; 29: 331-338
        • Berghoff A.S.
        • Wolpert F.
        • Holland-Letz T.
        • Koller R.
        • Widhalm G.
        • Gatterbauer B.
        • et al.
        Combining standard clinical blood values for improving survival prediction in patients with newly diagnosed brain metastases-development and validation of the LabBM score.
        Neuro Oncol. 2017; 19: 1255-1262
        • Ulas A.
        • Turkoz F.P.
        • Silay K.
        • Tokluoglu S.
        • Avci N.
        • Oksuzoglu B.
        • et al.
        A laboratory prognostic index model for patients with advanced non-small cell lung cancer.
        PLoS One. 2014; 9e114471
        • Nieder C.
        • Dalhaug A.
        A new prognostic score derived from phase I study participants with advanced solid tumours is also valid in patients with brain metastasis.
        Anticancer Res. 2010; 30: 977-979
        • Danner B.C.
        • Didilis V.N.
        • Wiemeyer S.
        • Stojanovic T.
        • Kitz J.
        • Emmert A.
        • et al.
        Long-term survival is linked to serum LDH and partly to tumour LDH-5 in NSCLC.
        Anticancer Res. 2010; 30: 1347-1351
        • Forrest L.M.
        • McMillan D.C.
        • McArdle C.S.
        • Angerson W.J.
        • Dunlop D.J.
        Comparison of an inflammation-based prognostic score (GPS) with performance status (ECOG) in patients receiving platinum-based chemotherapy for inoperable non-small-cell lung cancer.
        Br J Cancer. 2004; 90: 1704-1706
        • Kuroda D.
        • Sawayama H.
        • Kurashige J.
        • Iwatsuki M.
        • Eto T.
        • Tokunaga R.
        • et al.
        Controlling Nutritional Status (CONUT) score is a prognostic marker for gastric cancer patients after curative resection.
        Gastric Cancer. 2018; 21: 204-212
        • Harimoto N.
        • Yoshizumi T.
        • Inokuchi S.
        • Itoh S.
        • Adachi E.
        • Ikeda Y.
        • et al.
        Prognostic significance of preoperative controlling nutritional status (conut) score in patients undergoing hepatic resection for hepatocellular carcinoma: a multi-institutional study.
        Ann Surg Oncol. 2018; 25: 3316-3323
        • Rahman S.A.
        • Walker R.C.
        • Lloyd M.A.
        • Grace B.L.
        • van Boxel G.I.
        • Kingma B.F.
        • et al.
        Machine learning to predict early recurrence after oesophageal cancer surgery.
        Br J Surg. 2020; 107: 1042-1052
        • Sauerbrei W.
        • Royston P.
        • Binder H.
        Selection of important variables and determination of functional form for continuous predictors in multivariable model building.
        Stat Med. 2007; 26: 5512-5528
        • Lin J.X.
        • Tang Y.H.
        • Wang J.B.
        • Lu J.
        • Chen Q.Y.
        • Cao L.L.
        • et al.
        Blood parameters score predicts long-term outcomes in stage II-III gastric cancer patients.
        World J Gastroenterol. 2019; 25: 6258-6272
        • El Sharouni M.A.
        • Ahmed T.
        • Varey A.H.R.
        • Elias S.G.
        • Witkamp A.J.
        • Sigurdsson V.
        • et al.
        Development and validation of nomograms to predict local, regional, and distant recurrence in patients with thin (T1) melanomas.
        J Clin Oncol. 2021; 39: 1243-1252
        • Leon-Castillo A.
        • de Boer S.M.
        • Powell M.E.
        • Mileshkin L.R.
        • Mackay H.J.
        • Leary A.
        • et al.
        Molecular classification of the PORTEC-3 trial for high-risk endometrial cancer: impact on prognosis and benefit from adjuvant therapy.
        J Clin Oncol. 2020; 38: 3388-3397
        • Garrel R.
        • Poissonnet G.
        • Moya Plana A.
        • Fakhry N.
        • Dolivet G.
        • Lallemant B.
        • et al.
        Equivalence randomized trial to compare treatment on the basis of sentinel node biopsy versus neck node dissection in operable T1-T2N0 oral and oropharyngeal cancer.
        J Clin Oncol. 2020; 38: 4010-4018
        • Lee S.
        • Kim M.J.
        • Kim S.
        • Choi D.
        • Jang K.T.
        • Park Y.N.
        Intraductal papillary neoplasm of the bile duct: assessment of invasive carcinoma and long-term outcomes using MRI.
        J Hepatol. 2019; 70: 692-699
        • Chumsri S.
        • Li Z.
        • Serie D.J.
        • Mashadi-Hossein A.
        • Colon-Otero G.
        • Song N.
        • et al.
        Incidence of late relapses in patients with HER2-positive breast cancer receiving adjuvant trastuzumab: combined analysis of NCCTG N9831 (alliance) and NRG oncology/NSABP B-31.
        J Clin Oncol. 2019; 37: 3425-3435
        • Chan A.W.H.
        • Zhong J.
        • Berhane S.
        • Toyoda H.
        • Cucchetti A.
        • Shi K.
        • et al.
        Development of pre and post-operative models to predict early recurrence of hepatocellular carcinoma after surgical resection.
        J Hepatol. 2018; 69: 1284-1293
        • Ahn S.B.
        • Choi J.
        • Jun D.W.
        • Oh H.
        • Yoon E.L.
        • Kim H.S.
        • et al.
        Twelve-month post-treatment parameters are superior in predicting hepatocellular carcinoma in patients with chronic hepatitis B.
        Liver Int. 2021; 41: 1652-1661
        • Edwards J.A.
        • Santos-Medellin C.M.
        • Liechty Z.S.
        • Nguyen B.
        • Lurie E.
        • Eason S.
        • et al.
        Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice.
        PLoS Biol. 2018; 16e2003862
        • Huang Y.Q.
        • Liang C.H.
        • He L.
        • Tian J.
        • Liang C.S.
        • Chen X.
        • et al.
        Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer.
        J Clin Oncol. 2016; 34: 2157-2164
        • Vasquez M.M.
        • Hu C.
        • Roe D.J.
        • Chen Z.
        • Halonen M.
        • Guerra S.
        Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application.
        BMC Med Res Methodol. 2016; 16: 154
        • Kumamaru K.K.
        • Saboo S.S.
        • Aghayev A.
        • Cai P.
        • Quesada C.G.
        • George E.
        • et al.
        CT pulmonary angiography-based scoring system to predict the prognosis of acute pulmonary embolism.
        J Cardiovasc Comput Tomogr. 2016; 10: 473-479
        • Zhang B.
        • Tian J.
        • Dong D.
        • Gu D.
        • Dong Y.
        • Zhang L.
        • et al.
        Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma.
        Clin Cancer Res. 2017; 23: 4259-4269
        • Ayis S.A.
        • Coker B.
        • Rudd A.G.
        • Dennis M.S.
        • Wolfe C.D.
        Predicting independent survival after stroke: a European study for the development and validation of standardised stroke scales and prediction models of outcome.
        J Neurol Neurosurg Psychiatry. 2013; 84: 288-296
        • Timmerman D.
        • Testa A.C.
        • Bourne T.
        • Ferrazzi E.
        • Ameye L.
        • Konstantinovic M.L.
        • et al.
        Logistic regression model to distinguish between the benign and malignant adnexal mass before surgery: a multicenter study by the International Ovarian Tumor Analysis Group.
        J Clin Oncol. 2005; 23: 8794-8801
        • Heagerty P.J.
        • Zheng Y.
        Survival model predictive accuracy and ROC curves.
        Biometrics. 2005; 61: 92-105
        • Poretsky E.
        • Huffaker A.
        MutRank: an R shiny web-application for exploratory targeted mutual rank-based coexpression analyses integrated with user-provided supporting information.
        PeerJ. 2020; 8e10264
        • Jiang Y.
        • Jin C.
        • Yu H.
        • Wu J.
        • Chen C.
        • Yuan Q.
        • et al.
        Development and validation of a deep learning CT signature to predict survival and chemotherapy benefit in gastric cancer: a multicenter, retrospective study.
        Ann Surg. 2021; 274: e1153-e1161
        • Marrelli D.
        • Morgagni P.
        • de Manzoni G.
        • Coniglio A.
        • Marchet A.
        • Saragoni L.
        • et al.
        Prognostic value of the 7th AJCC/UICC TNM classification of noncardia gastric cancer: analysis of a large series from specialized Western centers.
        Ann Surg. 2012; 255: 486-491
        • Santa-Maria C.A.
        • Coughlin J.W.
        • Sharma D.
        • Armanios M.
        • Blackford A.L.
        • Schreyer C.
        • et al.
        The effects of a remote-based weight loss program on adipocytokines, metabolic markers, and telomere length in breast cancer survivors: the POWER-remote trial.
        Clin Cancer Res. 2020; 26: 3024-3034
        • McGuirk S.
        • Audet-Delage Y.
        • St-Pierre J.
        Metabolic fitness and plasticity in cancer progression.
        Trends Cancer. 2020; 6: 49-61
        • Siska P.J.
        • Singer K.
        • Evert K.
        • Renner K.
        • Kreutz M.
        The immunological Warburg effect: can a metabolic-tumor-stroma score (MeTS) guide cancer immunotherapy?.
        Immunol Rev. 2020; 295: 187-202
        • Chen H.
        • Zheng X.
        • Zong X.
        • Li Z.
        • Li N.
        • Hur J.
        • et al.
        Metabolic syndrome, metabolic comorbid conditions and risk of early-onset colorectal cancer.
        Gut. 2021; 70: 1147-1154
        • Sawada T.
        • Yashiro M.
        • Sentani K.
        • Oue N.
        • Yasui W.
        • Miyazaki K.
        • et al.
        New molecular staging with G-factor supplements TNM classification in gastric cancer: a multicenter collaborative research by the Japan Society for Gastroenterological Carcinogenesis G-Project committee.
        Gastric Cancer. 2015; 18: 119-128
        • Sano T.
        • Coit D.G.
        • Kim H.H.
        • Roviello F.
        • Kassab P.
        • Wittekind C.
        • et al.
        Proposal of a new stage grouping of gastric cancer for TNM classification: international Gastric Cancer Association staging project.
        Gastric Cancer. 2017; 20: 217-225
        • Chae S.
        • Lee A.
        • Lee J.H.
        The effectiveness of the new (7th) UICC N classification in the prognosis evaluation of gastric cancer patients: a comparative study between the 5th/6th and 7th UICC N classification.
        Gastric Cancer. 2011; 14: 166-171
        • Rocken C.
        • Behrens H.M.
        Validating the prognostic and discriminating value of the TNM-classification for gastric cancer - a critical appraisal.
        Eur J Cancer. 2015; 51: 577-586