Literature DB >> 27503330

A Novel Nomogram to Predict the Prognosis of Patients Undergoing Liver Resection for Neuroendocrine Liver Metastasis: an Analysis of the Italian Neuroendocrine Liver Metastasis Database.

Andrea Ruzzenente1, Fabio Bagante1, Francesca Bertuzzo1, Luca Aldrighetti2, Giorgio Ercolani3, Felice Giuliante4, Alessandro Ferrero5, Guido Torzilli6, Gian Luca Grazi7, Francesca Ratti2, Alessandro Cucchetti3, Agostino M De Rose4, Nadia Russolillo5, Matteo Cimino6, Pasquale Perri7, Ivana Cataldo8,9, Aldo Scarpa8,9, Alfredo Guglielmi1, Calogero Iacono10,11.   

Abstract

Even though surgery remains the only potentially curative option for patients with neuroendocrine liver metastases, the factors determining a patient's prognosis following hepatectomy are poorly understood. Using a multicentric database including patients who underwent hepatectomy for NELMs at seven tertiary referral hepato-biliary-pancreatic centers between January 1990 and December 2014, we sought to identify the predictors of survival and develop a clinical tool to predict patient's prognosis after liver resection for NELMs. The median age of the 238 patients included in the study was 61.9 years (interquartile range 51.5-70.1) and 55.9 % (n = 133) of patients were men. The number of NELMs (hazard ratio = 1.05), tumor size (HR = 1.01), and Ki-67 index (HR = 1.07) were the predictors of overall survival. These variables were used to develop a nomogram able to predict survival. According to the predicted 5-year OS, patients were divided into three different risk classes: 19.3, 55.5, and 25.2 % of patients were in low (>80 % predicted 5-year OS), medium (40-80 % predicted 5-year OS), and high (<40 % predicted 5-year OS) risk classes. The 10-year OS was 97.0, 55.9, and 20.0 % in the low, medium, and high-risk classes, respectively (p < 0.001). We developed a novel nomogram that accurately (c-index >70 %) staged and predicted the prognosis of patients undergoing liver resection for NELMs.

Entities:  

Keywords:  Liver surgery; Neuroendocrine liver metastasis; Prognostic model

Mesh:

Year:  2016        PMID: 27503330     DOI: 10.1007/s11605-016-3228-6

Source DB:  PubMed          Journal:  J Gastrointest Surg        ISSN: 1091-255X            Impact factor:   3.452


  34 in total

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Review 2.  When should a liver resection be performed in patients with liver metastases from neuroendocrine tumours? A systematic review with practice recommendations.

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Journal:  HPB (Oxford)       Date:  2014-03-17       Impact factor: 3.647

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Authors:  Koray Karabulut; Hizir Yakup Akyildiz; Craig Lance; Federico Aucejo; Gordon McLennan; Orhan Agcaoglu; Allan Siperstein; Eren Berber
Journal:  Surgery       Date:  2011-08       Impact factor: 3.982

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Authors:  Andrea Frilling; Ashley K Clift
Journal:  Cancer       Date:  2014-10-01       Impact factor: 6.860

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Authors:  Taizo Hibi; Tsuyoshi Sano; Yoshihiro Sakamoto; Yu Takahashi; Norihisa Uemura; Hidenori Ojima; Kazuaki Shimada; Tomoo Kosuge
Journal:  Jpn J Clin Oncol       Date:  2007-01-18       Impact factor: 3.019

Review 6.  Incidence, patterns of care and prognostic factors for outcome of gastroenteropancreatic neuroendocrine tumors (GEP-NETs): results from the National Cancer Registry of Spain (RGETNE).

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Journal:  J Clin Oncol       Date:  2008-06-20       Impact factor: 44.544

8.  Prognostic variables in patients with gastrointestinal carcinoid tumours.

Authors:  E W McDermott; B Guduric; M F Brennan
Journal:  Br J Surg       Date:  1994-07       Impact factor: 6.939

9.  Prognostic factors influencing survival from metastatic (stage IV) gastroenteropancreatic well-differentiated endocrine carcinoma.

Authors:  Cosimo Durante; Houda Boukheris; Clarisse Dromain; Pierre Duvillard; Sophie Leboulleux; Dominique Elias; Thierry de Baere; David Malka; Jean Lumbroso; Joël Guigay; Martin Schlumberger; Michel Ducreux; Eric Baudin
Journal:  Endocr Relat Cancer       Date:  2009-02-24       Impact factor: 5.678

10.  Treatment of liver metastases from neuroendocrine tumours in relation to the extent of hepatic disease.

Authors:  A Frilling; J Li; E Malamutmann; K-W Schmid; A Bockisch; C E Broelsch
Journal:  Br J Surg       Date:  2009-02       Impact factor: 6.939

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  7 in total

Review 1.  Surgical management of neuroendocrine tumor-associated liver metastases: a review.

Authors:  Miu Yee Chan; Ka Wing Ma; Albert Chan
Journal:  Gland Surg       Date:  2018-02

2.  Nomogram individually predicts the overall survival of patients with gastroenteropancreatic neuroendocrine neoplasms.

Authors:  Cheng Fang; Wei Wang; Xingyu Feng; Jian Sun; Yu Zhang; Yujie Zeng; Junjiang Wang; Huishan Chen; Muyan Cai; Junzhong Lin; Minhu Chen; Ye Chen; Yong Li; Shengping Li; Jie Chen; Zhiwei Zhou
Journal:  Br J Cancer       Date:  2017-09-26       Impact factor: 7.640

3.  The impact of surgery in metastatic pancreatic neuroendocrine tumors: a competing risk analysis.

Authors:  Chao-Bin He; Yu Zhang; Zhi-Yuan Cai; Xiao-Jun Lin
Journal:  Endocr Connect       Date:  2019-03-01       Impact factor: 3.335

4.  A novel and validated nomogram to predict overall survival for gastric neuroendocrine neoplasms.

Authors:  Sheng Zhang; Yi Xin Tong; Xin Hua Zhang; Yu Jie Zhang; Xiang Shang Xu; Ai Tang Xiao; Teng Fei Chao; Jian Ping Gong
Journal:  J Cancer       Date:  2019-10-15       Impact factor: 4.207

5.  Prognostic nomogram based on the metastatic lymph node ratio for gastric neuroendocrine tumour: SEER database analysis.

Authors:  Jinluan Li; Yaobin Lin; Youjia Wang; Huaqin Lin; Feifei Lin; Qingyang Zhuang; Xijin Lin; Junxin Wu
Journal:  ESMO Open       Date:  2020-04

6.  Development and validation of a simple-to-use nomogram to predict liver metastasis in patients with pancreatic neuroendocrine neoplasms: a large cohort study.

Authors:  Maoen Pan; Yuanyuan Yang; Tianhong Teng; Fengchun Lu; Yanchan Chen; Heguang Huang
Journal:  BMC Gastroenterol       Date:  2021-03-04       Impact factor: 3.067

7.  Prognostic factors in patients with gallbladder adenocarcinoma identified using competing-risks analysis: A study of cases in the SEER database.

Authors:  Didi Han; Jin Yang; Fengshuo Xu; Qiao Huang; Ling Bai; Yuan-Long Wei; Rahel Elishilia Kaaya; ShengPeng Wang; Jun Lyu
Journal:  Medicine (Baltimore)       Date:  2020-07-31       Impact factor: 1.817

  7 in total

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