Literature DB >> 31696396

Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines.

Diamantis I Tsilimigras1, Rittal Mehta1, Dimitrios Moris1, Kota Sahara1, Fabio Bagante1,2, Anghela Z Paredes1, Ayesha Farooq1, Francesca Ratti3, Hugo P Marques4, Silvia Silva4, Olivier Soubrane5, Vincent Lam6, George A Poultsides7, Irinel Popescu8, Razvan Grigorie8, Sorin Alexandrescu8, Guillaume Martel9, Aklile Workneh9, Alfredo Guglielmi2, Tom Hugh10, Luca Aldrighetti3, Itaru Endo11, Timothy M Pawlik12.   

Abstract

BACKGROUND: There is an ongoing debate about expanding the resection criteria for hepatocellular carcinoma (HCC) beyond the Barcelona Clinic Liver Cancer (BCLC) guidelines. We sought to determine the factors that held the most prognostic weight in the pre- and postoperative setting for each BCLC stage by applying a machine learning method.
METHODS: Patients who underwent resection for BCLC-0, A and B HCC between 2000 and 2017 were identified from an international multi-institutional database. A Classification and Regression Tree (CART) model was used to generate homogeneous groups of patients relative to overall survival (OS) based on pre- and postoperative factors.
RESULTS: Among 976 patients, 63 (6.5%) had BCLC-0, 745 (76.3%) had BCLC-A, and 168 (17.2%) had BCLC-B HCC. Five-year OS among BCLC-0/A and BCLC-B patients was 64.2% versus 50.2%, respectively (p = 0.011). The preoperative CART model selected α-fetoprotein (AFP) and Charlson comorbidity score (CCS) as the first and second most important preoperative factors of OS among BCLC-0/A patients, whereas radiologic tumor burden score (TBS) was the best predictor of OS among BCLC-B patients. The postoperative CART model revealed lymphovascular invasion as the best postoperative predictor of OS among BCLC-0/A patients, whereas TBS remained the best predictor of long-term outcomes among BCLC-B patients in the postoperative setting. On multivariable analysis, pathologic TBS independently predicted worse OS among BCLC-0/A (hazard ratio [HR] 1.04, 95% confidence interval [CI] 1.02-1.07) and BCLC-B patients (HR 1.13, 95% CI 1.06-1.19) undergoing resection.
CONCLUSION: Prognostic stratification of patients undergoing resection for HCC within and beyond the BCLC resection criteria should include assessment of AFP and comorbidities for BCLC-0/A patients, as well as tumor burden for BCLC-B patients.

Entities:  

Year:  2019        PMID: 31696396     DOI: 10.1245/s10434-019-08025-z

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  8 in total

Review 1.  Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities.

Authors:  Chrysanthos D Christou; Georgios Tsoulfas
Journal:  World J Gastrointest Oncol       Date:  2022-04-15

Review 2.  Surgical data science - from concepts toward clinical translation.

Authors:  Lena Maier-Hein; Matthias Eisenmann; Duygu Sarikaya; Keno März; Toby Collins; Anand Malpani; Johannes Fallert; Hubertus Feussner; Stamatia Giannarou; Pietro Mascagni; Hirenkumar Nakawala; Adrian Park; Carla Pugh; Danail Stoyanov; Swaroop S Vedula; Kevin Cleary; Gabor Fichtinger; Germain Forestier; Bernard Gibaud; Teodor Grantcharov; Makoto Hashizume; Doreen Heckmann-Nötzel; Hannes G Kenngott; Ron Kikinis; Lars Mündermann; Nassir Navab; Sinan Onogur; Tobias Roß; Raphael Sznitman; Russell H Taylor; Minu D Tizabi; Martin Wagner; Gregory D Hager; Thomas Neumuth; Nicolas Padoy; Justin Collins; Ines Gockel; Jan Goedeke; Daniel A Hashimoto; Luc Joyeux; Kyle Lam; Daniel R Leff; Amin Madani; Hani J Marcus; Ozanan Meireles; Alexander Seitel; Dogu Teber; Frank Ückert; Beat P Müller-Stich; Pierre Jannin; Stefanie Speidel
Journal:  Med Image Anal       Date:  2021-11-18       Impact factor: 13.828

3.  Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic review.

Authors:  Quirino Lai; Gabriele Spoletini; Gianluca Mennini; Zoe Larghi Laureiro; Diamantis I Tsilimigras; Timothy Michael Pawlik; Massimo Rossi
Journal:  World J Gastroenterol       Date:  2020-11-14       Impact factor: 5.742

Review 4.  Artificial Intelligence in hepatology, liver surgery and transplantation: Emerging applications and frontiers of research.

Authors:  Fadl H Veerankutty; Govind Jayan; Manish Kumar Yadav; Krishnan Sarojam Manoj; Abhishek Yadav; Sindhu Radha Sadasivan Nair; T U Shabeerali; Varghese Yeldho; Madhu Sasidharan; Shiraz Ahmad Rather
Journal:  World J Hepatol       Date:  2021-12-27

5.  Advancements of Artificial Intelligence in Liver-Associated Diseases and Surgery.

Authors:  Anas Taha; Vincent Ochs; Leos N Kayhan; Bassey Enodien; Daniel M Frey; Lukas Krähenbühl; Stephanie Taha-Mehlitz
Journal:  Medicina (Kaunas)       Date:  2022-03-22       Impact factor: 2.948

6.  A Novel Nomogram Model to Predict the Recurrence-Free Survival and Overall Survival of Hepatocellular Carcinoma.

Authors:  Shu-Wen Zhang; Ning-Ning Zhang; Wen-Wen Zhu; Tian Liu; Jia-Yu Lv; Wen-Tao Jiang; Ya-Min Zhang; Tian-Qiang Song; Li Zhang; Yan Xie; Yong-He Zhou; Wei Lu
Journal:  Front Oncol       Date:  2022-07-22       Impact factor: 5.738

7.  A simple scoring system to estimate perioperative mortality following liver resection for primary liver malignancy-the Hepatectomy Risk Score (HeRS).

Authors:  Dimitrios Moris; Brian I Shaw; Cecilia Ong; Ashton Connor; Mariya L Samoylova; Samuel J Kesseli; Nader Abraham; Jared Gloria; Robin Schmitz; Zachary W Fitch; Bryan M Clary; Andrew S Barbas
Journal:  Hepatobiliary Surg Nutr       Date:  2021-06       Impact factor: 7.293

8.  Significance of liver resection for intermediate stage hepatocellular carcinoma according to subclassification.

Authors:  Masateru Yamamoto; Tsuyoshi Kobayashi; Masakazu Hashimoto; Shintaro Kuroda; Tomokazu Kawaoka; Hiroshi Aikata; Kazuaki Chayama; Hideki Ohdan
Journal:  BMC Cancer       Date:  2021-06-05       Impact factor: 4.430

  8 in total

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