A Machine-Based Approach to Preoperatively Identify Patients with the Most and Least Benefit Associated with Resection for Intrahepatic Cholangiocarcinoma: An International Multi-institutional Analysis of 1146 Patients

Diamantis I. Tsilimigras, Rittal Mehta, Dimitrios Moris, Kota Sahara, Fabio Bagante, Anghela Z. Paredes, Amika Moro, Alfredo Guglielmi, Luca Aldrighetti, Matthew Weiss, Todd W. Bauer, Sorin Alexandrescu, George A. Poultsides, Shishir K. Maithel, Hugo P. Marques, Guillaume Martel, Carlo Pulitano, Feng Shen, Olivier Soubrane, Bas Groot KoerkampItaru Endo, Timothy M. Pawlik

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Accurate risk stratification and patient selection is necessary to identify patients who will benefit the most from surgery or be better treated with other non-surgical treatment strategies. We sought to identify which patients in the preoperative setting would likely derive the most or least benefit from resection of intrahepatic cholangiocarcinoma (ICC). Methods: Patients who underwent curative-intent resection for ICC between 1990 and 2017 were identified from an international multi-institutional database. A machine-based classification and regression tree (CART) was used to generate homogeneous groups of patients relative to overall survival (OS) based on preoperative factors. Results: Among 1146 patients, CART analysis revealed tumor number and size, albumin-bilirubin (ALBI) grade and preoperative lymph node (LN) status as the strongest prognostic factors associated with OS among patients undergoing resection for ICC. In turn, four groups of patients with distinct outcomes were generated through machine learning: Group 1 (n = 228): single ICC, size ≤ 5 cm, ALBI grade I, negative preoperative LN status; Group 2 (n = 708): (1) single tumor > 5 cm, (2) single tumor ≤ 5 cm, ALBI grade 2/3, and (3) single tumor ≤ 5 cm, ALBI grade 1, metastatic/suspicious LNs; Group 3 (n = 150): 2–3 tumors; Group 4 (n = 60): ≥ 4 tumors. 5-year OS among Group 1, 2, 3, and 4 patients was 60.5%, 35.8%, 27.5%, and 3.8%, respectively (p < 0.001). Similarly, 5-year disease-free survival (DFS) among Group 1, 2, 3, and 4 patients was 47%, 27.2%, 6.8%, and 0%, respectively (p < 0.001). Conclusions: The machine-based CART model identified distinct prognostic groups of patients with distinct outcomes based on preoperative factors. Survival decision trees may be useful as guides in preoperative patient selection and risk stratification.

Original languageEnglish
Pages (from-to)1110-1119
Number of pages10
JournalAnnals of Surgical Oncology
Volume27
Issue number4
DOIs
Publication statusPublished - Apr 1 2020

ASJC Scopus subject areas

  • Surgery
  • Oncology

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