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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

2020-04Journal article Open access
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dc.contributor.authorTsilimigras, D
dc.contributor.authorMehta, R
dc.contributor.authorMoris, D
dc.contributor.authorSahara, K
dc.contributor.authorBagante, F
dc.contributor.authorParedes, A
dc.contributor.authorMoro, A
dc.contributor.authorGuglielmi, A
dc.contributor.authorAldrighetti, L
dc.contributor.authorWeiss, M
dc.contributor.authorBauer, T
dc.contributor.authorAlexandrescu, S
dc.contributor.authorPoultsides, G
dc.contributor.authorMaithel, S
dc.contributor.authorPinto Marques, H
dc.contributor.authorMartel, G
dc.contributor.authorPulitano, C
dc.contributor.authorShen, F
dc.contributor.authorSoubrane, O
dc.contributor.authorKoerkamp, B
dc.contributor.authorEndo, I
dc.contributor.authorPawlik, T
dc.date.accessioned2021-06-15T10:27:36Z
dc.date.available2021-06-15T10:27:36Z
dc.date.issued2020-04
dc.description.abstractBackground: 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAnn Surg Oncol. 2020 Apr;27(4):1110-1119.pt_PT
dc.identifier.doi10.1245/s10434-019-08067-3pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.17/3728
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.subjectAgedpt_PT
dc.subjectBile Duct Neoplasmspt_PT
dc.subjectBile Ducts, Intrahepaticpt_PT
dc.subjectBilirubinpt_PT
dc.subjectBiomarkerspt_PT
dc.subjectCholangiocarcinomapt_PT
dc.subjectDatabases, Factualpt_PT
dc.subjectDisease-Free Survivalpt_PT
dc.subjectFemalept_PT
dc.subjectHumanspt_PT
dc.subjectLiver Neoplasmspt_PT
dc.subjectMalept_PT
dc.subjectMiddle Agedpt_PT
dc.subjectPredictive Value of Testspt_PT
dc.subjectProportional Hazards Modelspt_PT
dc.subjectRetrospective Studiespt_PT
dc.subjectTime Factorspt_PT
dc.subjectTreatment Outcomept_PT
dc.subjectHepatectomypt_PT
dc.subjectHCC CIRpt_PT
dc.titleA 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 Patientspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage1119pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage1110pt_PT
oaire.citation.titleAnnals of Surgical Oncologypt_PT
oaire.citation.volume27pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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