Annals of Hepato-Biliary-Pancreatic Surgery (한국간담췌외과학회지)

The Korean Association of Hepato-Biliary-Pancreatic Surgery (한국간담췌외과학회)
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Scoring systems for the management of oncological hepato-pancreato-biliary patients

  • Alexander W. Coombs (Department of Surgery and Cancer, Imperial College London) ;
  • Chloe Jordan (Department of Surgery and Cancer, Imperial College London) ;
  • Sabba A. Hussain (Department of Surgery and Cancer, Imperial College London) ;
  • Omar Ghandour (Department of Surgery and Cancer, Imperial College London)
  • Received : 2021.07.28
  • Accepted : 2021.09.02
  • Published : 2022.02.28
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Abstract

Oncological scoring systems in surgery are used as evidence-based decision aids to best support management through assessing prognosis, effectiveness and recurrence. Currently, the use of scoring systems in the hepato-pancreato-biliary (HPB) field is limited as concerns over precision and applicability prevent their widespread clinical implementation. The aim of this review was to discuss clinically useful oncological scoring systems for surgical management of HPB patients. A narrative review was conducted to appraise oncological HPB scoring systems. Original research articles of established and novel scoring systems were searched using Google Scholar, PubMed, Cochrane, and Ovid Medline. Selected models were determined by authors. This review discusses nine scoring systems in cancers of the liver (CLIP, BCLC, ALBI Grade, RETREAT, Fong's score), pancreas (Genç's score, mGPS), and biliary tract (TMHSS, MEGNA). Eight models used exclusively objective measurements to compute their scores while one used a mixture of both subjective and objective inputs. Seven models evaluated their scoring performance in external populations, with reported discriminatory c-statistic ranging from 0.58 to 0.82. Selection of model variables was most frequently determined using a combination of univariate and multivariate analysis. Calibration, another determinant of model accuracy, was poorly reported amongst nine scoring systems. A diverse range of HPB surgical scoring systems may facilitate evidence-based decisions on patient management and treatment. Future scoring systems need to be developed using heterogenous patient cohorts with improved stratification, with future trends integrating machine learning and genetics to improve outcome prediction.

Keywords

Acknowledgement

We thank Dr. Ashley Clift for supporting this review by providing his guidance and expertise in clinical prediction modelling.

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