Red cell distribution width/platelet ratio predicts decompensation of metabolic dysfunction-associated steatotic liver disease-related compensated advanced chronic liver disease

World J Gastroenterol. 2025 Jan 21;31(3):100393. doi: 10.3748/wjg.v31.i3.100393.

Abstract

Prognostication of compensated advanced chronic liver disease (cACLD) is of paramount importance for the physician-and-patient communication and for rational clinical decisions. The paper published by Dallio et al reports on red cell distribution width (RDW)/platelet ratio (RPR) as a non-invasive biomarker in predicting decompensation of metabolic dysfunction-associated steatotic liver disease (MASLD)-related cACLD. Differently from other biomarkers and algorithms, RPR is inexpensive and widely available, based on parameters which are included in a complete blood count. RPR is computed on the grounds of two different items, one of which, RDW, mirrors the host's response to a variety of disease stimuli and is non-specific. The second parameter involved in RPR, platelet count, is more specific and has been used in the hepatological clinic to discriminate cirrhotic from non-cirrhotic chronic liver disease for decades. Cardiovascular disease is the primary cause of mortality among MASLD subjects, followed by extra-hepatic cancers and liver-related mortality. Therefore, MASLD biomarkers should be validated not only in terms of liver-related events but also in the prediction of major adverse cardiovascular events and cardiovascular mortality and extra-hepatic cancers. Adequately sized multi-ethnic confirmatory investigation is required to define the role and significance of RPR in the stratification of MASLD-cACLD.

Keywords: Cirrhosis; Liver fibrosis; Natural course; Prognostication; Stratification.

Publication types

  • Editorial

MeSH terms

  • Biomarkers* / blood
  • Blood Platelets* / metabolism
  • Chronic Disease
  • Erythrocyte Indices*
  • Fatty Liver / blood
  • Fatty Liver / complications
  • Fatty Liver / diagnosis
  • Humans
  • Platelet Count
  • Predictive Value of Tests
  • Prognosis

Substances

  • Biomarkers