Development of a risk score to guide targeted hepatitis C testing among human immunodeficiency virus patients in

Anja De Weggheleire1, Jozefien Buyze2, Sokkab An3

  • 1Department of Clinical Sciences, Institute of Tropical Medicine Antwerp, Antwerp 2000, Belgium. adeweggheleire@itg.be.

Insights

A new clinical prediction score (CPS) effectively identifies human immunodeficiency virus (HIV) patients at high risk for hepatitis C virus (HCV) coinfection, aiding targeted testing in resource-limited settings.

Area of Science:

  • Infectious Diseases
  • Hepatology
  • Public Health

Background:

  • The World Health Organization (WHO) recommends universal hepatitis C virus (HCV) screening for all human immunodeficiency virus (HIV) patients.
  • In resource-constrained settings with low-to-intermediate HCV prevalence, such as Cambodia, targeted testing may be more feasible and cost-effective than universal screening.
  • Prioritizing HCV testing is crucial where resources limit universal screening recommendations.

Purpose of the Study:

  • To develop a clinical prediction score (CPS) for risk-stratifying HIV patients for HCV coinfection.
  • To create a decision rule for prioritizing HCV testing in settings where universal testing is not feasible.
  • To guide cost-effective HCV screening strategies in HIV cohorts.

Main Methods:

  • Utilized data from a cross-sectional HCV diagnostic study in an HIV cohort in Phnom Penh, Cambodia.
  • Employed the Spiegelhalter and Knill-Jones method for score development, retaining predictors with adjusted likelihood ratios ≥ 1.5 or ≤ 0.67.
  • Evaluated CPS performance using area-under-the-ROC curve (AUROC) and diagnostic accuracy at various cut-offs.

Main Results:

  • Seven predictors were identified: age ≥ 50, diabetes mellitus, partner with liver disease, generalized pruritus, platelets < 200 × 10^9/L, AST < 30 IU/L, and APRI status.
  • The developed CPS demonstrated good discrimination with an AUROC of 0.84 (95% CI: 0.80-0.89).
  • A CPS threshold of ≥0 achieved a negative predictive value of 99.2%, enabling testing of 30% of patients while missing 15% of coinfections (none with advanced fibrosis).

Conclusions:

  • The clinical prediction score (CPS) shows promise for identifying HIV patients needing HCV testing in low-prevalence settings with limited resources.
  • The CPS can aid in risk-stratifying patients for HCV coinfection, optimizing testing strategies.
  • External validation of the CPS in diverse patient cohorts is recommended before widespread implementation.
Abstract