BMC Medical Informatics and Decision Making (Jun 2011)

A Prognostic Model for Estimating the Time to Virologic Failure in HIV-1 Infected Patients Undergoing a New Combination Antiretroviral Therapy Regimen

  • Micheli Valeria,
  • Bagnarelli Patrizia,
  • Penco Giovanni,
  • Callegaro Annapaola,
  • Bruzzone Bianca,
  • Meini Genny,
  • Fanti Iuri,
  • Di Giambenedetto Simona,
  • Prosperi Mattia CF,
  • Paolini Elisabetta,
  • Di Biagio Antonio,
  • Ghisetti Valeria,
  • Di Pietro Massimo,
  • Zazzi Maurizio,
  • De Luca Andrea

DOI
https://doi.org/10.1186/1472-6947-11-40
Journal volume & issue
Vol. 11, no. 1
p. 40

Abstract

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Abstract Background HIV-1 genotypic susceptibility scores (GSSs) were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART) switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed. Methods We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90th day after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems (Rega, ANRS and HIVdb) and other covariates by means of Cox regression and random survival forests (RSF). Prediction models were validated via the bootstrap and c-index measure. Results The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70), while RSF showed a better performance (c-index≈0.73, p Conclusions GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART.