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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2011

Open Access 01-12-2011 | Research article

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

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

Published in: BMC Medical Informatics and Decision Making | Issue 1/2011

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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 < 0.0001 vs. Cox regression). Variable importance according to RSF was concordant with the Cox hazards.

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.
Appendix
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Metadata
Title
A Prognostic Model for Estimating the Time to Virologic Failure in HIV-1 Infected Patients Undergoing a New Combination Antiretroviral Therapy Regimen
Authors
Mattia CF Prosperi
Simona Di Giambenedetto
Iuri Fanti
Genny Meini
Bianca Bruzzone
Annapaola Callegaro
Giovanni Penco
Patrizia Bagnarelli
Valeria Micheli
Elisabetta Paolini
Antonio Di Biagio
Valeria Ghisetti
Massimo Di Pietro
Maurizio Zazzi
Andrea De Luca
the ARCA cohort
Publication date
01-12-2011
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2011
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/1472-6947-11-40

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