Clinical evaluation of Rega 8: an updated genotypic interpretation system that significantly predicts HIV-therapy response

Abstract

Introduction: Clinically evaluating genotypic interpretation systems is essential to provide optimal guidance in designing potent individualized HIV-regimens. This study aimed at investigating the ability of the latest Rega algorithm to predict virological response on a short and longer period.

Materials methods: 9231 treatment changes episodes were extracted from an integrated patient database. The virological response after 8, 24 and 48 weeks was dichotomized to success and failure. Success was defined as a viral load below 50 copies/ml or alternatively, a 2 log decrease from the baseline viral load at 8 weeks. The predictive ability of Rega version 8 was analysed in comparison with that of previous evaluated version Rega 5 and two other algorithms (ANRS v2011.05 and Stanford HIVdb v6.0.11). A logistic model based on the genotypic susceptibility score was used to predict virological response, and additionally, confounding factors were added to the model. Performance of the models was compared using the area under the ROC curve (AUC) and a Wilcoxon signed-rank test.

Results: Per unit increase of the GSS reported by Rega 8, the odds on having a successful therapy response on week 8 increased significantly by 81% (OR = 1.81, CI = [1.76-1.86]), on week 24 by 73% (OR = 1.73, CI = [1.69-1.78]) and on week 48 by 85% (OR = 1.85, CI = [1.80-1.91]). No significant differences in AUC were found between the performance of Rega 8 and Rega 5, ANRS v2011.05 and Stanford HIVdb v6.0.11, however Rega 8 had the highest sensitivity: 76.9%, 76.5% and 77.2% on 8, 24 and 48 weeks respectively. Inclusion of additional factors increased the performance significantly.

Conclusion: Rega 8 is a significant predictor for virological response with a better sensitivity than previously, and with rules for recently approved drugs. Additional variables should be taken into account to ensure an effective regimen.

Figure 1. Prevalence rates (%) of antiretroviral drugs.

Nucleotide/side reverse transcriptase inhibitors (N(t)RTIs): lamivudine (3TC), tenofovir (TDF), zidovudine (AZT), emtricitabine (FTC), didanosine (DDI), abacavir (ABC), stavudine (D4T), zalcitabine (DDC); non-nucleoside reverse transcriptase inhibitors (NNRTIs): efavirenz (EFV), nevirapine (NVP), etravirine (ETR); protease inhibitors (PIs): lopinavir (LPV/r), atazanavir (ATV), nelfinavir (NFV), saquinavir (SQV), indinavir (IDV), fosamprenavir (FPV), darunavir (DRV), amprenavir (APV), tipranavir (TPV), along with boosting ritonavir (RTV).

Figure 2. Distribution of the regimen-specific genotypic susceptibility scores reported by different versions of the Rega algorithm, ANRS v2011.05 and Stanford HIVdb v6.0.11.

Figure 3. Receiver operating Characteristic (ROC) analysis of the 24-weeks-performance of the regimen-specific genotypic susceptibility score (GSS) according to Rega 8, ANRS v2011.05 and Stanford HIVdb v6.0.11 algorithms.