Virologic Response to Lopinavir-Ritonavir-Based Antiretroviral Regimens in a Multicenter International Clinical Cohort: Comparison of Genotypic Interpretation Scores

Recruitment and data collection.The Clinic-Based Investigator Group is comprised of 20 academic, private, and public clinics. Participating clinics (n = 8) retrospectively identified previously LPV/r-naive patients who had received an LPV/r-based regimen, had a baseline viral load and genotype, and had follow-up viral loads. Participating clinics were sent a standardized seven-page data acquisition form.

Inclusion criteria.Patients were included for analysis if they had at least one viral load determination within 12 weeks prior to the initiation of LPV/r treatment, a baseline genotype within 24 weeks prior to and up to 3 weeks after LPV/r initiation, at least one viral load measurement during the first 18 weeks on LPV/r, and at least one viral load measurement between 18 and 30 weeks after LPV/r initiation (used as the 24-week viral load).

Definitions.Given the use of different viral load assays having different lower limits of quantification, the VR was defined by a viral load of <500 copies/ml at 24 weeks of therapy (i.e., the lower limit of quantification of the least sensitive assay).

A genotypic susceptibility score for the ART was calculated using the Stanford HIV drug resistance database. For each drug used in the new LPV/r-based regimen, a score was given based on the interpretation of the genotype (1, susceptible; 0.75, potential low-level resistance; 0.5, low-level resistance; 0.25, intermediate resistance; and 0, high-level resistance). The genotypic susceptibility score was calculated by adding the activity of all the antiretroviral medications used in the regimen. In addition, a partial genotypic susceptibility score was defined as the genotypic susceptibility score minus the PI's contribution to the regimen.

Scores.Not all mutations used to calculate the scores were captured in the data acquisition form. Not all the labs performing genotypic resistance testing reported all the mutations of interest in their genotype reports, while some of the mutations of interest had not been described at the time of the study.

The LPV mutation score (10) is the unweighted sum of the numbers of mutations appearing at amino acid positions 10, 20, 24, 46, 53, 54, 63, 71, 82, 84, and 90.

The ViroLogic (16) score is the weighted sum of the following mutations: 10I/F, 16E, 20I/M, 32I, 33F, 34Q, 43T, 46L/I, 47V, 48 M/V, 50V, 54A/M/S/T/V, 58E, 63T, 73T, 74S, 82A/F/S, and 89I/M. All mutations were given a weight of one except for those at positions 50, 54, and 82, which were given a weight of three. The following mutations were not included in the data acquisition form and were excluded from the calculations: 16E, 20I, 34Q, 43T, 48M, 54S, 54T, 63T, 82S, 89I, and 89M.

The ATU (11) score is the unweighted sum of mutations appearing at positions 10, 20, 24, 33, 36, 47, 48, 54, 82, and 84.

The Stanford score is the weighted sum of the following mutations (the points for each mutation are in parentheses): 10F (4), 10I (2), 10R (2), 10V (2), 10Y (2), 11I (2), 24I (2), 24F (1), 32I (10), 32A (5), 33F (5), 46I (12), 46L (12), 46V (10), 47V (10), 47A (40), 48V (10), 48M (10), 48A (5), 48S (5), 48T (5), 50V (20), 53L (3), 53Y (2), 54L (12), 54M (12), 54S (10), 54T (10), 54V (12), 54A (10), 71T (1), 71V (3), 71I (2), 73C (2), 73S (2), 73T (2), 73A (2), 76V (8), 82A (20), 82F (20), 82S (20), 82T (20), 82M (10), 82L (10), 82C (10), 84A (10), 84V (12), 84C (10), 89V (1), 89I (1), 89T (1), and 90M (10). The following mutations were not included in the data acquisition form and were excluded from the calculations: 10R, 10Y, 11I, 24F, 32A, 46V, 47A, 48A, 48M, 48S, 48T, 53Y, 54S, 54T, 71I, 76V, 82S, 82C, 82L, 82M, 84A, 84C, 89I, 89T, and 89V.

The IAS-USA (8) score is the unweighted sum of the following mutations: 10F/I/R/V, 20M/R, 24I, 32I, 33F, 46I/L, 47A/V, 50V, 53L, 54V/L/A/M/T/S, 63P, 71V/T, 73S, 76V, 82A/F/T/S, 84V, and 90M. The following mutations were not included in the data acquisition form and were excluded from the calculations: 10R, 47A, 54S, 54T, 76V, and 82S.

Laboratory methods.A variety of genotype methods were used across the participating sites. Thirty-six percent of the genotypes were run at hospital-based labs, and 64% were run at commercial reference labs.

Statistical analysis.Virologic responses were evaluated in predefined demographic and clinical subgroups. Chi-square tests were used to assess statistical significance within each subgroup at an α level of 0.05 (two-tailed).

Fisher's exact test was used to evaluate the association between VR and the presence or absence of mutations in protease at each position of interest. The Benjamini-Hochberg procedure was used to correct for multiple comparisons. Statistical significance was assessed at an α level of 0.05 (two-tailed) (1).

Multivariate stepwise logistic regression models were used to assess the association between VR and demographic characteristics, clinical predictors, and mutations in protease. Demographic characteristics consisted of age, clinic, and gender. Clinical predictors included baseline log₁₀ viral load, baseline CD4⁺ T-cell count, and partial genotypic susceptibility score. Mutations in protease found to be significant from the univariate analysis and the 20 mutations thought a priori to be important to LPV/r resistance (based on the LPV mutation, ATU, ViroLogic, Stanford, and IAS-USA scores) were included in the starting model. The criterion for entry into the stepwise models was at an α level of 0.10. Predictors were retained in the stepwise models if they remained significant at an α level of 0.05.

To compare the performance of the different scores, receiver-operator characteristic (ROC) curves were constructed and their corresponding areas under the curve (AUC) were calculated. The AUC of the ROC curve is used to evaluate the predictive value of a given test. An AUC of 1 denotes a perfect test, while an AUC of 0.5 reflects a test without discriminatory power. The precision of the AUC estimates was evaluated by constructing 95% bootstrap confidence intervals (5,000 replicates) (4).

All statistical analyses were done using SAS 9.1.3 (Cary, NC). Institutional review board approval was obtained from participating centers.

Patient characteristics.A total of 103 patients were included in the study. The median age was 42.2 years (Table 1). The patients were predominantly male (75%) and Caucasian (64%). Patients were enrolled from the United States (77%) and from Italy (23%), with the majority being treated in academic centers (69%). The majority of the patients were antiretroviral (97%) and PI experienced (79%). The most commonly prescribed PI prior to enrollment was nelfinavir (55%) followed by indinavir (43%). The median baseline viral load and CD4⁺ T-cell count were 17,000 copies/ml and 247 cells/μl, respectively. The median numbers of PI, nonnucleoside reverse transcriptase inhibitor, and nucleoside reverse transcriptor inhibitor mutations as defined by the IAS-USA were 3, 1, and 4, respectively. The frequencies of PI mutations are summarized in Fig. 1.

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FIG. 1.

Frequency of PI mutations by position.

Virologic/immunologic response.The median CD4⁺ T-cell count increase from the baseline was 63 cells/μl. Overall, 76% of patients achieved VR at 24 weeks (Table 2). As expected, more ART- and PI-naive patients experienced VR at week 24 compared to their ART- and PI-experienced counterparts (ART naive versus ART experienced, 100% versus 75%; PI naive versus PI experienced, 82% versus 74%); however, these differences were not statistically significant (P = 0.32 and P = 0.45, respectively). There were no significant differences between the responses in patients across the different clinic settings or by gender or race. There was a trend toward an improved response in those with baseline viral loads less than 100,000 copies/ml (80% versus 60%; P = 0.068), but there appeared to be no difference in VR in patients with CD4 T-cell counts of <200 cells/μl compared to those with ≥200 cells/μl (71% versus 79%, respectively; P = 0.34).

Virologic response was improved in patients with higher baseline genotypic susceptibility scores. In particular, patients with genotypic susceptibility scores of <1, 1 to <1.5, 1.5 to <2, and ≥2 had virologic responses of 38%, 71%, 90%, and 80%, respectively (P = 0.0046).

Importantly, all of the LPV/r scores with defined breakpoints (the LPV mutation score, ViroLogic score, ATU score, and Stanford score) were able to distinguish VR with similar accuracy. Using the LPV mutation score, 81% of patients with a score less than 6 experienced VR at week 24 compared to only 30% of patients with a score of 6 or greater (P = 0.0004). For the ViroLogic score, 84% of patients with a score less than 7 experienced VR at week 24 compared to only 31% of patients with a score of 7 or greater (P < 0.0001). Similarly, 82% of patients with an ATU score less than 3 experienced VR at week 24 compared to only 50% of patients with an ATU score of 3 or greater (P = 0.0028). Using the Stanford score, 87% versus 73% versus 46% of patients responded with increasing levels of resistance to LPV/r (susceptible and potential low-level resistance versus low-level resistance versus intermediate- and high-level resistance, respectively) (P = 0.0003).

Univariate analyses.In the univariate analyses, mutations at positions 10, 54, and 82 were significantly associated with a lack of VR (P = 0.020, P = 0.00145, and P = 0.014, respectively). Additionally, there was a trend toward a significant association with a lack of VR and mutations at positions 30 and 90 (P = 0.074 and P = 0.074, respectively) (Table 3).

Multivariate analysis.In the multivariate analysis, an improved VR was associated with a lower baseline viral load. In addition, a lack of VR was associated with mutations at positions 54, 84, and 90 (Table 4).

Evaluation of scoring systems.ROC curves for each of the scores are presented in Fig. 2. Each of the genotypic interpretation scores appears to have performed reasonably well in our cohort. AUCs for the ROC curves were similar, with values ranging from 0.73 to 0.76 and their 95% confidence intervals having substantive overlap (Table 5). Prediction error and misclassification rates were calculated and also showed no clear advantage for any genotypic interpretation score (data not shown).

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FIG. 2.

ROC curves for genotypic interpretation systems. The ROC curves depict the tradeoff between the true positive rate (sensitivity) and false positive rate (1-specificity) of each genotypic interpretation system, as the clinical cutoff is varied.