Poster # 42 Resistance in PBMCs Can Predict Virological Rebound after Therapy Switch in cart- Treated Patients with Undetectable HIV-RNA

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1 Poster # 42 Resistance in PBMCs Can Predict Virological Rebound after Therapy Switch in cart- Treated Patients with Undetectable HIV-RNA D Armenia 1, M Zaccarelli 2, V Borghi 3, W Gennari 3, A Giannetti 2, F Forbici 2, C Pinnetti 2, F Ceccherini Silberstein 1, C Mussini 3, CF Perno 2, A Antinori 2, and MM Santoro 1 1 University of Rome Tor Vergata, Rome, Italy; 2 L. Spallanzani Hospital, Rome, Italy; 3 Polyclinic of Modena, Modena, Italy.

2 Background (I) The presence of resistant HIV strains is routinely verified in plasma samples, since circulating virus variants are considered representative of the viral population escaping the drug pressure. Nevertheless, several studies suggested that genotypic resistance test (GRT) from peripheral blood mononuclear cells (PBMCs) can be useful for detection of drug resistance mutations in blood samples. Opravil M et al., J Infect Dis 2002; Parisi SG et al., JCM 2007; De Castro N et al., CID 2009; Palmisano L et al., JAIDS 2009; Banks L et al., Journal of AIDS & clin res 2012; Delaugerre C et al., HIV Med 2012; Gallien S et al., JAC 2015; Lubke N et al., Intervirol 2015; Zaccarelli et al., XXIV International HIV Drug Resistance Workshop, 2015.

3 Background (II) GRT from PBMCs may be a valid alternative in patients on combined antiretroviral therapy (cart) with low or undetectable virus load to plan drug switches. However, the clinical relevance of resistance detected in PBMC compartment is still debated.

4 Aim Thus, we evaluated the impact of baseline resistance detected in PBMC GRT on maintaining virological suppression after therapy switching in cart treated patients with undetectable HIV-1 RNA.

5 cart-experienced patients switching therapy with a GRT from PBMCs available before therapy change were included. Inclusion criteria: Methods (I) Undetectable viremia at baseline of therapy switch; PBMC genotyping available before therapy switching; HIV-1 RNA follow-up available after therapy switching; Availability of nadir CD4 cell count and baseline CD4 cell count. Analyses were performed on patients who did not discontinue therapy. Patients were censored at the last viremia measurement available before therapy discontinuation or at treatment interruption.

6 Methods (II) Resistance to nucleos(t)ide reverse transcriptase inhibitors (NRTIs), non-nrtis (NNRTIs), protease inhibitors (PIs) and integrase inhibitors (INIs) was evaluated at PBMC GRTs available before therapy switching. Resistance to each drug-class was defined as follows: For NRTIs, by the presence of at least one major mutation associated with resistance to NRTIs; For NNRTIs, by the presence of at least one major mutation associated with resistance to NNRTIs; For PIs, by the presence of at least one major mutation associated with resistance to PIs; For INIs, by the presence of at least one major mutation associated with resistance to INIs (only in patients who switched to an INI containing regimen). The prevalence of resistance in PBMCs was evaluated using IAS/Stanford resistance lists Genotypic susceptibility score (GSS) for optimized therapy was calculated according to HIVdb ver.7.1 algorithm, based on the sum of genotype sensitivities to all drugs administered at therapy switch.

7 Methods (III) Kaplan-Meier estimates was used to assess the probability of virological rebound (VR: two consecutive viremia values >50 copies/ml or one viremia >1000 copies/ml after therapy switching) overall and according to both baseline PBMC GSS and the duration of virological suppression before therapy switching. Cox-regression analysis was used to evaluate potential predictors of VR among the following variables: age, gender, subtype, nadir CD4, duration of virological suppression before switching, number of previous regimens, number of antiretrovirals administered at switch, INI usage at switch, maraviroc usage at switch. All the analyses were performed using the software package SPSS (version 19.0) for Windows (SPSS Inc., Chicago, Illinois).

8 Results

9 Patients characteristics at PBMC genotyping Variables N=136 Male, n (%) 95 (69.9) Age, year, median (IQR) 48 (41-52) Risk factor, n (%) Homosexual 34 (25.0) Heterosexual 48 (35.3) Drug abuser 44 (32.4) Other/unknown 10 (7.3) B subtype, n (%) 119 (87.5) Nadir CD4 cell count (cells/mm 3 ), median (IQR) 164 (66-300) Baseline CD4 cell count (cells/mm 3 ), median (IQR) 537 ( ) Time under undetectable HIV-1 RNA before therapy switching, years, median (IQR) 3.8 ( ) Time under undetectable HIV-1 RNA before therapy switching, n (%) a <1 year 28 (20.6) 1-3 years 30 (22.1) 4 years 55 (40.4) Unknown 23 (16.9) Time between PBMC GRT and therapy switch, months, median (IQR) 1.6 ( ) Viral load measurements per year of follow-up 3.2 ( ) Time of follow-up after therapy switching, months, median (IQR) 13 ( ) a. Time from the last undetectable HIV-1 RNA after detectable viremia (regardless single blips with HIV-RNA <1000 copies/ml) to the date of therapy switch.

10 Therapy overview at PBMC genotyping Variables N=136 No. of regimens administered before PBMC GRT 1 12 (8.8) (39.0) >5 47 (34.6) Unknown 24 (17.6) No. of antiretrovirals experienced before PBMC GRT, median (IQR) a 7 (5-10) No. of antiretroviral classes experienced before PBMC GRT, n (%) 2 43 (31.6) 3 51 (37.5) 4 10 (7.3) 5 8 (5.8) Unknown 24 (17.6) Time under antiretroviral treatment, year, median (IQR) a 10 (4-16) Drug classes administered at DNA GRT, n (%) NRTI 121 (89.0) PI 104 (76.5) NNRTI 30 (22.1) INI 15 (11.0) CCR5 antagonists 4 (2.9) FI 3 (2.2) Unknown 7 (5.1) Single tablet regimen administered at PBMC GRT, n (%) TDF/FTC/EFV 9 (6.6) a. Calculated on 112/136 patients with complete therapeutic history. FI: fusion inhibitors; INI: integrase inhibitors; PI: protease inhibitors; NRTI: Nucleos(t)ide reverse transcriptase inhibitors; NNRTI: Non-NRTI.

11 Overview of therapy switches Variables N=136 No of antiretrovirals administered at therapy switch, n(%) 1 a 5 (3.7) 2 43 (31.6) 3 75 (55.1) >3 13 (9.6) Drugs administered at therapy switch, n (%) NRTI 109 (80.1) PI 65 (47.8) NNRTI 37 (27.2) INI 26 (19.1) Maraviroc 20 (14.7) Single tablet regimen administered at therapy switch, n (%) TDF/FTC/RPV 6 (4.4) TDF/FTC/EFV 3 (2.2) TDF/FTC/EVG/COBI 3 (2.2) a. All patients received DRV/r monotherapy. INI: integrase inhibitors; PI: protease inhibitors; NRTI: Nucleos(t)ide reverse transcriptase inhibitors; NNRTI: Non-NRTI.

12 Resistance prevalence (%) Genotypic resistance from PBMC GRT at baseline Resistance prevalence No resistance Any PI NRTI NNRTI INI Class resistance prevalence 52% 32% 3% 13% 0 classes 1 class 2 classes 3 classes INI: integrase inhibitors; PI: protease inhibitors; NRTI: Nucleos(t)ide reverse transcriptase inhibitors; NNRTI: Non-NRTI.

13 30N 46I 46L 48V 50L 50V 54T 54V 58E 82A 82V 84V 90M 0.7% 2.2% 0.7% 0.7% 0.7% 1.5% 2.2% 2.2% 5.1% 2.9% 5.1% 3.7% 5.1% 41L 62V 67N 70R 74I 74V 184I 184V 210W 215F 215Y 219E 219Q 100I 101P 101E 103N 103S 106A 108I 138A 138K 179D 190S 190A Prevalence of PI/NRTI/NNRTI major mutations at baseline PBMC GRT NRTI mutations NNRTI mutations PI mutations PI: protease inhibitor; NRTI: Nucleos(t)ide reverse transcriptase inhibitor; NNRTI: Non-NRTI.

14 PBMC genotypic susceptibility score for optimized therapy switch 84% 2% 14% Fully resistant Intermediate resistant Fully susceptible *According to HIVdb ver.7.1 algorithm. GSS was based on the sum of genotype sensitivities to all drugs administered at therapy switch.

15 Probability of experiencing virological rebound Twenty-four months after therapy switching, the overall probability of VR was 18%. Patients showing in PBMCs an intermediate or fully resistant GSS to the regimen administered had a higher probability of experiencing VR compared to those showing full susceptibility. 1.0 Kaplan Meyer estimates of virological rebound stratified for GSS (VR: 2 consecutive HIV-1 RNA >50 copies/ml or 1 HIV-RNA >1000 copies/ml after therapy switching) Genotypic susceptybility score Fully or intermediate resistant Fully susceptible 0.4 P= % % Time (months from therapy switch) No. at risk

16 Probability of experiencing virological rebound Patients virologically suppressed for less than one year before therapy switching showed the highest probability of experiencing VR compared to those with a longer time of virological suppression Kaplan Meyer estimates of virological rebound (VR: 2 consecutive HIV-1 RNA >50 copies/ml or 1 HIV-RNA >1000 copies/ml after therapy switching) Time under undetectable HIV-1 RNA before therapy switching <1 year 1-3 years 4 years Unknown P= Time (months from therapy switch) No. at risk 43.5% 17.5% 12.0% 8.1%

17 Cox-regression confirmed that a higher hazard of experiencing VR was found in patients with an intermediate or fully resistant GSS in PBMCs as compared to those with a fully susceptible GSS, and in patients virologically suppressed for less than one year compared to those with a time of virological suppression of at least 4 years. Crude relative hazard of Adjusted a relative hazard of experiencing VR experiencing VR Variables 95% C.I. 95% C.I. RH P value RH P value L U L U Genotipic susceptibility score Fully susceptible b 1 1 Intermediate or fully resistant Time under undetectable HIV-1 RNA before therapy switching, years 4 b < Unknown Nadir CD4 cell count (cells/mm 3 ) < a. Adjusted for age, gender, subtype, nadir CD4, duration of virological suppression before switching, number of previous regimens, number of antiretrovirals administered at switch, INI usage at switch, maraviroc usage at switch. In the table are reported only variables with a p value <0.2 at univariable analysis; these variables were then retained in multivariable model. Factors significantly associated (p <0.05) to virological rebound at uni-multi variable Cox regression are indicated in bold. b. Reference (dummy).

18 Conclusions In clinical practice, treatment switch with long-term undetectable HIV-1 RNA warrants a high rate of maintaining virological suppression. However, patients with intermediate or fully resistant GSS in PBMCs have a higher risk of rebound after therapy switching. In patients under virological suppression, PBMC genotyping can be a useful tool for tailoring antiretroviral treatment switch.

19 Acknowledgements University of Rome Tor Vergata, Rome Italy C.F. Perno F. Ceccherini-Silberstein D. Armenia D. Di Carlo A. Bertoli A. Biddittu M. Romani M. Bruni C. Mussini V. Borghi W. Gennari - The Patients Modena University Hospital, Modena, Italy G. Ippolito A. Antinori M. Zaccarelli G. D Offizi U. Visco-Comandini N. Petrosillo G. Liuzzi F. Antonucci E. Boumis P. De Longis E. Nicastri A. Ammassari R. Bellagamba C. Pinnetti C. Tommasi L. Lo Iacono M.L. Giancola R. Acinapura INMI L Spallanzani, Rome, Italy M.R. Capobianchi L. Fabeni C. Gori F. Forbici S. Carta V. Fedele G. Berno D. Pizzi F. Continenza A. Giannetti and the Resistance Study Group

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