Reducing Number of Pills or Number of Drugs
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Reducing Number of Pills or Number of Drugs
Reducing Number of Pills or Number of Drugs as Strategy of HIV Treatment Simplification. Data from the Italian Icona Cohort Zaccarelli Mauro1, Lorenzini Patrizia1, Gianotti Nicola2, Rusconi Stefano3, Viale Pierluigi4, Chirianni Antonio5, Sighinolfi Laura6, 7Parruti Giustino, 8D'Arminio Monforte Antonella, Antinori Andrea1, on behalf of ICONA Foundation, Study Group. P101 1National Institute for Infectious Diseases Lazzaro Spallanzani, Rome; 2San Raffaele Scientific Institute, Università Vita-Salute San Raffaele, Milan; 3DIBIC Luigi Sacco, University of Milan; 4Sant'Orsola Hospital, University of Bologna; 5D.Cotugno Hospital-AORN dei Colli, Naples; 6 S. Anna Hospital Ferrara; 7Pescara General Hospital; 8ASST Santi Paolo e Carlo, University of Milan, Italy. Background Results In order to reduce toxicity and improve adherence for Overall, 842 patients (525 STR, 317 LDR) were included. STR included TDF/FTC/EFV (36.8%), TDF/FTC/RPV long term efficacy, different antiretroviral (ARV) approaches are currently available in clinical practice. (48.4%) and EVG/COBI/FTC/TDF (14.9%). LDR included dual regimens: LPV/r, ATV/r, DRV/r plus 3TC/FTC (29.7%), or any MVC, RAL, ETV (15.7%) and PI/r monotherapy (54.6%). Patients switching to STR more frequently were receiving NNRTI, were on first regimen, had higher hemoglobin, transaminase, and MDRD levels at switching as compared to LDR. In contrast, patients switching to LDR were more often on PI/r and changed for toxicity, were older, had longer history of HIV infection, had high number of previous regimens, higher triglycerides and creatinine levels (Table 1). Overall, 240 patients (107 STR, 133 LDR) discontinued therapy during 1525 PYFU. The crude IR of DAC was 10.8 x 100 PYFU (95%CI: 8.9-13.0) in STR and 24.9 (95%CI: 21.0-29.6) in LDR (p<0.001). Among causes of discontinuation, toxicity, as reported by the treating physician, was significantly higher in STR patients (57.0% vs. 28.6%, p<0.001). By multivariable Poisson regression (table 2), HCV co-infection, higher creatinine and switching from PI/r or INI were associated with higher risk of DAC; longer duration of HIV, being at second regimen vs first, and switch for simplification, as reported by treating physician were found associated with lower risk. Switching to STR was associated with about a 50% reduction of DAC as compared to switch to LDR. Within STR group, the risk of DAC did not differ among the three STR; while, within LDR group, probability of DAC was higher in mono than dual regimens (IRR: 1.89; 95%CI: 1.33-2.69) with no difference between 3TC/PI/r vs. other dual regimens. Generally, different switching strategies are involved as reducing pill burden up one pill fixed dose combination (single table regimen – STR) or drug burden, in order to reduce regimen toxicity, up to regimens with only two or one drug (less drug regimen, LDR). Objectives The present analysis aims to compare durability and effectiveness of the two approaches in patients who simplified with suppressed HIV-RNA. Methods 201 (38.3%) 54 (10.3%) 238 (45.3%) 32 (6.1%) 0.064 61 (19.2%) 240 (75.7%) 16 (5.1%) 74 (14.1%) 429 (81.7%) 22 (4.2%) 0.106 315 (60.0%) 100 (19.1%) 110 (20.9%) 23.2 (8-54) 3 (1-6) 1.00 0.75 0.50 3 4 202 296 113 168 52 110 21 77 LDR STR 1.00 Log rank P<0.001 1.28 0.107 Years from first HIV test and visit (each) 0.96 0.94 0.99 0.003 1.00 0.85 0.76 0.76 0.50 0.56 0.41 1.44 1.02 1.39 0.548 0.063 0.373 1.00 2.01 1.08 1.27 0.61 3.17 1.91 0.003 0.801 1.00 0.60 0.93 0.41 0.65 0.86 1.32 0.006 0.676 1.00 1.31 1.01 0.99 1.02 0.99 1.01 1.67 1.03 0.809 0.031 0.341 1.00 1.60 2.24 1.14 1.19 2.23 4.23 0.006 0.013 1.00 1.11 0.69 0.65 0.50 0.48 0.48 2.48 1.00 0.89 0.796 0.052 0.008 0.54 0.40 0.73 0.000 Number of regimens at switch 0 Number at risk dual 145 mono 172 1 2 Years from switch 3 4 103 98 60 52 27 26 11 11 mono 1.00 1 2 >=3 Laboratory tests Triglycerides (per 10 mg/dl) Creatinine (per 10 mg/dl) ALT (per 10 UI/l more) Patients who switched to LDR, n=525 Type of pre-switch regimen Log rank P=0.726 NRTI/NNRTI NRTI/PI/r NRTI/INI Reason of switching 0 Number at risk atripla 200 eviplera 258 stribild 75 0.130 0.145 0.98 negative positive unknown 0.75 <0.001 1.12 HCV co-infection Patients who switched to LDR, n=317 dual 0.970 1 2 Years from switch 3 4 167 117 17 138 28 7 111 3 1 80 2 0 atripla stribild eviplera Toxicity Adherence/patient decision Other/unknown Simplfication STR vs LDR 14.6 (13.5-15.5) 6300 (5100-7680) 133 (94-198) 193 (165-221) 0.95 (0.80-1.13) 82 (67-96) 23 (16-33) 598 (464-807) 14.8 (13.8-15.6) 5990 (5000-7300) 121 (85-169) 188 (161-217) 0.89 (0.78-1) 91 (80-104) 28 (20-40) 606 (463-805) 0.026 0.088 0.004 0.255 <0.001 <0.001 <0.001 0.734 44 (13.9%) 265 (83.6%) 8 (2.5%) 197 (37.5%) 296 (56.4%) 32 (6.1%) <0.001 106 (33.4%) 8 (2.5%) 146 (46.0%) 57 (18.1%) 104 (19.8%) 15 (2.9%) 278 (52.9%) 128 (24.4%) <0.001 p-value Age (per 10 years older) heterosexual IVDU MSM Other/unknown 0.25 139 (43.8%) 71 (22.4%) 107 (33.7%) 25.4 (12-52) 3 (2-8) 2 Years from switch 0.00 17 (3.2%) 469 (89.3%) 39 (7.4%) Number at risk LDR 317 STR 525 1 0.75 0.487 <0.001 0.002 119 (37.5%) 51 (16.1%) 134 (42.3%) 13 (4.1%) 10 (3.1%) 282 (89.0%) 25 (7.9%) 0 0.50 p-value 95% CI Mode of HIV transmission 0.25 525 418 (79.6%) 43 (36-50) 4.8 (2.4-9.8) ARR Log rank P<0.001 0.00 317 246 (77.6%) 46 (39-52) 5.8 (2.8-15.3) All patients, n=942 0.50 STR Cumulative probability of discontinuation n. Male gender, n (%) Age, years, median (IQR) Years from HIV test and first visit, median (IQR) Mode of HIV transmission heterosexual IVDU MSM Other/unknown HCV co-infection positive negative not known HBV co-infection positive negative not known Number of regimens at switch 1 2 >=3 Months of undetectable HIV-RNA pre-switch Overall years of cART, median (IQR) Laboratory data Haemoglobin, mg/dl White blood cells Triglicerides, mg/dl Cholesterol, mg/dl Creatinine, mg/dl MDRD, ml/min ALT, mg/dl CD4 count at switch Type of pre-switch regimen NRTI/NNRTI NRTI/PI/r NRTI/INI Reason of switching Toxicity Adherence/patient ‘s decision Simplification Other/unknown LDR Cumulative probability of discontinuation Table 1. Characteristics of patients according to type of switch to STR or LDR Table 2. Rate ratio of all causes discontinuation from fitting a Poisson regression. 0.25 Cumulative probability of discontinuation 2008 switched to STR or LDR from any triple drug regimen, including two NRTI plus PI/r, NNRTI or INI with undetectable HIV-RNA were selected. STR included TDF/FTC plus EFV, RPV or EVG fixed dose combinations; LDR included dual regimens composed by boosted PI (LPV/r, ATV/r DRV/r) plus any 3TC/FTC, MAR, RAL or ETV, and PI/r monotherapy. End-point of the analysis was the discontinuation of the regimen by any cause (DAC). Poisson regression was used to evaluate statistical associations with the outcome. Figure 1. Kaplan Meier estimates Outcome: discontinuation for any cause 0.00 From the Italian Icona Cohort, patients who after January Conclusions Reducing pill burden (STR) and reducing drug burden (LDR) are strategies that recognize different clinical reasons and settings. Switching to STR was associated to greater stability of the regimen and consequently lower treatment discontinuation. LDR can be useful in limited settings in order to reduce toxicity. PI/r monotherapy predicted higher rates of discontinuation. ICONA Foundation Study Group BOARD OF DIRECTORS A d’Arminio Monforte (Vice-President), M Andreoni, G Angarano, A Antinori, F Castelli, R Cauda, G Di Perri, M Galli, R Iardino, G Ippolito, A Lazzarin, CF Perno, F von Schloesser, P Viale. SCIENTIFIC SECRETARY A d’Arminio Monforte, A Antinori, A Castagna, F Ceccherini-Silberstein, A Cozzi-Lepri, E Girardi, S Lo Caputo, C Mussini, M Puoti. STEERING COMMITTEE M Andreoni, A Ammassari, A Antinori, C Balotta, A Bandera, P Bonfanti, S Bonora, M Borderi, A Calcagno, L Calza, MR Capobianchi, A Castagna, F CeccheriniSilberstein, A Cingolani, P Cinque, A Cozzi-Lepri, A d’Arminio Monforte, A De Luca, A Di Biagio, E Girardi, N Gianotti, A Gori, G Guaraldi, G Lapadula, M Lichtner, S Lo Caputo, G Madeddu, F Maggiolo, G Marchetti, S Marcotullio, L Monno, C Mussini, S Nozza, M Puoti, E Quiros Roldan, R Rossotti, S Rusconi, MM Santoro, A Saracino, M Zaccarelli. STATISTICAL AND MONITORING TEAM A Cozzi-Lepri, I Fanti, L Galli, P Lorenzini, A Rodano, M Shanyinde, A Tavelli. BIOLOGICAL BANK INMI F Carletti, S Carrara, A Di Caro, S Graziano, F Petrone, G Prota, S Quartu, S Truffa. PARTICIPATING PHYSICIANS AND CENTERS A Giacometti, A Costantini, C Valeriani (Ancona); G Angarano, L Monno, C Santoro (Bari); F Maggiolo, C Suardi (Bergamo); P Viale, V Donati, G Verucchi (Bologna); F Castelli, E Quiros Roldan, C Minardi (Brescia); T Quirino, C Abeli (Busto Arsizio); PE Manconi, P Piano (Cagliari); B Cacopardo, B Celesia (Catania); J Vecchiet, K Falasca (Chieti); L Sighinolfi, D Segala (Ferrara); F Mazzotta, F Vichi (Firenze); G Cassola, C Viscoli, A Alessandrini, N Bobbio, G Mazzarello (Genova); C Mastroianni, V Belvisi (Latina); P Bonfanti, I Caramma (Lecco); A Chiodera, P Milini (Macerata); M Galli, A Lazzarin, G Rizzardini, M Puoti, A d’Arminio Monforte, AL Ridolfo, R Piolini, A Castagna, S Salpietro, L Carenzi, MC Moioli, C Tincati, G Marchetti (Milano); C Mussini, C Puzzolante (Modena); A Gori, G Lapadula (Monza); N Abrescia, A Chirianni, G Borgia, R Orlando, F Di Martino, L Maddaloni, I Gentile, G Bonadies (Napoli); A Cascio, C Colomba (Palermo); F Baldelli, E Schiaroli (Perugia); G Parruti, T Ursini (Pescara); G Magnani, MA Ursitti (Reggio Emilia); R Cauda, M Andreoni, A Antinori, V Vullo, A Cristaudo, A Cingolani, G Baldin, S Cicalini, L Gallo, E Nicastri, R Acinapura, M Capozzi, R Libertone, S Savinelli, A Latini, G Iaiani, L Fontanelli Sulekova (Roma); M Cecchetto, F Viviani (Rovigo); MS Mura, G Madeddu (Sassari); A De Luca, B Rossetti (Siena); D Francisci, C Di Giuli (Terni); P Caramello, G Di Perri, GC Orofino, S Bonora, M Sciandra (Torino); M Bassetti, A Londero (Udine); G Pellizzer, V Manfrin (Vicenza).