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).