17 results on '"Trezzi, M."'
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2. 96 Week follow-up of HIV-infected patients in rescue with raltegravir plus optimized backbone regimens: a multicentre Italian experience.
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Capetti A, Landonio S, Meraviglia P, Di Biagio A, Lo Caputo S, Sterrantino G, Ammassari A, Menzaghi B, Franzetti M, De Socio GV, Pellicanò G, Mazzotta E, Soria A, Meschiari M, Trezzi M, Sasset L, Celesia BM, Zucchi P, Melzi S, Ricci E, and Rizzardini G
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- Adult, Antiretroviral Therapy, Highly Active, CD4 Lymphocyte Count, CD4-Positive T-Lymphocytes drug effects, CD4-Positive T-Lymphocytes virology, Drug Resistance, Viral drug effects, Female, Follow-Up Studies, HIV Infections virology, HIV-1 physiology, Humans, Italy, Male, Middle Aged, Raltegravir Potassium, Viral Load drug effects, HIV Infections drug therapy, HIV Integrase Inhibitors therapeutic use, HIV-1 drug effects, Pyrrolidinones therapeutic use, Salvage Therapy
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Background: Long term efficacy of raltegravir (RAL)-including regimens in highly pre-treated HIV-1-infected patients has been demonstrated in registration trials. However, few studies have assessed durability in routine clinical settings., Methods: Antiretroviral treatment-experienced patients initiating a RAL-containing salvage regimen were enrolled. Routine clinical and laboratory follow-up was performed at baseline, week 4, 12, and every 12 weeks thereafter. Data were censored at week 96., Results: Out of 320 patients enrolled, 292 (91.25%) subjects maintained their initial regimen for 96 weeks; 28 discontinued prematurely for various reasons: death (11), viral failure (8), adverse events (5), loss to follow-up (3), consent withdrawal (1). Eight among these 28 subjects maintained RAL but changed the accompanying drugs. The mean CD4+ T-cell increase at week 96 was 227/mm(3); 273 out of 300 patients (91%), who were still receiving RAL at week 96, achieved viral suppression (HIV-1 RNA <50 copies/mL). When analyzing the immuno-virologic outcome according to the number of drugs used in the regimen, 2 (n = 45), 3 (n = 111), 4 (n = 124), or >4 (n = 40), CD4+ T-cell gain was similar across strata: +270, +214, +216, and +240 cells/mm(3), respectively, as was the proportion of subjects with undetectable viral load. Laboratory abnormalities (elevation of liver enzymes, total cholesterol and triglycerides) were rare, ranging from 0.9 to 3.1%. The mean 96-week total cholesterol increase was 23.6 mg/dL., Conclusions: In a routine clinical setting, a RAL-based regimen allowed most patients in salvage therapy to achieve optimal viral suppression for at least 96 weeks, with relevant immunologic gain and very few adverse events.
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- 2012
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3. Effectiveness of antiretroviral regimens containing abacavir with tenofovir in treatment-experienced patients: predictors of virological response and drug resistance evolution in a multi-cohort study.
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Di Giambenedetto S, Torti C, Prosperi M, Manca N, Lapadula G, Paraninfo G, Ladisa N, Zazzi M, Trezzi M, Cicconi P, Corsi P, Nasta P, Cauda R, and De Luca A
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- Adenine therapeutic use, Adult, Cohort Studies, Female, HIV Infections virology, HIV-1 isolation & purification, Humans, Male, Middle Aged, Mutation, Missense, Tenofovir, Treatment Failure, Treatment Outcome, Viral Load, Viral Proteins genetics, Adenine analogs & derivatives, Anti-HIV Agents therapeutic use, Antiretroviral Therapy, Highly Active methods, Dideoxynucleosides therapeutic use, Drug Resistance, Viral, HIV Infections drug therapy, HIV-1 drug effects, Organophosphonates therapeutic use
- Abstract
Background: In treatment-naïve patients, a combination antiretroviral therapy (cART) containing tenofovir (TDF) and abacavir (ABC) with lamivudine leads to unacceptably high virological failure rates with frequent selection of reverse transcriptase mutations M184V and K65R. We explored the efficacy of at least 16 weeks of ABC + TDF-containing cART regimens in 307 antiretroviral-experienced HIV-1-infected individuals included in observational databases., Methods: Virological failure was defined as an HIV RNA > 400 copies/ml after at least 16 weeks of treatment. Patients had received a median of three prior cART regimens. Of these, 76% concomitantly received a potent or high genetic barrier regimen (with at least one protease inhibitor [PI]) or non-nucleoside reverse transcriptase inhibitor or thymidine analogue) while a third non-thymidine nucleoside analogue was used in the remaining patients., Results: The 1-year estimated probability of virological failure was 34% in 165 patients with HIV RNA > 400 copies/ ml at ABC + TDF regimen initiation. Independent predictors of virological failure were the absence of a potent or high genetic barrier cART, the higher number of cART regimens experienced, and the use of a new drug class. In the subset of 136 patients for whom there were genotypic resistance test results prior to ABC + TDF initiation, the virological failure (1-year estimated probability 46%) was independently predicted by the higher baseline viral load, the concomitant use of boosted PI, and the presence of reverse transcriptase mutation M41L. In 142 patients starting ABC + TDF therapy with HIV RNA pound < or =400 copies/ml, virological failure (1-year estimated probability 17%) was associated only with the transmission category. In a small subset of subjects for whom there were an available paired baseline and follow-up genotype (n = 28), the prevalence of most nucleoside analogue reverse transcriptase inhibitor resistance mutations decreased, suggesting a possible low adherence to treatment. No selection of K65R was detected., Conclusion: The virological response to ABC + TDF-containing regimens in this moderately-to-heavily treatment experienced cohort was good. Higher viral load and the presence of M41L at baseline were associated with worse virological responses, while the concomitant prescription of drugs enhancing the genetic barrier of the regimen conveyed a reduced risk of virological failure. The Appendix provides the names of other members of the MASTER cohort.
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- 2009
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4. Prevalence of transmitted HIV-1 drug resistance in HIV-1-infected patients in Italy: evolution over 12 years and predictors.
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Bracciale L, Colafigli M, Zazzi M, Corsi P, Meraviglia P, Micheli V, Maserati R, Gianotti N, Penco G, Setti M, Di Giambenedetto S, Butini L, Vivarelli A, Trezzi M, and De Luca A
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- Adult, Amino Acid Substitution, Anti-HIV Agents pharmacology, Female, Genotype, HIV Infections transmission, HIV Protease Inhibitors pharmacology, HIV-1 genetics, HIV-1 isolation & purification, Humans, Italy epidemiology, Male, Mutation, Missense, Prevalence, RNA, Viral genetics, Retrospective Studies, Reverse Transcriptase Inhibitors pharmacology, Drug Resistance, Viral, HIV Infections epidemiology, HIV Infections virology, HIV-1 classification, HIV-1 drug effects
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Objectives: Transmitted HIV-1 drug resistance (TDR) can reduce the efficacy of first-line antiretroviral therapy., Patients and Methods: A retrospective analysis was performed to assess the prevalence and correlates of TDR in Italy over time. TDR was defined as the presence of at least one of the mutations present in the surveillance drug resistance mutation (SDRM) list., Results: Among 1690 antiretroviral therapy-naive patients, the most frequent HIV subtypes were B (78.8%), CRF02_AG (5.6%) and C (3.6%). Overall, TDR was 15%. TDR was 17.3% in subtype B and 7.0% in non-B carriers (P < 0.001). TDR showed a slight, although not significant, decline (from 16.3% in 1996-2001 to 13.4% in 2006-07, P = 0.15); TDR declined for nucleoside reverse transcriptase inhibitors (from 13.1% to 8.2%, P = 0.003) but remained stable for protease inhibitors (from 3.7% to 2.5%, P = 0.12) and non-nucleoside reverse transcriptase inhibitors (from 3.7% to 5.8%). TDR to any drug was stable in B subtype and showed a decline trend in non-B. In multivariable analysis, F1 subtype or any non-B subtype, compared with B subtype, and higher HIV RNA were independent predictors of reduced odds of TDR., Conclusions: Prevalence of TDR to nucleoside reverse transcriptase inhibitors seems to have declined in Italy over time. Increased prevalence of non-B subtypes partially justifies this phenomenon.
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- 2009
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5. Evolution and predictors of HIV type-1 drug resistance in patients failing combination antiretroviral therapy in Italy.
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Di Giambenedetto S, Zazzi M, Corsi P, Gonnelli A, Di Pietro M, Giacometti A, Almi P, Trezzi M, Boeri E, Gianotti N, Menzo S, Del Gobbo R, Francisci D, Nerli A, Galli L, and De Luca A
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- Adult, Anti-HIV Agents pharmacology, Antiretroviral Therapy, Highly Active, Female, HIV Infections drug therapy, HIV Protease genetics, HIV-1 classification, HIV-1 drug effects, Heterosexuality, Humans, Italy epidemiology, Male, Mutation, Risk Factors, Treatment Failure, Viral Load, Anti-HIV Agents therapeutic use, Drug Resistance, Multiple, Viral genetics, Evolution, Molecular, HIV Infections epidemiology, HIV Infections virology, HIV-1 genetics
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Background: This study aimed to examine the evolution of genotypic drug resistance prevalence in treatment-failing patients in the multicentre, Italian, Antiretroviral Resistance Cohort Analysis (ARCA)., Methods: Patients with a drug resistance genotype test performed between 1999 and 2006 at failure of a combination antiretroviral therapy and with complete treatment history were selected. The prevalence of resistance was measured overall, per calendar year, per drug class and per treatment line at failure., Results: The overall resistance prevalence was 81%. Resistance to nucleoside reverse transcriptase inhibitors (NRTIs) declined after 2002 (68% in 2006; chi(2) for trend P=0.004); resistance to non-NRTIs (NNRTIs) stabilized after 2004; and resistance to protease inhibitors (PIs) declined after 2001 (43% in 2006; P=0.004). In first-line failures, NRTI resistance decreased after 2002 (P=0.006), NNRTI resistance decreased after 2003 (P=0.001) and PI resistance decreased after 2001 (P<0.001). Independent predictors of resistance to any class were HIV type-1 transmission by heterosexual contacts as compared with injecting drug use, a higher number of experienced regimens, prior history of suboptimal therapy, higher viral load and CD4+ T-cell counts, more recent calendar year and viral subtype B carriage, whereas the use of PI-based versus NNRTI-based regimens at failure was associated with a reduced risk of resistance. There was an increase of type-1 thymidine analogue and of protease mutations L33F, I47A/V, I50V and I54L/M, whereas L90M decreased over calendar years., Conclusions: During more recent years, emerging drug resistance has decreased, particularly in first-line failures. The prevalence continues to be high in multiregimen-failing patients.
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- 2009
6. Determinants of HIV-1 genotypic resistance to darunavir (TMC114) in a large Italian resistance database (Antiretroviral Resistance Cohort Analysis).
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Rusconi S, Gianotti N, Adorni F, Boeri E, Menzo S, Gonnelli A, Micheli V, Meraviglia P, Trezzi M, Paolini E, Giacometti A, Corsi P, Di Pietro M, Monno L, Punzi G, and Zazzi M
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- CD4 Lymphocyte Count, Cohort Studies, Darunavir, Genotype, Humans, Italy, Viral Load, Drug Resistance, Viral, HIV Protease Inhibitors therapeutic use, HIV-1 drug effects, HIV-1 genetics, Sulfonamides therapeutic use
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- 2007
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7. Prevalence of acquired resistance mutations in a large cohort of perinatally infected HIV-1 patients
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Ungaro, R., Taramasso, L., Bruzzone, B., Vicenti, I., Galli, L., Borghi, V., Francisci, D., Pecorari, M., Zoncada, A., Callegaro, A. P., Paolini, E., Monno, L., Bonora, S., Di Biagio, A., ARCA Study Group, Giacometti, A., Butini, L., del Gobbo, R., Bagnarelli, P., Tacconi, D., Corbelli, G., Zanussi, S., Punzi, G., Maggiolo, F., Calza, L., Carla Re, M., Pristera, R., Turconi, P., Mandas, A., Tini, S., Amadio, G., Sighinolfi, L., Corsi, P., Di Pietro, M., Colao, G., Tosti, A., Setti, M., Cenderello, G., Trezzi, M., Orani, A., Arcidiacono, I., Degiuli, A., De Gennaro, M., Chiodera, A., Scalzini, A., Palvarini, L., Todaro, G., Rusconi, S., Gismondo, M. R., Micheli, V., Biondi, M. L., Capetti, A., Meraviglia, P., Boeri, E., Mussini, C., Soria, A., Vecchi, L., Santirocchi, M., Brustia, D., Ravanini, P., Dal Bello, F., Romano, N., Mancuso, S., Calzetti, C., Maserati, R., Filice, G., Baldanti, F., Parruti, G., Polilli, E., Sacchini, D., Martinelli, C., Consolini, R., Vatteroni, L., Vivarelli, A., Nerli, A., Lenzi, L., Magnani, G., Ortolani, P., Andreoni, M., Fimiani, C., Palmisano, L., Di Giambenedetto, S., Vullo, V., Turriziani, O., Montano, M., Antinori, A., Zaccarelli, M., Dentone, C., Gonnelli, A., De Luca, A., Palumbo, M., Ghisetti, V., Delle Foglie, P., Rossi, C., Mondino, V., Malena, M., Grossi, P., Seminari, E., Poletti, F., Ungaro R., Taramasso L., Bruzzone B., Vicenti I., Galli L., Borghi V., Francisci D., Pecorari M., Zoncada A., Callegaro A.P., Paolini E., Monno L., Bonora S., Di Biagio A., Giacometti A., Butini L., del Gobbo R., Bagnarelli P., Tacconi D., Corbelli G., Zanussi S., Punzi G., Maggiolo F., Calza L., Carla Re M., Pristera R., Turconi P., Mandas A., Tini S., Amadio G., Sighinolfi L., Corsi P., Di Pietro M., Colao G., Tosti A., Setti M., Cenderello G., Trezzi M., Orani A., Arcidiacono I., Degiuli A., De Gennaro M., Chiodera A., Scalzini A., Palvarini L., Todaro G., Rusconi S., Gismondo M.R., Micheli V., Biondi M.L., Capetti A., Meraviglia P., Boeri E., Mussini C., Soria A., Vecchi L., Santirocchi M., Brustia D., Ravanini P., Dal Bello F., Romano N., Mancuso S., Calzetti C., Maserati R., Filice G., Baldanti F., Parruti G., Polilli E., Sacchini D., Martinelli C., Consolini R., Vatteroni L., Vivarelli A., Nerli A., Lenzi L., Magnani G., Ortolani P., Andreoni M., Fimiani C., Palmisano L., Di Giambenedetto S., Vullo V., Turriziani O., Montano M., Antinori A., Zaccarelli M., Dentone C., Gonnelli A., De Luca A., Palumbo M., Ghisetti V., Delle Foglie P., Rossi C., Mondino V., Malena M., Grossi P., Seminari E., and Poletti F.
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Male ,antiretroviral treatment ,Infectious Disease Transmission ,genotype ,Human immunodeficiency virus (HIV) ,Drug Resistance ,HIV Infections ,Drug resistance ,medicine.disease_cause ,Retrospective Studie ,Genotype ,pol Gene Products, Human Immunodeficiency Viru ,Prevalence ,Medicine ,Vertical ,HIV Infection ,Viral ,pol Gene Products ,Young adult ,General Medicine ,Infectious Diseases ,Italy ,Mutation (genetic algorithm) ,Female ,Human Immunodeficiency Virus ,Human ,Microbiology (medical) ,Adult ,Settore MED/17 - Malattie Infettive ,Adolescent ,Anti-HIV Agents ,Young Adult ,Acquired resistance ,Drug Resistance, Viral ,Humans ,vertical HIV transmission ,HIV-1 ,Mutation ,Retrospective Studies ,pol Gene Products, Human Immunodeficiency Virus ,Infectious Disease Transmission, Vertical ,HIV perinatally infection ,business.industry ,Anti-HIV Agent ,Retrospective cohort study ,Virology ,Large cohort ,business - Published
- 2019
8. The Effect of Switching to Maraviroc + Darunavir/Ritonavir Dual Therapy in Virologically Suppressed Patients on the Progression of Liver Fibrosis: Findings From a Randomized Study
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Rossetti, B., Gagliardini, R., Sterrantino, G., Colangeli, V., Latini, A., Colafigli, M., Vignale, F., Rusconi, S., Di Biagio, A., Orofino, G., Mezzaroma, I., Vullo, V., Francisci, D., Mastroianni, C., Trezzi, M., Canovari, B., Lamonica, S., Ciccullo, A., Borghetti, A., D'Arminio Monforte, A., Di Giambenedetto, S., De Luca, A., and GUSTA trial study group
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Oncology ,Liver Cirrhosis ,Male ,medicine.medical_specialty ,Darunavir+Ritonavir ,Anti-HIV Agents ,Liver fibrosis ,Antiretroviral Therapy ,HIV Infections ,Darunavir ,Disease Progression ,Drug Substitution ,Female ,HIV-1 ,Humans ,Maraviroc ,Middle Aged ,Ritonavir ,Antiretroviral Therapy, Highly Active ,Settore MED/17 - MALATTIE INFETTIVE ,law.invention ,chemistry.chemical_compound ,Randomized controlled trial ,law ,Internal medicine ,medicine ,Pharmacology (medical) ,Highly Active ,Dual therapy ,Letters to the Editor ,business.industry ,fibrosis ,Disease progression ,HIV ,Antiretroviral therapy ,Infectious Diseases ,chemistry ,business - Published
- 2019
9. Declining Prevalence of HIV-1 Drug Resistance in Antiretroviral Treatment-exposed Individuals in Western Europe
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De Luca, A, Dunn, D, Zazzi, M, Camacho, R, Torti, C, Fanti, I, Kaiser, R, Sönnerborg, A, Codoñer, Fm, Van Laethem, K, Vandamme, Am, Bansi, L, Ghisetti, V, van de Vijver DA, Asboe, D, Prosperi, Mc, Di Giambenedetto, S, Collaborators: Giacometti A, SEHERE collaboration in C. h. a. i. n., Butini, L, del Gobbo, R, Menzo, S, Tacconi, D, Corbelli, G, Zanussi, S, Monno, L, Punzi, G, Maggiolo, F, Callegaro, A, Calza, L, Pristerà, R, Turconi, P, Mandas, A, Tini, S, Zoncada, A, Paolini, E, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Corsi, P, Galli, L, Di Pietro, M, Bartalesi, F, Colao, G, Tosti, A, Di Biagio, A, Setti, M, Bruzzone, B, Penco, G, Trezzi, M, Orani, A, Pardelli, R, De Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, Monforte, Ad, Cicconi, P, Rusconi, S, Gismondo, Mr, Micheli, V, Biondi, Ml, Gianotti, N, Capetti, A, Meraviglia, P, Boeri, E, Mussini, C, Pecorari, M, Soria, A, Vecchi, L, Santirocchi, M, Brustia, D, Ravanini, P, Dal Bello, F, Romano, N, Mancuso, S, Calzetti, C, Maserati, R, Filice, G, Baldanti, F, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, Rita, De Luca, A, Dunn, D, Zazzi, M, Camacho, R, Torti, C, Fanti, I, Kaiser, R, Sönnerborg, A, Codoñer, F, Van Laethem, K, Vandamme, A, Bansi, L, Ghisetti, V, Van De Vijver, D, Asboe, D, Prosperi, M, Di Giambenedetto, S, Mancuso, S, and Virology
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Male ,Multivariate analysis ,Databases, Factual ,Drug Resistance ,HIV Infections ,Drug resistance ,0302 clinical medicine ,Retrospective Studie ,Risk Factors ,Epidemiology ,Genotype ,pol Gene Products, Human Immunodeficiency Viru ,Odds Ratio ,Prevalence ,Immunology and Allergy ,HIV Infection ,030212 general & internal medicine ,pol Gene Products ,Viral ,Multivariate Analysi ,media_common ,0303 health sciences ,Drug Resistance Prevalence HIV-1 ,Middle Aged ,Resistance mutation ,3. Good health ,Reverse Transcriptase Inhibitor ,Europe ,Infectious Diseases ,Reverse Transcriptase Inhibitors ,epidemiology ,Female ,Multiple ,Human Immunodeficiency Virus ,Human ,Drug ,Adult ,medicine.medical_specialty ,Evolution ,media_common.quotation_subject ,Sexual Behavior ,antiretroviral therapy ,Infectious Disease ,Biology ,Settore MED/17 - MALATTIE INFETTIVE ,Evolution, Molecular ,03 medical and health sciences ,Databases ,SDG 3 - Good Health and Well-being ,Drug Resistance, Multiple, Viral ,medicine ,Humans ,HIV Protease Inhibitor ,Factual ,Retrospective Studies ,030306 microbiology ,Risk Factor ,Molecular ,Retrospective cohort study ,Odds ratio ,HIV Protease Inhibitors ,CD4 Lymphocyte Count ,drug resistance ,genotyping ,HIV-1 ,Multivariate Analysis ,Mutation ,pol Gene Products, Human Immunodeficiency Virus ,Immunology ,Demography - Abstract
HIV-1 drug resistance represents a major obstacle to infection and disease control. This retrospective study analyzes trends and determinants of resistance in antiretroviral treatment (ART)-exposed individuals across 7 countries in Europe. Of 20 323 cases, 80% carried at least one resistance mutation: these declined from 81% in 1997 to 71% in 2008. Predicted extensive 3-class resistance was rare (3.2% considering the cumulative genotype) and peaked at 4.5% in 2005, decreasing thereafter. The proportion of cases exhausting available drug options dropped from 32% in 2000 to 1% in 2008. Reduced risk of resistance over calendar years was confirmed by multivariable analysis. © 2013 The Author.
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- 2013
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10. Genotypic resistance profiles associated with virological failure to darunavir-containing regimens: a cross-sectional analysis
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Sterrantino, G, Zaccarelli, M, Colao, G, Baldanti, F, Di Giambenedetto, S, Carli, T, Maggiolo, F, Zazzi, M, Giacometti, A, Butini, L, Del Gobbo, R, Bagnarelli, P, Tacconi, D, Corbelli, G, Zanussi, S, Monno, L, Punzi, G, Callegaro, A, Calza, L, Re, MC, Pristera, R, Turconi, P, Mandas, A, Tini, S, Zoncada, A, Paolini, E, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Corsi, P, Galli, L, Di Pietro, M, Bartalesi, F, Tosti, A, Di Biagio, A, Setti, M, Bruzzone, B, di Biagio, A, Penco, G, Trezzi, M, Orani, A, Pardelli, R, Arcidiacono, I, Degiuli, A, de Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, Cicconi, P, Rusconi, S, Gismondo, MR, Micheli, V, Biondi ML, Gianotti, N, Capetti, A, Meraviglia, P, Boeri, E, Mussini, C, Pecorari, M, Soria, A, Vecchi, L, Gerardo, AO, Santirocchi, M, Brustia, D, Maggiore, AO, Ravanini, P, Bello, FD, Romano, N, MANCUSO, Salvatrice, Calzetti, C, Maserati, R, Filice, G, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, R, Vatteroni, L, Vivarelli, A, Nerli, A, Lenzi, L, Magnani, G, Ortolani, P, Andreoni, M, Palamara, G, Fimiani, C, Palmisano, L, di Giambenedetto, S, Colafigli, M, Vullo, V, Turriziani, O, Montano, M, Antinori, A, Dentone, C, Gonnelli, A, de Luca, A, Palumbo, M, Ghisetti, V, Bonora, S, Foglie, PD, Rossi, C, Mondino, V, Malena, M, Grossi, P, Seminari, E, Poletti, F., Sterrantino, G, Zaccarelli, M, Colao, G, Baldanti, F, Di Giambenedetto, S, Carli, T, Maggiolo, F, Zazzi, M, Giacometti, A, Butini, L, Del Gobbo, R, Bagnarelli, P, Tacconi, D, Corbelli, G, Zanussi, S, Monno, L, Punzi, G, Callegaro, A, Calza, L, Re, MC, Pristera, R, Turconi, P, Mandas, A, Tini, S, Zoncada, A, Paolini, E, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Corsi, P, Galli, L, Di Pietro, M, Bartalesi, F, Tosti, A, Di Biagio, A, Setti, M, Bruzzone, B, di Biagio, A, Penco, G, Trezzi, M, Orani, A, Pardelli, R, Arcidiacono, I, Degiuli, A, de Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, Cicconi, P, Rusconi, S, Gismondo, MR, Micheli, V, Biondi ML, Gianotti, N, Capetti, A, Meraviglia, P, Boeri, E, Mussini, C, Pecorari, M, Soria, A, Vecchi, L, Gerardo, AO, Santirocchi, M, Brustia, D, Maggiore, AO, Ravanini, P, Bello, FD, Romano, N, Mancuso, S, Calzetti, C, Maserati, R, Filice, G, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, R, Vatteroni, L, Vivarelli, A, Nerli, A, Lenzi, L, Magnani, G, Ortolani, P, Andreoni, M, Palamara, G, Fimiani, C, Palmisano, L, di Giambenedetto, S, Colafigli, M, Vullo, V, Turriziani, O, Montano, M, Antinori, A, Dentone, C, Gonnelli, A, de Luca, A, Palumbo, M, Ghisetti, V, Bonora, S, Foglie, PD, Rossi, C, Mondino, V, Malena, M, Grossi, P, Seminari, E, and Poletti, F
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Male ,Time Factors ,Cross-sectional study ,Human immunodeficiency virus (HIV) ,Drug Resistance ,HIV Infections ,Drug resistance ,medicine.disease_cause ,Cohort Studies ,Antiretroviral Therapy, Highly Active ,Ritonavir-boosted darunavir ,Genotype ,HIV Infection ,Treatment Failure ,Viral ,Genotypic resistance ,Darunavir ,Sulfonamides ,General Medicine ,Middle Aged ,Virological failure ,Infectious Diseases ,Female ,Human ,medicine.drug ,Adult ,Microbiology (medical) ,Logistic Model ,Time Factor ,Antiretroviral Therapy ,Settore MED/17 - MALATTIE INFETTIVE ,Sulfonamide ,Drug Resistance, Viral ,medicine ,Humans ,Highly Active ,Protease inhibitors ,Cross-Sectional Studies ,HIV Protease Inhibitors ,HIV-1 ,Logistic Models ,Mutation ,HIV Protease Inhibitor ,Cross-Sectional Studie ,business.industry ,Antiretroviral therapy ,Virology ,Protease inhibitor ,Cohort Studie ,business - Abstract
Introduction: This study aimed at defining protease (PR) resistance mutations associated with darunavir (DRV) failure and PR resistance evolution at DRV failure in a large database of treatment-experienced human immunodeficiency virus (HIV) patients. Results: Overall, 1,104 patients were included: 118 (10.7%) failed at a median observation time of 16 months. The mean number of PR mutations at baseline was 2.7, but it was higher in patients who subsequently failed DRV. In addition, the number of PR mutations increased at failure. The increase in the mean number of mutations was completely related to mutations considered to be associated with DRV resistance following the indications of the main DRV clinical trials. Discussion The higher statistical difference at baseline between failing versus non-failing patients was observed for the V32I and I84V mutations. At DRV failure, the major increase was still observed for V32I; I54L, V11I, T74P and I50V also increased. Despite the increment in the mean number of mutations per patient between baseline and failure, in 21 patients (17.8%) at baseline and 36 (30.5%) at failure, no PR mutation was detected. Conclusion: The HIV-DB interpretation algorithm identified few patients with full DRV resistance at baseline and few patients developed full resistance at DRV failure, indicating that complete resistance to DRV is uncommon. © Springer-Verlag 2011.
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- 2012
11. No pol mutation is associated independently with the lack of immune recovery in patients infected with HIV and failing antiretroviral therapy
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Gianotti, N1, Galli, L, Zazzi, M, Ghisetti, V, Bonora, S, Micheli, V, Meraviglia, P, Corsi, P, Bruzzone, B, Menzo, S, Di Giambenedetto, S, De Luca, A, Filice, G, Penco, G, Castagna, A, Collaborators Giacometti A, ARCA database i. n. i. t. i. a. t. i. v. e., Butini, L, del Gobbo, R, Tacconi, D, Corbelli, G, Zanussi, S, Monno, L, Punzi, G, Maggiolo, F, Callegaro, A, Calza, L, Re, Mc, Pristerà, R, Turconi, P, Mandas, A, Tini, S, Carnevale, G, Paolini, E, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Di Pietro, M, Bartalesi, F, Colao, G, Tosti, A, Di Biagio, A, Setti, M, Trezzi, M, Orani, A, Pardelli, R, De Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, Gianotti, N, Cicconi, P, Rusconi, S, Gismondo, Mr, Biondi, Ml, Capetti, A, Boeri, E, Pecorari, M, Mussini, C, Santirocchi, M, Brustia, D, Ravanini, P, Dal Bello, F, Romano, N, Mancuso, S, Calzetti, C, Maserati, R, Baldanti, F, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, R, Vatteroni, L, Vivarelli, A, Nerli, A, Lenzi, L, Magnani, G, Ortolani, P, Andreoni, M, Palamara, G, Fimiani, C, Palmisano, L, Antinori, A, Vullo, Vincenzo, Turriziani, O, Perno, Cf, Montano, M, Cenderello, G, Gonnelli, A, Romano, L, Palumbo, M, Delle Foglie, P, Rossi, C, Poletti, F, Mondino, V, Malena, M, Lattuada, E., Gianotti, N, Galli, L, Zazzi, M, Ghisetti, V, Bonora, S, Micheli, V, Meraviglia, P, Corsi, P, Bruzzone, B, Menzo, S, Di Giambenedetto, S, De Luca, A, Filice, G, Penco, G, Castagna, A, Mancuso, S, Gianotti N, Galli L, Zazzi M, Ghisetti V, Bonora S, Micheli V, Meraviglia P, Corsi P, Bruzzone B, Menzo S, Di Giambenedetto S, De Luca A, Filice G, Penco G, Castagna A, Giacometti A, Butini L, del Gobbo R, Tacconi D, Corbelli G, Zanussi S, Monno L, Punzi G, Maggiolo F, Callegaro A, Calza L, Re MC, Pristerà R, Turconi P, Mandas A, Tini S, Carnevale G, Paolini E, Amadio G, Sighinolfi L, Zuccati G, Morfini M, Manetti R, Di Pietro M, Bartalesi F, Colao G, Tosti A, Di Biagio A, Setti M, Trezzi M, Orani A, Pardelli R, De Gennaro M, Chiodera A, Scalzini A, Palvarini L, Almi P, Todaro G, Cicconi P, Rusconi S, Gismondo MR, Biondi ML, Capetti A, Boeri E, Pecorari M, Mussini C, Santirocchi M, Brustia D, Ravanini P, Dal Bello F, Romano N, Mancuso S, Calzetti C, Maserati R, Baldanti F, Francisci D, Parruti G, Polilli E, Sacchini D, Martinelli C, Consolini R, Vatteroni L, Vivarelli A, Nerli A, Lenzi L, Magnani G, Ortolani P, Andreoni M, Palamara G, Fimiani C, Palmisano L, Antinori A, Vullo V, Turriziani O, Perno CF, Montano M, Cenderello G, Gonnelli A, Romano L, Palumbo M, Delle Foglie P, Rossi C, Poletti F, Mondino V, Malena M, Lattuada E., Gianotti, Nicola, Galli, Laura, Zazzi, Maurizio, Ghisetti, Valeria, Bonora, Stefano, Micheli, Valeria, Meraviglia, Paola, Corsi, Paola, Bruzzone, Bianca, Menzo, Stefano, Di Giambenedetto, Simona, De Luca, Andrea, Filice, Gaetano, Penco, Giovanni, and Castagna, Antonella
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Male ,HIV Infections ,Drug resistance ,Logistic regression ,Resistance to nucleoside reverse transcriptase inhibitor ,CD4+ T-lymphocyte ,Retrospective Studie ,Immunopathology ,Antiretroviral Therapy, Highly Active ,Resistance to non-nucleoside reverse transcriptase inhibitor ,genetics ,Resistance to protease inhibitor ,HIV Infection ,resistance to nucleoside reverse transcriptase inhibitors ,Viral ,Sida ,resistance to protease inhibitors ,biology ,Reverse-transcriptase inhibitor ,Viral Load ,Genes, pol ,drug therapy/immunology/virology ,Reverse Transcriptase Inhibitor ,Infectious Diseases ,Treatment Outcome ,resistance to non-nucleoside reverse transcriptase inhibitors ,Reverse Transcriptase Inhibitors ,Female ,Viral load ,medicine.drug ,Human ,pol ,Anti-HIV Agents ,Antiretroviral Therapy ,Viremia ,Infectious Disease ,Settore MED/17 - MALATTIE INFETTIVE ,pharmacology/therapeutic use ,Acquired immunodeficiency syndrome (AIDS) ,Virology ,Drug Resistance, Viral ,medicine ,Humans ,Highly Active ,Retrospective Studies ,pharmacology/therapeutic use, Antiretroviral Therapy ,Highly Active, CD4 Lymphocyte Count, Drug Resistance ,genetics, Female, Genes ,pol, HIV Infections ,drug therapy/immunology/virology, HIV-1 ,drug effects/enzymology/genetics, Humans, Male, Mutation, Retrospective Studies, Reverse Transcriptase Inhibitors ,therapeutic use, Treatment Outcome, Viral Load ,drug resistance ,Anti-HIV Agent ,biology.organism_classification ,medicine.disease ,CD4 Lymphocyte Count ,Genes ,drug effects/enzymology/genetics ,therapeutic use ,Mutation ,CD4+ T-lymphocytes ,HIV-1 - Abstract
An investigation was undertaken to determine whether specific pol mutations hinder long-term immune recovery regardless of virological response. In total, 826 patients with >50 HIV RNA copies/ml, who underwent genotypic resistance testing between 1 January 2000 and 31 December 2003 after >3 years of antiretroviral treatment, and were followed up for >3 years after genotypic resistance testing, were analyzed retrospectively. The outcome of the study was the lack of immune recovery after >3 years of follow-up, defined as a slope by linear regression 50 copies/ml divided by the number of HIV RNA measurements during follow-up. Logistic regression was used for univariable and multivariable analysis. Median (Q1, Q3) values at baseline were the following: age 40 (37, 45) years, years on antiretroviral therapy 4.45 (3.65, 5.47), HIV RNA 3.91 (3.39, 4.53) log 10 copies/ml, CD4+ T-cell 358 (211, 524)/μl. After 3.13 years of follow-up, 375 patients (45.4%) showed a lack of immune recovery. The risk of lack of immune recovery increased independently with increasing baseline CD4+ counts (OR=1.104 per 50-cell increase, 95% CI=1.069-1.142, P
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- 2011
12. A novel methodology for large-scale phylogeny partition
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Prosperi, Mattia C. F., Ciccozzi, Massimo, Fanti, Iuri, Saladini, Francesco, Pecorari, Monica, Borghi, Vanni, Di Giambenedetto, Simona, Bruzzone, Bianca, Capetti, Amedeo, Vivarelli, Angela, Rusconi, Stefano, Maria Carla, Re, Gismondo, Maria Rita, Sighinolfi, Laura, Gray, Rebecca R., Salemi, Marco, Zazzi, Maurizio, De Luca, Andrea, Giacometti, A, Butini, L, Menzo, S, Tacconi, D, Corbelli, G, Zanussi, S, Monno, L, Punzi, G, Maggiolo, F, Callegaro, A, Calza, L, Re, Mc, Pristerà, R, Turconi, P, Mandas, A, Tini, S, Zoncada, A, Paolini, E, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Corsi, P, Galli, L, Di Pietro, M, Bartalesi, F, Colao, G, Tosti, A, Di Biagio, A, Setti, M, Bruzzone, B, Penco, G, Trezzi, M, Orani, A, Pardelli, R, De Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, Cicconi, P, Rusconi, S, Gismondo, Mr, Micheli, V, Biondi, Ml, Gianotti, N, Capetti, A, Meraviglia, P, Boeri, E, Mussini, C, Pecorari, M, Soria, A, Vecchi, L, Santirocchi, M, Brustia, D, Ravanini, P, Dal Bello, F, Romano, N, Mancuso, S, Calzetti, C, Maserati, R, Filice, G, Baldanti, F, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, R, Vatteroni, L, Vivarelli, A, Dionisio, D, Nerli, A, Lenzi, L, Magnani, G, Ortolani, P, Andreoni, M, Palamara, G, Fimiani, C, Palmisano, L, De Luca, A, Fadda, G, Vullo, Vincenzo, Turriziani, Ombretta, Montano, M, Cenderello, G, Gonnelli, A, Palumbo, M, Ghisetti, V, Bonora, S, Delle Foglie, P, Rossi, C, Grossi, P, Seminari, E, Poletti, F, Mondino, V, Malena, M, Lattuada, E., Prosperi MC, Ciccozzi M, Fanti I, Saladini F, Pecorari M, Borghi V, Di Giambenedetto S, Bruzzone B, Capetti A, Vivarelli A, Rusconi S, Re MC, Gismondo MR, Sighinolfi L, Gray RR, Salemi M, Zazzi M, De Luca A, ARCA collaborative group., Prosperi, M, Ciccozzi, M, Fanti, I, Saladini, F, Pecorari, M, Borghi, V, Di Giambenedetto, S, Bruzzone, B, Capetti, A, Vivarelli, A, Rusconi, S, Re, M, Gismondo, M, Sighinolfi, L, Gray, R, Salemi, M, Zazzi, M, De Luca, A, and Mancuso, S
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Genetics and Molecular Biology (all) ,Male ,pol ,Theoretical computer science ,Inference ,Gene Products, pol ,General Physics and Astronomy ,HIV Infections ,Biology ,Network topology ,Settore MED/17 - MALATTIE INFETTIVE ,Biochemistry ,Article ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,Physics and Astronomy (all) ,0302 clinical medicine ,Search algorithm ,phylogenetic analysis ,virus transmission ,Gene Products ,Humans ,HIV Infection ,030212 general & internal medicine ,Phylogeny ,030304 developmental biology ,Algorithms ,Classification ,Female ,HIV-1 ,Biochemistry, Genetics and Molecular Biology (all) ,Chemistry (all) ,Genetics ,0303 health sciences ,Multidisciplinary ,Phylogenetic tree ,Node (networking) ,HIV ,General Chemistry ,Partition (database) ,Algorithm ,Identification (information) ,Transmission (telecommunications) ,METHODOLOGY ,Human - Abstract
Understanding the determinants of virus transmission is a fundamental step for effective design of screening and intervention strategies to control viral epidemics. Phylogenetic analysis can be a valid approach for the identification of transmission chains, and very-large data sets can be analysed through parallel computation. Here we propose and validate a new methodology for the partition of large-scale phylogenies and the inference of transmission clusters. This approach, on the basis of a depth-first search algorithm, conjugates the evaluation of node reliability, tree topology and patristic distance analysis. The method has been applied to identify transmission clusters of a phylogeny of 11,541 human immunodeficiency virus-1 subtype B pol gene sequences from a large Italian cohort. Molecular transmission chains were characterized by means of different clinical/demographic factors, such as the interaction between male homosexuals and male heterosexuals. Our method takes an advantage of a flexible notion of transmission cluster and can become a general framework to analyse other epidemics. © 2011 Macmillan Publishers Limited. All rights reserved.
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- 2011
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13. Detection of drug resistance mutations at low plasma HIV-1 RNA load in a European multicentre cohort study
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Prosperi, Mc1, Mackie, N, Di Giambenedetto, S, Zazzi, M, Camacho, R, Fanti, I, Torti, C, Sönnerborg, A, Kaiser, R, Codoñer, Fm, Van Laethem, K, Bansi, L, van de Vijver DA, Geretti, Am, De Luca, A, Giacometti A, SEHERE c. o. n. s. o. r. t. i. u. m., Butini, L, del Gobbo, R, Menzo, S, Tacconi, D, Corbelli, G, Zanussi, S, Monno, L, Punzi, G, Maggiolo, F, Callegaro, A, Calza, L, Carla Re, M, Pristerà, R, Turconi, P, Mandas, A, Tini, S, Zoncada, A, Paolini, E, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Corsi, P, Galli, L, Di Pietro, M, Bartalesi, F, Colao, G, Tosti, A, Di Biagio, A, Setti, M, Bruzzone, B, Penco, G, Trezzi, M, Orani, A, Pardelli, R, De Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, d'Arminio Monforte, A, Cicconi, P, Rusconi, S, Gismondo, Mr, Micheli, V, Biondi, Ml, Gianotti, N, Capetti, A, Meraviglia, P, Boeri, E, Mussini, C, Pecorari, M, Soria, A, Vecchi, L, Santirocchi, M, Brustia, D, Ravanini, P, Bello, Fd, Romano, N, Mancuso, S, Calzetti, C, Maserati, R, Filice, G, Baldanti, F, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, R, Vatteroni, L, Vivarelli, A, Dionisio, D, Nerli, A, Lenzi, L, Magnani, G, Ortolani, P, Andreoni, M, Palamara, G, Fimiani, C, Palmisano, L, Fadda, G, Vullo, Vincenzo, Turriziani, O, Montano, M, Cenderello, G, Gonnelli, A, Palumbo, M, Ghisetti, V, Bonora, S, Foglie, Pd, Rossi, C, Grossi, P, Seminari, E, Poletti, F, Mondino, V, Malena, M, Lattuada, E, Lengauer, T, Däumer, M, Hoffmann, D, Schülter, E, Müller, C, Oette, M, Reuter, S, Esser, S, Fätkenheuer, G, Rockstroh, J, Incardona, F, Rosen Zvi, M, Clotet, B, Thalme, A, Svedhem, V, Bratt, G, Gargiulo, F, Lapadula, G, Manca, N, Paraninfo, G, Quiros Roldan, E, Carosi, G, Castelnuovo, F, Vandamme, Am, Van Wijngaerden, E, Ainsworth, J, Anderson, J, Babiker, A, Dunn, D, Easterbrook, P, Fisher, M, Gazzard, B, Garrett, N, Gilson, R, Gompels, M, Hill, T, Johnson, M, Leen, C, Orkin, C, Phillips, A, Pillay, D, Porter, K, Post, F, Sabin, C, Sadiq, T, Schwenk, A, Walsh, J, Delpech, V, Palfreeman, A, Glabay, A, Lynch, J, Hand, J, de Souza, C, Perry, N, Tilbury, S, Churchill, D, Nelson, M, Waxman, M, Mandalia, S, Kall, M, Korat, H, Taylor, C, Ibrahim, F, Campbell, L, James, L, Brima, N, Williams, I, Youle, M, Lampe, F, Smith, C, Grabowska, H, Chaloner, C, Puradiredja, Di, Weber, J, Ramzan, F, Carder, M, Wilson, A, Dooley, D, Asboe, D, Pozniak, A, Cameron, S, Cane, P, Chadwick, D, Clark, D, Collins, S, Lazarus, L, Dolling, D, Fearnhill, E, Castro, H, Coughlin, K, Zuckerman, M, Booth, C, Goldberg, D, Hale, A, Kaye, S, Kellam, P, Leigh Brown, A, Smit, E, Templeton, K, Tilston, P, Tong, W, Zhang, H, Ushiro Lumb, I, Oliver, T, Bibby, D, Mitchell, S, Mbisa, T, Wildfire, A, Tandy, R, Shepherd, J, Maclean, A, Bennett, D, Hopkins, M, Garcia Diaz, A, Kirk, S, Sloot, P. M., Virology, Prosperi, M, Mackie, N, di Giambenedetto, S, Zazzi, M, Camacho, R, Fanti, I, Torti, C, Sönnerborg, A, Kaiser, R, Codoñer, F, van laethem, K, Bansi, L, van de Vijver, D, Geretti, A, de luca, A, and Mancuso, S
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Male ,Drug Resistance ,HIV Infections ,Drug resistance ,Cohort Studies ,0302 clinical medicine ,Genotype ,HIV Infection ,Pharmacology (medical) ,030212 general & internal medicine ,Viral ,0303 health sciences ,Proteolytic enzymes ,Genotypic testing ,HIV ,Viral load ,Adult ,Anti-HIV Agents ,CD4 Lymphocyte Count ,Europe ,Female ,HIV-1 ,Humans ,RNA, Viral ,Viral Proteins ,Drug Resistance, Viral ,Mutation, Missense ,Viral Load ,Pharmacology ,Infectious Diseases ,3. Good health ,Cohort ,Cohort study ,Human ,Microbiology (medical) ,Biology ,Settore MED/17 - MALATTIE INFETTIVE ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,Viral Protein ,030306 microbiology ,Anti-HIV Agent ,Virology ,Reverse transcriptase ,Regimen ,genotypic testing ,viral load ,Immunology ,Mutation ,RNA ,Missense ,Cohort Studie - Abstract
Background and objectives: Guidelines indicate a plasma HIV-1 RNA load of 500-1000 copies/mL as the minimal threshold for antiretroviral drug resistance testing. Resistance testing at lower viral load levels may be useful to guide timely treatment switches, although data on the clinical utility of this remain limited. We report here the influence of viral load levels on the probability of detecting drug resistance mutations (DRMs) and other mutations by routine genotypic testing in a large multicentre European cohort, with a focus on tests performed at a viral load
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- 2011
14. Low Rate of Virological Failure and Maintenance of Susceptibility to HIV-1 Protease Inhibitors with First-Line Lopinavir/Ritonavir-Based Antiretroviral Treatment in Clinical Practice
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Prosperi, Mc, Zazzi, M, Punzi, G, Monno, L, Colao, G, Corsi, P, Di Giambenedetto, S, Meini, G, Ghisetti, V, Bonora, S, Pecorari, M, Gismondo, Mr, Bagnarelli, P, Carli, T, De Luca, A, ARCA Collaborative Group, Giacometti, A, Butini, L, del Gobbo, R, Menzo, S, Tacconi, D, Corbelli, G, Zanussi, S, Maggiolo, F, Callegaro, A, Calza, L, Re, Mc, Raffaele, P, Turconi, P, Mandas, A, Tini, S, Zoncada, A, Paolini, E, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Galli, L, Di Pietro, M, Bartalesi, F, Tosti, A, Di Biagio, A, Setti, M, Bruzzone, B, Penco, G, Trezzi, M, Orani, A, Pardelli, R, De Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, Monforte, A, Cicconi, P, Rusconi, S, Micheli, V, Biondi, Ml, Gianotti, N, Capetti, A, Meraviglia, P, Boeri, E, Mussini, C, Soria, A, Vecchi, L, Santirocchi, M, Brustia, D, Ravanini, P, Dal Bello, F, Romano, N, Mancuso, S, Calzetti, C, Maserati, R, Filice, G, Baldanti, F, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, Rita, Clinic of Infectious Diseases, Università cattolica del Sacro Cuore [Roma] (Unicatt), Molecular Biology, Microbiology and Virology, Bari University Hospital, Clinical Infectious Diseases, Careggi University Hospital, Unit of Infectious Diseases, Catholic Universisty of Sacred Heart, A. Savoia Hospital, infectiuos diseases, Università degli studi di Torino (UNITO), Modena University Hospital, L. Sacco University Hospital, Ancona University Hospital, Grosseto General Hospital, Institute of Infectious Diseases, Sacro Cuore Catholic University, Infectious Diseases Unit, University Hospital of Siena, Prosperi, M, Zazzi, M, Punzi, G, Monno, L, Colao, G, Corsi, P, Di Giambenedetto, S, Meini, G, Ghisetti, V, Bonora, S, Pecorari, M, Gismondo, M, Bagnarelli, P, Carli, T, De Luca, A, Mancuso, S, Prosperi MC, Zazzi M, Punzi G, Monno L, Colao G, Corsi P, Di Giambenedetto S, Meini G, Ghisetti V, Bonora S, Pecorari M, Gismondo MR, Bagnarelli P, Carli T, De Luca A, ARCA Collaborative Group [.., Giacometti A, Butini L, del Gobbo R, Menzo S, Tacconi D, Corbelli G, Zanussi S, Maggiolo F, Callegaro A, Calza L, Re MC, Raffaele P, Turconi P, Mandas A, Tini S, Zoncada A, Paolini E, Amadio G, Sighinolfi L, and ]
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Male ,Lopinavir/ritonavir ,HIV Infections ,boosted protease inhibitor ,Lopinavir ,Cohort Studies ,0302 clinical medicine ,Antiretroviral Therapy, Highly Active ,virologic failure ,HIV Infection ,Treatment Failure ,030212 general & internal medicine ,Pyrimidinone ,0303 health sciences ,education.field_of_study ,lopinavir/ritonavir ,Viral Load ,Resistance mutation ,first-line antiretroviral therapy ,Reverse Transcriptase Inhibitor ,3. Good health ,Treatment Outcome ,Infectious Diseases ,RNA, Viral ,Reverse Transcriptase Inhibitors ,Medicine ,Drug Therapy, Combination ,Female ,Survival Analysi ,Viral load ,Human ,medicine.drug ,Anti-HIV Agents ,Population ,Pyrimidinones ,Settore MED/17 - MALATTIE INFETTIVE ,Emtricitabine ,human immunodeficiency virus type 1 ,03 medical and health sciences ,Virology ,Drug Resistance, Viral ,antiretroviral drug resistance ,medicine ,Humans ,Protease inhibitor (pharmacology) ,education ,HIV Protease Inhibitor ,Ritonavir ,030306 microbiology ,business.industry ,Anti-HIV Agent ,HIV Protease Inhibitors ,Survival Analysis ,HIV-1 ,Cohort Studie ,business - Abstract
Protease inhibitor (PI)-resistant HIV-1 has hardly ever been detected at failed boosted PI-based first-line antiretroviral regimens in clinical trials. However, this phenomenon has not been investigated in clinical practice. To address this gap, data from patients starting a first-line lopinavir/ritonavir (LPV/rtv)-based therapy with available baseline HIV-1 RNA load, a viral genotype and follow-up viral load after 3 and 6 months of treatment were extracted from the Italian Antiretroviral Resistance Cohort Analysis (ARCA) observational database. Based on survival analysis, 39 (7.1%) and 43 (7.8%) of the 548 examined patient cases had an HIV-1 RNA >500 and >50 copies/ml, respectively, after 6 months of treatment. Cox proportional hazard models detected baseline HIV-1 RNA (RH 1.79, 95%CI 1.10-2.92 per 1 - log10 increase, P = 0.02) and resistance to the nucleoside backbone (RH 1.04, 95%CI 1.02-1.06 per 10-point increase using the Stanford HIVdb algorithm, P < 0.001) as independent predictors of HIV-1 RNA at >500 copies/ml, but not at the >50 copies/ml cutoff criteria. Higher baseline viral load, older patient age, heterosexual route of infection and use of tenofovir/emtricitabine were predictors of failure at month 3 using the 50-copy and/or 500-copy threshold. Resistance to LPV/rtv did not occur or increase in any of the available 36 follow-up HIV-1 genotypes. Resistance to the nucleoside backbone (M184V) developed in four cases. Despite the likely differences in patient population and adherence, both the low rate of virological failure and the lack of development of LPV/rtv resistance documented in clinical trials are thus confirmed in clinical practice. J. Med. Virol. 82:1996-2003, 2010. © 2010 Wiley-Liss, Inc.
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- 2010
15. Rules-based HIV-1 genotypic resistance interpretation systems predict 8 week and 24 week virological antiretroviral treatment outcome and benefit from drug potency weighting
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Zazzi, M, Prosperi, M, Vicenti, I, Di Giambenedetto, S, Callegaro, A, Bruzzone, B, Baldanti, F, Gonnelli, A, Boeri, E, Paolini, E, Rusconi, S, Giacometti, A, Maggiolo, F, Menzo, S, De Luca, A, ARCA Collaborative Group, Butini, L, del Gobbo, R, Tacconi, D, Corbelli, G, Zanussi, S, Monno, L, Punzi, G, Calza, L, Re, Mc, Pristerà, R, Turconi, P, Mandas, A, Tini, S, Carnevale, G, Amadio, G, Sighinolfi, L, Zuccati, G, Morfini, M, Manetti, R, Corsi, P, Galli, L, Di Pietro, M, Bartalesi, F, Colao, G, Tosti, A, Di Biagio, A, Setti, M, Penco, G, Trezzi, M, Orani, A, Pardelli, R, De Gennaro, M, Chiodera, A, Scalzini, A, Palvarini, L, Almi, P, Todaro, G, Cicconi, P, Gismondo, Mr, Micheli, V, Biondi, Ml, Gianotti, N, Capetti, A, Meraviglia, P, Mussini, C, Pecorari, M, Santirocchi, M, Brustia, D, Ravanini, P, Dal Bello, F, Romano, N, Mancuso, S, Calzetti, C, Maserati, R, Filice, G, Francisci, D, Parruti, G, Polilli, E, Sacchini, D, Martinelli, C, Consolini, Rita, Zazzi, M, Prosperi, M, Vicenti, I, Di Giambenedetto, S, Callegaro, A, Bruzzone, B, Baldanti, F, Gonnelli, A, Boeri, E, Paolini, E, Rusconi, S, Giacometti, A, Maggiolo, F, Menzo, S, De Luca, A, Mancuso, S, Zazzi M, Prosperi M, Vicenti I, Di Giambenedetto S, Callegaro A, Bruzzone B, Baldanti F, Gonnelli A, Boeri E, Paolini E, Rusconi S, Giacometti A, Maggiolo F, Menzo S, De Luca A, ARCA Collaborative Group: [.., Butini L, del Gobbo R, Tacconi D, Corbelli G, Zanussi S, Monno L, Punzi G, Calza L, Re M C, Pristerà R, Turconi P, Mandas A, Tini S, and ]
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Male ,interpretation system ,HIV Infections ,Drug resistance ,Logistic regression ,Retrospective Studie ,HIV Infection ,Pharmacology (medical) ,Microbial Sensitivity Test ,Middle Aged ,Prognosis ,genotype, drug resistance, algorithm ,Algorithm ,Treatment Outcome ,Infectious Diseases ,Italy ,RNA, Viral ,Female ,Cohort study ,Human ,Microbiology (medical) ,Adult ,medicine.medical_specialty ,Genotype ,Logistic Model ,Anti-HIV Agents ,Prognosi ,antiretroviral ,Microbial Sensitivity Tests ,Internal medicine ,medicine ,Potency ,Animals ,Humans ,Retrospective Studies ,Pharmacology ,Receiver operating characteristic ,business.industry ,Animal ,Anti-HIV Agent ,Retrospective cohort study ,Odds ratio ,genotype ,drug potency weighting ,Weighting ,Logistic Models ,ROC Curve ,Immunology ,HIV-1 ,business - Abstract
Objectives: To test retrospectively the ability of four freely available rules-based expert systems to predict short- and medium-term virological outcome following an antiretroviral treatment switch in pre-treated HIV-1 patients. Methods: The HIV-1 genotype interpretation systems (GISs) HIVdb, ANRS, Rega and AntiRetroScan were tested for their accuracy in predicting response to highly active antiretroviral therapy using 8 week (n = 765) and 24 week (n = 634) follow-up standardized treatment change episodes extracted from the Italian Antiretroviral Resistance Cohort Analysis (ARCA) database. A genotypic sensitivity score (GSS) was derived for each genotype-treatment pair for the different GISs and tested as a predictor of virological treatment outcome by univariable and multivariable logistic regression as well as by receiver operating characteristic curve analysis. The two systems implementing drug potency weights (AntiRetroScan and Rega) were evaluated with and without this correction factor. Results: All four GSSs were strong predictors of virological treatment outcome at both 8 and 24 weeks after adjusting for baseline viro-immunological parameters and previous drug exposure (odds ratios ranging from 2.04 to 2.43 per 1 unit GSS increase; P < 0.001 for all the systems). The accuracy of AntiRetroScan and Rega was significantly increased by drug potency weighting with respect to the unweighted versions (P ≤ 0.001). HIVdb and ANRS also increased their performance with the same drug potency weighting adopted by AntiRetroScan and Rega, respectively (P < 0.001 for both analyses). Conclusions: Currently available GISs are valuable tools for assisting antiretroviral treatment choices. Drug potency weighting can increase the accuracy of all systems. © The Author 2009. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.
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- 2009
16. A Prognostic Model for Estimating the Time to Virologic Failure in HIV-1 Infected Patients Undergoing a New Combination Antiretroviral Therapy Regimen
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PProsperi MC, Di Giambenedetto S, Fanti I, Meini G, Bruzzone B, Callegaro A, Penco G, Bagnarelli P, Micheli V, Paolini E, Di Biagio A, Ghisetti V, Di Pietro M, Zazzi M, De Luca A, Giacometti A, Butini L, del Gobbo R, Menzo S, Tacconi D, Corbelli G, Zanussi S, Monno L, Punzi G, Maggiolo F, CALZA, LEONARDO, RE, MARIA CARLA, Pristerà R, Turconi P, Mandas A, Tini S, Carnevale G, Amadio G, Sighinolfi L, Zuccati G, Morfini M, Manetti R, Galli L, Bartalesi F, Colao G, Tosti A, Setti M, Trezzi M, Orani A, Pardelli R, De Gennaro M, Chiodera A, Scalzini A, Palvarini L, Almi P, Todaro G, Gianotti N, Cicconi P, Rusconi S, Gismondo MR, Biondi ML, Capetti A, Meraviglia P, Boeri E, Pecorari M, Mussini C, Santirocchi M, Brustia D, Ravanini P, Dal Bello F, Romano N, Mancuso S, Calzetti C, Maserati R, Baldanti F, Francisci D, Parruti G, Polilli E, Sacchini D, Martinelli C, Consolini R, Vatteroni L, Vivarelli A, Nerli A, Lenzi L, Magnani G, Ortolani P, Andreoni M, Palamara G, Fimiani C, Palmisano L, Antinori A, Vullo V, Turriziani O, Perno CF, Montano M, Cenderello G, Gonnelli A, Romano L, Palumbo M, Bonora S, Delle Foglie P, Rossi C, Poletti F, Mondino V, Malena M, Lattuada E., PProsperi MC, Di Giambenedetto S, Fanti I, Meini G, Bruzzone B, Callegaro A, Penco G, Bagnarelli P, Micheli V, Paolini E, Di Biagio A, Ghisetti V, Di Pietro M, Zazzi M, De Luca A, Giacometti A, Butini L, del Gobbo R, Menzo S, Tacconi D, Corbelli G, Zanussi S, Monno L, Punzi G, Maggiolo F, Calza L, Re MC, Pristerà R, Turconi P, Mandas A, Tini S, Carnevale G, Amadio G, Sighinolfi L, Zuccati G, Morfini M, Manetti R, Galli L, Bartalesi F, Colao G, Tosti A, Setti M, Trezzi M, Orani A, Pardelli R, De Gennaro M, Chiodera A, Scalzini A, Palvarini L, Almi P, Todaro G, Gianotti N, Cicconi P, Rusconi S, Gismondo MR, Biondi ML, Capetti A, Meraviglia P, Boeri E, Pecorari M, Mussini C, Santirocchi M, Brustia D, Ravanini P, Dal Bello F, Romano N, Mancuso S, Calzetti C, Maserati R, Baldanti F, Francisci D, Parruti G, Polilli E, Sacchini D, Martinelli C, Consolini R, Vatteroni L, Vivarelli A, Nerli A, Lenzi L, Magnani G, Ortolani P, Andreoni M, Palamara G, Fimiani C, Palmisano L, Antinori A, Vullo V, Turriziani O, Perno CF, Montano M, Cenderello G, Gonnelli A, Romano L, Palumbo M, Bonora S, Delle Foglie P, Rossi C, Poletti F, Mondino V, Malena M, Lattuada E., Prosperi, M, Di Giambenedetto, S, Fanti, I, Meini, G, Bruzzone, B, Callegaro, A, Penco, G, Bagnarelli, P, Micheli, V, Paolini, E, Di Biagio, A, Ghisetti, V, Di Pietro, M, Zazzi, M, De Luca, A, and Mancuso, S
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Oncology ,Male ,Adult ,Anti-HIV Agents ,Cohort Studies ,Drug Therapy, Combination ,Female ,HIV Infections ,HIV-1 ,Humans ,Middle Aged ,Proportional Hazards Models ,Treatment Failure ,Viral Load ,0302 clinical medicine ,ANTIRETROVIRAL THERAPY ,Medicine ,HIV Infection ,030212 general & internal medicine ,0303 health sciences ,Health Policy ,3. Good health ,Computer Science Applications ,Censoring (clinical trials) ,Cohort ,Combination ,lcsh:R858-859.7 ,Viral load ,Human ,Research Article ,Cart ,medicine.medical_specialty ,antiretroviral therapy ,Health Informatics ,Settore MED/17 - MALATTIE INFETTIVE ,lcsh:Computer applications to medicine. Medical informatics ,03 medical and health sciences ,Drug Therapy ,Internal medicine ,Survival analysis ,030306 microbiology ,business.industry ,Proportional hazards model ,ANTIRETROVIRAL DRUGS ,Anti-HIV Agent ,HIV ,GENOTYPES ,Discontinuation ,Regimen ,Immunology ,Proportional Hazards Model ,Cohort Studie ,business - Abstract
Background HIV-1 genotypic susceptibility scores (GSSs) were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART) switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed. Methods We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90th day after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems (Rega, ANRS and HIVdb) and other covariates by means of Cox regression and random survival forests (RSF). Prediction models were validated via the bootstrap and c-index measure. Results The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70), while RSF showed a better performance (c-index≈0.73, p < 0.0001 vs. Cox regression). Variable importance according to RSF was concordant with the Cox hazards. Conclusions GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART.
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- 2011
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17. Effectiveness of antiretroviral regimens containing abacavir with tenofovir in treatment-experienced patients: predictors of virological response and drug resistance evolution in a multi-cohort study
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S, Di Giambenedetto, C, Torti, M, Prosperi, N, Manca, G, Lapadula, G, Paraninfo, N, Ladisa, M, Zazzi, M, Trezzi, P, Cicconi, P, Corsi, P, Nasta, R, Cauda, A, De Luca, A, Gori, Di Giambenedetto, S, Torti, C, Prosperi, M, Manca, N, Lapadula, G, Paraninfo, G, Ladisa, N, Zazzi, M, Trezzi, M, Cicconi, P, Corsi, P, Nasta, P, Cauda, R, and De Luca, A
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Oncology ,Male ,HIV Infections ,Cohort Studies ,Abacavir ,Organophosphonate ,Antiretroviral Therapy, Highly Active ,HIV Infection ,Treatment Failure ,Reverse-transcriptase inhibitor ,Lamivudine ,General Medicine ,Middle Aged ,Viral Load ,Resistance mutation ,Dideoxynucleoside ,Infectious Diseases ,Treatment Outcome ,Female ,Viral load ,medicine.drug ,Human ,Microbiology (medical) ,Adult ,medicine.medical_specialty ,Anti-HIV Agents ,virological response ,Mutation, Missense ,Organophosphonates ,Settore MED/17 - MALATTIE INFETTIVE ,Viral Proteins ,Internal medicine ,Drug Resistance, Viral ,medicine ,Viral Protein ,Humans ,Tenofovir ,drug resistance ,Nucleoside analogue ,business.industry ,Adenine ,abacavir ,Anti-HIV Agent ,Virology ,Dideoxynucleosides ,Regimen ,Concomitant ,HIV-1 ,Cohort Studie ,business - Abstract
Background: : In treatment-naïve patients, a combination antiretroviral therapy (cART) containing tenofovir (TDF) and abacavir (ABC) with lamivudine leads to unacceptably high virological failure rates with frequent selection of reverse transcriptase mutations M184V and K65R. We explored the efficacy of at least 16 weeks of ABC + TDF-containing cART regimens in 307 antiretroviral-experienced HIV-1-infected individuals included in observational databases. Methods: : Virological failure was defined as an HIV RNA > 400 copies/ml after at least 16 weeks of treatment. Patients had received a median of three prior cART regimens. Of these, 76% concomitantly received a potent or high genetic barrier regimen (with at least one protease inhibitor [PI]) or non-nucleoside reverse transcriptase inhibitor or thymidine analogue) while a third non-thymidine nucleoside analogue was used in the remaining patients. Results: : The 1-year estimated probability of virological failure was 34% in 165 patients with HIV RNA > 400 copies/ ml at ABC + TDF regimen initiation. Independent predictors of virological failure were the absence of a potent or high genetic barrier cART, the higher number of cART regimens experienced, and the use of a new drug class. In the subset of 136 patients for whom there were genotypic resistance test results prior to ABC + TDF initiation, the virological failure (1-year estimated probability 46%) was independently predicted by the higher baseline viral load, the concomitant use of boosted PI, and the presence of reverse transcriptase mutation M41L. In 142 patients starting ABC + TDF therapy with HIV RNA £ 400 copies/ml, virological failure (1-year estimated probability 17%) was associated only with the transmission category. In a small subset of subjects for whom there were an available paired baseline and follow-up genotype (n = 28), the prevalence of most nucleoside analogue reverse transcriptase inhibitor resistance mutations decreased, suggesting a possible low adherence to treatment. No selection of K65R was detected. Conclusion: : The virological response to ABC + TDF-containing regimens in this moderately-to-heavily treatmentexperienced cohort was good. Higher viral load and the presence of M41L at baseline were associated with worse virological responses, while the concomitant prescription of drugs enhancing the genetic barrier of the regimen conveyed a reduced risk of virological failure. The Appendix provides the names of other members of the MASTER cohort. © 2009 Springer.
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- 2008
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