HCV kinetic and modeling analyses indicate similar time to cure among sofosbuvir combination regimens with daclatasvir, simeprevir or ledipasvir
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Citações na Scopus
61
Tipo de produção
article
Data de publicação
2016
Título da Revista
ISSN da Revista
Título do Volume
Editora
ELSEVIER SCIENCE BV
Autores
DAHARI, Harel
CANINI, Laetitia
GRAW, Frederik
UPRICHARD, Susan L.
PENARANDA, Guillaume
COQUET, Emilie
CHICHE, Laurent
RISO, Aurelie
RENOU, Christophe
Citação
JOURNAL OF HEPATOLOGY, v.64, n.6, p.1232-1239, 2016
Resumo
Background & Aims: Recent clinical trials of direct-acting-antiviral agents (DAAs) against hepatitis C virus (HCV) achieved >90% sustained virological response (SVR) rates, suggesting that cure often took place before the end of treatment (EOT). We sought to evaluate retrospectively whether early response kinetics can provide the basis to individualize therapy to achieve optimal results while reducing duration and cost. Methods: 58 chronic HCV patients were treated with 12-week sofosbuvir + simeprevir (n = 19), sofosbuvir + daclatasvir (n = 19), or sofosbuvir + ledipasvir in three French referral centers. HCV was measured at baseline, day 2, every other week, EOT and 12 weeks post EOT. Mathematical modeling was used to predict the time to cure, i.e., <1 virus copy in the entire extracellular body fluid. Results: All but one patient who relapsed achieved SVR. Mean age was 60 +/- 11 years, 53% were male, 86% HCV genotype-1, 9% HIV coinfected, 43% advanced fibrosis (F3), and 57% had cirrhosis. At weeks 2, 4 and 6, 48%, 88% and 100% of patients had HCV <15 IU/ml, with 27%, 74% and 91% of observations having target not detected, respectively. Modeling results predicted that 23 (43%), 16 (30%), 7 (13%), 5 (9%) and 3 (5%) subjects were predicted to reach cure within 6, 8, 10, 12 and 13 weeks of therapy, respectively. The modeling suggested that the patient who relapsed would have benefitted from an additional week of sofosbuvir + ledipasvir. Adjusting duration of treatment according to the modeling predicts reduced medication costs of 43-45% and 17-30% in subjects who had HCV <15 IU/ml at weeks 2 and 4, respectively. Conclusions: The use of early viral kinetic analysis has the potential to individualize duration of DAA therapy with a projected average cost saving of 16-20% per 100-treated persons.
Palavras-chave
HCV, Viral kinetics, Mathematical modeling, SVR, Duration of therapy
Referências
- Neumann AU, 1998, SCIENCE, V282, P103, DOI 10.1126/science.282.5386.103
- Shaheen AAM, 2007, AM J GASTROENTEROL, V102, P2589, DOI 10.1111/j.1572-0241.2007.01466.x
- Kwo P, 2015, J HEPATOL, V62, pS270
- Stattermayer AF, 2015, CURR OPIN VIROL, V14, P50, DOI 10.1016/j.coviro.2015.07.011
- Welzel TW, 2015, J HEPATOL, V62, pS667
- Mizokami M, 2015, LANCET INFECT DIS, V15, P645, DOI 10.1016/S1473-3099(15)70099-X
- Harrington PR, 2015, CLIN INFECT DIS, V61, P666, DOI 10.1093/cid/civ402
- Castera L, 2005, GASTROENTEROLOGY, V128, P343, DOI 10.1053/j.gastro.2004.11.018
- Rein DB, 2015, CLIN INFECT DIS, V61, P157, DOI 10.1093/cid/civ220
- Kohli A, 2015, LANCET, V385, P1107, DOI 10.1016/S0140-6736(14)61228-9
- Ferenci P, 2008, GASTROENTEROLOGY, V135, P451, DOI 10.1053/j.gastro.2008.04.015
- Pawlotsky JM, 2015, J HEPATOL, V62, pS87, DOI 10.1016/j.jhep.2015.02.006
- Kessler HH, 2015, J CLIN VIROL, V67, P67, DOI 10.1016/j.jcv.2015.03.023
- Snoeck E, 2010, CLIN PHARMACOL THER, V87, P706, DOI 10.1038/clpt.2010.35
- Sulkowski MS, 2014, JAMA-J AM MED ASSOC, V312, P353, DOI 10.1001/jama.2014.7734
- Dahari H, 2014, HEPATOLOGY, V59, P2422, DOI 10.1002/hep.26772
- [Anonymous], 2014, J HEPATOL S
- Dahari H, 2015, LIVER INT, V35, P289, DOI 10.1111/liv.12692
- Sarrazin C, 2015, J VIROL METHODS, V214, P29, DOI 10.1016/j.jviromet.2014.11.027
- Kuhn E, 2005, COMPUT STAT DATA AN, V49, P1020, DOI 10.1016/j.csda.2004.07.002
- Reddy KR, 2015, HEPATOLOGY, V62, P79, DOI 10.1002/hep.27826
- Kowdley KV, 2014, NEW ENGL J MED, V370, P1879, DOI 10.1056/NEJMoa1402355
- Bourliere M, 2015, LANCET INFECT DIS, V15, P397, DOI [10.1016/S1473-3099(15)70050-2, 10.1016/51473-3099(15)70050-2]
- Hoofnagle JH, 2009, J INFECT DIS, V199, P1112, DOI 10.1086/597384
- Schinazi R, 2014, LIVER INT, V34, P69, DOI 10.1111/liv.12423
- Guedj J, 2011, HEPATOLOGY, V53, P1801, DOI 10.1002/hep.24272
- Zarski JP, 2012, J HEPATOL, V56, P55, DOI 10.1016/j.jhep.2011.05.024
- Hezode C, 2015, J HEPATOL, V62, pS654
- Dixit NM, 2004, NATURE, V432, P922, DOI 10.1038/nature03153
- Guedj J, 2013, P NATL ACAD SCI USA, V110, P3991, DOI 10.1073/pnas.1203110110
- Biopredictive, NON LIV BIOM
- Bonder Alan, 2014, Curr Gastroenterol Rep, V16, P372, DOI 10.1007/s11894-014-0372-6
- Bourliere M, 2015, HEPATITIS C TREATMEN
- Dhumeaux D, 2014, PRISE CHARGE PERSONN
- Gambato M, 2015, HEPATOLOGY, V62, p691A
- Gane E, 2014, HEPATOLOGY, V60, pLB
- Lau KG, 2015, HEPATOLOGY, V62, p1394A
- Lawitz E, 2014, HEPATOLOGY, V60, p1286A
- Poynard T, 2004, COMP HEPATOL, V3, P8, DOI 10.1186/1476-5926-3-8
- Rong LB, 2013, PLOS COMPUT BIOL, V9, DOI 10.1371/journal.pcbi.1002959
- Sansone N, 2014, HEPATOLOGY, V60, p1165A
- Sidharthan S, 2015, CLIN INFECT DIS
- Sulkowski MS, 2014, HEPATOLOGY, V60, p1144A
- Webster DP, 2015, LANCET, V385, P1124, DOI 10.1016/S0140-6736(14)62401-6
- Wyles D, 2015, CROI