Title |
Consequences of inaccurate hepatitis C virus genotyping on the costs of prescription of direct antiviral agents in an Italian district
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Published in |
ClinicoEconomics and Outcomes Research: CEOR, September 2016
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DOI | 10.2147/ceor.s106238 |
Pubmed ID | |
Authors |
Ennio Polilli, Valeria Cento, Umberto Restelli, Francesca Ceccherini-Silberstein, Marianna Aragri, Velia Chiara Di Maio, Antonina Sciacca, Fiorenzo Santoleri, Paolo Fazii, Alberto Costantini, Carlo Federico Perno, Giustino Parruti |
Abstract |
Available commercial assays may yield inaccurate hepatitis C virus (HCV) genotype assignment in up to 10% of cases. We investigated the cost-effectiveness of re-evaluating HCV genotype by population sequencing, prior to choosing a direct acting antiviral (DAA) regimen. Between March and September 2015, HCV sequence analysis was performed in order to confirm commercial LiPA-HCV genotype (Versant(®) HCV Genotype 2.0) in patients eligible for treatment with DAAs. Out of 134 consecutive patients enrolled, sequencing yielded 21 (15.7%) cases of discordant results. For three cases of wrong genotype assignment, the putative reduction in efficacy was gauged between 15% and 40%. Among the eight cases for whom G1b was assigned by commercial assays instead of G1a, potentially suboptimal treatments would have been prescribed. Finally, for five patients with G1 and indeterminate subtype, the choice of regimens would have targeted the worst option, with a remarkable increase in costs, as in the case of the four mixed HCV infections for whom pan-genotypic regimens would have been mandatory. Precise assignment of HCV genotype and subtype by sequencing may, therefore, be more beneficial than expected, until more potent pan-genotypic regimens are available for all patients. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 28 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 18% |
Other | 3 | 11% |
Student > Ph. D. Student | 3 | 11% |
Student > Postgraduate | 3 | 11% |
Professor > Associate Professor | 3 | 11% |
Other | 4 | 14% |
Unknown | 7 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 7 | 25% |
Immunology and Microbiology | 5 | 18% |
Medicine and Dentistry | 5 | 18% |
Agricultural and Biological Sciences | 2 | 7% |
Economics, Econometrics and Finance | 1 | 4% |
Other | 0 | 0% |
Unknown | 8 | 29% |