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Understanding the Natural History of Chronic Hepatitis D: Proposal of a Model for Cost-Effectiveness Studies.
Kaushik, Ankita; Dusheiko, Geoffrey; Kim, Chong; Smith, Nathaniel J; Kinyik-Merena, Csilla; Di Tanna, Gian Luca; Wong, Robert J.
Afiliación
  • Kaushik A; Gilead Sciences, Inc., Foster City, CA, USA.
  • Dusheiko G; School of Medicine, University College London, London, UK.
  • Kim C; Kings College Hospital, London, UK.
  • Smith NJ; Gilead Sciences, Inc., Foster City, CA, USA. chong.kim9@gilead.com.
  • Kinyik-Merena C; Maple Health Group, New York, NY, USA.
  • Di Tanna GL; Maple Health Group, New York, NY, USA.
  • Wong RJ; Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland.
Pharmacoecon Open ; 8(2): 333-343, 2024 Mar.
Article en En | MEDLINE | ID: mdl-38172472
ABSTRACT

BACKGROUND:

As new therapeutic options become available, better understanding the potential impact of emerging therapies on clinical outcomes of hepatits D virus (HDV) is critical.

OBJECTIVE:

The aim of this study was to develop a natural history model for patients with hepatitis D virus.

METHODS:

We developed a model (decision tree followed by a Markov cohort model) in adults with chronic HDV infection to assess the natural history and impact of novel treatments on disease progression versus best supportive care (BSC). The model time horizon was over a lifetime (up to 100 years of age); state transitions and health states were defined by responder status. Patients in fibrosis stages 0 through 4 received treatment; decompensated patients were not treated. Response was defined as the combined response endpoint of achievement of HDV-RNA undetectability/≥2-log10 decline and alanine aminotransferase normalization; response rates of 50% and 75% were explored. Health events associated with advanced liver disease were modeled as the number of events per 10,000 patients. Scenario analyses of early treatment, alternate treatment response, and no fibrosis regression for treatment responders were also explored.

RESULTS:

The model was able to reflect disease progression similarly to published natural history studies for patients with HBV/HDV infection. In a hypothetical cohort of patients reflecting a population enrolled in a recent clinical trial, fewer advanced liver disease events were observed with a novel HDV treatment versus BSC. Fewer liver-related deaths were observed under 50% and 75% response (900 and 1,358 fewer deaths, respectively, per 10,000 patients). Scenario analyses showed consistently fewer advanced liver disease events with HDV treatment compared with BSC, with greater reductions observed with earlier treatment.

CONCLUSION:

This HDV disease progression model replicated findings from natural history studies. Furthermore, it found that a hypothetical HDV treatment results in better clinical outcomes for patients versus BSC, with greater benefit observed when starting treatment early. This validated natural history model for HBV/HDV infection can serve as a foundation for future clinical and economic analyses of novel HDV treatments that can support healthcare stakeholders in the management of patients with chronic HDV.

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Pharmacoecon Open Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Pharmacoecon Open Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos