Risk prediction algorithms in guiding antiviral therapy initiation among patients with chronic hepatitis B in Thailand: an economic evaluation and budget impact analysis

ABSTRACT

Objective

Several risk prediction algorithms have been developed to guide antiviral therapy initiation among patients with chronic hepatitis B (CHB). This study assessed the cost-effectiveness and budget impact of three risk prediction algorithms among patients with CHB in Thailand.

Methods

A decision tree with a Markov model was constructed. Three risk prediction algorithms were compared with current practices including HePAA, TREAT-B and REACH-B. PubMed was searched from its inception to December 2022 to identify inputs. Tenofovir alafenamide and best supportive care were selected for antiviral-eligible patients, and incremental cost-effectiveness ratios per quality-adjusted life year (QALY) were calculated.

Results

Our base case analysis showed that HePAA and REACH-B could provide better QALY (0.098 for HePAA and 0.921 for REACH-B) with decreased total healthcare costs (−10909 THB for HePAA and −8,637 THB for REACH-B). TREAT-B provided worse QALY (−0.144) with increased total healthcare costs (10,435 THB). The budget impacts for HePAA and REACH-B were 387 million THB and 3,653 million THB, respectively.

Conclusion

HePAA and REACH-B algorithms are cost-effective in guiding antiviral therapy initiation. REACH-B is the most cost-effective option, but has a high budget impact. Policymakers should consider both cost-effectiveness and budget impact findings when deciding which algorithm should be implemented.

KEYWORDS:

• economic evaluation
• Budget impact analysis
• risk prediction algorithms
• chronic hepatitis b
• hepatocellular carcinoma

Article highlights

• Several risk prediction algorithms have been developed to guide antiviral therapy initiation among patients with chronic hepatitis B (CHB).

• HePAA and REACH-B algorithms provide better quality of life and decrease total healthcare cost among patients with CHB.

• HePAA and REACH-B algorithms are cost-effective compared with current situations for guiding antiviral therapy initiation in Thailand.

• REACH-B is the most cost-effective option, but has high budget impact.

• Policymakers should consider both cost-effectiveness and budget impact findings when deciding which algorithm should be implemented.

Author contributions

P. Dilokthornsakul: Study design, Data collection, Data analysis, Manuscript preparation and Final approval of the manuscript

R. Sawangjit: Study design, Data collection, Manuscript preparation and Final approval of the manuscript

P. Tangkijvanich: Study design, Data analysis and Final approval of the manuscript

M. Chayanupatkul: Study design, Data collection, Manuscript preparation and Final approval of the manuscript

P. Sriuttha: Study design, Data collection and Final approval of the manuscript

U. Permsuwan: Study design, Data collection, Data analysis and Final approval of the manuscript

Acknowledgments

We would like to acknowledge the International Relations Unit, Faculty of Pharmacy, Chiang Mai University for providing English editing services and the Thai Association for the Study of the Liver (THSAL).

Declaration of interest

P. Dilothornsakul received research financial support from Novartis (Thailand), Pfizer (Thailand) and honoraria from GSK (Thailand). However, the support was unrelated to this research. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Data availability statement

The datasets generated during or analyzed during the current study are available from the corresponding author upon reasonable request.

Code availability

Models used in the current study are available from the corresponding author upon reasonable request.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/14737167.2023.2231636

Additional information

Funding

This research project is partially supported by the Ratchadapisek Sompoch Endowment Fund, Chulalongkorn University (765007-RES01)