Modelling the cost-effectiveness of interventions to treat or prevent neuropathic ulcers arising from leprosy: application to L-PRF

Leprosy remains a public health problem in low- and middle-income countries (LMIC), often causing extensive nerve damage leading to neuropathic ulcers with significant morbidity. Whether interventions to prevent and treat such ulcers offer good value for money requires modelling their lifetime costs and benefits and consideration of opportunity costs. This paper provides the first decision analytical model for the economic evaluation of interventions to manage neuropathic ulcers in leprosy, and applies it to assess the cost-effectiveness of leukocyte- and platelet-rich fibrin (L-PRF) ulcer dressings in Nepal. A discrete time Markov model is developed in consultation with clinical experts and informed by reviews of the literature. It is parameterised using evidence from the literature and from a trial of L-PRF enabling the model to be adapted to evaluate a range of interventions. To estimate the effectiveness of L-PRF, we implement parametric survival modelling to extrapolate time to healing beyond the trial follow-up period and calculate the relative risk of recurrence. Costs and effects are assessed over patients’ lifetimes. No existing model of neuropathic ulcers arising from leprosy in LMIC was identified in the literature, and literature to inform model parameters is scarce. Our model-based analysis demonstrates how models can be parameterised, including from trial data. Our application of the model found that L-PRF increased mean costs by 6,731 NRP per patient and generated 0.006 additional QALYs compared with saline dressings. At an estimated health opportunity cost threshold of 38,970 NRP per QALY, the incremental net health benefit was − 0.167 QALYs per patient (− 167 per 1,000 patients), with substantial uncertainty. Under these assumptions, L-PRF was unlikely to be cost-effective in the hospital setting analysed. Given uncertainty in the data, there is potentially significant value from generating additional trial evidence. This study presents a structured decision-analytic framework for evaluating neuropathic ulcer interventions in leprosy, informed by limited available data. Researchers intending to use the model to evaluate interventions should carefully consider whether the parameters estimated here are relevant to their clinical and geographical context and update these as required. ClinicalTrials.gov ISRCTN14933421. Registered on 16 June 2020.

Authors

Institutions

Publication Details

Journal
Cost Effectiveness and Resource Allocation
Published
2026-03-26
DOI
https://doi.org/10.1186/s12962-026-00739-8
Primary Topic
Leprosy Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modelling the cost-effectiveness of interventions to treat or prevent neuropathic ulcers arising from leprosy: application to L-PRF

Jessica Ochalek, P Saramago, Dilip Shrestha, Karuna Neupane et al.
Cost Effectiveness and Resource Allocation
Leprosy Research and Treatment
article

Modelling the cost-effectiveness of interventions to treat or prevent neuropathic ulcers arising from leprosy: application to L-PRF

Jessica Ochalek, P Saramago, Dilip Shrestha, Karuna Neupane, Indra Bahadur Napit, Naomi Gibbs, Anju Adhikari, Joydeepa Darlong, Rita Faria, Mark Sculpher, Karthikeyen Govindasamy, Richard Lilford
article en

Abstract

Leprosy remains a public health problem in low- and middle-income countries (LMIC), often causing extensive nerve damage leading to neuropathic ulcers with significant morbidity. Whether interventions to prevent and treat such ulcers offer good value for money requires modelling their lifetime costs and benefits and consideration of opportunity costs. This paper provides the first decision analytical model for the economic evaluation of interventions to manage neuropathic ulcers in leprosy, and applies it to assess the cost-effectiveness of leukocyte- and platelet-rich fibrin (L-PRF) ulcer dressings in Nepal. A discrete time Markov model is developed in consultation with clinical experts and informed by reviews of the literature. It is parameterised using evidence from the literature and from a trial of L-PRF enabling the model to be adapted to evaluate a range of interventions. To estimate the effectiveness of L-PRF, we implement parametric survival modelling to extrapolate time to healing beyond the trial follow-up period and calculate the relative risk of recurrence. Costs and effects are assessed over patients’ lifetimes. No existing model of neuropathic ulcers arising from leprosy in LMIC was identified in the literature, and literature to inform model parameters is scarce. Our model-based analysis demonstrates how models can be parameterised, including from trial data. Our application of the model found that L-PRF increased mean costs by 6,731 NRP per patient and generated 0.006 additional QALYs compared with saline dressings. At an estimated health opportunity cost threshold of 38,970 NRP per QALY, the incremental net health benefit was − 0.167 QALYs per patient (− 167 per 1,000 patients), with substantial uncertainty. Under these assumptions, L-PRF was unlikely to be cost-effective in the hospital setting analysed. Given uncertainty in the data, there is potentially significant value from generating additional trial evidence. This study presents a structured decision-analytic framework for evaluating neuropathic ulcer interventions in leprosy, informed by limited available data. Researchers intending to use the model to evaluate interventions should carefully consider whether the parameters estimated here are relevant to their clinical and geographical context and update these as required. ClinicalTrials.gov ISRCTN14933421. Registered on 16 June 2020.

Cost Effectiveness and Resource Allocation
University of Warwick (GB), Anandaban Hospital (NP), University of York (GB), University of Birmingham (GB)
No poverty
Openalex Percentile: Top 8%
Leprosy Research and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.