Exploring Heterogeneity in the Cost-Effectiveness of High-Flow Nasal Cannula Therapy in Acutely Ill Children—Insights From the Step-Up First-line Support for Assistance in Breathing in Children Trial Using a Machine Learning Method

Jan 1, 2025, 00:00
10.1016/j.jval.2024.08.008
https://www.valueinhealthjournal.com/article/S1098-3015(24)02853-5/fulltext
Title : Exploring Heterogeneity in the Cost-Effectiveness of High-Flow Nasal Cannula Therapy in Acutely Ill Children—Insights From the Step-Up First-line Support for Assistance in Breathing in Children Trial Using a Machine Learning Method
Citation : https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(24)02853-5&doi=10.1016/j.jval.2024.08.008
First page : 60
Section Title : Economic Evaluation
Open access? : Yes
Section Order : 60

Objectives

To investigate heterogeneity in the cost-effectiveness of high-flow nasal cannula (HFNC) therapy compared with continuous positive airway pressure (CPAP) for acutely ill children requiring noninvasive respiratory support.

Methods

Using data from the First-line Support for Assistance in Breathing in Children trial, we explore heterogeneity at the patient and subgroup levels using 2 causal forest approaches and a seemingly unrelated regression approach for comparison. First-line Support for Assistance in Breathing in Children is a noninferiority randomized controlled trial (ISRCTN60048867) involving 24 UK pediatric intensive care units. The Step-up trial focuses on acutely ill children aged 0 to 15 years, requiring noninvasive respiratory support. A total of 600 children were randomly assigned to HFNC and CPAP groups in a 1:1 allocation ratio, with 94 patients excluded because of data unavailability.

Results

The primary outcome is the incremental net monetary benefit (INB) of HFNC compared with CPAP, using a willingness-to-pay threshold of £20 000 per quality-adjusted life year gain. INB is derived from total costs and quality-adjusted life years at 6 months. Subgroup analysis showed that some subgroups, such as male children, those aged less than 12 months, and those without severe respiratory distress at randomization, had more favorable INB results. Patient-level analysis revealed heterogeneity in INB estimates, particularly driven by the cost component, with greater uncertainty for those with higher INBs.

Conclusions

The estimated overall INB of HFNC is significantly larger for specific patient subgroups, suggesting that the cost-effectiveness of HFNC can be heterogeneous, which highlights the importance of considering patient characteristics in evaluating the cost-effectiveness of HFNC.

Categories :
  • Artificial Intelligence, Machine Learning, Predictive Analytics
  • Cost-comparison, Effectiveness, Utility, Benefit Analysis
  • Economic Evaluation
  • Methodological & Statistical Research
  • Pediatrics
  • Specific Diseases & Conditions
  • Trial-Based Economic Evaluation
Tags :
  • causal forest
  • cost-effectiveness
  • heterogeneous effects
  • machine learning
Regions :
  • Western Europe
ViH Article Tags :
  • Open Access