# Integrated treatment-decision algorithms for childhood TB: modelling diagnostic performance and costs

## TL;DR

This study models diagnostic performance and costs of treatment-decision algorithms for childhood TB in Uganda, comparing primary health centers and hospitals.

## Contribution

The novel contribution is evaluating integrated TB treatment-decision algorithms with and without chest X-ray in different healthcare settings.

## Key findings

- TDAs showed high sensitivity (80.8%–91.9%) but low specificity (50.9%–60.9%).
- Using mobile CXR at PHCs had the lowest cost per treatment-decision (I$287).
- DH referral was the most expensive scenario (I$449 per treatment-decision).

## Abstract

To improve childhood TB diagnosis, treatment-decision algorithms (TDAs) with and without chest X-ray (CXR) were developed for children under age 10. We aimed to model diagnostic performance and costs of implementing TDAs in primary health centre (PHC) and district hospital (DH) settings in Uganda.

We developed decision-tree models following the TDA pathway from evaluation to treatment-decision. We compared six scenarios with combinations of diagnostic testing (stool and respiratory Xpert, urine lipoarabinomannan, and/or CXR) at PHCs and DHs. Outcomes were diagnostic accuracy and cost per correct treatment-decision for a cohort of 10,000 children with presumptive TB using a Monte Carlo simulation from a health system perspective. Costs were reported in 2024 international dollars (I$).

In all scenarios, TDAs had high sensitivity (80.8%–91.9%) but low specificity (50.9%–60.9%). Total diagnostic and treatment costs for the cohort were I$1,768,958–2,470,298, largely driven by overtreatment of false-positive cases. Diagnostic costs were mostly offset by reducing overtreatment. The cost per treatment-decision was lowest using mobile CXR at PHCs (I$287) and highest with DH referral (I$449).

The TDAs have high sensitivity and can be implemented at PHCs with lower costs than DHs. Improving specificity and reducing treatment costs would enable affordable, large-scale implementation.