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Published on: August 16, 2021
Integrated treatment-decision algorithms for childhood TB: modelling diagnostic performance and costs
Mary Gaeddert1, Devan Jaganath2,3, Abdulkadir Civan1
1Department of Infectious Diseases and Tropical Medicine, University Hospital Heidelberg, Heidelberg, Germany.
Insights
Treatment-decision algorithms (TDAs) for childhood tuberculosis (TB) show high sensitivity but low specificity. Implementing TDAs with chest X-ray (CXR) at primary healthcare (PHC) settings in Uganda is cost-effective for improving TB diagnosis.
Area of Science:
- Public Health
- Medical Diagnostics
- Health Economics
Background:
- Childhood tuberculosis (TB) diagnosis requires improved strategies.
- Treatment-decision algorithms (TDAs) were developed for children under 10, with and without chest X-ray (CXR).
- Implementation of TDAs in Ugandan primary healthcare (PHC) and district hospital (DH) settings was modeled.
Purpose of the Study:
- To model the diagnostic performance of TDAs for childhood TB.
- To assess the costs associated with implementing TDAs in different healthcare settings.
- To compare the cost-effectiveness of various diagnostic testing combinations.
Main Methods:
- Decision-tree models were used to simulate TDA pathways.
- Six scenarios combined diagnostic tests (Xpert, urine LAM, CXR) at PHC and DH levels.
- Monte Carlo simulation evaluated diagnostic accuracy and cost per correct treatment-decision for 10,000 children, from a health system perspective.
Main Results:
- TDAs demonstrated high sensitivity (80.8-91.9%) but low specificity (51.2-60.9%).
- Total costs ranged from I$1,768,958 to I$2,458,790, driven by overtreatment of false positives.
- Mobile CXR at PHC yielded the lowest cost per treatment-decision (I$287.40).
Conclusions:
- TDAs offer high sensitivity for childhood TB diagnosis.
- Implementation at PHC settings is more cost-effective than at DH settings.
- Improving specificity and reducing overtreatment are key for affordable, large-scale TDA deployment.
Background:
To improve childhood tuberculosis (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 healthcare (PHC) and district hospital (DH) settings in Uganda.
Methods:
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.
Results:
In all scenarios, TDA's had high sensitivity (80.8-91.9%) but low specificity (51.2-60.9%). Total diagnostic and treatment costs for the cohort were I$1,768,958-2,458,790; 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 PHC (I$287.40) and highest with DH referral (I$445.84).
Conclusion:
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.
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