A micro-costing study of mass-spectrometry based quantitative proteomics testing applied to the diagnostic pipeline of mitochondrial and other rare disorders

Abstract

Abstract Background Mass spectrometry-based quantitative proteomics has a demonstrated utility in increasing the diagnostic yield of mitochondrial disorders (MDs) and other rare diseases. However, for this technology to be widely adopted in routine clinical practice, it is crucial to accurately estimate delivery costs. Resource use and unit costs required to undertake a proteomics test were measured and categorized into consumables, equipment, and labor. Unit costs were aggregated to obtain a total cost per patient, reported in 2023 Australian dollars (AUD). Probabilistic and deterministic sensitivity analysis were conducted to evaluate parameter uncertainty and identify key cost drivers. Results The mean cost of a proteomics test was $897 (US$ 607) per patient (95% CI: $734-$1,111). Labor comprised 53% of the total costs. At $342 (US$ 228) per patient, liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) was the most expensive non-salary component. An integrated analysis pipeline where all the standard analysis are performed automatically, as well as discounts or subsidized LC-MS/MS equipment or consumables can lower the cost per test. Conclusions Proteomics testing provide a lower-cost option and wider application compared to respiratory chain enzymology for mitochondrial disorders and potentially other functional assays in Australia. Our analysis suggests that streamlining and automating workflows can reduce labor costs. Using PBMC samples may be a cheaper and more efficient alternative to generating fibroblasts, although their use has not been extensively tested yet. Use of fibroblasts could potentially lower costs when fibroblasts are already available by avoiding the expense of isolating PBMCs. A joint evaluation of the health and economic implications of proteomics is now needed to support its introduction to routine clinical care.

Keywords

• Proteomics
• Mitochondrial disorders
• Micro-costing
• Functional genomics
• Health economics