The economic costs of precision medicine for clinical translational research among children with high-risk cancer

Childhood cancer is a leading cause of disease-related death in high-income countries. While survival rates have improved for some cancers, high-risk malignancies (expected survival <30%) affect 20-25% of diagnosed children annually in Australia. Conventional treatments (chemotherapy, radiotherapy) cause significant acute and chronic side effects, burdening the healthcare system. Precision medicine offers a potential solution by tailoring treatment to individual tumors, potentially reducing toxicity and improving outcomes. Several global pediatric precision oncology programs utilize advanced technologies to identify cancer drivers and match them with effective therapies. However, there's limited evidence on the economic feasibility of these programs. This study aims to fill this gap by evaluating the cost of precision medicine in high-risk childhood cancers using Australia's Zero Childhood Cancer Precision Medicine Programme (ZERO).

While numerous studies explore precision medicine in childhood cancer, data on the economic aspects of related testing are scarce. Existing research focuses on individual next-generation sequencing technologies or smaller ranges of tests, lacking a comprehensive assessment of multi-omics and preclinical platforms specific to pediatric oncology. This study addresses this gap by micro-costing a comprehensive platform, unlike previous research which often only considered the cost of individual tests like genome sequencing.

This cost study, "The economic impact of precision medicine in childhood cancer" (EPIC-CC PRISM Cohort), is a sub-study of the ZERO PRISM clinical trial. It uses a micro-costing approach to estimate costs from sample receipt to MTB report issuance (average 8.7 weeks). Data on costs and labor were collected from ZERO's laboratory information management system and expenditure reports. All sequencing was outsourced at a fixed price per test type. The study analyzed costs for three outcomes: (A) cost per patient for accessing assays; (B) cost per molecular diagnosis; and (C) cost per actionable MTB recommendation. Three cost scenarios were modeled: high (ca. 2020, low volume), base case (ca. 2022, current volume), and low (ca. 2025, high volume). The analysis included costs for multi-omics (WGS, RNAseq, methylation profiling), preclinical analyses (HTS, PDX), consumables, labor, shipping, data analysis, storage, curation, and MTB reporting. Costs not expected in a public roll-out (e.g., capital expenditure, staff training, long-term data storage) were excluded. Mean per-patient costs and uncertainty intervals were calculated using bootstrapping. Differences in access costs were analyzed by cancer type and stage using linear regression and post-hoc comparisons.

The EPIC-CC study enrolled 423 patients (August 2019 - December 2021), with approximately equal gender distribution. Over half were deceased by study's end. The mean age was 10.3 years. The base-case (current cost) estimated mean total cost for accessing the multi-omics and preclinical platforms was $12,743 per patient ($11,136 for omics, $1607 for preclinical). The cost per molecular diagnosis (Outcome B) was $14,262, and the cost per actionable MTB recommendation (Outcome C) was $21,769. Preclinical testing costs were diluted by low test completion rates (19.2% for HTS or PDX). Mean access costs for HTS and PDX were $3171 and $19,757 respectively (considering only successful completions). A significant difference in mean access cost was found between CNS and hematological cancers ($2461.88 difference; p=0.0021), attributed to lower PDX usage in CNS cancers. No significant difference was found based on cancer stage. Scenario analysis showed a substantial cost reduction with increasing volumes and technological advancements: a 43% reduction over two years and an anticipated 33% reduction over the next three years. The largest cost component was multi-omics due to higher feasibility across cancer types.

This is the first study to micro-cost a comprehensive precision medicine platform in pediatric oncology, providing detailed operating cost data for multi-omics and preclinical testing from ZERO. The platform generated clinically significant information for nearly all patients within a clinically feasible timeframe (8.7 weeks on average). The study highlights the importance of outcomes beyond diagnostic information, including molecular cause identification and actionable MTB recommendations. The results demonstrate a favorable cost reduction over time driven by economies of scale and technological improvements. While preclinical testing costs are expected to remain stable, multi-omics costs are projected to decrease further. This research underscores the potential cost-effectiveness of comprehensive precision medicine in pediatric oncology with increasing volume and technological improvements. The heterogeneity of cancer types and stages in the study needs to be acknowledged, suggesting a need for larger studies to better determine cost differences based on these factors. The study focused solely on testing costs, neglecting clinical care and treatment uptake. Future research should integrate cost and outcome data.

This study provides the first detailed economic evaluation of a comprehensive precision medicine platform in pediatric oncology. The findings reveal substantial costs but also demonstrate a clear downward cost trend with increasing sample volume and technological advancements. Future research should focus on cost-effectiveness analyses incorporating clinical outcomes and broader implementation in routine clinical care, while carefully considering the cost variations based on tumor characteristics and integrating the results with clinical care.

The study focused on costs from sample receipt to report issuance, excluding clinical care costs and treatment uptake. The study cohort may not entirely represent the routine clinical setting due to potential heterogeneity of cancer types and progression stages. Further research is needed to address these limitations and expand the analysis across various risk groups and treatment protocols.