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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Real-world cost-effectiveness of panel-based genomic testing to inform therapeutic decisions for metastatic
Reka E Pataky1, Deirdre Weymann1, Ian Bosdet2
1Canadian Centre for Applied Research in Cancer Control, Canada; Cancer Control Research, BC Cancer, Vancouver, BC, Canada.
Background:
Mutations in KRAS and NRAS are associated with a lack of response to cetuximab and panitumumab, two biologics used for third-line therapy of metastatic colorectal cancer (mCRC). In British Columbia, Canada, eligibility for cetuximab or panitumumab was first based on single-gene KRAS testing. OncoPanel, a multi-gene next-generation sequencing panel with both KRAS and NRAS, was introduced in 2016. Our objective was to estimate the real-world cost-effectiveness of OncoPanel versus to single-gene KRAS testing to inform eligibility for cetuximab or panitumumab in mCRC.
Methods:
Using population-based administrative health data, we identified a cohort of mCRC patients who had received a KRAS or OncoPanel test, and completed prior chemotherapy in 2010-2019. We matched KRAS- and OncoPanel-tested patients (1:1) using genetic matching to balance baseline covariates. Mean and incremental 3-year costs, survival, and quality-adjusted survival were estimated using inverse-probability-of-censoring weighting and bootstrapping. We conducted scenario-based sensitivity analysis for key costs and assumptions.
Findings:
All OncoPanel-tested cases (n=371) were matched to a KRAS-tested comparator. In the KRAS and OncoPanel groups, respectively, 55·8 % and 41·2 % of patients were potentially eligible for cetuximab or panitumumab based on mutation status. Incremental cost and effectiveness of OncoPanel were $72 (95 % CI: -6387, 6107), -0·004 life-years (95 % CI: -0·119, 0·113), and -0·011 quality-adjusted life-years (95 % CI: -0·094, 0·075). Reductions in systemic therapy costs were offset by increased costs in other resources. Results were moderately sensitive to time horizon and changes in testing or treatment cost.
Interpretation:
The use of OncoPanel resulted in more precise targeting of cetuximab and panitumumab, but there was no change in incremental cost or quality-adjusted survival. Understanding the balance of costs achieved in practice can provide insight into the effect of future changes in testing policy, test cost, treatment eligibility, or drug prices in this setting.
Insights
OncoPanel testing for metastatic colorectal cancer (mCRC) precisely targets cetuximab/panitumumab but shows no significant difference in cost or survival compared to KRAS testing. This finding informs future testing policies for mCRC treatments.
Area of Science:
- Oncology
- Genetics
- Health Economics
Background:
- KRAS/NRAS mutations impact response to cetuximab/panitumumab in metastatic colorectal cancer (mCRC).
- Initial mCRC treatment eligibility in British Columbia relied on single-gene KRAS testing.
- OncoPanel, a multi-gene NGS panel, was introduced in 2016 to include NRAS testing.
Purpose of the Study:
- To estimate the real-world cost-effectiveness of OncoPanel versus single-gene KRAS testing for mCRC.
- To inform eligibility for cetuximab or panitumumab in mCRC patients.
Main Methods:
- Population-based administrative health data from 2010-2019 were used.
- A 1:1 matched cohort of KRAS- and OncoPanel-tested mCRC patients was created using genetic matching.
- Inverse-probability-of-censoring weighting and bootstrapping estimated 3-year costs, survival, and quality-adjusted survival.
Main Results:
- OncoPanel testing identified 41.2% of patients eligible for targeted therapy, versus 55.8% with KRAS testing.
- Incremental cost-effectiveness was negligible: $72, -0.004 life-years, and -0.011 quality-adjusted life-years.
- Reductions in systemic therapy costs were balanced by increases in other resource costs.
Conclusions:
- OncoPanel enables more precise targeting of mCRC therapies but does not alter incremental cost or quality-adjusted survival.
- This analysis provides insights for future testing policies, test costs, and drug pricing strategies.

