Metastatic colorectal cancer (mCRC) imposes a substantial health burden on individual patients and society. Furthermore, rising costs in oncology cause a growing concern about reimbursement for innovations in this sector. The promise of pharmacogenomic profiling and related stratified therapies in mCRC is to improve treatment efficacy and potentially save costs. Among other examples, the commonly used epidermal growth factor receptor (EGFR) antibodies cetuximab and panitumumab are only effective in patients with kirsten rat sarcoma viral oncogene homolog (KRAS) wild-type cancers. Hence, the adaptation of predictive biomarker testing might be a valid strategy for healthcare systems worldwide.Objective
This study aims to review the clinical and economic evidence supporting pharmacogenomic profiling prior to the administration of pharmaceutical treatment in mCRC. Moreover, key drivers and areas of uncertainty in cost-effectiveness evaluations are analysed.Methods
A systematic literature review was conducted to identify studies evaluating the cost effectiveness of predictive biomarkers and the result dependent usage of pharmaceutical agents in mCRC.Results
The application of predictive biomarkers to detect KRAS mutations prior to the administration of EGFR antibodies saved treatment costs and was cost effective in all identified evaluations. However, because of the lack of data regarding cost-effectiveness analyses for predictive biomarker testing, e.g. for first-line treatment, definitive conclusions cannot be stated. Key drivers and areas of uncertainty in current cost-effectiveness analyses are, among others, the consideration of predictive biomarker costs, the characteristics of single predictive biomarkers and the availability of clinical data for the respective pharmaceutical intervention. Especially the cost effectiveness of uridine diphosphate-glucuronyl transferase 1A1 (UGT1A1) mutation analysis prior to irinotecan-based chemotherapy remains unclear.Conclusion
Pharmacogenomic profiling has the potential to improve the cost effectiveness of pharmaceutical treatment in mCRC. Hence, quantification of the economic impact of stratified medicine as well as cost-effectiveness analyses of pharmacogenomic profiling are becoming more important. Nevertheless, the methods applied in cost-effectiveness evaluations for the usage of predictive biomarkers for patient selection as well as the level of evidence required to determine clinical effectiveness are areas for further research. However, mCRC is one of the first indications in which stratified therapies are used in clinical practice. Thus, clinical and economic experiences could be helpful when adopting pharmacogenomic profiling into clinical practice for other indications.