TY - JOUR
T1 - Cost-Effectiveness and Budget Impact of Future Developments With Whole-Genome Sequencing for Patients With Lung Cancer
AU - Simons, Martijn J. H. G.
AU - Uyl-de Groot, Carin A.
AU - Retèl, Valesca P.
AU - Mankor, Joanne M.
AU - Ramaekers, Bram L. T.
AU - Joore, Manuela A.
AU - van Harten, Wim H.
N1 - Funding Information: Funding/Support: This work was supported by ZonMw, Netherlands (grant number 846001002), the Dutch Cancer Society, Netherlands, and the Dutch healthcare insurance company Zilveren Kruis-Achmea, Netherlands . Funding Information: Conflict of Interest Disclosures: Drs Simons and Retèl have received grants from governmental funding of medical research by The Netherlands Organisation for Health Research and Development (ZonMw). Dr Retèl has received grants from Agendia BV and Intuitive BV outside the submitted work. No other disclosures were reported. Funding Information: The authors thank Dr Marthe Paats from the Erasmus Medical Centre for providing expert opinion within the field of clinical oncology. The authors also thank Dr Sabine Grimm from the Maastricht University Medical Centre for providing support on the value of information analyses. Furthermore, the authors thank all members of the Technology Assessment of Next-Generation Sequencing in Personalized Oncology consortium ( https://zenodo.org/communities/tango-wgs/?page=1&size=20 ) and the funding organizations: ZonMw (grant numbers 846001002), the Dutch Cancer Society, and the Dutch healthcare insurance company Zilveren Kruis Achmea for making this research possible. Publisher Copyright: © 2022
PY - 2023/1
Y1 - 2023/1
N2 - Objectives: This study aimed to investigate the cost-effectiveness, budget impact (BI), and impact of uncertainty of future developments concerning whole-genome sequencing (WGS) as a clinical diagnostic test compared with standard of care (SoC) in patients with locally advanced and metastatic non–small cell lung cancer. Methods: A total of 3 likely scenarios to take place within 5 years (according to experts) were simulated using a previously developed, peer reviewed, and published decision model. The scenarios concerned “WGS results used for treatment selection” (scenario 1), “WGS-based biomarker for immunotherapy” (scenario 2), and “off-label drug approval for WGS results” (scenario 3). Two diagnostic strategies of the original model, “SoC” and “WGS as a diagnostic test” (base model), were used to compare our scenarios with. Outcomes were reported for the base model, all scenarios separately, combined (combined unweighted), and weighted by likelihood (combined weighted). Cost-effectiveness, BI, and value of information analyses were performed for WGS compared with SoC. Results: Total costs and quality-adjusted life-years for SoC in metastatic non–small cell lung cancer were €149 698 and 1.235. Incremental outcomes of WGS were €1529/0.002(base model), −€222/0.020(scenario 1), −€2576/0.023(scenario 2), €388/0.024(scenario 3), −€5041/0.060(combined unweighted), and −€1715/0.029(combined weighted). The annual BI for adopting WGS for this population in The Netherlands ranged between €682 million (combined unweighted) and €714 million (base model). The consequences of uncertainty amounted to €3.4 million for all scenarios (combined weighted) and to €699 000 for the diagnostic yield of WGS alone (combined weighted). Conclusions: Our findings suggest that it is likely for WGS to become cost-effective within the near future if it identifies more patients with actionable targets and show the impact of uncertainty regarding its diagnostic yield. Modeling future scenarios can be useful to consider early adoption of WGS while timely anticipating on unforeseen developments before final conclusions are reached.
AB - Objectives: This study aimed to investigate the cost-effectiveness, budget impact (BI), and impact of uncertainty of future developments concerning whole-genome sequencing (WGS) as a clinical diagnostic test compared with standard of care (SoC) in patients with locally advanced and metastatic non–small cell lung cancer. Methods: A total of 3 likely scenarios to take place within 5 years (according to experts) were simulated using a previously developed, peer reviewed, and published decision model. The scenarios concerned “WGS results used for treatment selection” (scenario 1), “WGS-based biomarker for immunotherapy” (scenario 2), and “off-label drug approval for WGS results” (scenario 3). Two diagnostic strategies of the original model, “SoC” and “WGS as a diagnostic test” (base model), were used to compare our scenarios with. Outcomes were reported for the base model, all scenarios separately, combined (combined unweighted), and weighted by likelihood (combined weighted). Cost-effectiveness, BI, and value of information analyses were performed for WGS compared with SoC. Results: Total costs and quality-adjusted life-years for SoC in metastatic non–small cell lung cancer were €149 698 and 1.235. Incremental outcomes of WGS were €1529/0.002(base model), −€222/0.020(scenario 1), −€2576/0.023(scenario 2), €388/0.024(scenario 3), −€5041/0.060(combined unweighted), and −€1715/0.029(combined weighted). The annual BI for adopting WGS for this population in The Netherlands ranged between €682 million (combined unweighted) and €714 million (base model). The consequences of uncertainty amounted to €3.4 million for all scenarios (combined weighted) and to €699 000 for the diagnostic yield of WGS alone (combined weighted). Conclusions: Our findings suggest that it is likely for WGS to become cost-effective within the near future if it identifies more patients with actionable targets and show the impact of uncertainty regarding its diagnostic yield. Modeling future scenarios can be useful to consider early adoption of WGS while timely anticipating on unforeseen developments before final conclusions are reached.
KW - budget impact
KW - cost-effectiveness
KW - decision analytic model
KW - future scenarios
KW - implementation
KW - molecular diagnostics
KW - value of information
KW - whole-genome sequencing
UR - http://www.scopus.com/inward/record.url?scp=85135892366&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.jval.2022.07.006
DO - https://doi.org/10.1016/j.jval.2022.07.006
M3 - Article
C2 - 35973926
SN - 1098-3015
VL - 26
SP - 71
EP - 80
JO - Value in Health
JF - Value in Health
IS - 1
ER -