Cell-Free DNA at Diagnosis for Stage IV Non-Small Cell Lung Cancer: Costs, Time to Diagnosis and Clinical Relevance
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Clinical Data Retrieval
2.2. Discrete Event Simulation
- (1)
- Diagnostic procedure with tissue biopsy alone (standard of care). Patients undergo 1, or 2 tissue biopsy attempts; in case of failure (“tissue only”);
- (2)
- Diagnostic procedure starting with cfDNA, if no definitive result is retrieved, a tissue biopsy is still required; (“cfDNA first”); and
- (3)
- Diagnostic procedure starting with tissue biopsy, if the first attempt failed, blood is collected for cfDNA analysis. performed (“tissue first”).
2.3. Input for the Model
2.3.1. Patient Data
2.3.2. Throughput Time
- (1)
- Immunohistochemical (IHC) staining was performed in parallel with NGS. The mean number of days between tissue arrival and request for IHC and NGS was three days. The throughput time of NGS was estimated based on the mean throughput time of eight days, measured by the pathology department of the Netherlands Cancer Institute for isolation and analysis.
- (2)
- Complementary molecular diagnostics (e.g., rtPCR/FISH) after NGS were performed in parallel. The mean throughput time of rtPCR and FISH combined was estimated to be five days, based on estimations of the pathology department of the Netherlands Cancer Institute.
- (3)
- The throughput time for cfDNA sequencing including blood withdrawal was estimated based on expert opinions (LB, DV), and set to a mean of 7.5 days. The assumption was made that isolation and sequencing for cfDNA analysis would be performed once a week.
2.3.3. Costs of Tissue-Based Diagnostics
2.3.4. Costs of cfDNA Analysis
2.4. Definitions of Success and Output of the Model
- -
- A “clinically relevant test result” is defined as a simulated patient who has a negative or positive test result after molecular diagnostics without any failures. This includes patients with a “complete test result,” but also patients with a nearly “complete result.” For example, a cfDNA test result positive for KRAS but without biopsy PDL1 staining is considered clinically relevant. See the definitions of the possible diagnostic results below:
- “Complete Test Result”: Patients have successfully undergone all required tests for the previously mentioned oncogenes and PDL1, and there is a complete result. This also applies to patients with all required tests performed, but negative results for all 9 oncogenes and PDL1 staining.The proportion of patients with “a positive test result for a biomarker” means the simulated cases for which a biomarker is found and indicates the proportion of simulated patients with an oncogenic EGFR, BRAF, ALK, ROS, KRAS, METe14, RET, NRAS, or ERBB2 mutation (including all oncogenic BRAF and KRAS variants).
- ”Incomplete test result: cfDNA targets found but no PDL1 status (failed biopsy)” applies to patients with a complete molecular profile, or a result based on cfDNA but incomplete subsequent tissue analysis (e.g., cfDNA positive for KRAS but no PDL1 staining available). This is considered clinically relevant
- -
- If there is no test result for the nine oncogenes (EGFR, BRAF, ALK, ROS, KRAS, METe14, RET, NRAS, and ERBB2) due to failure of biopsies or failure of NGS, then a simulated patient is considered to have “no conclusive molecular result.”
2.5. Model Description
2.5.1. Input Data
2.5.2. Discrete Event Simulation (DES)
2.5.3. Deterministic Analysis
2.5.4. Probabilistic Analysis
2.5.5. Scenario Analysis
3. Results
3.1. Deterministic Analysis
3.2. Probabilistic Analysis
3.3. Scenario Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Rosell, R.; Karachaliou, N. Large-scale screening for somatic mutations in lung cancer. Lancet 2016, 387, 1354–1356. [Google Scholar] [CrossRef]
- Kris, M.G.; Johnson, B.E.; Berry, L.D.; Kwiatkowski, D.J.; Iafrate, A.J.; Wistuba, I.I.; Varella-Garcia, M.; Franklin, W.A.; Aronson, S.L.; Su, P.F.; et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA 2014, 311, 1998–2006. [Google Scholar] [CrossRef] [PubMed]
- Barlesi, F.; Mazieres, J.; Merlio, J.P.; Debieuvre, D.; Mosser, J.; Lena, H.; Ouafik, L.H.; Besse, B.; Rouquette, I.; Westeel, V.; et al. Routine molecular profiling of patients with advanced non-small-cell lung cancer: Results of a 1-year nationwide programme of the French Cooperative Thoracic Intergroup (IFCT). Lancet 2016, 387, 1415–1426. [Google Scholar] [CrossRef]
- Gagan, J.; Van Allen, E.M. Next-generation sequencing to guide cancer therapy. Genome Med. 2015, 7, 80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhang, Y.; Shi, L.; Simoff, M.J.; Wagner, O.J.; Lavin, J. Biopsy frequency and complications among lung cancer patients in the United States. Lung Cancer Manag. 2020, 9, Lmt40. [Google Scholar] [CrossRef] [PubMed]
- Otto, S.; Mensel, B.; Friedrich, N.; Schäfer, S.; Mahlke, C.; von Bernstorff, W.; Bock, K.; Hosten, N.; Kühn, J.P. Predictors of technical success and rate of complications of image-guided percutaneous transthoracic lung needle biopsy of pulmonary tumors. PLoS ONE 2015, 10, e0124947. [Google Scholar]
- Heerink, W.J.; de Bock, G.H.; de Jonge, G.J.; Groen, H.J.; Vliegenthart, R.; Oudkerk, M. Complication rates of CT-guided transthoracic lung biopsy: Meta-analysis. Eur. Radiol. 2017, 27, 138–148. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Siravegna, G.; Mussolin, B.; Venesio, T.; Marsoni, S.; Seoane, J.; Dive, C.; Papadopoulos, N.; Kopetz, S.; Corcoran, R.B.; Siu, L.L.; et al. How liquid biopsies can change clinical practice in oncology. Ann. Oncol. 2019, 30, 1580–1590. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cescon, D.W.; Bratman, S.V.; Chan, S.M.; Siu, L.L. Circulating tumor DNA and liquid biopsy in oncology. Nat. Cancer 2020, 1, 276–290. [Google Scholar] [CrossRef] [PubMed]
- Aggarwal, C.; Rolfo, C.D.; Oxnard, G.R.; Gray, J.E.; Sholl, L.M.; Gandara, D.R. Strategies for the successful implementation of plasma-based NSCLC genotyping in clinical practice. Nat. Rev. Clin. Oncol. 2021, 18, 56–62. [Google Scholar] [CrossRef] [PubMed]
- Schouten, R.D.; Vessies, D.C.; Bosch, L.J.; Barlo, N.P.; van Lindert, A.S.; Cillessen, S.A.; van den Broek, D.; van den Heuvel, M.M.; Monkhorst, K. Clinical Utility of Plasma-Based Comprehensive Molecular Profiling in Advanced Non–Small-Cell Lung Cancer. JCO Precis. Oncol. 2021, 5, 1112–1121. [Google Scholar] [CrossRef] [PubMed]
- Leighl, N.B.; Page, R.D.; Raymond, V.M.; Daniel, D.B.; Divers, S.G.; Reckamp, K.L.; Villalona-Calero, M.A.; Dix, D.; Odegaard, J.I.; Lanman, R.B.; et al. Clinical Utility of Comprehensive Cell-free DNA Analysis to Identify Genomic Biomarkers in Patients with Newly Diagnosed Metastatic Non-small Cell Lung Cancer. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2019, 25, 4691–4700. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pasmans, C.T.; Tops, B.B.; Steeghs, E.M.; Coupé, V.M.; Grünberg, K.; de Jong, E.K.; Schuuring, E.M.; Willems, S.M.; Ligtenberg, M.J.L.; Retèl, V.P.; et al. Micro-costing diagnostics in oncology: From single-gene testing to whole- genome sequencing. Expert Rev. Pharmacoecon. Outcomes Res. 2021, 21, 413–414. [Google Scholar] [CrossRef] [PubMed]
- Hakkaart-van Roijen, L.; Tan, S.S.; Bouwmans, C.A.M. Manual for Cost Analyses, Methods and Standard Prices for Economic Evaluations in Health Care; Zorginstituut Nederland (The National Health Care Institute): Diemen, The Netherlands, 2015. [Google Scholar]
- Dutch Healthcare Authority (Nederlandse Zorgautoriteit [NZa]). Pricelist Healthcare Products 2016 (Tarievenlijst DBC-Zorgproducten en Overige Producten 2016). Available online: https://puc.overheid.nl/nza/ (accessed on 19 December 2016).
- Degeling, K.; Franken, M.D.; May, A.M.; van Oijen, M.G.; Koopman, M.; Punt, C.J.; IJzerman, M.J.; Koffijberg, H. Matching the model with the evidence: Comparing discrete event simulation and state-transition modeling for time-to-event predictions in a cost-effectiveness analysis of treatment in metastatic colorectal cancer patients. Cancer Epidemiol. 2018, 57, 60–67. [Google Scholar] [CrossRef] [PubMed]
- Degeling, K.; Koffijberg, H.; Franken, M.D.; Koopman, M.; IJzerman, M.J. Comparing Strategies for Modeling Competing Risks in Discrete-Event Simulations: A Simulation Study and Illustration in Colorectal Cancer. Med. Decis. Mak. 2019, 39, 57–73. [Google Scholar] [CrossRef] [Green Version]
- Briggs, A.; Sculpher, M.; Claxton, K. Decicion Modelling for Health Economic Evaluation; Oxford Unversity Press: Oxford, UK, 2006. [Google Scholar]
- Remon, J.; Lacroix, L.; Jovelet, C.; Caramella, C.; Howarth, K.; Plagnol, V.; Rosenfeld, N.; Morris, C.; Mezquita, L.; Pannet, C.; et al. Real-World Utility of an Amplicon-Based Next-Generation Sequencing Liquid Biopsy for Broad Molecular Profiling in Patients with Advanced Non-Small-Cell Lung Cancer. JCO Precis. Oncol. 2019, 3, 1–14. [Google Scholar] [CrossRef]
- Paweletz, C.P.; Sacher, A.G.; Raymond, C.K.; Alden, R.S.; O’Connell, A.; Mach, S.L.; Kuang, Y.; Gandhi, L.; Kirschmeier, P.; English, J.M.; et al. Bias-Corrected Targeted Next-Generation Sequencing for Rapid, Multiplexed Detection of Actionable Alterations in Cell-Free DNA from Advanced Lung Cancer Patients. Clin. Cancer Res. 2016, 22, 915–922. [Google Scholar] [CrossRef] [Green Version]
- Müller, J.N.; Falk, M.; Talwar, J.; Neemann, N.; Mariotti, E.; Bertrand, M.; Zacherle, T.; Lakis, S.; Menon, R.; Gloeckner, C.; et al. Concordance between Comprehensive Cancer Genome Profiling in Plasma and Tumor Specimens. J. Thorac. Oncol. 2017, 12, 1503–1511. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rolfo, C.; Mack, P.; Scagliotti, G.V.; Aggarwal, C.; Arcila, M.E.; Barlesi, F.; Bivona, T.; Diehn, M.; Dive, C.; Dziadziuszko, R.; et al. Liquid Biopsy for Advanced Non-Small Cell Lung Cancer: A Consensus Statement from The International Association for the Study of Lung Cancer (IASLC). J. Thorac. Oncol. 2021, 16, 1647–1662. [Google Scholar] [CrossRef]
Scenarios | ||||||
---|---|---|---|---|---|---|
Outcomes of Deterministic Analysis | 1. BIOPSY ALONE | 1. BIOPSY ALONE | 1. BIOPSY ALONE | |||
Scenario 1 | 10,000 Patients | Scenario 2 | 10,000 Patients | Scenario 3 | 10,000 Patients | |
Cost | ||||||
Mean cost of the run in Euro (SD) | €2294 | (€868) | €3350 | (€1172) | €2443 | (€592) |
Throughput time | ||||||
Median throughput time of the run, in days (IQR) | 20 | (16–23) | 10 | (7–25) | 18 | (16–22) |
Test result | ||||||
Nr. of patients with clinically relevant test result in the run (%) | 8414 | (84%) | 9187 | (92%) | 8767 | (88%) |
Complete test result (%) | 8414 | (84%) | 8808 | (88%) | 7734 | (77%) |
Incomplete: cfDNA targets but no PDL1 status (%) | NA | - | 379 | (4%) | 1033 | (10%) |
Nr. of patients with no conclusive result (%) | 1586 | (16%) | 813 | (8%) | 1233 | (12%) |
Outcomes of Probabilistic Analysis | Scenarios | ||||||||
---|---|---|---|---|---|---|---|---|---|
1. BIOPSY ALONE | 2. cfDNA at Diagnosis, if EGFR, BRAF ALK, ROS1: Biopsy Cancelled | 3. cfDNA if Biopsy Failed | |||||||
1000 Runs | Scen. 2 | 1000 Runs | Scen. 3 | 1000 Runs | |||||
95% CrI | 95% CrI | 95% CrI | |||||||
Mean | Upper | Lower | Mean | Upper | Lower | Mean | Upper | Lower | |
Cost | |||||||||
Mean price of all runs, in Euro | €2304 | €2067 | €2507 | €3218 | €3071 | €3396 | €2448 | €2382 | €2506 |
Throughput time | |||||||||
Mean throughput time of all runs, in days | 20 | 17 | 23 | 9 | 7.0 | 10.6 | 19 | 16.2 | 21.7 |
Clinically relevant test result | |||||||||
Mean nr. of patients with clinically relevant test result of all runs | 8397 (84%) | 6978 | 9428 | 9286 (93%) | 8604 | 9759 | 9272 (93%) | 8588 | 9889 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Koole, S.N.; Vessies, D.C.L.; Schuurbiers, M.M.F.; Kramer, A.; Schouten, R.D.; Degeling, K.; Bosch, L.J.W.; van den Heuvel, M.M.; van Harten, W.H.; van den Broek, D.; et al. Cell-Free DNA at Diagnosis for Stage IV Non-Small Cell Lung Cancer: Costs, Time to Diagnosis and Clinical Relevance. Cancers 2022, 14, 1783. https://doi.org/10.3390/cancers14071783
Koole SN, Vessies DCL, Schuurbiers MMF, Kramer A, Schouten RD, Degeling K, Bosch LJW, van den Heuvel MM, van Harten WH, van den Broek D, et al. Cell-Free DNA at Diagnosis for Stage IV Non-Small Cell Lung Cancer: Costs, Time to Diagnosis and Clinical Relevance. Cancers. 2022; 14(7):1783. https://doi.org/10.3390/cancers14071783
Chicago/Turabian StyleKoole, Simone N., Daan C. L. Vessies, Milou M. F. Schuurbiers, Astrid Kramer, Robert D. Schouten, Koen Degeling, Linda J. W. Bosch, Michel M. van den Heuvel, Wim H. van Harten, Daan van den Broek, and et al. 2022. "Cell-Free DNA at Diagnosis for Stage IV Non-Small Cell Lung Cancer: Costs, Time to Diagnosis and Clinical Relevance" Cancers 14, no. 7: 1783. https://doi.org/10.3390/cancers14071783