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Bayle A, Marino P, Baffert S, Margier J, Bonastre J. [Cost of high-throughput sequencing (NGS) technologies: Literature review and insights]. Bull Cancer 2024; 111:190-198. [PMID: 37852801 DOI: 10.1016/j.bulcan.2023.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 08/02/2023] [Accepted: 08/28/2023] [Indexed: 10/20/2023]
Abstract
Although high-throughput sequencing technologies (Next-Generation Sequencing [NGS]) are revolutionizing medicine, the estimation of their production cost for pricing/tariffication by health systems raises methodological questions. The objective of this review of cost studies of high-throughput sequencing techniques is to draw lessons for producing robust cost estimates of these techniques. We analyzed, using an eleven item analysis framework, micro-costing studies of high-throughput sequencing technologies (n=17), including two studies conducted in the French context. The factors of variability between the studies that we identified were temporality (early evaluation of the innovation vs. evaluation of a mature technology), the choice of cost evaluation method (scope, micro- vs. gross-costing technique), the choice of production steps observed and the transposability of these studies. The lessons we have learned are that it is necessary to have a comprehensive vision of the sequencing production process by integrating all the steps from the collection of the biological sample to the delivery of the result to the clinician. It is also important to distinguish between what refers to the local context and what refers to the general context, by favouring the use of mixed methods to calculate costs. Finally, sensitivity analyses and periodic re-estimation of the costs of the techniques must be carried out in order to be able to revise the tariffs according to changes linked to the diffusion of the technology and to competition between reagent suppliers.
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Affiliation(s)
- Arnaud Bayle
- Gustave-Roussy, université Paris-Saclay, bureau biostatistique et épidémiologie, Villejuif, France; Inserm, université Paris-Saclay, CESP U1018 Oncostat, labelisé Ligue contre le cancer, Villejuif, France.
| | - Patricia Marino
- Institut Paoli-Calmettes, SESSTIM, équipe CAN-BIOS, Marseille, France
| | | | - Jennifer Margier
- Hospices civils de Lyon, service d'évaluation économique en santé (SEES), Lyon, France
| | - Julia Bonastre
- Gustave-Roussy, université Paris-Saclay, bureau biostatistique et épidémiologie, Villejuif, France; Inserm, université Paris-Saclay, CESP U1018 Oncostat, labelisé Ligue contre le cancer, Villejuif, France
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2
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Thangavelu T, Wirta V, Orsmark-Pietras C, Cavelier L, Fioretos T, Barbany G, Olsson-Arvidsson L, Pandzic T, Staffas A, Rosenquist R, Levin LÅ. Micro-costing of genetic diagnostics in acute leukemia in Sweden: from standard-of-care to whole-genome sequencing. J Med Econ 2024; 27:1053-1060. [PMID: 39101813 DOI: 10.1080/13696998.2024.2387515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/29/2024] [Accepted: 07/30/2024] [Indexed: 08/06/2024]
Abstract
AIMS AND BACKGROUND Whole-genome sequencing (WGS) is increasingly applied in clinical practice and expected to replace standard-of-care (SoC) genetic diagnostics in hematological malignancies. This study aims to assess and compare the fully burdened cost ('micro-costing') per patient for Swedish laboratories using WGS and SoC, respectively, in pediatric and adult patients with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). METHODS The resource use and cost details associated with SoC, e.g. chromosome banding analysis, fluorescent in situ hybridization, and targeted sequencing analysis, were collected via activity-based costing methods from four diagnostic laboratories. For WGS, corresponding data was collected from two of the centers. A simulation-based scenario model was developed for analyzing the WGS cost based on different annual sample throughput to evaluate economy of scale. RESULTS The average SoC total cost per patient was €2,465 for pediatric AML and €2,201 for pediatric ALL, while in adults, the corresponding cost was €2,458 for AML and €1,207 for ALL. The average WGS cost (90x tumor/30x normal; sequenced on the Illumina NovaSeq 6000 platform) was estimated to €3,472 based on an annual throughput of 2,500 analyses, however, with an annual volume of 7,500 analyses the average cost would decrease by 23% to €2,671. CONCLUSION In summary, WGS is currently more costly than SoC, however the cost can be reduced by utilizing laboratories with higher throughput and by the expected decline in cost of reagents. Our data provides guidance to decision-makers for the resource allocation needed when implementing WGS in diagnostics of hematological malignancies.
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Affiliation(s)
- Tharshini Thangavelu
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Department of Register and Statistics, The National Board of Health and Welfare, Stockholm, Sweden
| | - Valtteri Wirta
- Science for Life Laboratory, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, School of Engineering Sciences in Chemistry Biotechnology and Health, KTH Royal Instititute of Technology, Stockholm, Sweden
- Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | - Christina Orsmark-Pietras
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
- Department of Clinical Genetics, Pathology, and Molecular Diagnostics, Office for Medical Services, Lund, Sweden
| | - Lucia Cavelier
- Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Thoas Fioretos
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
- Department of Clinical Genetics, Pathology, and Molecular Diagnostics, Office for Medical Services, Lund, Sweden
| | - Gisela Barbany
- Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Linda Olsson-Arvidsson
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
- Department of Clinical Genetics, Pathology, and Molecular Diagnostics, Office for Medical Services, Lund, Sweden
| | - Tatjana Pandzic
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Anna Staffas
- Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Richard Rosenquist
- Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Lars-Åke Levin
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
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Afonso S, Vieira AC, Pereira C, Oliveira MD. Advancing hospital-based health technology assessment: evaluating genomic panel contracting strategies for blood tumors through a multimethodology. Int J Technol Assess Health Care 2023; 39:e76. [PMID: 38130159 PMCID: PMC11579695 DOI: 10.1017/s0266462323002751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 10/26/2023] [Accepted: 11/14/2023] [Indexed: 12/23/2023]
Abstract
INTRODUCTION The adoption of genomic technologies in the context of hospital-based health technology assessment presents multiple practical and organizational challenges. OBJECTIVE This study aimed to assist the Instituto Português de Oncologia de Lisboa Francisco Gentil (IPO Lisboa) decision makers in analyzing which acute myeloid leukemia (AML) genomic panel contracting strategies had the highest value-for-money. METHODS A tailored, three-step approach was developed, which included: mapping clinical pathways of AML patients, building a multicriteria value model using the MACBETH approach to evaluate each genomic testing contracting strategy, and estimating the cost of each strategy through Monte Carlo simulation modeling. The value-for-money of three contracting strategies - "Standard of care (S1)," "FoundationOne Heme test (S2)," and "New diagnostic test infrastructure (S3)" - was then analyzed through strategy landscape and value-for-money graphs. RESULTS Implementing a larger gene panel (S2) and investing in a new diagnostic test infrastructure (S3) were shown to generate extra value, but also to entail extra costs in comparison with the standard of care, with the extra value being explained by making available additional genetic information that enables more personalized treatment and patient monitoring (S2 and S3), access to a broader range of clinical trials (S2), and more complete databases to potentiate research (S3). CONCLUSION The proposed multimethodology provided IPO Lisboa decision makers with comprehensive and insightful information regarding each strategy's value-for-money, enabling an informed discussion on whether to move from the current Strategy S1 to other competing strategies.
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Affiliation(s)
- Susana Afonso
- CEGIST, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Ana C.L. Vieira
- CEGIST, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Carla Pereira
- Instituto Português de Oncologia de Lisboa Francisco Gentil (IPO Lisboa), Lisbon, Portugal
| | - Mónica D. Oliveira
- CEGIST, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- iBB – Institute for Bioengineering and Biosciences and i4HB – Associate Laboratory Institute for Health and Bioeconomy, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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4
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You J, Osea J, Mendoza S, Shiomi T, Gallego E, Pham B, Kim A, Sinay-Smith A, Zayas Z, Neto AG, Boytard L, Chiriboga L, Cotzia P, Moreira AL. Automated and robust extraction of genomic DNA from various leftover blood samples. Anal Biochem 2023; 678:115271. [PMID: 37543277 DOI: 10.1016/j.ab.2023.115271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/27/2023] [Accepted: 07/31/2023] [Indexed: 08/07/2023]
Abstract
With the development of genomic technologies, the isolation of genomic DNA (gDNA) from clinical samples is increasingly required for clinical diagnostics and research studies. In this study, we explored the potential of utilizing various leftover blood samples obtained from routine clinical tests as a viable source of gDNA. Using an automated method with optimized pre-treatments, we obtained gDNA from seven types of clinical leftover blood, with average yields of gDNA ranging from 3.11 ± 0.45 to 22.45 ± 4.83 μg. Additionally, we investigated the impact of storage conditions on gDNA recovery, resulting in yields of 8.62-68.08 μg when extracting gDNA from EDTA leftover blood samples stored at 4 °C for up to 13 weeks or -80 °C for up to 78 weeks. Furthermore, we successfully obtained sequenceable gDNA from both Serum Separator Tube and EDTA Tube using a 96-well format extraction, with yields ranging from 0.61 to 71.29 μg and 3.94-215.98 μg, respectively. Our findings demonstrate the feasibility of using automated high-throughput platforms for gDNA extraction from various clinical leftover blood samples with the proper pre-treatments.
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Affiliation(s)
- Jianlan You
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA.
| | - Jan Osea
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Sandra Mendoza
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Tomoe Shiomi
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Estefania Gallego
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Bernice Pham
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Angie Kim
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Abraham Sinay-Smith
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Zasha Zayas
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Antonio G Neto
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Ludovic Boytard
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Luis Chiriboga
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA; Department of Pathology, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Paolo Cotzia
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Andre L Moreira
- Center for Biospecimen Research & Development, New York University Grossman School of Medicine, New York, NY, 10016, USA; Department of Pathology, New York University Grossman School of Medicine, New York, NY, 10016, USA
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5
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Topham JT, Renouf DJ, Schaeffer DF. Circulating tumor DNA: toward evolving the clinical paradigm of pancreatic ductal adenocarcinoma. Ther Adv Med Oncol 2023; 15:17588359231157651. [PMID: 36895849 PMCID: PMC9989430 DOI: 10.1177/17588359231157651] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 01/30/2023] [Indexed: 03/06/2023] Open
Abstract
Over a decade of sequencing-based genomics research has unveiled a diverse somatic mutation landscape across patients with pancreatic ductal adenocarcinoma (PDAC), and the identification of druggable mutations has aligned with the development of novel targeted therapeutics. However, despite these advances, direct translation of years of PDAC genomics research into the clinical care of patients remains a critical and unmet need. Technologies that enabled the initial mapping of the PDAC mutation landscape, namely whole-genome and transcriptome sequencing, remain overly expensive in terms of both time and financial resources. Consequentially, dependence on these technologies to identify the relatively small subset of patients with actionable PDAC alterations has greatly impeded enrollment for clinical trials testing novel targeted therapies. Liquid biopsy tumor profiling using circulating tumor DNA (ctDNA) generates new opportunities by overcoming these challenges while further addressing issues particularly relevant to PDAC, namely, difficulty of obtaining tumor tissue via fine-needle biopsy and the need for faster turnaround time due to rapid disease progression. Meanwhile, ctDNA-based approaches for tracking disease kinetics with respect to surgical and therapeutic interventions offer a means to elevate the current clinical management of PDAC toward higher granularity and accuracy. This review provides a clinically focused summary of ctDNA advances, limitations, and opportunities in PDAC and postulates ctDNA sequencing technology as a catalyst for evolving the clinical decision-making paradigm of this disease.
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Affiliation(s)
| | - Daniel J Renouf
- Pancreas Centre BC, Vancouver, BC, Canada.,Division of Medical Oncology, BC Cancer, Vancouver, BC, Canada.,Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - David F Schaeffer
- Division of Anatomic Pathology, Vancouver General Hospital, 910 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada.,Pancreas Centre BC, Vancouver, BC, Canada.,Department of Pathology and Laboratory Medicine, UBC, Vancouver, BC, Canada
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6
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Hayeems RZ, Bernier F, Boycott KM, Hartley T, Michaels-Igbokwe C, Marshall DA. Positioning whole exome sequencing in the diagnostic pathway for rare disease to optimise utility: a protocol for an observational cohort study and an economic evaluation. BMJ Open 2022; 12:e061468. [PMID: 36216418 PMCID: PMC9557316 DOI: 10.1136/bmjopen-2022-061468] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
INTRODUCTION Despite the superior diagnostic performance of exome and genome sequencing compared with conventional genetic tests, evidence gaps related to clinical utility and cost effectiveness have limited their availability in routine clinical practice in many jurisdictions. To inform adoption and reimbursement policy, this protocol provides a chain of evidence approach to determining the diagnostic utility, clinical utility and cost-effectiveness of whole exome sequencing (WES) from seven medical genetic centres in two Canadian provinces. METHODS AND ANALYSIS Using a multicentre observational cohort design, we will extract data specific to the pre-WES diagnostic pathway and 1-year post-WES medical management from electronic medical records for 650 patients with rare disease of suspected genetic aetiology who receive WES. The date from the clinical record will be linked to provincial administrative health database to capture healthcare resource use and estimate costs. Our analysis will: (1) define and describe diagnostic testing pathways that occur prior to WES among patients with rare disease, (2) determine the diagnostic utility of WES, characterised as the proportion of patients for whom causative DNA variants are identified, (3) determine the clinical utility of WES, characterised as a change in medical management triggered by WES results, (4) determine the pattern and cost of health service utilisation prior and 1 year following WES among patients who receive a diagnosis, do not receive a diagnosis, or receive an uncertain diagnosis and (5) estimate the cost-effectiveness of WES compared with conventional diagnostic testing pathways, measured by the incremental cost per additional patient diagnosed by WES using simulation modelling. ETHICS AND DISSEMINATION This protocol was approved by Clinical Trials Ontario (CTO-1577) and research ethics boards at the University of Calgary (REB18-0744 and REB20-1449) and University of Alberta (Pro0009156). Findings will be disseminated through academic publications and policy reports.
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Affiliation(s)
- Robin Z Hayeems
- Child Health Evaluative Sciences, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Francois Bernier
- Department of Medical Genetics, Alberta Children's Hospital, Calgary, Alberta, Canada
- Cummings School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Kym M Boycott
- Department of Genetics, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
- Department of Paediatrics, Facuty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Taila Hartley
- Department of Genetics, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Christine Michaels-Igbokwe
- Cummings School of Medicine, University of Calgary, Calgary, Alberta, Canada
- O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada
| | - Deborah A Marshall
- Cummings School of Medicine, University of Calgary, Calgary, Alberta, Canada
- O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada
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Abbott M, McKenzie L, Moran BVG, Heidenreich S, Hernández R, Hocking-Mennie L, Clark C, Gomes J, Lampe A, Baty D, McGowan R, Miedzybrodzka Z, Ryan M. Continuing the sequence? Towards an economic evaluation of whole genome sequencing for the diagnosis of rare diseases in Scotland. J Community Genet 2022; 13:487-501. [PMID: 34415556 PMCID: PMC9530076 DOI: 10.1007/s12687-021-00541-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 07/15/2021] [Indexed: 11/21/2022] Open
Abstract
Novel developments in genomic medicine may reduce the length of the diagnostic odyssey for patients with rare diseases. Health providers must thus decide whether to offer genome sequencing for the diagnosis of rare conditions in a routine clinical setting. We estimated the costs of singleton standard genetic testing and trio-based whole genome sequencing (WGS), in the context of the Scottish Genomes Partnership (SGP) study. We also explored what users value about genomic sequencing. Insights from the costing and value assessments will inform a subsequent economic evaluation of genomic medicine in Scotland. An average cost of £1,841 per singleton was estimated for the standard genetic testing pathway, with significant variability between phenotypes. WGS cost £6625 per family trio, but this estimate reflects the use of WGS during the SGP project and large cost savings may be realised if sequencing was scaled up. Patients and families valued (i) the chance of receiving a diagnosis (and the peace of mind and closure that brings); (ii) the information provided by WGS (including implications for family planning and secondary findings); and (iii) contributions to future research. Our costings will be updated to address limitations of the current study for incorporation in budget impact modelling and cost-effectiveness analysis (cost per diagnostic yield). Our insights into the benefits of WGS will guide the development of a discrete choice experiment valuation study. This will inform a user-perspective cost-benefit analysis of genome-wide sequencing, accounting for the broader non-health outcomes. Taken together, our research will inform the long-term strategic development of NHS Scotland clinical genetics testing services, and will be of benefit to others seeking to undertake similar evaluations in different contexts.
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Affiliation(s)
- Michael Abbott
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK.
| | - Lynda McKenzie
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
| | | | - Sebastian Heidenreich
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
- Evidera Inc., London, UK
| | - Rodolfo Hernández
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
| | | | - Caroline Clark
- Department of Medical Genetics, University of Aberdeen, Aberdeen, UK
- NHS Grampian Regional Genetics Service, Aberdeen Royal Infirmary, Aberdeen, UK
| | - Joana Gomes
- NHS Grampian Regional Genetics Service, Aberdeen Royal Infirmary, Aberdeen, UK
| | - Anne Lampe
- South East Scotland Clinical Genetics Service, Western General Hospital, Edinburgh, UK
| | - David Baty
- NHS Tayside Regional Genetics Service, Ninewells Hospital, Dundee, UK
| | - Ruth McGowan
- South East Scotland Clinical Genetics Service, Queen Elizabeth University Hospital, Glasgow, UK
| | | | - Mandy Ryan
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
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8
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Bayle A, Droin N, Besse B, Zou Z, Boursin Y, Rissel S, Solary E, Lacroix L, Rouleau E, Borget I, Bonastre J. Whole exome sequencing in molecular diagnostics of cancer decreases over time: evidence from a cost analysis in the French setting. THE EUROPEAN JOURNAL OF HEALTH ECONOMICS : HEPAC : HEALTH ECONOMICS IN PREVENTION AND CARE 2021; 22:855-864. [PMID: 33765190 DOI: 10.1007/s10198-021-01293-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 03/16/2021] [Indexed: 05/06/2023]
Abstract
OBJECTIVES Although high-throughput sequencing is revolutionising medicine, data on the actual cost of whole exome sequencing (WES) applications are needed. We aimed at assessing the cost of WES at a French cancer institute in 2015 and 2018. METHODS Actual costs of WES application in oncology research were determined using both micro-costing and gross-costing for the years 2015 and 2018, before and after the acquisition of a new sequencer. The entire workflow process of a WES test was tracked, and the number and unit price of each resource were identified at the most detailed level, from library preparation to bioinformatics analyses. In addition, we conducted an ad hoc analysis of the bioinformatics storage costs of data issued from WES analyses. RESULTS The cost of WES has decreased substantially, from €1921 per sample (i.e. cost of €3842 per patient) in 2015 to €804 per sample (i.e. cost of €1,608 per patient) in 2018, representing a decrease of 58%. In the meantime, the cost of bioinformatics storage has increased from €19,836 to €200,711. CONCLUSION This study suggests that WES cost has decreased significantly in recent years. WES has become affordable, even though clinical utility and efficiency still need to be confirmed.
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Affiliation(s)
- Arnaud Bayle
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France.
- Centre for Research in Epidemiology and Population Health, INSERM U1018, Villejuif, France.
- Université Paris-Sud, Orsay, France.
| | - N Droin
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
- UMS CNRS 3655 and INSERM US23, AMMICa, Gustave Roussy, Villejuif, France
| | - B Besse
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
| | - Z Zou
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
- Centre for Research in Epidemiology and Population Health, INSERM U1018, Villejuif, France
| | - Y Boursin
- Digital Transformation and IT System Department, Gustave Roussy Cancer Centre, 94805, Villejuif, France
| | - S Rissel
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
| | - E Solary
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
- Université Paris-Sud, Orsay, France
| | - L Lacroix
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
- UMS CNRS 3655 and INSERM US23, AMMICa, Gustave Roussy, Villejuif, France
- Université Paris-Sud, Orsay, France
| | - E Rouleau
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
| | - I Borget
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
- Centre for Research in Epidemiology and Population Health, INSERM U1018, Villejuif, France
- Université Paris-Sud, Orsay, France
| | - J Bonastre
- Biostatistics and Epidemiology Unit, Gustave Roussy Cancer Centre, 114 rue Edouard Vaillant, 94805, Villejuif Cedex, France
- Centre for Research in Epidemiology and Population Health, INSERM U1018, Villejuif, France
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9
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Simons M, Van De Ven M, Coupé V, Joore M, IJzerman M, Koffijberg E, Frederix G, Uyl-De Groot C, Cuppen E, Van Harten W, Retèl V. Early technology assessment of using whole genome sequencing in personalized oncology. Expert Rev Pharmacoecon Outcomes Res 2021; 21:343-351. [PMID: 33910430 DOI: 10.1080/14737167.2021.1917386] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Introduction: Personalized medicine-based treatments in advanced cancer hold the promise to offer substantial health benefits to genetic subgroups, but require efficient biomarker-based patient stratification to match the right treatment and may be expensive. Standard molecular diagnostics are currently very heterogeneous, and tests are often performed sequentially. The alternative to whole genome sequencing (WGS) i.e. simultaneously testing for all relevant DNA-based biomarkers thereby allowing immediate selection of the most optimal therapy, is more costly than current techniques. In the current implementation stage, it is important to explore the added value and cost-effectiveness of using WGS on a patient level and to assess optimal introduction of WGS on the level of the healthcare system.Areas covered: First, an overview of current worldwide initiatives concerning the use of WGS in clinical practice for cancer diagnostics is given. Second, a comprehensive, early health technology assessment (HTA) approach of evaluating WGS in the Netherlands is described, relating to the following aspects: diagnostic value, WGS-based treatment decisions, assessment of long-term health benefits and harms, early cost-effectiveness modeling, nation-wide organization, and Ethical, Legal and Societal Implications.Expert opinion: This study provides evidence to guide further development and implementation of WGS in clinical practice and the healthcare system.
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Affiliation(s)
- Martijn Simons
- Department of Clinical Epidemiology and Medical Technology Assessment, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Michiel Van De Ven
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Veerle Coupé
- Department of Epidemiology and Data Science, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Manuela Joore
- Department of Clinical Epidemiology and Medical Technology Assessment, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Maarten IJzerman
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, The Netherlands.,University of Melbourne Centre for Cancer Research, Melbourne Australia
| | - Erik Koffijberg
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Geert Frederix
- Division of Pharmacoepidemiology and Clinical Pharmacology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Carin Uyl-De Groot
- Erasmus School of Health Policy & Management (ESHPM), Erasmus University, Rotterdam, The Netherlands
| | - Edwin Cuppen
- Center for Molecular Medicine and Oncode Institute, University Medical Center Utrecht, Utrecht, The Netherlands.,Hartwig Medical Foundation, Amsterdam, The Netherlands
| | - Wim Van Harten
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, The Netherlands.,Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute.,Executive Board, Rijnstate General Hospital, Arnhem, The Netherlands
| | - Valesca Retèl
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, The Netherlands.,Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute
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10
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Pasmans CTB, Tops BBJ, Steeghs EMP, Coupé VMH, Grünberg K, de Jong EK, Schuuring EMD, Willems SM, Ligtenberg MJL, Retèl VP, van Snellenberg H, de Bruijn E, Cuppen E, Frederix GWJ. Micro-costing diagnostics in oncology: from single-gene testing to whole- genome sequencing. Expert Rev Pharmacoecon Outcomes Res 2021; 21:413-414. [PMID: 33852815 DOI: 10.1080/14737167.2021.1917385] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Purpose: Predictive diagnostics play an increasingly important role in personalized medicine for cancer treatment. Whole-genome sequencing (WGS)-based treatment selection is expected to rapidly increase worldwide. This study aimed to calculate and compare the total cost of currently used diagnostic techniques and of WGS in treatment of non-small cell lung carcinoma (NSCLC), melanoma, colorectal cancer (CRC), and gastrointestinal stromal tumor (GIST) in the Netherlands.Methods: The activity-based costing (ABC) method was conducted to calculate total cost of included diagnostic techniques based on data provided by Dutch pathology laboratories and the Dutch-centralized cancer WGS facility. Costs were allocated to four categories: capital costs, maintenance costs, software costs, and operational costs.Results: The total cost per cancer patient per technique varied from € 58 (Sanger sequencing, three amplicons) to € 2925 (paired tumor-normal WGS). The operational costs accounted for the vast majority (over 90%) of the total per cancer patient technique costs.Conclusion: This study outlined in detail all costing aspects and cost prices of current and new diagnostic modalities used in treatment of NSCLC, melanoma, CRC, and GIST in the Netherlands. Detailed cost differences and value comparisons between these diagnostic techniques enable future economic evaluations to support decision-making.
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Affiliation(s)
- Clémence T B Pasmans
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Bastiaan B J Tops
- Princess Máxima Center for Pediatric Oncology, Bilthoven, The Netherlands
| | - Elisabeth M P Steeghs
- Department of Pathology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Veerle M H Coupé
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, VU Amsterdam, Amsterdam, The Netherlands
| | - Katrien Grünberg
- Department of Pathology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Eiko K de Jong
- Department of Pathology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ed M D Schuuring
- Department of Pathology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Stefan M Willems
- Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,PALGA Foundation, Houten, The Netherlands
| | - Marjolijn J L Ligtenberg
- Department of Pathology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.,Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Valesca P Retèl
- Department of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Health Technology and Services Research, University of Twente, Enschede, The Netherlands
| | | | | | - Edwin Cuppen
- Hartwig Medical Foundation, Amsterdam, The Netherlands.,Center for Molecular Medicine and Cancer Genomics Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Geert W J Frederix
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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11
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van de Ven M, Koffijberg H, Retèl V, Monkhorst K, Smit E, van Harten W, IJzerman M. Real-World Utilization of Biomarker Testing for Patients with Advanced Non-Small Cell Lung Cancer in a Tertiary Referral Center and Referring Hospitals. J Mol Diagn 2021; 23:484-494. [PMID: 33493663 DOI: 10.1016/j.jmoldx.2021.01.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 12/21/2020] [Accepted: 01/12/2021] [Indexed: 12/26/2022] Open
Abstract
The continued introduction of biomarkers and innovative testing methods makes already complex diagnosis in patients with stage IV non-small-cell lung cancer (NSCLC) even more complex. This study primarily analyzed variations in biomarker testing in clinical practice in patients referred to a comprehensive cancer center in the Netherlands. The secondary aim was to compare the cost of biomarker testing with the cost of whole-genome sequencing. The cohort included 102 stage IV NSCLC patients who received biomarker testing in 2017 or 2018 at the comprehensive cancer center. The complete biomarker testing history of the cohort was identified using linked data from the comprehensive cancer center and the nationwide network and registry of histopathology and cytopathology in the Netherlands. Unique biomarker-test combinations, costs, turnaround times, and test utilization were examined. The results indicate substantial variation in test utilization and sequences. The mean cost per patient of biomarker testing was 2259.92 ± 1217.10 USD, or 1881.23 ± 1013.15 EUR. Targeted gene panels were most frequently conducted, followed by IHC analysis for programmed cell death protein ligand 1. Typically, the most common biomarkers were assessed within the first tests, and emerging biomarkers were tested further down the test sequence. At the cost of current biomarker testing, replacing current testing with whole-genome sequencing would have led to cost-savings in only two patients (2%).
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Affiliation(s)
- Michiel van de Ven
- Health Technology and Services Research, TechMed Center, University of Twente, Enschede, the Netherlands
| | - Hendrik Koffijberg
- Health Technology and Services Research, TechMed Center, University of Twente, Enschede, the Netherlands
| | - Valesca Retèl
- Health Technology and Services Research, TechMed Center, University of Twente, Enschede, the Netherlands; Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Kim Monkhorst
- Department of Pathology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Egbert Smit
- Department of Thoracic Oncology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Wim van Harten
- Health Technology and Services Research, TechMed Center, University of Twente, Enschede, the Netherlands; Rijnstate General Hospital, Arnhem, the Netherlands
| | - Maarten IJzerman
- Health Technology and Services Research, TechMed Center, University of Twente, Enschede, the Netherlands; Centre for Cancer Research and Centre for Health Policy, University of Melbourne, Melbourne, Australia; Peter MacCallum Cancer Centre, Melbourne, Australia.
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12
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Costa SS, Guimarães LC, Silva A, Soares SC, Baraúna RA. First Steps in the Analysis of Prokaryotic Pan-Genomes. Bioinform Biol Insights 2020; 14:1177932220938064. [PMID: 32843837 PMCID: PMC7418249 DOI: 10.1177/1177932220938064] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 05/26/2020] [Indexed: 01/14/2023] Open
Abstract
Pan-genome is defined as the set of orthologous and unique genes of a specific group of organisms. The pan-genome is composed by the core genome, accessory genome, and species- or strain-specific genes. The pan-genome is considered open or closed based on the alpha value of the Heap law. In an open pan-genome, the number of gene families will continuously increase with the addition of new genomes to the analysis, while in a closed pan-genome, the number of gene families will not increase considerably. The first step of a pan-genome analysis is the homogenization of genome annotation. The same software should be used to annotate genomes, such as GeneMark or RAST. Subsequently, several software are used to calculate the pan-genome such as BPGA, GET_HOMOLOGUES, PGAP, among others. This review presents all these initial steps for those who want to perform a pan-genome analysis, explaining key concepts of the area. Furthermore, we present the pan-genomic analysis of 9 bacterial species. These are the species with the highest number of genomes deposited in GenBank. We also show the influence of the identity and coverage parameters on the prediction of orthologous and paralogous genes. Finally, we cite the perspectives of several research areas where pan-genome analysis can be used to answer important issues.
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Affiliation(s)
- Sávio Souza Costa
- Centro de Genômica e Biologia de Sistemas, Universidade Federal do Pará, Belém, Brazil
- Laboratório de Engenharia Biológica, Espaço Inovação, Parque de Ciência e Tecnologia Guamá, Belém, Brazil
| | - Luís Carlos Guimarães
- Centro de Genômica e Biologia de Sistemas, Universidade Federal do Pará, Belém, Brazil
| | - Artur Silva
- Centro de Genômica e Biologia de Sistemas, Universidade Federal do Pará, Belém, Brazil
- Laboratório de Engenharia Biológica, Espaço Inovação, Parque de Ciência e Tecnologia Guamá, Belém, Brazil
| | - Siomar Castro Soares
- Instituto de Ciências Biológicas e Naturais, Universidade Federal do Triângulo Mineiro, Uberaba, Brazil
| | - Rafael Azevedo Baraúna
- Centro de Genômica e Biologia de Sistemas, Universidade Federal do Pará, Belém, Brazil
- Laboratório de Engenharia Biológica, Espaço Inovação, Parque de Ciência e Tecnologia Guamá, Belém, Brazil
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13
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Estimating the costs of genomic sequencing in cancer control. BMC Health Serv Res 2020; 20:492. [PMID: 32493298 PMCID: PMC7268398 DOI: 10.1186/s12913-020-05318-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 05/11/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Despite the rapid uptake of genomic technologies within cancer care, few studies provide detailed information on the costs of sequencing across different applications. The objective of the study was to examine and categorise the complete costs involved in genomic sequencing for a range of applications within cancer settings. METHODS We performed a cost-analysis using gross and micro-costing approaches for genomic sequencing performed during 2017/2018 across different settings in Brisbane, Australia. Sequencing was undertaken for patients with lung, breast, oesophageal cancers, melanoma or mesothelioma. Aggregated resource data were captured for a total of 1433 patients and point estimates of per patient costs were generated. Deterministic sensitivity analyses addressed the uncertainty in the estimates. Estimated costs to the public health system for resources were categorised into seven distinct activities in the sequencing process: sampling, extraction, library preparation, sequencing, analysis, data storage and clinical reporting. Costs were also aggregated according to labour, consumables, testing, equipment and 'other' categories. RESULTS The per person costs were AU$347-429 (2018 US$240-297) for targeted panels, AU$871-$2788 (2018 US$604-1932) for exome sequencing, and AU$2895-4830 (2018 US$2006-3347) for whole genome sequencing. Cost proportions were highest for library preparation/sequencing materials (average 76.8% of total costs), sample extraction (8.1%), data analysis (9.2%) and data storage (2.6%). Capital costs for the sequencers were an additional AU$34-197 (2018 US$24-67) per person. CONCLUSIONS Total costs were most sensitive to consumables and sequencing activities driven by commercial prices. Per person sequencing costs for cancer are high when tumour/blood pairs require testing. Using the natural steps involved in sequencing and categorising resources accordingly, future evaluations of costs or cost-effectiveness of clinical genomics across cancer projects could be more standardised and facilitate easier comparison of cost drivers.
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14
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Abstract
Abstract
Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research.
Lay Summary
Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.
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15
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Laviolle B, Perche O, Gueyffier F, Bégué É, Bilbault P, Espérou H, Gaillard-Bigot F, Grenet G, Guérin JF, Guillot C, Longeray PH, Morere J, Perrier L, Sanlaville D, Thevenon J, Varoqueaux N. Apport de la génomique dans la médecine de demain, applications cliniques et enjeux. Therapie 2019; 74:1-8. [DOI: 10.1016/j.therap.2018.11.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Accepted: 11/13/2018] [Indexed: 11/24/2022]
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16
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Laviolle B, Denèfle P, Gueyffier F, Bégué É, Bilbault P, Espérou H, Gaillard-Bigot F, Grenet G, Guérin JF, Guillot C, Longeray PH, Morere J, Perche O, Perrier L, Sanlaville D, Thevenon J, Varoqueaux N. The contribution of genomics in the medicine of tomorrow, clinical applications and issues. Therapie 2019; 74:9-15. [DOI: 10.1016/j.therap.2018.11.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Accepted: 11/13/2018] [Indexed: 10/27/2022]
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17
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Pritikin JN, Schmitt JE, Neale MC. Cloud computing for voxel-wise SEM analysis of MRI data. STRUCTURAL EQUATION MODELING : A MULTIDISCIPLINARY JOURNAL 2018; 26:470-480. [PMID: 31133771 PMCID: PMC6534137 DOI: 10.1080/10705511.2018.1521285] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
As data collection costs fall and vast quantities of data are collected, data analysis time can become a bottleneck. For massively parallel analyses, cloud computing offers the short-term rental of ample processing power. Recent software innovations have reduced the offort needed to take advantage of cloud computing. To demonstrate, we replicate a voxel-wise examination of the genetic contributions to cortical development by age using evidence from 1,748 MRI scans. Specifically, we employ off-the-shelf Kubernetes software that permits us to re-run our analyses using almost the same computer code as was published in the original article. Large, well funded institutions may continue to maintain their own computing clusters. However, the modest cost of renting and ease of utilizing cloud computing services makes unprecedented compute power available to all researchers, whether or not affliated with a research institution. We expect this to spur innovation in the sophisticated modeling of large datasets.
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Affiliation(s)
- Joshua N Pritikin
- Department of Psychiatry and Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University
| | - J Eric Schmitt
- Departments of Radiology and Psychiatry, Hospital of the University of Pennsylvania
| | - Michael C Neale
- Departments of Psychiatry and Human & Molecular Genetics, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University
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18
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A survey of undetected, clinically relevant chromosome abnormalities when replacing postnatal karyotyping by Whole Genome Sequencing. Eur J Med Genet 2018; 62:103543. [PMID: 30248410 DOI: 10.1016/j.ejmg.2018.09.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 07/30/2018] [Accepted: 09/18/2018] [Indexed: 11/21/2022]
Abstract
Whole genome sequencing (WGS) holds the potential to identify pathogenic gene mutations, copy number variation, uniparental disomy and structural rearrangements in a single genetic test. With its high diagnostic yield and decreasing costs, the question arises whether WGS can serve as a single test for all referrals to diagnostic genome laboratories ("one test fits all"). Here, we provide an estimate for the proportion of clinically relevant aberrations identified by light microscopy in postnatal referrals that would go undetected by WGS. To this end, we compiled the clinically relevant abnormal findings for each of the different referral categories in our laboratory during the period 2006-2015. We assumed that WGS would be performed on 300-500 bp DNA fragments with 150-bp paired sequence reads, and that the mean genome coverage is 30x, corresponding to current practice. For the detection of chromosomal mosaicism we set minimum thresholds of 10% for monosomy and 20% for trisomy. Based on the literature we assumed that balanced Robertsonian translocations and ∼9% of other, balanced chromosome rearrangements would not be detectable because of breakpoints in sequences of repetitive DNA. Based on our analysis of all 14,957 referrals, including 1455 abnormal cases, we show that at least 8.1% of these abnormalities would escape detection (corresponding to 0.79% of all referrals). The highest rate occurs in referrals of premature ovarian failure, as 73.3% of abnormalities would not be identified because of the frequent occurrence of low-level sex chromosome mosaicism. Among referrals of recurrent miscarriage, 25.6% of abnormalities would go undetected, mainly because of a high proportion of balanced Robertsonian translocations. In referrals of mental retardation (with or without multiple congenital anomalies) the abnormality would be missed in only 0.35% of referrals. These include cases without imbalances of unique DNA sequences but of clinical relevance, as for example, r(20) epilepsy syndrome. The expected shift to large-scale implementation of WGS ("one test fits most") as initial genetic test will be beneficial to patients and their families, since a cause for the clinical phenotype can be identified in more cases by a single genetic test at an early phase in the diagnostic process. However, a niche for genome analysis by light microscopy will remain. For example, in referrals of newborns with a suspicion of Down syndrome, karyotyping is not only a cost-effective method for providing a quick diagnosis, but also discriminates between trisomy 21 and a Robertsonian translocation involving chromosome 21. Thus, when replacing karyotyping by WGS, one must be aware of the rates and spectra of undetected abnormalities. In addition, it is equally important that requirements for cytogenetic follow-up studies are recognized.
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19
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Christensen KD, Phillips KA, Green RC, Dukhovny D. Cost Analyses of Genomic Sequencing: Lessons Learned from the MedSeq Project. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2018; 21:1054-1061. [PMID: 30224109 PMCID: PMC6444358 DOI: 10.1016/j.jval.2018.06.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 06/11/2018] [Indexed: 05/17/2023]
Abstract
OBJECTIVE To summarize lessons learned while analyzing the costs of integrating whole genome sequencing into the care of cardiology and primary care patients in the MedSeq Project by conducting the first randomized controlled trial of whole genome sequencing in general and specialty medicine. METHODS Case study that describes key methodological and data challenges that were encountered or are likely to emerge in future work, describes the pros and cons of approaches considered by the study team, and summarizes the solutions that were implemented. RESULTS Major methodological challenges included defining whole genome sequencing, structuring an appropriate comparator, measuring downstream costs, and examining clinical outcomes. Discussions about solutions addressed conceptual and practical issues that arose because of definitions and analyses around the cost of genomic sequencing in trial-based studies. CONCLUSIONS The MedSeq Project provides an instructive example of how to conduct a cost analysis of whole genome sequencing that feasibly incorporates best practices while being sensitive to the varied applications and diversity of results it may produce. Findings provide guidance for researchers to consider when conducting or analyzing economic analyses of whole genome sequencing and other next-generation sequencing tests, particularly regarding costs.
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Affiliation(s)
- Kurt D Christensen
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Kathryn A Phillips
- Department of Clinical Pharmacy, Center for Translational and Policy Research on Personalized Medicine (TRANSPERS), University of California San Francisco, San Francisco, CA, USA; Philip R. Lee Institute for Health Policy and Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Robert C Green
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Partners HealthCare Personalized Medicine, Boston, MA, USA
| | - Dmitry Dukhovny
- Department of Pediatrics, Oregon Health & Science University, Portland, OR, USA
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20
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Gong J, Pan K, Fakih M, Pal S, Salgia R. Value-based genomics. Oncotarget 2018; 9:15792-15815. [PMID: 29644010 PMCID: PMC5884665 DOI: 10.18632/oncotarget.24353] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 01/19/2018] [Indexed: 12/18/2022] Open
Abstract
Advancements in next-generation sequencing have greatly enhanced the development of biomarker-driven cancer therapies. The affordability and availability of next-generation sequencers have allowed for the commercialization of next-generation sequencing platforms that have found widespread use for clinical-decision making and research purposes. Despite the greater availability of tumor molecular profiling by next-generation sequencing at our doorsteps, the achievement of value-based care, or improving patient outcomes while reducing overall costs or risks, in the era of precision oncology remains a looming challenge. In this review, we highlight available data through a pre-established and conceptualized framework for evaluating value-based medicine to assess the cost (efficiency), clinical benefit (effectiveness), and toxicity (safety) of genomic profiling in cancer care. We also provide perspectives on future directions of next-generation sequencing from targeted panels to whole-exome or whole-genome sequencing and describe potential strategies needed to attain value-based genomics.
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Affiliation(s)
- Jun Gong
- Department of Medical Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Kathy Pan
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marwan Fakih
- Department of Medical Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Sumanta Pal
- Department of Medical Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Ravi Salgia
- Medical Oncology and Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
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21
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Marino P, Touzani R, Perrier L, Rouleau E, Kossi DS, Zhaomin Z, Charrier N, Goardon N, Preudhomme C, Durand-Zaleski I, Borget I, Baffert S. Cost of cancer diagnosis using next-generation sequencing targeted gene panels in routine practice: a nationwide French study. Eur J Hum Genet 2018; 26:314-323. [PMID: 29367707 PMCID: PMC5838982 DOI: 10.1038/s41431-017-0081-3] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 11/21/2017] [Accepted: 12/05/2017] [Indexed: 12/25/2022] Open
Abstract
It is currently unclear if next-generation sequencing (NGS) technologies can be implemented in the diagnosis setting at an affordable cost. The aim of this study was to measure the total cost of performing NGS in clinical practice in France, in both germline and somatic cancer genetics.The study was performed on 15 French representative cancer molecular genetics laboratories performing NGS panels' tests. The production cost was estimated using a micro-costing method with resources consumed collected in situ in each laboratory from a healthcare provider perspective. In addition, we used a top-down methodology for specific post-sequencing steps including bioinformatics, technical validation, and biological validation. Additional non-specific costs were also included. Costs were detailed per step of the process (from the pre-analytical phase to delivery of results), and per cost driver (consumables, staff, equipment, maintenance, overheads). Sensitivity analyses were performed.The mean total cost of NGS for targeted gene panels was estimated to 607€ (±207) in somatic genetics and 550€ (±140) in germline oncogenetic analysis. Consumables were the highest cost driver of the sequencing process. The sensitivity analysis showed that a 25% reduction of consumables resulted in a 15% decrease in total NGS cost in somatic genetics, and 13% in germline analysis. Additional costs accounted for 30-32% of the total NGS costs.Beyond cost assessment considerations, the diffusion of NGS technologies will raise questions about their efficiency when compared to more targeted approaches, and their added value in a context of routine diagnosis.
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Affiliation(s)
- Patricia Marino
- Institut Paoli Calmettes, SESSTIM, Marseille, France.
- INSERM, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l'Information Médicale, Aix Marseille Univ, Marseille, France.
| | - Rajae Touzani
- Institut Paoli Calmettes, SESSTIM, Marseille, France
- INSERM, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l'Information Médicale, Aix Marseille Univ, Marseille, France
| | - Lionel Perrier
- Léon Berard Cancer Centre, GATE L-SE, UMR-CNRS 5824, Lyon, France
| | - Etienne Rouleau
- Department of Pathology and Medical Biology, Gustave Roussy, Villejuif, France
| | | | - Zou Zhaomin
- Gustave Roussy, Etudes et Recherche en économie de la santé, Villejuif, France
| | | | - Nicolas Goardon
- Cancer Comprehensive Center François Baclesse, Cancer Biology and Genetics Laboratory, Caen, France
| | - Claude Preudhomme
- CHRU of Lille, Biology & Pathology Center, Laboratory of Hematology, Lille, France
| | | | - Isabelle Borget
- Gustave Roussy, Etudes et Recherche en économie de la santé, Villejuif, France
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Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature. Genet Med 2018; 20:1122-1130. [PMID: 29446766 DOI: 10.1038/gim.2017.247] [Citation(s) in RCA: 341] [Impact Index Per Article: 48.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Accepted: 11/27/2017] [Indexed: 12/14/2022] Open
Abstract
PURPOSE We conducted a systematic literature review to summarize the current health economic evidence for whole-exome sequencing (WES) and whole-genome sequencing (WGS). METHODS Relevant studies were identified in the EMBASE, MEDLINE, Cochrane Library, EconLit and University of York Centre for Reviews and Dissemination databases from January 2005 to July 2016. Publications were included in the review if they were economic evaluations, cost studies, or outcome studies. RESULTS Thirty-six studies met our inclusion criteria. These publications investigated the use of WES and WGS in a variety of genetic conditions in clinical practice, the most common being neurological or neurodevelopmental disorders. Study sample size varied from a single child to 2,000 patients. Cost estimates for a single test ranged from $555 to $5,169 for WES and from $1,906 to $24,810 for WGS. Few cost analyses presented data transparently and many publications did not state which components were included in cost estimates. CONCLUSION The current health economic evidence base to support the more widespread use of WES and WGS in clinical practice is very limited. Studies that carefully evaluate the costs, effectiveness, and cost-effectiveness of these tests are urgently needed to support their translation into clinical practice.
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23
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Plöthner M, Frank M, Graf von der Schulenburg JM. [Whole-genome sequencing in German clinical practice : Economic impacts of its use in selected areas of application]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2017; 60:143-150. [PMID: 27999872 DOI: 10.1007/s00103-016-2492-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
BACKGROUND The diagnostic use of whole-genome sequencing (WGS) is a growing issue in medical care. Due to limited resources in public health service, budget-impact analyses are necessary prior to implementation. OBJECTIVE A budget-impact analysis for WGS of all newborns and diagnostic investigation of tumor patients in different oncologic indications were evaluated. METHODS A cost analysis of WGS based on a quality-assured process chart for WGS at the German Cancer Research Center (DKFZ), Heidelberg, constitutes the basis for this evaluation. Data from the National Association of Statutory Health Insurance Funds and the Robert-Koch-Institute, Berlin, were used for calculations of specific clinical applications. RESULTS AND DISCUSSION WGS in newborn screening leads to costs of € 2.85 bn and to an increase of total expenditure by 1.41%. Sequencing of all tumor patients would cost approximately € 0.84 bn, which corresponds to 0.42% of total expenditures. In all scenarios, the sole consideration of procedure costs results in increasing costs. However, in cost discussions potential savings (reduction of disease-related follow-up-costs, improved cost-effectiveness of medical measures etc.) should be considered. Such considerations are the subject of economic indication-specific evaluations. WGS has the potential to generate a large number of deterministic findings for which treatment options are limited. Hence, it is necessary to limit indications, in which WGS has proven medical evidence.
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Affiliation(s)
- Marika Plöthner
- Center for Health Economics Research Hannover (CHERH), Leibniz University Hannover, Otto-Brenner-Straße 1, 30159, Hannover, Deutschland.
| | - Martin Frank
- Center for Health Economics Research Hannover (CHERH), Leibniz University Hannover, Otto-Brenner-Straße 1, 30159, Hannover, Deutschland
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Weymann D, Laskin J, Roscoe R, Schrader KA, Chia S, Yip S, Cheung WY, Gelmon KA, Karsan A, Renouf DJ, Marra M, Regier DA. The cost and cost trajectory of whole-genome analysis guiding treatment of patients with advanced cancers. Mol Genet Genomic Med 2017; 5:251-260. [PMID: 28546995 PMCID: PMC5441418 DOI: 10.1002/mgg3.281] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Revised: 01/18/2017] [Accepted: 02/08/2017] [Indexed: 12/21/2022] Open
Abstract
Background Limited data exist on the real‐world costs of applying whole‐genome analysis (WGA) in a clinical setting. We estimated the costs of applying WGA to guide treatments for patients with advanced cancers and characterized how costs evolve over time. Methods The setting is the British Columbia Cancer Agency Personalized OncoGenomics (POG) program in British Columbia, Canada. Cost data were obtained for patients who enrolled in the program from 2012 to 2015. We estimated mean WGA costs using bootstrapping. We applied time series analysis and produced 10‐year forecasts to determine when costs are expected to reach critical thresholds. Results The mean cost of WGA over the study period was CDN$34,886 per patient (95% CI: $34,051, $35,721). Over time, WGA costs decreased, driven by a reduction in costs of sequencing. Yet, costs of other components of WGA increased. Forecasting showed WGA costs may not reach critical thresholds within the next 10 years. Conclusion WGA costs decreased over the studied time horizon, but expenditures needed to realize WGA remain significant. Future research exploring costs and benefits of WGA‐guided cancer care are crucial to guide health policy.
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Affiliation(s)
- Deirdre Weymann
- Canadian Centre for Applied Research in Cancer Control (ARCC)Cancer Control ResearchBC Cancer AgencyVancouverBritish ColumbiaCanada
| | - Janessa Laskin
- Division of Medical OncologyBC Cancer AgencyVancouverBritish ColumbiaCanada
| | - Robyn Roscoe
- Canada's Michael Smith Genome Sciences CentreBC Cancer AgencyVancouverBritish ColumbiaCanada
| | - Kasmintan A Schrader
- Department of Medical GeneticsFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada.,Department of Molecular OncologyBC Cancer AgencyVancouverBritish ColumbiaCanada
| | - Stephen Chia
- Division of Medical OncologyBC Cancer AgencyVancouverBritish ColumbiaCanada.,Department of MedicineFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Stephen Yip
- Department of Pathology & Laboratory MedicineFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada.,Department of PathologyBC Cancer AgencyVancouverBritish ColumbiaCanada
| | - Winson Y Cheung
- Division of Medical OncologyBC Cancer AgencyVancouverBritish ColumbiaCanada.,Department of MedicineFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Karen A Gelmon
- Division of Medical OncologyBC Cancer AgencyVancouverBritish ColumbiaCanada.,Department of MedicineFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Aly Karsan
- Division of Medical OncologyBC Cancer AgencyVancouverBritish ColumbiaCanada.,Canada's Michael Smith Genome Sciences CentreBC Cancer AgencyVancouverBritish ColumbiaCanada.,Department of Pathology & Laboratory MedicineFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Daniel J Renouf
- Division of Medical OncologyBC Cancer AgencyVancouverBritish ColumbiaCanada.,Department of MedicineFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Marco Marra
- Canada's Michael Smith Genome Sciences CentreBC Cancer AgencyVancouverBritish ColumbiaCanada.,Department of Medical GeneticsFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Dean A Regier
- Canadian Centre for Applied Research in Cancer Control (ARCC)Cancer Control ResearchBC Cancer AgencyVancouverBritish ColumbiaCanada.,School of Population and Public HealthFaculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
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