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van Delft FA, Schuurbiers M, Muller M, Burgers SA, van Rossum HH, IJzerman MJ, Koffijberg H, van den Heuvel MM. Modeling strategies to analyse longitudinal biomarker data: An illustration on predicting immunotherapy non-response in non-small cell lung cancer. Heliyon 2022; 8:e10932. [PMID: 36254284 PMCID: PMC9568827 DOI: 10.1016/j.heliyon.2022.e10932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 09/09/2022] [Accepted: 09/29/2022] [Indexed: 11/03/2022] Open
Abstract
Serum tumor markers acquired through a blood draw are known to reflect tumor activity. Their non-invasive nature allows for more frequent testing compared to traditional imaging methods used for response evaluations. Our study aims to compare nine prediction methods to accurately, and with a low false positive rate, predict progressive disease despite treatment (i.e. non-response) using longitudinal tumor biomarker data. Bi-weekly measurements of CYFRA, CA-125, CEA, NSE, and SCC were available from a cohort of 412 advanced stage non-small cell lung cancer (NSCLC) patients treated up to two years with immune checkpoint inhibitors. Serum tumor marker measurements from the first six weeks after treatment initiation were used to predict treatment response at 6 months. Nine models with varying complexity were evaluated in this study, showing how longitudinal biomarker data can be used to predict non-response to immunotherapy in NSCLC patients.
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Affiliation(s)
- Frederik A. van Delft
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, Overijssel, 7522NH, the Netherlands
| | - Milou Schuurbiers
- Department of Respiratory Diseases, Radboud University Medical Center, Nijmegen, Gelderland, 6525GA, the Netherlands
| | - Mirte Muller
- Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, Noord-Holland, 1066CX, the Netherlands
| | - Sjaak A. Burgers
- Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, Noord-Holland, 1066CX, the Netherlands
| | - Huub H. van Rossum
- Department of Laboratory Medicine, Netherlands Cancer Institute, Amsterdam, Noord-Holland, 1066CX, the Netherlands
| | - Maarten J. IJzerman
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, Overijssel, 7522NH, the Netherlands,Centre for Cancer Research and Centre for Health Policy, University of Melbourne, Parkville, Melbourne, Victoria, Australia,Peter MacCallum Cancer Centre, Parkville, Melbourne, Victoria, Australia
| | - Hendrik Koffijberg
- Health Technology and Services Research Department, Technical Medical Centre, University of Twente, Enschede, Overijssel, 7522NH, the Netherlands,Corresponding author.
| | - Michel M. van den Heuvel
- Department of Respiratory Diseases, Radboud University Medical Center, Nijmegen, Gelderland, 6525GA, the Netherlands
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Smith AF, Shinkins B, Hall PS, Hulme CT, Messenger MP. Toward a Framework for Outcome-Based Analytical Performance Specifications: A Methodology Review of Indirect Methods for Evaluating the Impact of Measurement Uncertainty on Clinical Outcomes. Clin Chem 2019; 65:1363-1374. [PMID: 31444309 PMCID: PMC7055686 DOI: 10.1373/clinchem.2018.300954] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 06/20/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND For medical tests that have a central role in clinical decision-making, current guidelines advocate outcome-based analytical performance specifications. Given that empirical (clinical trial-style) analyses are often impractical or unfeasible in this context, the ability to set such specifications is expected to rely on indirect studies to calculate the impact of test measurement uncertainty on downstream clinical, operational, and economic outcomes. Currently, however, a lack of awareness and guidance concerning available alternative indirect methods is limiting the production of outcome-based specifications. Therefore, our aim was to review available indirect methods and present an analytical framework to inform future outcome-based performance goals. CONTENT A methodology review consisting of database searches and extensive citation tracking was conducted to identify studies using indirect methods to incorporate or evaluate the impact of test measurement uncertainty on downstream outcomes (including clinical accuracy, clinical utility, and/or costs). Eighty-two studies were identified, most of which evaluated the impact of imprecision and/or bias on clinical accuracy. A common analytical framework underpinning the various methods was identified, consisting of 3 key steps: (a) calculation of "true" test values; (b) calculation of measured test values (incorporating uncertainty); and (c) calculation of the impact of discrepancies between (a) and (b) on specified outcomes. A summary of the methods adopted is provided, and key considerations are discussed. CONCLUSIONS Various approaches are available for conducting indirect assessments to inform outcome-based performance specifications. This study provides an overview of methods and key considerations to inform future studies and research in this area.
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Affiliation(s)
- Alison F Smith
- Test Evaluation Group, Academic Unit of Health Economics, University of Leeds, Leeds, UK;
- NIHR Leeds In Vitro Diagnostic (IVD) Co-operative, Leeds, UK
| | - Bethany Shinkins
- Test Evaluation Group, Academic Unit of Health Economics, University of Leeds, Leeds, UK
- NIHR Leeds In Vitro Diagnostic (IVD) Co-operative, Leeds, UK
- CanTest Collaborative, UK
| | - Peter S Hall
- Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Claire T Hulme
- Test Evaluation Group, Academic Unit of Health Economics, University of Leeds, Leeds, UK
- Health Economics Group, University of Exeter, Exeter, UK
| | - Mike P Messenger
- NIHR Leeds In Vitro Diagnostic (IVD) Co-operative, Leeds, UK
- CanTest Collaborative, UK
- Leeds Centre for Personalised Medicine and Health, University of Leeds, Leeds, UK
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Moritz R, Muller M, Korse C, van den Broek D, Baas P, van den Noort V, ten Hoeve J, van den Heuvel M, van Rossum H. Diagnostic validation and interpretation of longitudinal circulating biomarkers using a biomarker response characteristic plot. Clin Chim Acta 2018; 487:6-14. [DOI: 10.1016/j.cca.2018.09.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 09/07/2018] [Accepted: 09/07/2018] [Indexed: 10/28/2022]
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Abu Hassan SO, Petersen PH, Lund F, Nielsen DL, Tuxen MK, Sölétormos G. Monitoring performance of progression assessment criteria for cancer antigen 125 among patients with ovarian cancer compared by computer simulation. Biomark Med 2015; 9:911-22. [PMID: 26145714 DOI: 10.2217/bmm.15.47] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Cancer antigen 125 (CA125) is used to monitor tumor burden among patients with advanced serous epithelial ovarian cancer. The purpose is to compare the monitoring performance of seven previously proposed criteria. MATERIALS & METHODS The CA125 assessment criteria were applied to simulated datasets. We investigated the ability to provide information on CA125 increments as well as their robustness against false positive signals. RESULTS For baseline concentrations above cut-off, the best performing criterion was based on a confirmed increment ≥2.5-times the nadir concentration. For baseline concentrations below cut-off, the best performing criterion was based on a confirmed increment from ≤ cut-off to >two-times cut-off. DISCUSSION Computer simulation models may be useful for a preclinical validation of criteria to be investigated in clinical trials.
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Affiliation(s)
- Suher Othman Abu Hassan
- Department of Clinical Biochemistry, North Zealand Hospital Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Per Hyltoft Petersen
- Department of Clinical Biochemistry, North Zealand Hospital Hospital, University of Copenhagen, Copenhagen, Denmark.,Norwegian Quality Improvement Primary Care Laboratories (NOKLUS), Section for General Practice, University of Bergen, Bergen, Norway
| | - Flemming Lund
- Department of Clinical Biochemistry, North Zealand Hospital Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Dorte L Nielsen
- Department of Oncology, Herlev Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Malgorzata K Tuxen
- Department of Oncology, Herlev Hospital, University of Copenhagen, Copenhagen, Denmark
| | - György Sölétormos
- Department of Clinical Biochemistry, North Zealand Hospital Hospital, University of Copenhagen, Copenhagen, Denmark
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Lund F, Petersen PH, Fraser CG, Sölétormos G. Calculation of limits for significant unidirectional changes in two or more serial results of a biomarker based on a computer simulation model. Ann Clin Biochem 2014; 52:237-44. [DOI: 10.1177/0004563214534636] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background Reference change values (RCVs) were introduced more than 30 years ago and provide objective tools for assessment of the significance of differences in two consecutive results from an individual. However, in practice, more results are usually available for monitoring, and using the RCV concept on more than two results will increase the number of false-positive results. Therefore, a simple method is needed to interpret the significance of a difference when all available serial biomarker results are considered. Methods A computer simulation model using Excel was developed. Based on 10,000 simulated data from healthy individuals, a series of up to 20 results from an individual was generated using different values for the within-subject biological variation plus the analytical variation. Each new result in this series was compared to the initial measurement result. These successive serial relative differences were computed to give limits for significant unidirectional differences with a constant cumulated maximum probability of both 95% ( P < 0.05) and 99% ( P < 0.01). Results Factors used to multiply the first result from an individual were calculated to create the limits for constant cumulated significant differences. The factors were shown to become a simple function of the number of results and the total coefficient of variation. Conclusions To interpret unidirectional differences in two or more serial results of a biomarker, the limits for significances are easily calculated using the presented factors. The first result is multiplied by the appropriate factor for increase or decrease, which gives the limits for a significant difference.
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Affiliation(s)
- Flemming Lund
- Department of Clinical Biochemistry, North Zealand Hospital, University of Copenhagen, Hillerød, Denmark
| | - Per Hyltoft Petersen
- Department of Clinical Biochemistry, North Zealand Hospital, University of Copenhagen, Hillerød, Denmark
- Norwegian Quality Improvement of Primary Care Laboratories (NOKLUS), Section for General Practice, University of Bergen, Bergen, Norway
| | - Callum G Fraser
- Centre for Research into Cancer Prevention and Screening, University of Dundee, Dundee, Scotland
| | - György Sölétormos
- Department of Clinical Biochemistry, North Zealand Hospital, University of Copenhagen, Hillerød, Denmark
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