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Lee CK, Huan PT, Chai CN, Ng LJ, Koay ESC, Lee OF, Tan M, Loh TP. Novel thiopurine S-methyltransferase ( TPMT) variant identified in Malay individuals. Clin Chem Lab Med 2024; 0:cclm-2024-0494. [PMID: 38661453 DOI: 10.1515/cclm-2024-0494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Accepted: 04/21/2024] [Indexed: 04/26/2024]
Affiliation(s)
- Chun Kiat Lee
- Department of Laboratory Medicine, 150744 National University Health System , Singapore, Singapore
| | - Pei Tee Huan
- Department of Paediatrics, Yong Loo Lin School of Medicine, 37580 National University of Singapore , Singapore, Singapore
| | - Chean Nee Chai
- Department of Laboratory Medicine, 150744 National University Health System , Singapore, Singapore
| | - Li Jie Ng
- Department of Laboratory Medicine, 150744 National University Health System , Singapore, Singapore
| | - Evelyn Siew-Chuan Koay
- Department of Pathology, Yong Loo Lin School of Medicine, 37580 National University of Singapore , Singapore, Singapore
| | - Ogestelli Fabia Lee
- School of Life and Physical Sciences, 464889 PSB Academy , Singapore, Singapore
| | - Malcolm Tan
- Department of Gastroenterology and Hepatology, 37581 Singapore General Hospital , Singapore, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, 150744 National University Health System , Singapore, Singapore
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Ho CS, Hoad K, Cooke BR, Andersen T, Graham P, van den Berg SAA, Hartmann MF, Lo CWS, Loh TP, de Rijke YB, van Zelst BD, Wudy SA, Zakaria R, Greaves RF. Ensuring quality in 17OHP mass spectrometry measurement: an international study assessing isomeric steroid interference. Clin Chem Lab Med 2024; 62:911-918. [PMID: 38063179 DOI: 10.1515/cclm-2023-0864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 11/26/2023] [Indexed: 04/05/2024]
Abstract
OBJECTIVES Interference from isomeric steroids is a potential cause of disparity between mass spectrometry-based 17-hydroxyprogesterone (17OHP) results. We aimed to assess the proficiency of mass spectrometry laboratories to report 17OHP in the presence of known isomeric steroids. METHODS A series of five samples were prepared using a previously demonstrated commutable approach. These samples included a control (spiked to 15.0 nmol/L 17OHP) and four challenge samples further enriched with equimolar concentrations of 17OHP isomers (11α-hydroxyprogesterone, 11β-hydroxyprogesterone, 16α-hydroxyprogesterone or 21-hydroxyprogesterone). These samples were distributed to 38 participating laboratories that reported serum 17OHP results using mass spectrometry in two external quality assurance programs. The result for each challenge sample was compared to the control sample submitted by each participant. RESULTS Twenty-six laboratories (68 % of distribution) across three continents returned results. Twenty-five laboratories used liquid chromatography-tandem mass spectrometry (LC-MS/MS), and one used gas chromatography-tandem mass spectrometry to measure 17OHP. The all-method median of the control sample was 14.3 nmol/L, ranging from 12.4 to 17.6 nmol/L. One laboratory had results that approached the lower limit of tolerance (minus 17.7 % of the control sample), suggesting the isomeric steroid caused an irregular result. CONCLUSIONS Most participating laboratories demonstrated their ability to reliably measure 17OHP in the presence of the four clinically relevant isomeric steroids. The performance of the 12 (32 %) laboratories that did not engage in this activity remains unclear. We recommend that all laboratories offering LC-MS/MS analysis of 17OHP in serum, plasma, or dried bloodspots determine that the isomeric steroids are appropriately separated.
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Affiliation(s)
- Chung Shun Ho
- Department of Chemical Pathology, Biomedical Mass Spectrometry Unit, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR China
| | - Kirsten Hoad
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Perth, WA, Australia
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Perth, WA, Australia
| | | | - Peter Graham
- Royal College of Pathologists of Australasia Quality Assurance Programs, Sydney, NSW, Australia
| | - Sjoerd A A van den Berg
- Department Internal Medicine, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
- Department Clinical Chemistry, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - Michaela F Hartmann
- Steroid Research & Mass Spectrometry Unit of the Laboratory for Translational Hormone Analytics in Pediatric Endocrinology at the Justus Liebig University in Giessen, Giessen, Germany
| | - Clara W S Lo
- Department of Chemical Pathology, Biomedical Mass Spectrometry Unit, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR China
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Yolanda B de Rijke
- Department Clinical Chemistry, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - Bertrand D van Zelst
- Department Internal Medicine, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - Stefan A Wudy
- Steroid Research & Mass Spectrometry Unit of the Laboratory for Translational Hormone Analytics in Pediatric Endocrinology at the Justus Liebig University in Giessen, Giessen, Germany
| | - Rosita Zakaria
- School of Health and Biomedical Sciences, RMIT University, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Ronda F Greaves
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, The Royal Children's Hospital Melbourne, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
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Choy KW, Carobene A, Loh TP, Chiang C, Wijeratne N, Locatelli M, Coskun A, Cavusoglu C, Unsal I. Biological Variation Estimates for Plasma Copeptin and Clinical Implications. J Appl Lab Med 2024:jfae005. [PMID: 38576222 DOI: 10.1093/jalm/jfae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 11/15/2023] [Indexed: 04/06/2024]
Abstract
BACKGROUND Plasma copeptin measurement is useful for the differential diagnoses of polyuria-polydipsia syndrome. It has also been proposed as a prognostic marker for cardiovascular diseases. However, limited information is available about the within- (CVI) and between-subject (CVG) biological variation (BV). This study presents BV estimates for copeptin in healthy individuals. METHODS Samples were collected weekly from 41 healthy subjects over 5 weeks and analyzed using the BRAHMS Copeptin proAVP KRYPTOR assay after at least 8 h of food and fluid abstinence. Outlier detection, variance homogeneity, and trend analysis were performed followed by CV-ANOVA for BV and analytical variation (CVA) estimation with 95% confidence intervals. Reference change values (RCVs), index of individuality (II), and analytical performance specification (APS) were also calculated. RESULTS The analysis included 178 results from 20 males and 202 values from 21 females. Copeptin concentrations were significantly higher in males than in females (mean 8.5 vs 5.2 pmol/L, P < 0.0001). CVI estimates were 18.0% (95% CI, 15.4%-21.6%) and 19.0% (95% CI, 16.4%-22.6%), for males and females, respectively; RCVs were -35% (decreasing value) and 54% (increasing value). There was marked individuality for copeptin. No result exceeded the diagnostic threshold (>21.4 pmol/L) for arginine vasopressin resistance. CONCLUSIONS The availability of BV data allows for refined APS and associated II, and RCVs applicable as aids in the serial monitoring of patients with specific diseases such as heart failure. The BV estimates are only applicable in subjects who abstained from oral intake due to the rapid and marked effects of fluids on copeptin physiology.
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Affiliation(s)
- Kay Weng Choy
- Department of Pathology, Northern Health, Epping, Australia
| | - Anna Carobene
- Laboratory Medicine, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Cherie Chiang
- Department of Pathology, The University of Melbourne, Royal Melbourne Hospital, Parkville, Australia
| | - Nilika Wijeratne
- Eastern Health Pathology, Eastern Health, Box Hill, Australia
- Department of Biochemistry, Dorevitch Pathology, Heidelberg, Australia
- School of Clinical Sciences at Monash Health, Department of Medicine, Nursing and Health Sciences, Monash University, Clayton, Australia
| | - Massimo Locatelli
- Laboratory Medicine, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Abdurrahman Coskun
- School of Medicine, Acibadem Mehmet Ali Aydınlar University, Istanbul, Turkey
| | - Coskun Cavusoglu
- School of Medicine, Acibadem Mehmet Ali Aydınlar University, Istanbul, Turkey
| | - Ibrahim Unsal
- School of Medicine, Acibadem Mehmet Ali Aydınlar University, Istanbul, Turkey
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Choy KW, Cornu P, Dighe AS, Georgiou A, Peters L, Sikaris KA, Loh TP. Clinical Decision Support in Laboratory Medicine. Clin Chem 2024; 70:474-481. [PMID: 38300892 DOI: 10.1093/clinchem/hvae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 01/08/2024] [Indexed: 02/03/2024]
Affiliation(s)
- Kay Weng Choy
- Director of Chemical Pathology, Department of Pathology, Northern Health, Epping, Australia
| | - Pieter Cornu
- Clinical Decision Support Coordinator, Department of ICT, Universitair Ziekenhuis Brussel, Brussels, Belgium
- Assistant Professor, Department of Pharmaceutical and Pharmacological Sciences, Research Group Clinical Pharmacology and Clinical Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Anand S Dighe
- Deputy Chief for Clinical Operations, Mass General Brigham Pathology, Boston, MA, United States
- Associate Professor of Pathology, Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Andrew Georgiou
- Professor of Diagnostic Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Lindsay Peters
- Principal Advisor for Expert Systems, Beamtree Holdings Ltd, Redfern, Australia
| | - Kenneth A Sikaris
- Director of Clinical Decision Support, Sonic Healthcare, Collingwood, Australia
- Associate Professor, Department of Pathology, The University of Melbourne, Parkville, Australia
| | - Tze Ping Loh
- Consultant Chemical Pathologist, Department of Laboratory Medicine, National University Hospital, Singapore
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Loh TP, Cooke BR, Tran TCM, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures. Pract Lab Med 2024; 39:e00355. [PMID: 38313811 PMCID: PMC10830849 DOI: 10.1016/j.plabm.2024.e00355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 01/04/2024] [Indexed: 02/06/2024] Open
Abstract
Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Brian R. Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
| | - Thi Chi Mai Tran
- Faculty of Medical Technology, Hanoi Medical University, Viet Nam
- Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Viet Nam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
| | - Rosita Zakaria
- RMIT University, School of Health and Biomedical Sciences, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
| | - Elvar Theodorsson
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, SE-58183 Linkoping, Sweden
| | - Ronda F. Greaves
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - IFCC Working Group on Method Evaluation Protocols (WG-MEP)
- Department of Laboratory Medicine, National University Hospital, Singapore
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
- Faculty of Medical Technology, Hanoi Medical University, Viet Nam
- Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Viet Nam
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
- RMIT University, School of Health and Biomedical Sciences, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, SE-58183 Linkoping, Sweden
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
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Loh TP, Cooke BR, Tran TCM, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP Checklist for Laboratory Evaluation and Analytical Performance Characteristics Reporting of Clinical Measurement Procedures. Ann Lab Med 2024; 44:122-125. [PMID: 37869780 PMCID: PMC10628757 DOI: 10.3343/alm.2023.0342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 08/31/2023] [Accepted: 09/07/2023] [Indexed: 10/24/2023] Open
Abstract
Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the Laboratory Evaluation and Analytical Performance Characteristics (LEAP) checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia
| | - Thi Chi Mai Tran
- Faculty of Medical Technology, Hanoi Medical University, Ha Noi, Vietnam
- Department of Clinical Biochemistry, National Children’s Hospital, Hanoi, Vietnam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
| | - Rosita Zakaria
- Department of Laboratory Medicine, School of Health and Biomedical Sciences, RMIT University, Victoria, Australia
- Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
| | - Elvar Theodorsson
- Division of Clinical Chemistry and Pharmacology, Department of Biomedical and Clinical Sciences, Linkoping University, Linkoping, Sweden
| | - Ronda F Greaves
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
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Lim SM, Wijeratne N, Choy KW, Nguyen TTH, Setiawan L, Loh TP. A review of clinical guidelines, laboratory recommendations and external quality assurance programs for monoclonal gammopathy testing. Crit Rev Clin Lab Sci 2024; 61:107-126. [PMID: 37776896 DOI: 10.1080/10408363.2023.2257306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 09/06/2023] [Indexed: 10/02/2023]
Abstract
Monoclonal gammopathy (MG) is a spectrum of diseases ranging from the benign asymptomatic monoclonal gammopathy of undetermined significance to the malignant multiple myeloma. Clinical guidelines and laboratory recommendations have been developed to inform best practices in the diagnosis, monitoring, and management of MG. In this review, the pathophysiology, relevant laboratory testing recommended in clinical practice guidelines and laboratory recommendations related to MG testing and reporting are examined. The clinical guidelines recommend serum protein electrophoresis, serum immunofixation and serum free light chain measurement as initial screening. The laboratory recommendations omit serum immunofixation as it offers limited additional diagnostic value. The laboratory recommendations offer guidance on reporting findings beyond monoclonal protein, which was not required by the clinical guidelines. The clinical guidelines suggested monitoring total IgA concentration by turbidimetry or nephelometry method if the monoclonal protein migrates in the non-gamma region, whereas the laboratory recommendations make allowance for involved IgM and IgG. Additionally, several external quality assurance programs for MG protein electrophoresis and free light chain testing are also appraised. The external quality assurance programs show varied assessment criteria for protein electrophoresis reporting and unit of measurement. There is also significant disparity in reported monoclonal protein concentrations with wide inter-method analytical variation noted for both monoclonal protein quantification and serum free light chain measurement, however this variation appears smaller when the same method was used. Greater harmonization among laboratory recommendations and reporting format may improve clinical interpretation of MG testing.
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Affiliation(s)
| | - Nilika Wijeratne
- Dorevitch Pathology, Melbourne, Australia
- School of Clinical Sciences at Monash Health, Department of Medicine, Nursing and Health Sciences, Monash University, Clayton, Australia
- Eastern Health Pathology, Eastern Health, Box Hill, Australia
- Dorevitch Pathology, Heidelberg, Australia
| | | | | | - Lyana Setiawan
- Dharmais Hospital National Cancer Centre, West Jakarta, Indonesia
| | - Tze Ping Loh
- National University Hospital, Singapore, Singapore
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Vasikaran S, Thambiah SC, Tan RZ, Loh TP. The Use of Bone-Turnover Markers in Asia-Pacific Populations. Ann Lab Med 2024; 44:126-134. [PMID: 37869778 PMCID: PMC10628755 DOI: 10.3343/alm.2023.0214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 08/03/2023] [Accepted: 09/14/2023] [Indexed: 10/24/2023] Open
Abstract
Bone-turnover marker (BTM) measurements in the blood or urine reflect the bone-remodeling rate and may be useful for studying and clinically managing metabolic bone diseases. Substantial evidence supporting the diagnostic use of BTMs has accumulated in recent years, together with the publication of several guidelines. Most clinical trials and observational and reference-interval studies have been performed in the Northern Hemisphere and have mainly involved Caucasian populations. This review focuses on the available data for populations from the Asia-Pacific region and offers guidance for using BTMs as diagnostic biomarkers in these populations. The procollagen I N-terminal propeptide and β-isomerized C-terminal telopeptide of type-I collagen (measured in plasma) are reference BTMs used for investigating osteoporosis in clinical settings. Premenopausal reference intervals (established for use with Asia-Pacific populations) and reference change values and treatment targets (used to monitor osteoporosis treatment) help guide the management of osteoporosis. Measuring BTMs that are not affected by renal failure, such as the bone-specific isoenzyme alkaline phosphatase and tartrate-resistant acid phosphatase 5b, may be advantageous for patients with advanced chronic kidney disease. Further studies of the use of BTMs in individuals with metabolic bone disease, coupled with the harmonization of commercial assays to provide equivalent results, will further enhance their clinical applications.
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Affiliation(s)
- Samuel Vasikaran
- Department of Clinical Biochemistry, Fiona Stanley Hospital, Perth, Australia
| | - Subashini C. Thambiah
- Department of Pathology, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
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Badrick T, Loh TP. Integrating patient-based quality control and patient-based quality assurance. Clin Biochem 2024; 124:110708. [PMID: 38215871 DOI: 10.1016/j.clinbiochem.2024.110708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 12/29/2023] [Accepted: 01/02/2024] [Indexed: 01/14/2024]
Affiliation(s)
- Tony Badrick
- RCPA Quality Assurance Programs, St Leonards, Sydney, Australia.
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Loh TP, Ehrenkranz J, Halsall D, Hoff K, Spencer CA, Van Uytfanghe K, Köhrle J. Response to Fitzgerald et al. re: "Thyroid Stimulating Hormone and Thyroid Hormones (Triiodothyronine and Thyroxine): An American Thyroid Association-Commissioned Review of Current Clinical and Laboratory Status". Thyroid 2024; 34:276-278. [PMID: 38236706 DOI: 10.1089/thy.2023.0604] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Joel Ehrenkranz
- Department of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA
| | - David Halsall
- Cambridge University Hospitals Trust, Addenbrookes Hospital, Cambridge, United Kingdom
| | - Kelly Hoff
- American Thyroid Association, Headquarters, Alexandria, Virginia, USA
| | - Carole A Spencer
- Department of Medicine, University of Southern California, Los Angeles, California, USA
| | - Katleen Van Uytfanghe
- Ref4U-Laboratory of Toxicology, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
| | - Josef Köhrle
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institut für Experimentelle Endokrinologie, Berlin, Germany
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Loh TP, Cooke BR, Tran MTC, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures. Pathology 2024; 56:142-143. [PMID: 38065819 DOI: 10.1016/j.pathol.2023.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 11/23/2023] [Indexed: 01/24/2024]
Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore.
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, WA, Australia
| | - Mai Thi Chi Tran
- Faculty of Medical Technology, Hanoi Medical University, Viet Nam; Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Viet Nam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, SA, Australia
| | - Rosita Zakaria
- RMIT University, School of Health and Biomedical Sciences, Vic, Australia; Murdoch Children's Research Institute, Melbourne, Vic, Australia
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
| | - Elvar Theodorsson
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, Linkoping, Sweden
| | - Ronda F Greaves
- Department of Paediatrics, The University of Melbourne, Melbourne, Vic, Australia; Murdoch Children's Research Institute, Parkville, Vic, Australia.
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Lee ARYB, Yau CE, Chua CKT, Cheng WL, Chia AJL, Wong SY, Kow NY, Gong L, Lee BTK, Ling LH, Mak A, Loh TP, Tay SH. High-density lipoprotein cholesterol subfraction HDL2 is associated with improved endothelial function in systemic lupus erythematosus. Lupus Sci Med 2024; 11:e001030. [PMID: 38262630 PMCID: PMC10806503 DOI: 10.1136/lupus-2023-001030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 01/05/2024] [Indexed: 01/25/2024]
Abstract
OBJECTIVE Patients with systemic lupus erythematosus (SLE) have increased risk of premature atherosclerosis but the exact mechanisms remains unclear. Flow-mediated dilatation (FMD) is an established non-invasive assessment of vascular endothelial function. Lipoprotein subfractions may be better predictors of FMD than conventional cholesterol measurements. We tested the hypothesis that lipoprotein subfractions are independently associated with FMD. METHODS Forty-one consecutive adult patients with SLE without known cardiovascular risk factors or disease were recruited in this cross-sectional study. Endothelial function and early atherosclerosis were assessed by brachial FMD and common carotid artery (CCA) intima-media thickness (IMT). High-density lipoprotein (HDL)/low-density lipoprotein (LDL) subfractions were measured. Machine learning models were also constructed to predict FMD and CCA IMT. RESULTS Median FMD was 4.48% (IQR 5.00%) while median IMT was 0.54 mm (IQR 0.12 mm). Univariate analysis showed lower LDL1 (r=-0.313, p<0.05) and higher HDL2 subfractions (r=0.313, p<0.05) were significantly associated with higher log-transformed FMD. In a multiple linear regression model, HDL2 (β=0.024, SE=0.012, p<0.05) remained an independent predictor of higher FMD after adjusting for age, body mass index, LDL1 and systolic blood pressure. The machine learning model included parameters such as HDL2 (positive association), prednisolone dose, LDL cholesterol and LDL1 for prediction of FMD (r=0.433, p<0.01). Age, LDL cholesterol and systolic blood pressure were independently associated with higher CCA IMT after adjusting for body mass index and HDL2. CONCLUSIONS HDL 2, a large HDL particle, was independently associated with greater FMD and may be a biomarker of vascular health in SLE.
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Affiliation(s)
| | - Chun En Yau
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Cheryl Kai Ting Chua
- Division of Rheumatology, Department of Medicine, National University Hospital, Singapore
| | - Wan Ling Cheng
- Department of Laboratory Medicine, National University Hospital, Singapore
| | | | - Shi Yin Wong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Nien Yee Kow
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Lingli Gong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Bernett Teck Kwong Lee
- Centre for Biomedical Informatics, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Lieng Hsi Ling
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Cardiology, National University Heart Centre, National University Hospital, Singapore
| | - Anselm Mak
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Division of Rheumatology, Department of Medicine, National University Hospital, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Sen Hee Tay
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Division of Rheumatology, Department of Medicine, National University Hospital, Singapore
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13
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Cheng WL, Chew S, Sethi SK, Ho CS, Loh TP. Methanol interference in LC-MS/MS vitamin D: need for lot-to-lot verification. Pathology 2024:S0031-3025(24)00032-1. [PMID: 38395678 DOI: 10.1016/j.pathol.2023.10.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/12/2023] [Accepted: 10/26/2023] [Indexed: 02/25/2024]
Affiliation(s)
- Wan Ling Cheng
- Department of Laboratory Medicine, National University Hospital, Singapore.
| | - Suru Chew
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Sunil Kumar Sethi
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
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Abstract
OBJECTIVES An increase in analytical imprecision and/or the introduction of bias can affect the interpretation of quantitative laboratory results. In this study, we explore the impact of varying assay imprecision and bias introduction on the classification of patients based on fixed thresholds. METHODS Simple spreadsheets (Microsoft Excel) were constructed to simulate conditions of assay deterioration, expressed as coefficient of variation and bias (in percentages). The impact on patient classification was explored based on fixed interpretative limits. A combined matrix of imprecision and bias of 0%, 2%, 4%, 6%, 8%, and 10% (tool 1) as well as 0%, 2%, 5%, 10%, 15%, and 20% (tool 2) was simulated, respectively. The percentage of patients who were reclassified following the addition of simulated imprecision and bias was summarized and presented in tables and graphs. RESULTS The percentage of patients who were reclassified increased with increasing/decreasing magnitude of imprecision and bias. The impact of imprecision lessens with increasing bias such that at high biases, the bias becomes the dominant cause for reclassification. CONCLUSIONS The spreadsheet tools, available as Supplemental Material, allow laboratories to visualize the impact of additional analytical imprecision and bias on the classification of their patients when applied to locally extracted historical results.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore
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15
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Loh TP, Cooke BR, Tran TCM, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures. Ann Clin Biochem 2024; 61:3-7. [PMID: 37838926 DOI: 10.1177/00045632231206029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2023]
Abstract
Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia
| | - Thi Chi Mai Tran
- Faculty of Medical Technology, Hanoi Medical University, Vietnam
- Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Vietnam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
| | - Rosita Zakaria
- School of Health and Biomedical Sciences, RMIT University, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong
| | - Elvar Theodorsson
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, Linkoping, Sweden
| | - Ronda F Greaves
- Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, VIC, Australia
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16
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Loh TP, Lim CY, Markus C. Reply to "The trade-off between bias and imprecision: debunking the myth of bias as the primary culprit in patient result misclassification". Am J Clin Pathol 2023:aqad165. [PMID: 38113374 DOI: 10.1093/ajcp/aqad165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023] Open
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17
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Masroni MSB, Lee KW, Lee VKM, Ng SB, Law CT, Poon KS, Lee BTK, Liu Z, Tan YP, Chng WL, Tucker S, Ngo LSM, Yip GWC, Nga ME, Hue SSS, Putti TC, Bay BH, Lin Q, Zhou L, Hartman M, Loh TP, Lakshmanan M, Lee SY, Tergaonkar V, Chua H, Lee AVH, Yeo EYM, Li MH, Chang CF, Kee Z, Tan KML, Tan SY, Koay ESC, Archetti M, Leong SM. Dynamic altruistic cooperation within breast tumors. Mol Cancer 2023; 22:206. [PMID: 38093346 PMCID: PMC10720132 DOI: 10.1186/s12943-023-01896-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 11/05/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Social behaviors such as altruism, where one self-sacrifices for collective benefits, critically influence an organism's survival and responses to the environment. Such behaviors are widely exemplified in nature but have been underexplored in cancer cells which are conventionally seen as selfish competitive players. This multidisciplinary study explores altruism and its mechanism in breast cancer cells and its contribution to chemoresistance. METHODS MicroRNA profiling was performed on circulating tumor cells collected from the blood of treated breast cancer patients. Cancer cell lines ectopically expressing candidate miRNA were used in co-culture experiments and treated with docetaxel. Ecological parameters like relative survival and relative fitness were assessed using flow cytometry. Functional studies and characterization performed in vitro and in vivo include proliferation, iTRAQ-mass spectrometry, RNA sequencing, inhibition by small molecules and antibodies, siRNA knockdown, CRISPR/dCas9 inhibition and fluorescence imaging of promoter reporter-expressing cells. Mathematical modeling based on evolutionary game theory was performed to simulate spatial organization of cancer cells. RESULTS Opposing cancer processes underlie altruism: an oncogenic process involving secretion of IGFBP2 and CCL28 by the altruists to induce survival benefits in neighboring cells under taxane exposure, and a self-sacrificial tumor suppressive process impeding proliferation of altruists via cell cycle arrest. Both processes are regulated concurrently in the altruists by miR-125b, via differential NF-κB signaling specifically through IKKβ. Altruistic cells persist in the tumor despite their self-sacrifice, as they can regenerate epigenetically from non-altruists via a KLF2/PCAF-mediated mechanism. The altruists maintain a sparse spatial organization by inhibiting surrounding cells from adopting the altruistic fate via a lateral inhibition mechanism involving a GAB1-PI3K-AKT-miR-125b signaling circuit. CONCLUSIONS Our data reveal molecular mechanisms underlying manifestation, persistence and spatial spread of cancer cell altruism. A minor population behave altruistically at a cost to itself producing a collective benefit for the tumor, suggesting tumors to be dynamic social systems governed by the same rules of cooperation in social organisms. Understanding cancer cell altruism may lead to more holistic models of tumor evolution and drug response, as well as therapeutic paradigms that account for social interactions. Cancer cells constitute tractable experimental models for fields beyond oncology, like evolutionary ecology and game theory.
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Affiliation(s)
- Muhammad Sufyan Bin Masroni
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Kee Wah Lee
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, MD10, 4 Medical Drive, Singapore, 117594, Singapore
| | - Victor Kwan Min Lee
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
- NUS Centre for Cancer Research (N2CR), MD6, Centre for Translational Medicine, National University of Singapore, 14 Medical Drive, #12-01, Singapore, 117599, Singapore
| | - Siok Bian Ng
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
- NUS Centre for Cancer Research (N2CR), MD6, Centre for Translational Medicine, National University of Singapore, 14 Medical Drive, #12-01, Singapore, 117599, Singapore
| | - Chao Teng Law
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Kok Siong Poon
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Bernett Teck-Kwong Lee
- Centre for Biomedical Informatics, Lee Kong Chian School of Medicine, Nanyang Technological University, Experimental Medicine Building, NTU Main Campus, 59 Nanyang Drive, Level 4, Singapore, 636921, Singapore
| | - Zhehao Liu
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, MD10, 4 Medical Drive, Singapore, 117594, Singapore
| | - Yuen Peng Tan
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Wee Ling Chng
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Steven Tucker
- Tucker Medical Pte Ltd, Novena Specialist Centre, 8 Sinaran Drive #04-03, Singapore, 307470, Singapore
| | - Lynette Su-Mien Ngo
- Raffles Cancer Centre, Raffles Hospital, 585 North Bridge Road, Singapore, 188770, Singapore
- Current address: Curie Oncology Pte Ltd, Mount Elizabeth Novena Specialist Centre, 38 Irrawaddy Road, Level 8, #08-29/30, Singapore, 329563, Singapore
| | - George Wai Cheong Yip
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, MD10, 4 Medical Drive, Singapore, 117594, Singapore
- NUS Centre for Cancer Research (N2CR), MD6, Centre for Translational Medicine, National University of Singapore, 14 Medical Drive, #12-01, Singapore, 117599, Singapore
| | - Min En Nga
- Department of Pathology, National University Hospital, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Susan Swee Shan Hue
- Department of Pathology, National University Hospital, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos, 61 Biopolis Drive, Singapore, 138673, Singapore
| | - Thomas Choudary Putti
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Boon Huat Bay
- Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, MD10, 4 Medical Drive, Singapore, 117594, Singapore
| | - Qingsong Lin
- Department of Biological Sciences, Faculty of Science, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore
| | - Lihan Zhou
- MiRXES Pte Ltd, JTC MedTech Hub, 2 Tukang Innovation Grove #08-01, Singapore, 618305, Singapore
| | - Mikael Hartman
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 8, Singapore, 119228, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Level 3 NUH Main Building, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore
| | - Manikandan Lakshmanan
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos, 61 Biopolis Drive, Singapore, 138673, Singapore
| | - Sook Yee Lee
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos, 61 Biopolis Drive, Singapore, 138673, Singapore
| | - Vinay Tergaonkar
- NUS Centre for Cancer Research (N2CR), MD6, Centre for Translational Medicine, National University of Singapore, 14 Medical Drive, #12-01, Singapore, 117599, Singapore
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos, 61 Biopolis Drive, Singapore, 138673, Singapore
| | - Huiwen Chua
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Adeline Voon Hui Lee
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Eric Yew Meng Yeo
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Mo-Huang Li
- CellSievo Pte Ltd, Block 289A, Bukit Batok Street 25, #15-218, Singapore, 650289, Singapore
| | - Chan Fong Chang
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117594, Singapore
| | - Zizheng Kee
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore
| | - Karen Mei-Ling Tan
- Department of Laboratory Medicine, National University Hospital, Level 3 NUH Main Building, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore.
- Singapore Institute For Clinical Sciences, Brenner Centre for Molecular Medicine, 30 Medical Drive, Singapore, 117609, Singapore.
| | - Soo Yong Tan
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore.
- NUS Centre for Cancer Research (N2CR), MD6, Centre for Translational Medicine, National University of Singapore, 14 Medical Drive, #12-01, Singapore, 117599, Singapore.
- Department of Pathology, National University Hospital, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore.
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos, 61 Biopolis Drive, Singapore, 138673, Singapore.
| | - Evelyn Siew-Chuan Koay
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore.
- Department of Laboratory Medicine, National University Hospital, Level 3 NUH Main Building, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore.
| | - Marco Archetti
- Department of Biology, Pennsylvania State University, W210 Millennium Science Complex, University Park, PA, 16802, USA.
| | - Sai Mun Leong
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore.
- NUS Centre for Cancer Research (N2CR), MD6, Centre for Translational Medicine, National University of Singapore, 14 Medical Drive, #12-01, Singapore, 117599, Singapore.
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18
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Tan RZ, C Thambiah S, Loh TP, Vasikaran S, Yeap SS. Reference intervals for CTX and P1NP in a multi-ethnic Malaysian cohort. Malays J Pathol 2023; 45:391-396. [PMID: 38155380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Abstract
BACKGROUND Well defined reference intervals are central to the utility of serum C-terminal telopeptide of type 1 collagen (CTX) and N-terminal propeptide of type I procollagen (P1NP), designated as reference markers in osteoporosis, and useful for monitoring therapeutic response in that condition. This study reports the reference intervals for plasma CTX and serum P1NP in a multi-ethnic Malaysian population. METHODS Ethnic Malay, Chinese or Indian subjects aged 45-90 years old were recruited from Selangor, Malaysia from June 2016 to August 2018. Subjects with known medical conditions (e.g., bone disorders, malnutrition, immobilisation, renal impairment, hormonal disorders) and medications (including regular calcium or vitamin D supplements) that may affect CTX and P1NP were excluded. Additionally, subjects with osteoporosis or fracture on imaging studies were excluded. The blood samples were collected between 8 a.m. and 9 a.m. in fasting state. The CTX and P1NP were measured on Roche e411 platform in batches. RESULTS The 2.5th-97.5th percentiles reference intervals (and bootstrapped 90%CI) for plasma CTX in men (n = 91) were 132 (94-175) - 775 (667-990) ng/L; in post-menopausal women (n = 132) 152 (134-177) - 1025 (834-1293) ng/L. The serum P1NP reference intervals in men were 23.7 (19.1-26.4) - 83.9 (74.0-105.0) µg/L, and in post-menopausal women, 25.9 (19.5-29.3) - 142.1 (104.7-229.7) µg/L. CONCLUSION The reference intervals for plasma CTX and serum PINP for older Malaysian men and post-menopausal women are somewhat different to other published studies from the region, emphasising the importance of establishing specific reference intervals for each population.
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Affiliation(s)
- R Z Tan
- Singapore Institute of Technology, Engineering Cluster, Singapore
| | - S C Thambiah
- Universiti Putra Malaysia, Faculty of Medicine and Health Sciences, Department of Pathology, Selangor, Malaysia
| | - T P Loh
- National University Hospital, Department of Laboratory Medicine, Singapore
| | - S Vasikaran
- PathWest Laboratory Medicine, Department of Clinical Biochemistry, Australia
| | - S S Yeap
- Puchong Specialist Centre, Puchong, Selangor, Malaysia
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19
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Greaves R, Kricka L, Gruson D, Ferrari M, Martin H, Loh TP, Bernardini S. Toolkit for emerging technologies in laboratory medicine. Clin Chem Lab Med 2023; 61:2102-2114. [PMID: 37314970 DOI: 10.1515/cclm-2023-0571] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 06/04/2023] [Indexed: 06/16/2023]
Abstract
An emerging technology (ET) for laboratory medicine can be defined as an analytical method (including biomarkers) or device (software, applications, and algorithms) that by its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics. Considering the laboratory medicine-specific definition, this document examines eight key tools, encompassing clinical, analytical, operational, and financial aspects, used throughout the life cycle of ET implementation. The tools provide a systematic approach starting with identifying the unmet need or identifying opportunities for improvement (Tool 1), forecasting (Tool 2), technology readiness assessment (Tool 3), health technology assessment (Tool 4), organizational impact map (Tool 5), change management (Tool 6), total pathway to method evaluation checklist (Tool 7), and green procurement (Tool 8). Whilst there are differences in clinical priorities between different settings, the use of this set of tools will help support the overall quality and sustainability of the emerging technology implementation.
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Affiliation(s)
- Ronda Greaves
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Larry Kricka
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Medical Center, Philadelphia, PA, USA
| | - Damien Gruson
- Cliniques Universitaires Saint Luc, Département des Laboratoires Cliniques, Biochimie Médicale, Brussels, Belgium
| | | | | | - Tze Ping Loh
- National University Hospital, Singapore, Singapore
| | - Sergio Bernardini
- Department of Experimental Medicine, University Tor Vergata, Rome, Italy
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20
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Loh TP, Cooke BR, Tran TCM, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP checklist for Laboratory Evaluation and Analytical Performance characteristics reporting of clinical measurement procedures. Clin Chim Acta 2023; 551:117605. [PMID: 37844680 DOI: 10.1016/j.cca.2023.117605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 10/11/2023] [Indexed: 10/18/2023]
Abstract
Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore.
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
| | - Thi Chi Mai Tran
- Faculty of Medical Technology, Hanoi Medical University, Viet Nam; Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Viet Nam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
| | - Rosita Zakaria
- RMIT University, School of Health and Biomedical Sciences, Melbourne, Victoria, Australia; Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
| | - Elvar Theodorsson
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, SE-58183 Linkoping, Sweden
| | - Ronda F Greaves
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia.
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21
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Chong YP, Lim SM, Loh TP, Mollee P, Wijeratne N, Choy KW. Screening for and diagnosis of monoclonal gammopathy. J Clin Pathol 2023; 76:727-733. [PMID: 37604683 DOI: 10.1136/jcp-2023-208774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 08/03/2023] [Indexed: 08/23/2023]
Abstract
Monoclonal gammopathy is a spectrum of disorders characterised by clonal proliferation of plasma cells or lymphocytes, which produce abnormal immunoglobulin or its components (monoclonal proteins). Monoclonal gammopathies are often categorised as low-tumour-burden diseases (eg, amyloid light chain (AL) amyloidosis), premalignant disorders (such as monoclonal gammopathy of undetermined significance and smouldering multiple myeloma), and malignancies (eg, multiple myeloma and Waldenström's macroglobulinaemia). Such diversity of concentration and structure makes monoclonal protein a challenging clonal marker. This article provides an overview on initial laboratory testing of monoclonal gammopathy to guide clinicians and laboratory professionals in the selection and interpretation of appropriate investigations.
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Affiliation(s)
- Yuh Ping Chong
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Victoria, Australia
| | - Say Min Lim
- Department of Pathology, Hospital Teluk Intan, Teluk Intan, Malaysia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Peter Mollee
- Pathology Queensland, Princess Alexandra Hospital, Brisbane, Queensland, Australia
- School of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Nilika Wijeratne
- Dorevitch Pathology, Heidelberg, Victoria, Australia
- School of Clinical Sciences at Monash Health, Department of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
- Eastern Health Pathology, Eastern Health, Box Hill, Victoria, Australia
| | - Kay Weng Choy
- Department of Pathology, Northern Health, Epping, Victoria, Australia
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22
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Cervinski MA, Bietenbeck A, Katayev A, Loh TP, van Rossum HH, Badrick T. Advances in clinical chemistry patient-based real-time quality control (PBRTQC). Adv Clin Chem 2023; 117:223-261. [PMID: 37973321 DOI: 10.1016/bs.acc.2023.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Patient-Based Real-Time Quality Control involves monitoring an assay using patient samples rather than external material. If the patient population does not change, then a shift in the long-term assay population results represents the introduction of a change in the assay. The advantages of this approach are that the sample(s) are commutable, it is inexpensive, the rules are simple to interpret and there is virtually continuous monitoring of the assay. The disadvantages are that the laboratory needs to understand their patient population and how they may change during the day, week or year and the initial change of mindset required to adopt the system. The concept is not new, having been used since the 1960s and widely adopted on hematology analyzers in the mid-1970s. It was not widely used in clinical chemistry as there were other stable quality control materials available. However, the limitations of conventional quality control approaches have become more evident. There is a greater understanding of how to collect and use patient data in real time and a range of powerful algorithms which can identify changes in assays. There are more assays on more samples being run. There is also a greater interest in providing a theoretical basis for the validation and integration of these techniques into routine practice.
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Affiliation(s)
- Mark A Cervinski
- Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, and the Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Andreas Bietenbeck
- Institut für Klinische Chemie und Pathobiochemie Klinikum, Munich, Germany
| | - Alex Katayev
- Laboratory Corporation of America Holdings, Elon, Burlington, NC, United States
| | | | - Huub H van Rossum
- The Netherlands Cancer Institute, Amsterdam, The Netherlands; Huvaros, The Netherlands
| | - Tony Badrick
- RCPA Quality Assurance Programs, St Leonards, Sydney, Australia.
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Loh TP, Cooke BR, Tran TCM, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP checklist for Laboratory Evaluation and Analytical Performance Characteristics reporting of clinical measurement procedures. Scand J Clin Lab Invest 2023; 83:467-469. [PMID: 37838359 DOI: 10.1080/00365513.2023.2261098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 09/17/2023] [Indexed: 10/16/2023]
Abstract
Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript.The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia
| | - Thi Chi Mai Tran
- Faculty of Medical Technology, Hanoi Medical University, Hanoi, Vietnam
- Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Vietnam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
| | - Rosita Zakaria
- School of Health and Biomedical Sciences, RMIT University, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Elvar Theodorsson
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, Linkoping, Sweden
| | - Ronda F Greaves
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
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Loh TP, Lim CY, Sethi SK, Tan RZ, Markus C. Advances in internal quality control. Crit Rev Clin Lab Sci 2023; 60:502-517. [PMID: 37194676 DOI: 10.1080/10408363.2023.2209174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 04/17/2023] [Accepted: 04/27/2023] [Indexed: 05/18/2023]
Abstract
Quality control practices in the modern laboratory are the result of significant advances over the many years of the profession. Major advance in conventional internal quality control has undergone a philosophical shift from a focus solely on the statistical assessment of the probability of error identification to more recent thinking on the capability of the measurement procedure (e.g. sigma metrics), and most recently, the risk of harm to the patient (the probability of patient results being affected by an error or the number of patient results with unacceptable analytical quality). Nonetheless, conventional internal quality control strategies still face significant limitations, such as the lack of (proven) commutability of the material with patient samples, the frequency of episodic testing, and the impact of operational and financial costs, that cannot be overcome by statistical advances. In contrast, patient-based quality control has seen significant developments including algorithms that improve the detection of specific errors, parameter optimization approaches, systematic validation protocols, and advanced algorithms that require very low numbers of patient results while retaining sensitive error detection. Patient-based quality control will continue to improve with the development of new algorithms that reduce biological noise and improve analytical error detection. Patient-based quality control provides continuous and commutable information about the measurement procedure that cannot be easily replicated by conventional internal quality control. Most importantly, the use of patient-based quality control helps laboratories to improve their appreciation of the clinical impact of the laboratory results produced, bringing them closer to the patients.Laboratories are encouraged to implement patient-based quality control processes to overcome the limitations of conventional internal quality control practices. Regulatory changes to recognize the capability of patient-based quality approaches, as well as laboratory informatics advances, are required for this tool to be adopted more widely.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Sunil Kumar Sethi
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia
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Loh TP, Cooke BR, Tran TCM, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures. Biochem Med (Zagreb) 2023; 33:030505. [PMID: 37841772 PMCID: PMC10564153 DOI: 10.11613/bm.2023.030505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 09/18/2023] [Indexed: 10/17/2023] Open
Abstract
Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the Laboratory Evaluation and Analytical Performance Characteristics (LEAP) checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Australia
| | - Thi Chi Mai Tran
- Faculty of Medical Technology, Hanoi Medical University, Hanoi, Vietnam
- Department of Clinical Biochemistry, National Children’s Hospital, Hanoi, Vietnam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
| | - Rosita Zakaria
- RMIT University, School of Health and Biomedical Sciences, Victoria, Australia
- Murdoch Children’s Research Institute, Melbourne, Australia
| | - Chung Shun Ho
- Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Elvar Theodorsson
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, SE-58183 Linkoping, Sweden
| | - Ronda F Greaves
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, Australia
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Loh TP, Cooke BR, Tran TCM, Markus C, Zakaria R, Ho CS, Theodorsson E, Greaves RF. The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures. Clin Chem Lab Med 2023:cclm-2023-0933. [PMID: 37838925 DOI: 10.1515/cclm-2023-0933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 08/24/2023] [Indexed: 10/16/2023]
Abstract
Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, WA, Australia
| | - Thi Chi Mai Tran
- Faculty of Medical Technology, Hanoi Medical University, Hanoi, Vietnam
- Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Vietnam
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, Australia
| | - Rosita Zakaria
- RMIT University, School of Health and Biomedical Sciences, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
| | - Elvar Theodorsson
- Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology, Linkoping University, Linkoping, Sweden
| | - Ronda F Greaves
- Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
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Van Uytfanghe K, Ehrenkranz J, Halsall D, Hoff K, Loh TP, Spencer CA, Köhrle J. Thyroid Stimulating Hormone and Thyroid Hormones (Triiodothyronine and Thyroxine): An American Thyroid Association-Commissioned Review of Current Clinical and Laboratory Status. Thyroid 2023; 33:1013-1028. [PMID: 37655789 PMCID: PMC10517335 DOI: 10.1089/thy.2023.0169] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
Background: Despite being the most performed laboratory endocrine investigation, the optimum use of thyroid tests (thyrotropin [TSH] and thyroid hormone [TH] measurement) is open to question and the interpretation of the results from these tests can be ambiguous. The American Thyroid Association (ATA) with its expertise support the endeavor of the U.S. Centers for Disease Control (CDC) and the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) to improve and maintain standardization and harmonization of thyroid testing. ATA mandated an international interdisciplinary working group panel to survey the status of thyroid testing by reviewing the recent literature to revise or update the criteria as needed in mutual agreement and to inform clinical care. Summary: This review represents the conclusions on the clinical use of current routine TSH and TH (thyroxine [T4] and triiodothyronine [T3]) assays, taking into account geographic differences in disease prevalence and clinical and laboratory practice among writing members. The interaction between physiological, pathophysiological, and pharmacological factors and thyroid assays can affect their measurements and confound result interpretation. These factors need to be considered in the clinical context of the patient for appropriate test ordering and result interpretation. Despite significant advances in laboratory methods over the past 50 years, routine thyroid assays remain susceptible to idiosyncratic analytical interference that may produce spurious results. Improved standardization needs to be demonstrated through ongoing international efforts before results from different assays can be considered equivalent. Emerging technology (e.g., mass spectrometry) shows promise for improved analytical performance, but more evidence of its clinical utility and improved throughput is required before it can be considered for routine use. Close clinical-laboratory collaboration is encouraged to overcome and avoid the pitfalls in thyroid testing as well as resolve clinically discrepant results. The evidence base supporting the conclusions of this review is summarized in four detailed online technical supplements. Conclusions: Over the past five decades, testing for TSH, T4, and T3 has evolved from manual radioisotopic immunoassays to nonisotopic multiplexed immunometric assays using highly automated equipment. Despite these technical advances, physicians and laboratorians performing these analyses must understand limitations of these methods to properly order tests and interpret results.
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Affiliation(s)
- Katleen Van Uytfanghe
- Ref4U—Laboratory of Toxicology, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
| | - Joel Ehrenkranz
- Department of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA
| | - David Halsall
- Cambridge University Hospitals Trust, Addenbrookes Hospital, Cambridge, United Kingdom
| | - Kelly Hoff
- American Thyroid Association, Headquarters, Alexandria, Virginia, USA
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Carole A. Spencer
- Department of Medicine, University of Southern California, Los Angeles, California, USA
| | - Josef Köhrle
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institut für Experimentelle Endokrinologie, Berlin, Germany
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Chuah TY, Lim CY, Tan RZ, Pratumvinit B, Loh TP, Vasikaran S, Markus C. Functional Reference Limits: Describing Physiological Relationships and Determination of Physiological Limits for Enhanced Interpretation of Laboratory Results. Ann Lab Med 2023; 43:408-417. [PMID: 37080741 PMCID: PMC10151278 DOI: 10.3343/alm.2023.43.5.408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 01/31/2023] [Accepted: 03/27/2023] [Indexed: 04/22/2023] Open
Abstract
Functional reference limits describe key changes in the physiological relationship between a pair of physiologically related components. Statistically, this can be represented by a significant change in the curvature of a mathematical function or curve (e.g., an observed plateau). The point at which the statistical relationship changes significantly is the point of curvature inflection and can be mathematically modeled from the relationship between the interrelated biomarkers. Conceptually, they reside between reference intervals, which describe the statistical boundaries of a single biomarker within the reference population, and clinical decision limits that are often linked to the risk of morbidity or mortality and set as thresholds. Functional reference limits provide important physiological and pathophysiological insights that can aid laboratory result interpretation. Laboratory professionals are in a unique position to harness data from laboratory information systems to derive clinically relevant values. Increasing research on and reporting of functional reference limits in the literature will enhance their contribution to laboratory medicine and widen the evidence base used in clinical decision limits, which are currently almost exclusively contributed to by clinical trials. Their inclusion in laboratory reports will enhance the intellectual value of laboratory professionals in clinical care beyond the statistical boundaries of a healthy reference population and pave the way to them being considered in shaping clinical decision limits. This review provides an overview of the concepts related to functional reference limits, clinical examples of their use, and the impetus to include them in laboratory reports.
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Affiliation(s)
- Tyng Yu Chuah
- Department of General Medicine (Rheumatology), Sengkang General Hospital,Singapore, Singapore
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | | | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Samuel Vasikaran
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Adelaide, Australia
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia
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Zhang Y, Wong CY, Lim CZJ, Chen Q, Yu Z, Natalia A, Wang Z, Pang QY, Lim SW, Loh TP, Ang BT, Tang C, Shao H. Multiplexed RNA profiling by regenerative catalysis enables blood-based subtyping of brain tumors. Nat Commun 2023; 14:4278. [PMID: 37460561 DOI: 10.1038/s41467-023-39844-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 06/29/2023] [Indexed: 07/20/2023] Open
Abstract
Current technologies to subtype glioblastoma (GBM), the most lethal brain tumor, require highly invasive brain biopsies. Here, we develop a dedicated analytical platform to achieve direct and multiplexed profiling of circulating RNAs in extracellular vesicles for blood-based GBM characterization. The technology, termed 'enzyme ZIF-8 complexes for regenerative and catalytic digital detection of RNA' (EZ-READ), leverages an RNA-responsive transducer to regeneratively convert and catalytically enhance signals from rare RNA targets. Each transducer comprises hybrid complexes - protein enzymes encapsulated within metal organic frameworks - to configure strong catalytic activity and robust protection. Upon target RNA hybridization, the transducer activates directly to liberate catalytic complexes, in a target-recyclable manner; when partitioned within a microfluidic device, these complexes can individually catalyze strong chemifluorescence reactions for digital RNA quantification. The EZ-READ platform thus enables programmable and reliable RNA detection, across different-sized RNA subtypes (miRNA and mRNA), directly in sample lysates. When clinically evaluated, the EZ-READ platform established composite signatures for accurate blood-based GBM diagnosis and subtyping.
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Affiliation(s)
- Yan Zhang
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Chi Yan Wong
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Carine Z J Lim
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Qingchang Chen
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Zhonglang Yu
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Auginia Natalia
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Zhigang Wang
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
| | - Qing You Pang
- Neuro-Oncology Research Laboratory, Department of Research, National Neuroscience Institute, Singapore, Singapore
| | - See Wee Lim
- Neuro-Oncology Research Laboratory, Department of Research, National Neuroscience Institute, Singapore, Singapore
| | - Tze Ping Loh
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Beng Ti Ang
- Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Carol Tang
- Neuro-Oncology Research Laboratory, Department of Research, National Neuroscience Institute, Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University Singapore, Singapore, Singapore
| | - Huilin Shao
- Institute for Health Innovation & Technology, National University of Singapore, Singapore, Singapore.
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore.
- National Neuroscience Institute, Singapore, Singapore.
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore.
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Markus C, Coat S, Marschall HU, Matthews S, Loh TP, Rankin W, Hague WM. Lot-to-lot reagent changes and commutability of quality testing materials for total bile acid measurements. Clin Chem Lab Med 2023; 61:e108-e111. [PMID: 36639839 DOI: 10.1515/cclm-2022-1278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 12/28/2022] [Indexed: 01/15/2023]
Affiliation(s)
- Corey Markus
- International Centre for Point-of-Care Testing, Flinders University, Adelaide, Australia
| | - Suzette Coat
- Robinson Research Institute, The University of Adelaide, Adelaide, Australia
| | | | - Susan Matthews
- International Centre for Point-of-Care Testing, Flinders University, Adelaide, Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Wayne Rankin
- Chemical Pathology Directorate, SA Pathology, Adelaide, Australia
- Endocrine and Metabolic Unit, Royal Adelaide Hospital, Adelaide, Australia
- Adelaide Medical School, The University of Adelaides, Adelaide, Australia
| | - William M Hague
- Robinson Research Institute, The University of Adelaide, Adelaide, Australia
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Lim CY, Markus C, Greaves R, Loh TP. Difference- and regression-based approaches for detection of bias. Clin Biochem 2023; 114:86-94. [PMID: 36822348 DOI: 10.1016/j.clinbiochem.2023.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 02/07/2023] [Accepted: 02/18/2023] [Indexed: 02/23/2023]
Abstract
OBJECTIVE This simulation study was undertaken to assess the statistical performance of six commonly used rejection criteria for bias detection. METHODS The false rejection rate (i.e. rejection in the absence of simulated bias) and the probability of bias detection were assessed for the following: difference in measurements for individual sample pair, the mean of the paired differences, t-statistics (paired t-test), slope < 0.9 or > 1.1, intercept > 50% of the lower limit of measurement range, and coefficient of determination (R2) > 0.95. The linear regressions evaluated were ordinary least squares, weighted least squares and Passing-Bablok regressions. A bias detection rate of < 50% and false rejection rates of >10% are considered unacceptable for the purpose of this study. RESULTS Rejection criteria based on regression slope, intercept and paired difference (10%) for individual samples have high false rejection rates and/ or low probability of bias detection. T-statistics (α = 0.05) performed best in low range ratio (lowest-to-highest concentration in measurement range) and low imprecision scenarios. Mean difference (10%) performed better in all other range ratio and imprecision scenarios. Combining mean difference and paired-t test improves the power of bias detection but carries higher false rejection rates. CONCLUSIONS This study provided objective evidence on commonly used rejection criteria to guide laboratory on the experimental design and statistical assessment for bias detection during method evaluation or reagent lot verification.
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Affiliation(s)
- Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia
| | - Ronda Greaves
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore.
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Loh TP, Tan RZ, Sethi SK, Lim CY, Markus C. Delta checks. Adv Clin Chem 2023; 115:175-203. [PMID: 37673520 DOI: 10.1016/bs.acc.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Abstract
Delta check is an electronic error detection tool. It compares the difference in sequential results within a patient against a predefined limit, and when exceeded, the delta check rule is considered triggered. The patient results should be withheld for review and troubleshooting before releasing to the clinical team for patient management. Delta check was initially developed as a tool to detect wrong-blood-in-tube (sample misidentification) errors. It is now applied to detect errors more broadly within the total testing process. Recent advancements in the theoretical understanding of delta check has allowed for more precise application of this tool to achieve the desired clinical performance and operational set up. In this Chapter, we review the different pre-implementation considerations, the foundation concepts of delta check, the process of setting up key delta check parameters, performance verification and troubleshooting of a delta check flag.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore.
| | - Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, Singapore
| | - Sunil Kumar Sethi
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, College of Medicine & Public Health, Flinders University, Adelaide, SA, Australia
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Badrick T, Loh TP. Developing an evidence-based approach to quality control. Clin Biochem 2023; 114:39-42. [PMID: 36736647 DOI: 10.1016/j.clinbiochem.2023.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 01/23/2023] [Accepted: 01/26/2023] [Indexed: 02/04/2023]
Abstract
Effective Quality Control remains one of the pillars of Clinical Biochemistry. An understanding of the possible analytical errors that may occur, how to detect them efficiently and how to prevent them from causing patient harm are critical components of a Quality System. For some time, there have been questions about the theoretical basis of the models used to describe and detect analytical error. The current theory recognises two types of error, systematic and random and a system based on sampling the analytical process using a synthetic material to detect these errors. However, there are at least two other errors that are present. One is related to the QC material and the other, irregular errors. In this Opinion Piece, some of the underlying assumptions of Quality Control systems are described and analysed.
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Affiliation(s)
- Tony Badrick
- RCPA Quality Assurance Programs, St Leonards, Sydney, Australia.
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34
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Loh TP, Ehrenkranz J, Halsall D, Spencer CA, Van Uytfanghe K, Köhrle J. Clinical interpretation of thyroid tests: considerations for reference intervals. Thyroid 2023; 33:404-406. [PMID: 36927102 DOI: 10.1089/thy.2023.0096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Affiliation(s)
- Tze Ping Loh
- National University Hospital, Singapore. , Department of Laboratory Medicine, , Singapore, Singapore;
| | - Joel Ehrenkranz
- California Institute of Technology, Department of Chemistry and Chemical Engineering, Pasadena, California, United States;
| | - David Halsall
- Cambridge University Hospitals NHS Foundation Trust, 2153, Clinical BIochemistry, Cambridge, United Kingdom of Great Britain and Northern Ireland, CB2 0QQ;
| | - Carole A Spencer
- University Southern California, Department of Medicine, Los Angeles, California, United States;
| | - Katleen Van Uytfanghe
- Ghent University, 26656, Ref4U (Former Laboratory for Analytical Chemistry) - Laboratory of Toxicology, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Gent, Belgium;
| | - Josef Köhrle
- Charité, Inst. Exp. Endokrinologie, Schumannstr. 20/21, Berlin, Germany, D-10098;
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Lo CWS, Hoad K, Loh TP, van den Berg S, Cooke BR, Greaves RF, Hartmann MF, Wudy SA, Ho CS. Endogenous isobaric interference on serum 17 hydroxyprogesterone by liquid chromatography-tandem mass spectrometry methods. Clin Chem Lab Med 2023; 61:e64-e66. [PMID: 36457285 DOI: 10.1515/cclm-2022-1086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/21/2022] [Indexed: 12/03/2022]
Affiliation(s)
- Clara Wai Shan Lo
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
| | - Kirsten Hoad
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Sjoerd van den Berg
- Department of Clinical Chemistry and Department of Internal Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia
| | - Ronda F Greaves
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Michaela F Hartmann
- Steroid Research & Mass Spectrometry Unit of the Laboratory for Translational Hormone Analytics in Pediatric Endocrinology at the Justus Liebig University, Giessen, Germany
| | - Stefan A Wudy
- Steroid Research & Mass Spectrometry Unit of the Laboratory for Translational Hormone Analytics in Pediatric Endocrinology at the Justus Liebig University, Giessen, Germany
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
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Lim CY, Markus C, Loh TP. Lot-to-lot difference: a new approach to evaluate regression studies. Scand J Clin Lab Invest 2023; 83:58-59. [PMID: 36519732 DOI: 10.1080/00365513.2022.2155992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Adelaide, Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
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Liu H, Ng CY, Liu Q, Teo TL, Loh TP, Wong MS, Sethi SK, Tan JG, Heng PY, Saw S, Lam LCW, Lee JMY, Khaled KB, Phyu HP, Ong NWT. Commutability assessment of human urine certified reference materials for albumin and creatinine on multiple clinical analyzers using different statistical models. Anal Bioanal Chem 2023; 415:787-800. [PMID: 36562812 DOI: 10.1007/s00216-022-04472-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/27/2022] [Accepted: 12/01/2022] [Indexed: 12/24/2022]
Abstract
Urine albumin concentration and albumin-creatinine ratio are important for the screening of early-stage kidney damage. Commutable urine certified reference materials (CRMs) for albumin and creatinine are necessary for standardization of urine albumin and accurate measurement of albumin-urine ratio. Two urine CRMs for albumin and creatinine with certified values determined using higher-order reference measurement procedures were evaluated for their commutability on five brands/models of clinical analyzers where different reagent kits were used, including Roche Cobas c702, Roche Cobas c311, Siemens Atellica CH, Beckman Coulter AU5800, and Abbott Architect c16000. The commutability study was conducted by measuring at least 26 authentic patient urine samples and the human urine CRMs using both reference measurement procedures and the routine methods. Both the linear regression model suggested by the Clinical and Laboratory Standard Institute (CLSI) guidelines and log-transformed model recommended by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Commutability Working Group were used to evaluate the commutability of the human urine CRMs. The commutability of the human urine CRMs was found to be generally satisfactory on all five clinical analyzers for both albumin and creatinine, suggesting that they are suitable to be used routinely by clinical laboratories as quality control or for method validation of urine albumin and creatinine measurements.
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Affiliation(s)
- Hong Liu
- Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore, 117528, Singapore
| | - Cheng Yang Ng
- Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore, 117528, Singapore
| | - Qinde Liu
- Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore, 117528, Singapore.
| | - Tang Lin Teo
- Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore, 117528, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Moh Sim Wong
- Department of Laboratory Medicine, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Sunil Kumar Sethi
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Jun Guan Tan
- Department of Laboratory Medicine, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Ping Ying Heng
- Department of Laboratory Medicine, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Sharon Saw
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | | | | | - Khairee Bin Khaled
- Department of Laboratory Medicine, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Hnin Pwint Phyu
- Department of Laboratory Medicine, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Noel Wan Ting Ong
- Department of Laboratory Medicine, Ng Teng Fong General Hospital, Singapore, Singapore
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Lim CY, Ow Yang S, Markus C, Loh TP. Calibration frequency and analytical variability of laboratory measurements. Clin Chim Acta 2023; 539:87-89. [PMID: 36513171 DOI: 10.1016/j.cca.2022.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/02/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND There is uncertainty whether increased frequency of calibrations may affect the overall analytical variability of a measurement procedure as reflected in quality control (QC) performance. In this simulation study, we examined the impact of calibration frequencies on the variability of laboratory measurements. METHODS A 5-point calibration curve was modeled with simulated concentrations ranging from 10 to 10,000 mmol/l, and signal intensities with CVs of 3 % around the mean, under a Gaussian distribution. 3 levels of QC (20, 150, 600 mmol/l) interspersed within the analytical measurement range were also simulated. RESULTS The CV of the 3 QC levels remained stable across the different calibration frequencies simulated (5, 10, 15 and 30 QC measurements per recalibration episode). The imprecision was greatest (18 %) at the lowest concentration of 20 mmol/l, when the calibration curve was derived using ordinary least squares regression, reducing to 3.5 % and 3.8 % at 150 and 600 mmol/l, respectively. The CV of all 3 QC concentrations remained constant at 3.4 % and close the predefined CV (3 %) when weighted least squares regression was used to derive the calibration model. Similar findings were observed with 2-point calibrations using WLS models at narrower concentration ranges (50 and 100 mmol/l as well as 50 and 500 mmol/l). DISCUSSION Within the parameters of the simulation study, an increased frequency of calibration events does not adversely impact the overall analytical performance of a measurement procedure under most circumstances.
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Affiliation(s)
- Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore
| | - Shin Ow Yang
- Engineering Cluster, Singapore Institute of Technology, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, SA, Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore.
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Cheng WL, Markus C, Lim CY, Tan RZ, Sethi SK, Loh TP. Calibration Practices in Clinical Mass Spectrometry: Review and Recommendations. Ann Lab Med 2023; 43:5-18. [PMID: 36045052 PMCID: PMC9467832 DOI: 10.3343/alm.2023.43.1.5] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 06/30/2022] [Accepted: 08/18/2022] [Indexed: 12/27/2022] Open
Abstract
Background Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and implementation of a new calibration curve is often underappreciated. This systematic review examined how calibration practices are applied to liquid chromatography-tandem mass spectrometry measurement procedures. Methods The electronic database PubMed was searched from the date of database inception to April 1, 2022. The search terms used were "calibration," "mass spectrometry," and "regression." Twenty-one articles were identified and included in this review, following evaluation of the titles, abstracts, full text, and reference lists of the search results. Results The use of matrix-matched calibrators and stable isotope-labeled internal standards helps to mitigate the impact of matrix effects. A higher number of calibration standards or replicate measurements improves the mapping of the detector response and hence the accuracy and precision of the regression model. Constructing a calibration curve with each analytical batch recharacterizes the instrument detector but does not reduce the actual variability. The analytical response and measurand concentrations should be considered when constructing a calibration curve, along with subsequent use of quality controls to confirm assay performance. It is important to assess the linearity of the calibration curve by using actual experimental data and appropriate statistics. The heteroscedasticity of the calibration data should be investigated, and appropriate weighting should be applied during regression modeling. Conclusions This review provides an outline and guidance for optimal calibration practices in clinical mass spectrometry laboratories.
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Affiliation(s)
- Wan Ling Cheng
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Sunil Kumar Sethi
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
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Ting HY, Ting IPL, Lo SC, Loh TP. Falsely low serum creatinine caused by immunoglobulin M paraprotein interference with enzymatic method. Pathology 2022; 54:959-962. [PMID: 35527046 DOI: 10.1016/j.pathol.2022.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/18/2022] [Accepted: 01/24/2022] [Indexed: 12/14/2022]
Affiliation(s)
- Huong Yew Ting
- Department of Pathology, Miri General Hospital, Sarawak, Malaysia.
| | | | - Shao Ching Lo
- Department of Pathology, Miri General Hospital, Sarawak, Malaysia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
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Loh TP, Markus C, Tan CH, Tran MTC, Sethi SK, Lim CY. Lot-to-lot variation and verification. Clin Chem Lab Med 2022; 61:769-776. [PMID: 36420533 DOI: 10.1515/cclm-2022-1126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 11/14/2022] [Indexed: 11/24/2022]
Abstract
Abstract
Lot-to-lot verification is an integral component for monitoring the long-term stability of a measurement procedure. The practice is challenged by the resource requirements as well as uncertainty surrounding experimental design and statistical analysis that is optimal for individual laboratories, although guidance is becoming increasingly available. Collaborative verification efforts as well as application of patient-based monitoring are likely to further improve identification of any differences in performance in a relatively timely manner. Appropriate follow up actions of failed lot-to-lot verification is required and must balance potential disruptions to clinical services provided by the laboratory. Manufacturers need to increase transparency surrounding release criteria and work closer with laboratory professionals to ensure acceptable reagent lots are released to end users. A tripartite collaboration between regulatory bodies, manufacturers, and laboratory medicine professional bodies is key to developing a balanced system where regulatory, manufacturing, and clinical requirements of laboratory testing are met, to minimize differences between reagent lots and ensure patient safety. Clinical Chemistry and Laboratory Medicine has served as a fertile platform for advancing the discussion and practice of lot-to-lot verification in the past 60 years and will continue to be an advocate of this important topic for many more years to come.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine , National University Hospital , Singapore , Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing , Flinders Health and Medical Research Institute , Adelaide , SA , Australia
| | - Chin Hon Tan
- Department of Industrial and Systems Engineering , National University of Singapore , Singapore , Singapore
| | - Mai Thi Chi Tran
- Faculty of Medical Technology , Hanoi Medical University , Hanoi , Vietnam
- Department of Clinical Biochemistry , National Children’s Hospital , Hanoi , Vietnam
| | - Sunil Kumar Sethi
- Department of Laboratory Medicine , National University Hospital , Singapore , Singapore
| | - Chun Yee Lim
- Engineering Cluster , Singapore Institute of Technology , Singapore , Singapore
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Loh TP, Cooke BR, Markus C, Zakaria R, Tran MTC, Ho CS, Greaves RF. Method evaluation in the clinical laboratory. Clin Chem Lab Med 2022; 61:751-758. [PMID: 36327459 DOI: 10.1515/cclm-2022-0878] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 09/22/2022] [Indexed: 11/06/2022]
Abstract
Method evaluation is one of the critical components of the quality system that ensures the ongoing quality of a clinical laboratory. As part of implementing new methods or reviewing best practices, the peer-reviewed published literature is often searched for guidance. From the outset, Clinical Chemistry and Laboratory Medicine (CCLM) has a rich history of publishing methods relevant to clinical laboratory medicine. An insight into submissions, from editors' and reviewers' experiences, shows that authors still struggle with method evaluation, particularly the appropriate requirements for validation in clinical laboratory medicine. Here, we consider through a series of discussion points an overview of the status, challenges, and needs of method evaluation from the perspective of clinical laboratory medicine. We identify six key high-level aspects of clinical laboratory method evaluation that potentially lead to inconsistency. 1. Standardisation of terminology, 2. Selection of analytical performance specifications, 3. Experimental design of method evaluation, 4. Sample requirements of method evaluation, 5. Statistical assessment and interpretation of method evaluation data, and 6. Reporting of method evaluation data. Each of these areas requires considerable work to harmonise the practice of method evaluation in laboratory medicine, including more empirical studies to be incorporated into guidance documents that are relevant to clinical laboratories and are freely and widely available. To further close the loop, educational activities and fostering professional collaborations are essential to promote and improve the practice of method evaluation procedures.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Brian R Cooke
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Fiona Stanley Hospital, Murdoch, WA, Australia
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Adelaide, SA, Australia
| | - Rosita Zakaria
- School of Health and Biomedical Sciences, RMIT University, Melbourne, VIC, Australia.,Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Mai Thi Chi Tran
- Faculty of Medical Technology, Hanoi Medical University, Hanoi, Vietnam.,Department of Clinical Biochemistry, National Children's Hospital, Hanoi, Vietnam
| | - Chung Shun Ho
- Biomedical Mass Spectrometry Unit, Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, NT, Hong Kong
| | - Ronda F Greaves
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, VIC, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia
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Loh TP, Tan RZ, Lim CY, Markus C. An Objective Approach to Deriving the Clinical Performance of Autoverification Limits. Ann Lab Med 2022; 42:597-601. [PMID: 35470278 PMCID: PMC9057817 DOI: 10.3343/alm.2022.42.5.597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 09/07/2021] [Accepted: 01/28/2022] [Indexed: 11/19/2022] Open
Abstract
This study describes an objective approach to deriving the clinical performance of autoverification rules to inform laboratory practice when implementing them. Anonymized historical laboratory data for 12 biochemistry measurands were collected and Box-Cox-transformed to approximate a Gaussian distribution. The historical laboratory data were assumed to be error-free. Using the probability theory, the clinical specificity of a set of autoverification limits can be derived by calculating the percentile values of the overall distribution of a measurand. The 5th and 95th percentile values of the laboratory data were calculated to achieve a 90% clinical specificity. Next, a predefined tolerable total error adopted from the Royal College of Pathologists of Australasia Quality Assurance Program was applied to the extracted data before subjecting to Box-Cox transformation. Using a standard normal distribution, the clinical sensitivity can be derived from the probability of the Z-value to the right of the autoverification limit for a one-tailed probability and multiplied by two for a two-tailed probability. The clinical sensitivity showed an inverse relationship with between-subject biological variation. The laboratory can set and assess the clinical performance of its autoverification rules that conforms to its desired risk profile.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia
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Loh TP, Greaves RF, Mak CM, Salomons GS, Bonham JR, Lang T. Impact of COVID-19 on Pediatric Laboratory Medicine: An IFCC C-ETPLM, SSIEM, ISNS Global Survey. EJIFCC 2022; 33:194-208. [PMID: 36313903 PMCID: PMC9562476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
OBJECTIVE Pediatric laboratory medicine is a unique practice serving a vulnerable group of patients including highly specialized testing aiming to detect and treat inherited conditions early to avoid adverse outcomes. Data on the actual impact of COVID-19 pandemic on this speciality is lacking. METHODS A survey was conducted by the IFCC Committee on Emerging Technologies in Pediatric Laboratory Medicine in partnership with the Society for the Study of Inborn Errors of Metabolism and International Society for Neonatal Screening, to assess the impact on the clinical service provision during the initial wave (January to July 2020) of the COVID-19 pandemic and to gather experiences learned in order to improve laboratory preparedness for future outbreaks. RESULTS 217 survey responses were received from 69 regions. Sixty-three laboratories (29%) reported a restriction or suspension of service for a median period of four months. The common tests/ services suspended were new-born screening program, body fluids and sweat testing. The reasons for the suspension were related to bio-safety risks of COVID-19 transmission, manpower constraints and supplies disruption. A minority (9-10%) of laboratories did observe delayed/missed diagnoses or a more severe presentation of a clinical disorder. The critical operational decisions that helped manage the initial wave of COVID-19 included modifying work shift patterns, split-teams arrangement, use of personal protection equipment and social distancing. CONCLUSION The provision and delivery of pediatric laboratories services were affected during the initial wave of the COVID-19 pandemic. Manpower preparedness for future potential disruptions to pediatric laboratory services is a key finding and recommendation from this survey.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore,Corresponding authors: Dr. Tze Ping Loh 5 Lower Kent Ridge Road Singapore 119074 Phone: (+65) 67724345 Fax: (+65) 67771613 E-mail:
| | - Ronda F. Greaves
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Victoria, Australia
| | - Chloe M. Mak
- Division of Chemical Pathology, Hong Kong Children’s Hospital, Hong Kong SAR, China
| | - Gajja S. Salomons
- Department of Clinical Chemistry, Metabolic Unit, VU University Medical Center & Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - James R. Bonham
- Pharmacy, Diagnostics and Genetics, Sheffield Children’s Hospital NHS Foundation Trust, Sheffield, United Kingdom
| | - Tim Lang
- Department of Clinical Biochemistry, University Hospital of North Durham, United Kingdom
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Koh NWX, Markus C, Loh TP, Lim CY. Lot-to-lot reagent verification: Effect of sample size and replicate measurement on linear regression approaches. Clin Chim Acta 2022; 534:29-34. [PMID: 35810798 DOI: 10.1016/j.cca.2022.07.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/30/2022] [Accepted: 07/05/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND We investigate the simulated impact of varying sample size and replicate number using ordinary least squares (OLS) and Deming regression (DR) in both weighted and unweighted forms, when applied to paired measurements in lot-to-lot verification. METHODS Simulation parameter investigated in this study were: range ratio, analytical coefficient of variation, sample size, replicates, alpha (level of significance) and constant and proportional biases. For each simulation scenario, 10,000 iterations were performed, and the average probability of bias detection was determined. RESULTS Generally, the weighted forms of regression significantly outperformed the unweighted forms for bias detection. At the low range ratio (1:10), for both weighted OLS and DR, improved bias detection was observed with greater number of replicates, than increasing the number of comparison samples. At the high range ratio (1:1000), for both weighted OLS and DR, increasing the number of replicates above two is only slightly more advantageous in the scenarios examined. Increasing the numbers of comparison samples resulted in better detection of smaller biases between reagent lots. CONCLUSIONS The results of this study allow laboratories to determine a tailored approach to lot-to-lot verification studies, balancing the number of replicates and comparison samples with the analytical performance of measurement procedures involved.
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Affiliation(s)
| | - Corey Markus
- Flinders University International Centre-for-Point of Care Testing, Flinders Health and Medical Research Institute, Bedford Park, Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore.
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore
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46
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Markus C, Tan RZ, Lim CY, Rankin W, Matthews SJ, Loh TP, Hague WM. Performance of four regression frameworks with varying precision profiles in simulated reference material commutability assessment. Clin Chem Lab Med 2022; 60:1164-1174. [PMID: 35647783 DOI: 10.1515/cclm-2022-0205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 05/12/2022] [Indexed: 11/15/2022]
Abstract
OBJECTIVES One approach to assessing reference material (RM) commutability and agreement with clinical samples (CS) is to use ordinary least squares or Deming regression with prediction intervals. This approach assumes constant variance that may not be fulfilled by the measurement procedures. Flexible regression frameworks which relax this assumption, such as quantile regression or generalized additive models for location, scale, and shape (GAMLSS), have recently been implemented, which can model the changing variance with measurand concentration. METHODS We simulated four imprecision profiles, ranging from simple constant variance to complex mixtures of constant and proportional variance, and examined the effects on commutability assessment outcomes with above four regression frameworks and varying the number of CS, data transformations and RM location relative to CS concentration. Regression framework performance was determined by the proportion of false rejections of commutability from prediction intervals or centiles across relative RM concentrations and was compared with the expected nominal probability coverage. RESULTS In simple variance profiles (constant or proportional variance), Deming regression, without or with logarithmic transformation respectively, is the most efficient approach. In mixed variance profiles, GAMLSS with smoothing techniques are more appropriate, with consideration given to increasing the number of CS and the relative location of RM. In the case where analytical coefficients of variation profiles are U-shaped, even the more flexible regression frameworks may not be entirely suitable. CONCLUSIONS In commutability assessments, variance profiles of measurement procedures and location of RM in respect to clinical sample concentration significantly influence the false rejection rate of commutability.
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Affiliation(s)
- Corey Markus
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Bedford Park, Australia
| | - Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Wayne Rankin
- Chemical Pathology Directorate, SA Pathology, Adelaide, Australia.,Endocrine and Metabolic Unit, Royal Adelaide Hospital, Adelaide, Australia.,Adelaide Medical School, The University of Adelaide, Adelaide, Australia
| | - Susan J Matthews
- Flinders University International Centre for Point-of-Care Testing, Flinders Health and Medical Research Institute, Bedford Park, Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - William M Hague
- Robinson Research Institute, The University of Adelaide, Adelaide, Australia
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47
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Koh NWX, Markus C, Loh TP, Lim CY. Comparison of six regression-based lot-to-lot verification approaches. Clin Chem Lab Med 2022; 60:1175-1185. [PMID: 35576605 DOI: 10.1515/cclm-2022-0274] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 04/29/2022] [Indexed: 11/15/2022]
Abstract
OBJECTIVES Detection of between-lot reagent bias is clinically important and can be assessed by application of regression-based statistics on several paired measurements obtained from the existing and new candidate lot. Here, the bias detection capability of six regression-based lot-to-lot reagent verification assessments, including an extension of the Bland-Altman with regression approach are compared. METHODS Least squares and Deming regression (in both weighted and unweighted forms), confidence ellipses and Bland-Altman with regression (BA-R) approaches were investigated. The numerical simulation included permutations of the following parameters: differing result range ratios (upper:lower measurement limits), levels of significance (alpha), constant and proportional biases, analytical coefficients of variation (CV), and numbers of replicates and sample sizes. The sample concentrations simulated were drawn from a uniformly distributed concentration range. RESULTS At a low range ratio (1:10, CV 3%), the BA-R performed the best, albeit with a higher false rejection rate and closely followed by weighted regression approaches. At larger range ratios (1:1,000, CV 3%), the BA-R performed poorly and weighted regression approaches performed the best. At higher assay imprecision (CV 10%), all six approaches performed poorly with bias detection rates <50%. A lower alpha reduced the false rejection rate, while greater sample numbers and replicates improved bias detection. CONCLUSIONS When performing reagent lot verification, laboratories need to finely balance the false rejection rate (selecting an appropriate alpha) with the power of bias detection (appropriate statistical approach to match assay performance characteristics) and operational considerations (number of clinical samples and replicates, not having alternate reagent lot).
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Affiliation(s)
- Norman Wen Xuan Koh
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
| | - Corey Markus
- Department of Chemical Pathology, New South Wales Health Pathology, Prince of Wales Hospital, Sydney, Australia
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Chun Yee Lim
- Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore
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Abstract
Lot-to-lot verification is an important laboratory activity that is performed to monitor the consistency of analytical performance over time. In this opinion paper, the concept, clinical impact, challenges and potential solutions for lot-to-lot verification are exained.
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Affiliation(s)
- Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Sverre Sandberg
- Norwegian Organization for Quality Improvement of Laboratory Examinations (NOKLUS), Haraldsplass Deaconess Hospital, Bergen, Norway
- Department of Medical Biochemistry and Pharmacology, Norwegian Porphyria Centre, Haukeland University Hospital, Bergen, Norway
- Institute of Public Health and Primary Health Care, University of Bergen, Bergen, Norway
| | - Andrea Rita Horvath
- Department of Chemical Pathology, New South Wales Health Pathology, Prince of Wales Hospital, Sydney, Australia
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49
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Magkos F, Lee MH, Lim M, Cook AR, Chhay V, Loh TP, Chia KS, Baig S, Ang IYH, Tay JYY, Khoo CM, Halter JB, Toh SA. Dynamic assessment of insulin secretion and insulin resistance in Asians with prediabetes. Metabolism 2022; 128:154957. [PMID: 34942192 DOI: 10.1016/j.metabol.2021.154957] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 12/03/2021] [Accepted: 12/13/2021] [Indexed: 11/18/2022]
Abstract
AIMS/HYPOTHESIS Prediabetes and type 2 diabetes are highly prevalent in Asia. Understanding the pathophysiology of abnormal glucose homeostasis in Asians will have important implications for reducing disease burden, but there have been conflicting reports on the relative contributions of insulin secretion and action in disease progression. In this study, we aimed to assess the contribution of β-cell dysfunction and insulin resistance in the Asian prediabetes phenotype. METHODS We recruited 1679 Asians with prediabetes (n = 659) or normoglycemia (n = 1020) from a multi-ethnic population in Singapore. Participants underwent an oral glucose tolerance test, an intravenous glucose challenge, and a hyperinsulinemic-euglycemic clamp procedure to determine glucose tolerance, β-cell responsivity, insulin secretion, insulin clearance and insulin sensitivity. RESULTS Participants with prediabetes had significantly higher glucose concentrations in the fasting state and after glucose ingestion than did normoglycemic participants. Insulin sensitivity (M/I ratio) was ~15% lower, acute insulin response (AIR) to intravenous glucose and β-cell responsivity to oral glucose were ~35% lower, but total insulin secretion rate in the fasting state and after glucose ingestion was ~10% greater in prediabetic than in normoglycemic participants. The decrease in β-cell function with worsening glucose homeostasis in Asians with prediabetes was associated with progressively greater defects in AIR rather than M/I. However, analysis using static surrogate measures (HOMA indices) of insulin resistance and β-cell function revealed a different pattern. CONCLUSIONS Lower AIR to intravenous glucose and β-cell responsivity to oral glucose, on a background of mild insulin resistance, are the major contributors to the dysregulation of glucose homeostasis in Asians with prediabetes.
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Affiliation(s)
- Faidon Magkos
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Michelle H Lee
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Maybritte Lim
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Vanna Chhay
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Kee Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Sonia Baig
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ian Yi Han Ang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | | | - Chin Meng Khoo
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Medicine, National University Hospital, Singapore
| | - Jeffrey B Halter
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Division of Geriatric and Palliative Medicine, University of Michigan, USA
| | - Sue-Anne Toh
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; NOVI Health, Singapore; Department of Medicine, National University Hospital, Singapore; Regional Health System Office, National University Health System, Singapore; Singapore Population HEalth ImpRovement Centre (SPHERiC), National University Health System, Singapore.
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50
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Thomas M, Greaves RF, Tingay DG, Loh TP, Ignjatovic V, Newall F, Oeum M, Tran MTC, Rajapaksa AE. Current and emerging technologies for the timely screening and diagnosis of neonatal jaundice. Crit Rev Clin Lab Sci 2022; 59:332-352. [PMID: 35188857 DOI: 10.1080/10408363.2022.2038074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Neonatal jaundice is one of the most common clinical conditions affecting newborns. For most newborns, jaundice is harmless, however, a proportion of newborns develops severe neonatal jaundice requiring therapeutic interventions, accentuating the need to have reliable and accurate screening tools for timely recognition across different health settings. The gold standard method in diagnosing jaundice involves a blood test and requires specialized hospital-based laboratory instruments. Despite technological advancements in point-of-care laboratory medicine, there is limited accessibility of the specialized devices and sample stability in geographically remote areas. Lack of suitable testing options leads to delays in timely diagnosis and treatment of clinically significant jaundice in developed and developing countries alike. There has been an ever-increasing need for a low-cost, simple to use screening technology to improve timely diagnosis and management of neonatal jaundice. Consequently, several point-of-care (POC) devices have been developed to address this concern. This paper aims to review the literature, focusing on emerging technologies in the screening and diagnosing of neonatal jaundice. We report on the challenges associated with the existing screening tools, followed by an overview of emerging sensors currently in pre-clinical development and the emerging POC devices in clinical trials to advance the screening of neonatal jaundice. The benefits offered by emerging POC devices include their ease of use, low cost, and the accessibility of rapid response test results. However, further clinical trials are required to overcome the current limitations of the emerging POC's before their implementation in clinical settings. Hence, the need for a simple to use, low-cost POC jaundice detection technology for newborns remains an unsolved challenge globally.
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Affiliation(s)
- Mercy Thomas
- New Vaccines, Murdoch Children's Research Institute, Melbourne, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Newborn Research Centre, Royal Women's Hospital, Melbourne, Australia.,Department of Nursing, Royal Children's Hospital, Melbourne, Australia
| | - Ronda F Greaves
- Department of Paediatrics, University of Melbourne, Melbourne, Australia.,School of Health and Biomedical Sciences, RMIT University, Melbourne, Australia.,Victorian Clinical Genetics Services, Melbourne, Australia.,International Federation of Clinical Chemistry and Laboratory Medicine-Emerging Technologies Division (C-ETPLM), Milan, Italy
| | - David G Tingay
- Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Newborn Research Centre, Royal Women's Hospital, Melbourne, Australia.,Neonatal Research, Murdoch Children's Research Institute, Melbourne, Australia.,Department of Neonatology, Royal Children's Hospital, Melbourne, Australia
| | - Tze Ping Loh
- International Federation of Clinical Chemistry and Laboratory Medicine-Emerging Technologies Division (C-ETPLM), Milan, Italy.,Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Vera Ignjatovic
- Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Hematology, Murdoch Children's Research Institute, Melbourne, Australia
| | - Fiona Newall
- Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Department of Nursing, Royal Children's Hospital, Melbourne, Australia
| | - Michelle Oeum
- New Vaccines, Murdoch Children's Research Institute, Melbourne, Australia
| | - Mai Thi Chi Tran
- International Federation of Clinical Chemistry and Laboratory Medicine-Emerging Technologies Division (C-ETPLM), Milan, Italy.,National Children's Hospital, Hanoi, Vietnam.,Hanoi Medical University, Hanoi, Vietnam
| | - Anushi E Rajapaksa
- New Vaccines, Murdoch Children's Research Institute, Melbourne, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Newborn Research Centre, Royal Women's Hospital, Melbourne, Australia.,Think Project Global, Melbourne, Australia
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