Kiyoshi Ichihara1, Yesim Ozarda2, Julian H Barth3, George Klee4, Ling Qiu5, Rajiv Erasmus6, Anwar Borai7, Svetlana Evgina8, Tester Ashavaid9, Dilshad Khan10, Laura Schreier11, Reynan Rolle12, Yoshihisa Shimizu13, Shogo Kimura14, Reo Kawano15, David Armbruster16, Kazuo Mori17, Binod K Yadav18. 1. Faculty of Health Sciences, Yamaguchi University Graduate School of Medicine, Ube, Japan. Electronic address: ichihara@yamaguchi-u.ac.jp. 2. Dept of Medical Biochemistry, Uludag University School of Medicine, Bursa, Turkey. 3. Blood Sciences, Leeds General Infirmary, Leeds, UK. 4. Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA. 5. Dept of Clinical Laboratory, Peking Union Medical College, Beijing, China. 6. Chemical Pathology, University of Stellenbosch and National Health Laboratory Services, Tygerberg, South Africa. 7. King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Pathology, King Abdulaziz Medical City, Jeddah, Saudi Arabia. 8. Beckman Coulter LLC, Moscow, Russia. 9. Dept of Laboratory Medicine, P. D. Hinduja National Hospital and Medical Research Centre, Mumbai, India. 10. Dept of Pathology, National University of Medical Sciences, Rawalpindi, Pakistan. 11. Dept of Clinical Biochemistry, Faculty of Pharmacy and Biochemistry, University of Buenos Aires, Argentina. 12. Newborn Screening Center Visayas, West Visayas State University Medical Center, Iloilo, Philippines. 13. Dept of Medical Life Science, Faculty of Medical Bioscience, Kyushu University of Health and Welfare, Nobeoka, Japan. 14. Faculty of Health Sciences, Yamaguchi University Graduate School of Medicine, Ube, Japan. 15. Faculty of Health Sciences, Yamaguchi University Graduate School of Medicine, Ube, Japan; Clinical Research Center, Yamaguchi University Hospital, Ube, Japan. 16. Abbott Laboratories, Abbott Park, IL, USA. 17. Beckman Coulter Japan, Tokyo, Japan. 18. Dept of Biochemistry, Maharajgunj Medical Campus, Institute of Medicine, Kathmandu, Nepal.
Abstract
OBJECTIVES: The IFCC Committee on Reference Intervals and Decision Limits coordinated a global multicenter study on reference values (RVs) to explore rational and harmonizable procedures for derivation of reference intervals (RIs) and investigate the feasibility of sharing RIs through evaluation of sources of variation of RVs on a global scale. METHODS: For the common protocol, rather lenient criteria for reference individuals were adopted to facilitate harmonized recruitment with planned use of the latent abnormal values exclusion (LAVE) method. As of July 2015, 12 countries had completed their study with total recruitment of 13,386 healthy adults. 25 analytes were measured chemically and 25 immunologically. A serum panel with assigned values was measured by all laboratories. RIs were derived by parametric and nonparametric methods. RESULTS: The effect of LAVE methods is prominent in analytes which reflect nutritional status, inflammation and muscular exertion, indicating that inappropriate results are frequent in any country. The validity of the parametric method was confirmed by the presence of analyte-specific distribution patterns and successful Gaussian transformation using the modified Box-Cox formula in all countries. After successful alignment of RVs based on the panel test results, nearly half the analytes showed variable degrees of between-country differences. This finding, however, requires confirmation after adjusting for BMI and other sources of variation. The results are reported in the second part of this paper. CONCLUSION: The collaborative study enabled us to evaluate rational methods for deriving RIs and comparing the RVs based on real-world datasets obtained in a harmonized manner.
OBJECTIVES: The IFCC Committee on Reference Intervals and Decision Limits coordinated a global multicenter study on reference values (RVs) to explore rational and harmonizable procedures for derivation of reference intervals (RIs) and investigate the feasibility of sharing RIs through evaluation of sources of variation of RVs on a global scale. METHODS: For the common protocol, rather lenient criteria for reference individuals were adopted to facilitate harmonized recruitment with planned use of the latent abnormal values exclusion (LAVE) method. As of July 2015, 12 countries had completed their study with total recruitment of 13,386 healthy adults. 25 analytes were measured chemically and 25 immunologically. A serum panel with assigned values was measured by all laboratories. RIs were derived by parametric and nonparametric methods. RESULTS: The effect of LAVE methods is prominent in analytes which reflect nutritional status, inflammation and muscular exertion, indicating that inappropriate results are frequent in any country. The validity of the parametric method was confirmed by the presence of analyte-specific distribution patterns and successful Gaussian transformation using the modified Box-Cox formula in all countries. After successful alignment of RVs based on the panel test results, nearly half the analytes showed variable degrees of between-country differences. This finding, however, requires confirmation after adjusting for BMI and other sources of variation. The results are reported in the second part of this paper. CONCLUSION: The collaborative study enabled us to evaluate rational methods for deriving RIs and comparing the RVs based on real-world datasets obtained in a harmonized manner.
Authors: Heba Baz; Kiyoshi Ichihara; May Selim; Ahmed Awad; Sarah Aglan; Dalia Ramadan; Amina Hassab; Lamia Mansour; Ola Elgaddar Journal: PLoS One Date: 2021-03-19 Impact factor: 3.240
Authors: Gabriel Abbam; Samuel Tandoh; Mary Tetteh; David Amoah Afrifah; Max Efui Annani-Akollor; Eddie-Williams Owiredu; Charles Gyasi; Constance Adu-Gyamfi; Benedict Sackey; Alexander Yaw Debrah; Otchere Addai-Mensah Journal: PLoS One Date: 2021-01-20 Impact factor: 3.240
Authors: Abigail S A Bawua; Kiyoshi Ichihara; Rosemary Keatley; John Arko-Mensah; Yvonne Dei-Adomakoh; Patrick F Ayeh-Kumi; Rajiv Erasmus; Julius Fobil Journal: Int J Lab Hematol Date: 2020-09-03 Impact factor: 2.877