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Ghazizadeh H, Kathryn Bohn M, Esmaily H, Boskabadi M, Mohammadi-Bajgiran M, Farahani E, Boshtam M, Mohammadifard N, Sarrafzadegan N, Adeli K, Ghayour-Mobarhan M. Comparison of reference intervals for biochemical and hematology markers derived by direct and indirect procedures based on the Isfahan cohort study. Clin Biochem 2023; 116:79-86. [PMID: 37030657 DOI: 10.1016/j.clinbiochem.2023.04.001] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 04/03/2023] [Accepted: 04/04/2023] [Indexed: 04/10/2023]
Abstract
INTRODUCTION Indirect methods for reference interval (RI) establishment apply statistical techniques to generate RIs for test result interpretation using stored laboratory data. They present unique advantages relative to traditional direct approaches such as fewer resource requirements; however, there is debate regarding their performance. Herein, we aimed to compare indirect and direct approaches for RI establishment by harnessing data from the Isfahan Cohort Study (ICS). This cohort includes both healthy individuals and those with a history of disease, enabling a direct comparison. METHODS Participants were recruited as part of ICS, including 6504 adults aged 34 years and older. Sociodemographic characteristics, anthropometry, blood pressure, various biochemical indices, and hematology parameters were collected. The refineR method was used to establish indirect RIs (before applying exclusion criteria). Direct RIs were calculated using nonparametric methods per CLSI EP28-A3 guidelines (after applying exclusion criteria). Bias ratios were calculated for each parameter to assess significant differences in estimations. RESULTS Direct and indirect RI estimations for most hematological and biochemical parameters were comparable. Statistically significant bias ratios between methods were observed for the upper limits of total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), hemoglobin (female), and platelet count as well as the lower limits of mean corpuscular hemoglobin (female), mean corpuscular volume, hemoglobin, and hematocrit (female). CONCLUSION Data presented indicate RIs derived from direct and indirect approaches are similar, but not identical. Further work should focus on the clinical significance of such differences as well as the investigation of necessary data-cleaning criteria before indirect method application.
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Affiliation(s)
- Hamideh Ghazizadeh
- CALIPER Program, Division of Clinical Biochemistry, Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada; International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mary Kathryn Bohn
- CALIPER Program, Division of Clinical Biochemistry, Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada; Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Habibollah Esmaily
- Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mostafa Boskabadi
- Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Maryam Mohammadi-Bajgiran
- International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Elina Farahani
- CALIPER Program, Division of Clinical Biochemistry, Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada; Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Maryam Boshtam
- Heart Failure Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Noushin Mohammadifard
- Interventional Cardiology Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Nizal Sarrafzadegan
- Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Khosrow Adeli
- CALIPER Program, Division of Clinical Biochemistry, Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada; Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON, Canada.
| | - Majid Ghayour-Mobarhan
- International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran.
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Boskabadi M, Doostparast M. Regression trees with splitting based on changes of dependencies among covariates. INTELL DATA ANAL 2021. [DOI: 10.3233/ida-205140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Regression trees are powerful tools in data mining for analyzing data sets. Observations are usually divided into homogeneous groups, and then statistical models for responses are derived in the terminal nodes. This paper proposes a new approach for regression trees that considers the dependency structures among covariates for splitting the observations. The mathematical properties of the proposed method are discussed in detail. To assess the accuracy of the proposed model, various criteria are defined. The performance of the new approach is assessed by conducting a Monte-Carlo simulation study. Two real data sets on classification and regression problems are analyzed by using the obtained results.
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