• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

你的实验室数据可重复吗?从重复测量的不精密度到临床决策的关键作用。

Are Your Laboratory Data Reproducible? The Critical Role of Imprecision from Replicate Measurements to Clinical Decision-making.

作者信息

Coskun Abdurrahman

机构信息

Department of Medical Biochemistry, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.

出版信息

Ann Lab Med. 2025 May 1;45(3):259-271. doi: 10.3343/alm.2024.0569. Epub 2025 Mar 21.

DOI:10.3343/alm.2024.0569
PMID:40114656
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11996692/
Abstract

Measurement results of biological samples are not perfect and vary because of numerous factors related to the biological samples themselves and the measurement procedures used to analyze them. The imprecision in patients' laboratory data arising from the measurement procedure, known as analytical variation, depends on the conditions under which the data are collected. Additionally, the sample type and sampling time significantly affect patients' laboratory results, particularly in serial measurements using samples collected at different time points. For accurate interpretation of patients' laboratory data, imprecision-both its analytical and biological components-should be properly evaluated and incorporated into data management. With advancements in measurement technologies, analytical imprecision can be minimized to an insignificant level compared to biological imprecision, which is inherent to all biomolecules because of the dynamic nature of metabolism. This review addresses: (i) the theoretical background of variation, (ii) the statistical and metrological evaluation of measurement variation, (iii) the assessment of variation under different conditions in medical laboratories, (iv) the impact of measurement variation on clinical decisions, (v) the influence of biases on measurement variation, and (vi) the variability of analytes in human metabolism. Collectively, both analytical and biological imprecision are inseparable aspects of all measurements in biological samples, with biological imprecision serving as the foundation of personalized laboratory medicine.

摘要

生物样本的测量结果并不完美,且会因与生物样本本身以及用于分析它们的测量程序相关的众多因素而有所不同。测量程序导致的患者实验室数据不精确性,即所谓的分析变异,取决于数据收集的条件。此外,样本类型和采样时间会显著影响患者的实验室结果,尤其是在使用不同时间点采集的样本进行连续测量时。为了准确解读患者的实验室数据,应正确评估不精确性(包括其分析和生物成分)并将其纳入数据管理。随着测量技术的进步,与生物不精确性相比,分析不精确性可被降至微不足道的水平,生物不精确性因新陈代谢的动态性质而存在于所有生物分子中。本综述探讨了:(i)变异的理论背景,(ii)测量变异的统计和计量评估,(iii)医学实验室不同条件下变异的评估,(iv)测量变异对临床决策的影响,(v)偏差对测量变异的影响,以及(vi)人体新陈代谢中分析物的变异性。总体而言,分析不精确性和生物不精确性都是生物样本所有测量中不可分割的方面,生物不精确性是个性化检验医学的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/95eb2e16be06/alm-45-3-259-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/2b4335e4e555/alm-45-3-259-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/159aa2760734/alm-45-3-259-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/9f94f0d9dade/alm-45-3-259-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/95eb2e16be06/alm-45-3-259-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/2b4335e4e555/alm-45-3-259-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/159aa2760734/alm-45-3-259-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/9f94f0d9dade/alm-45-3-259-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b979/11996692/95eb2e16be06/alm-45-3-259-f4.jpg

相似文献

1
Are Your Laboratory Data Reproducible? The Critical Role of Imprecision from Replicate Measurements to Clinical Decision-making.你的实验室数据可重复吗?从重复测量的不精密度到临床决策的关键作用。
Ann Lab Med. 2025 May 1;45(3):259-271. doi: 10.3343/alm.2024.0569. Epub 2025 Mar 21.
2
A new concept to derive permissible limits for analytical imprecision and bias considering diagnostic requirements and technical state-of-the-art.考虑诊断要求和技术现状,得出分析不精密度和偏倚允许限的新概念。
Clin Chem Lab Med. 2011 Apr;49(4):623-35. doi: 10.1515/CCLM.2011.116. Epub 2011 Feb 24.
3
Influence of analytical bias and imprecision on the number of false positive results using Guideline-Driven Medical Decision Limits.应用指南驱动的医学决策限界时,分析偏倚和不精密度对假阳性结果数量的影响。
Clin Chim Acta. 2014 Mar 20;430:1-8. doi: 10.1016/j.cca.2013.12.014. Epub 2013 Dec 18.
4
Reprint of "Influence of analytical bias and imprecision on the number of false positive results using Guideline-Driven Medical Decision Limits".《分析偏倚和不精密度对使用指南驱动的医学决策界限得出的假阳性结果数量的影响》重印版
Clin Chim Acta. 2014 May 15;432:127-34. doi: 10.1016/j.cca.2014.04.002. Epub 2014 Apr 18.
5
Using analytical performance specifications in a medical laboratory.在医学实验室中使用分析性能规范。
Clin Chem Lab Med. 2024 Apr 16;62(8):1512-1519. doi: 10.1515/cclm-2024-0102. Print 2024 Jul 26.
6
Not all biases are created equal: how to deal with bias on laboratory measurements.并非所有偏差都是一样的:如何处理实验室测量中的偏差。
Clin Chem Lab Med. 2024 Nov 26;63(5):916-922. doi: 10.1515/cclm-2024-1208. Print 2025 Apr 28.
7
Issues in assessing analytical performance specifications in healthcare systems assembling multiple laboratories and measuring systems.评估医疗保健系统中组装多个实验室和测量系统的分析性能规格时的问题。
Clin Chem Lab Med. 2024 Feb 9;62(8):1520-1530. doi: 10.1515/cclm-2023-1208. Print 2024 Jul 26.
8
Repeatability imprecision from analysis of duplicates of patient samples and control materials.对患者样本和对照材料的重复检测的重复性不精密度分析。
Scand J Clin Lab Invest. 2020 May;80(3):210-214. doi: 10.1080/00365513.2019.1710243. Epub 2020 Jan 3.
9
Requirements for reproducibility, trueness and error of measurement in internal quality control schemes.内部质量控制方案中测量的可重复性、真实性和误差要求。
Clin Chem Lab Med. 2003 May;41(5):693-9. doi: 10.1515/CCLM.2003.105.
10
A method to estimate the uncertainty of measurements in a conglomerate of instruments/laboratories.一种估算仪器/实验室集合中测量不确定度的方法。
Scand J Clin Lab Invest. 2005;65(7):551-8. doi: 10.1080/00365510500206567.

本文引用的文献

1
Diagnosis Based on Population Data versus Personalized Data: The Evolving Paradigm in Laboratory Medicine.基于群体数据与个性化数据的诊断:检验医学中不断演变的范式
Diagnostics (Basel). 2024 Sep 25;14(19):2135. doi: 10.3390/diagnostics14192135.
2
From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance - a Comprehensive Review.从数据到决策:利用人工智能和机器学习对抗抗菌药物耐药性——全面综述
J Med Syst. 2024 Aug 1;48(1):71. doi: 10.1007/s10916-024-02089-5.
3
Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy.
推进个性化医学:将统计算法与组学和纳米组学相结合,提高诊断准确性和治疗效果。
Biochim Biophys Acta Mol Basis Dis. 2024 Oct;1870(7):167339. doi: 10.1016/j.bbadis.2024.167339. Epub 2024 Jul 8.
4
Applying the Milan models to setting analytical performance specifications - considering all the information.运用米兰模型制定分析性能规范——考虑所有信息。
Clin Chem Lab Med. 2024 May 28;62(8):1531-1537. doi: 10.1515/cclm-2024-0104. Print 2024 Jul 26.
5
A New Concept for Reference Change Values-Regression to the Population Mean.参考值变化的新概念——向总体均值回归。
Clin Chem. 2024 Aug 1;70(8):1076-1084. doi: 10.1093/clinchem/hvae067.
6
The impact of physiological variations on personalized reference intervals and decision limits: an in-depth analysis.生理变异对个性化参考区间和决策限的影响:深入分析
Clin Chem Lab Med. 2024 Mar 11;62(11):2140-2147. doi: 10.1515/cclm-2024-0009. Print 2024 Oct 28.
7
How clinical laboratories select and use Analytical Performance Specifications (APS) in Italy.意大利临床实验室如何选择和使用分析性能规格(APS)。
Clin Chem Lab Med. 2024 Feb 28;62(8):1470-1473. doi: 10.1515/cclm-2023-1314. Print 2024 Jul 26.
8
When bias becomes part of imprecision: how to use analytical performance specifications to determine acceptability of lot-lot variation and other sources of possibly unacceptable bias.当偏倚成为不精确的一部分时:如何使用分析性能规范来确定批间变异和其他可能不可接受偏倚源的可接受性。
Clin Chem Lab Med. 2024 Feb 8;62(8):1505-1511. doi: 10.1515/cclm-2023-1303. Print 2024 Jul 26.
9
Impact of analytical imprecision and bias on patient classification.分析不精密度和偏倚对患者分类的影响。
Am J Clin Pathol. 2024 Jan 4;161(1):4-8. doi: 10.1093/ajcp/aqad115.
10
Personalized laboratory medicine in the digital health era: recent developments and future challenges.个体化实验室医学在数字健康时代:最新进展与未来挑战。
Clin Chem Lab Med. 2023 Sep 28;62(3):402-409. doi: 10.1515/cclm-2023-0808. Print 2024 Feb 26.