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Outcome-based analytical performance specifications: current status and future challenges

delete2024-06-06
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OA
AI
A
Andrea R. Horvath *
K
Katy Bell
F
Ferruccio Ceriotti
G
Graham Jones
T
Tze Ping Loh
L
Lord, Sally
S
Sverre Sandberg
DOI:10.1515/cclm-2024-0125delete
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摘要

摘要

En 中文
Analytical performance specifications (APS) based on outcomes refer to how 'good' the analytical performance of a test needs to be to do more good than harm to the patient. Analytical performance of a measurand affects its clinical performance. Without first setting clinical performance requirements, it is difficult to define how good analytically the test needs to be to meet medical needs. As testing is indirectly linked to health outcomes through clinical decisions on patient management, often simulation-based studies are used to assess the impact of analytical performance on the probability of clinical outcomes which is then translated to Model 1b APS according to the Milan consensus. This paper discusses the related key definitions, concepts and considerations that should assist in finding the most appropriate methods for deriving Model 1b APS. We review the advantages and limitations of published methods and discuss the criteria for transferability of Model 1b APS to different settings. We consider that the definition of the clinically acceptable misclassification rate is central to Model 1b APS. We provide some examples and guidance on a more systematic approach for first defining the clinical performance requirements for tests and we also highlight a few ideas to tackle the future challenges associated with providing outcome-based APS for laboratory testing.
Keyword:
analytical performance
clinical performance
laboratory test
outcomes

期刊

C
Clinical Chemistry and Laboratory Medicine
IF:
3.7
论文数:
7.7K
被引数:
1.1W

机构

S
St Vincent's Hospital Sydney
学者数:
3.3K
论文数: 2.7K
被引数: 2.2K
U
University of Sydney
学者数:
6.5W
论文数: 6.2W
被引数: 90
The University of Notre Dame Australia 封面图
The University of Notre Dame Australia
学者数:
1.5K
论文数: 1.4K
被引数: 1.5K
N
NSW Health
学者数:
1.9W
论文数: 1.5W
被引数: 12
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