Show simple item record

FieldValueLanguage
dc.contributor.authorLoh, Tze Ping
dc.contributor.authorSmith, Alison F.
dc.contributor.authorBell, Katy J.L.
dc.contributor.authorLord, Sarah J
dc.contributor.authorCeriotti, Ferruccio
dc.contributor.authorJones, Graham
dc.contributor.authorBossuyt, Patrick
dc.contributor.authorSandberg, Sverre
dc.contributor.authorHorvath, Andrea R
dc.date.accessioned2021-11-11T01:15:45Z
dc.date.available2021-11-11T01:15:45Z
dc.date.issued2021en_AU
dc.identifier.urihttps://hdl.handle.net/2123/26852
dc.description.abstractAnalytical performance specifications (APS) for measurands describe the minimum analytical quality requirements for their measurement. These APS are used to monitor and contain the systematic (trueness/bias) and random errors (precision/imprecision) of a laboratory measurement to ensure the results are “fit for purpose” in informing clinical decisions about managing a patient’s health condition. In this review, we highlighted the wide variation in the setting of APS, using different levels of evidence, as recommended by the Milan Consensus, and approaches. The setting of a priori defined outcome-based APS for HbA1c remains challenging. Promising indirect alternatives seek to link the clinical utility of HbA1c and APS by defining statistical confidence for interpreting the laboratory values, or through simulation of clinical performance at varying levels of analytical performance. APS defined based on biological variation estimates in healthy individuals using the current formulae are unachievable by nearly all routine laboratory methods for HbA1c testing. On the other hand, the APS employed in external quality assurance programs have been progressively tightened, and greatly facilitate the improved quality of HbA1c testing. Laboratories should select the APS that fits their intended clinical use and should document the data and rationale underpinning those selections. Where possible common APS should be adopted across a region or country to facilitate the movement of patients and patient data across health care facilities.en_AU
dc.language.isoenen_AU
dc.publisherElsevieren_AU
dc.relation.ispartofClinica Chimica Actaen_AU
dc.rightsCopyright All Rights Reserveden_AU
dc.subjectAnalytical performance specificationen_AU
dc.subjectBiasen_AU
dc.subjectImprecisionen_AU
dc.subjectExternal quality assuranceen_AU
dc.subjectProficiency testingen_AU
dc.subjectQuality goalen_AU
dc.subjectQuality controlen_AU
dc.titleSetting analytical performance specifications using HbA1c as a model measuranden_AU
dc.typeArticleen_AU
dc.subject.asrc1103 Clinical Sciencesen_AU
dc.subject.asrc1117 Public Health and Health Servicesen_AU
dc.identifier.doi10.1016/j.cca.2021.10.016
usyd.facultySeS faculties schools::Faculty of Medicine and Health::Sydney School of Public Healthen_AU
usyd.citation.volume523en_AU
usyd.citation.spage407en_AU
usyd.citation.epage414en_AU
workflow.metadata.onlyYesen_AU


Show simple item record

Associated file/s

There are no files associated with this item.

Associated collections

Show simple item record

There are no previous versions of the item available.