# CLSI EP15 A2 PDF

The EPA2 protocol from CLSI. • Uses control material with assigned concentration (e g from external quality control) or certified reference materials. We are pleased to have a guest essay explaining the latest in Method Verification , specifically the newest version of the CLSI guideline EP15 on Method. CLSI document EPA2 describes the protocols that should be undertaken by the user to verify precision claims by a manufacturer. Precision claims by a.

Author: | Fenrinris Goltigal |

Country: | Bulgaria |

Language: | English (Spanish) |

Genre: | Medical |

Published (Last): | 1 May 2013 |

Pages: | 220 |

PDF File Size: | 13.68 Mb |

ePub File Size: | 17.53 Mb |

ISBN: | 824-8-22535-950-9 |

Downloads: | 31693 |

Price: | Free* [*Free Regsitration Required] |

Uploader: | Yozshujas |

The contents of articles or advertisements in The Clinical Biochemist — Reviews are not to be construed as official statements, evaluations or endorsements by the AACB, its official bodies or its agents. Internationally recognized high order reference materials, such as a material from the U. For the purposes of this example the results of only a single level are shown Table 1.

If the mean concentration from the user’s experiment is beyond the verification interval, statistically significant bias exists. If QC material is being used for the precision assessment, it should be different to that used to control the assay. The assessment is performed on at least two levels, as precision can differ over the analytical range of an assay.

### CLSI EPA3: verification of precision and estimation of bias – Westgard

For this, longer-term assessment is required. Second, most manufacturers provide only regression statistics as the results of comparison experiments, and do not provide bias claims, so the user has to calculate the bias to be expected from the regression statistics provided and has little idea of the uncertainty of this a22 bias.

When evaluating the precision of an assay, the trivial approach for estimating repeatability 2a any given level is to perform 20 replicate analyses in a single run on a single day. However, for a method developed in-house a higher level of proof is required to validate the method, in which case EPA2 would be the appropriate guideline e1p5 use. Repeatability Repeatability is estimated using the equation below.

The EPA3 committee felt that the patient comparison experiment had little value as it was, and that users who needed to perform a patient comparison experiment should consult CLSI EP9-A3 “Measurement procedure comparison and bias estimation using patient samples.

It is generally assumed in the laboratory that the variation associated with repeated analysis will follow a normal distribution, also known as the Laplace-Gaussian or Gaussian distribution. For example, if the true standard deviations cli actually ep155 equal to their claimed counterparts, the calculated standard deviations would exceed their published counterparts fifty percent of the time in verification experiments. EPA2 should be used to validate a method against user requirements, and is generally used by reagent and instrument suppliers to demonstrate the precision of their methods.

## Evaluating Assay Precision

Note, some authors refer to total variation as just the between-run component instead of combined between-run and within-run shown above. When undertaking the assessment the data must be assessed for outliers, which are considered to be present if the absolute difference between replicates exceeds 5.

Care must be taken in knowing which term is being referred to. Tools, Technologies and Training for Healthcare Laboratories.

## Guest Essay

Unfortunately epp15 approach is insufficient, as it tends to under-estimate repeatability, as the operating conditions in effect at the time may not reflect usual operating parameters.

If this is true then using the principle of analysis of variance components:. Support Center Support Center. Two or more appropriate materials should be tested in the precision experiment. If the estimated bias is less than allowable bias, the bias is acceptable. Use of these materials is important in establishing the traceability of measurement procedures.

### CLSI/NCCLS: EPA2. User verification of performance for precision and trueness – ScienceOpen

This could be useful, for example, if the intent of the experiment was to estimate the bias of one laboratory in a system relative to another, or eo15 the mean of the laboratories in a system. EP15 first describes a precision verification experiment. As the period of assessment is quite short, the total SD or within-laboratory SD derived from these experiments should not generally be used to define acceptability limits for internal quality control.

Precision claims by a manufacturer should be tested at at-least two levels, by running three replicates over five days. To allow for this possibility, the user calculates a “verification limit” based on the published standard deviation and the size of the user’s experiment. National Center for Biotechnology InformationU. However, if the values achieved are greater than those reported cli the manufacturer, a statistical test needs to be performed to determine whether this difference is statistically significant.

A spreadsheet for assisting with the calculations described in this article is available from the AACB web-site.

If the user is interested in estimating bias relative to the peer group for proficiency testing, and wants to estimate how the measurement procedure will perform well on proficiency testing, cldi testing materials with peer group values for the measurement procedure being evaluated are appropriate.

Journal List Clin Biochem Rev v.

Thus we need to find the Clinical and Laboratory Standards Institute. In order to compare the estimated repeatability to a claimed value we can calculate the critical or verification value using the equation:.

The repeatability previously termed “within-run” and the within-laboratory previously termed “total” standard deviations are calculated by an analysis of variance technique ANOVA that properly accounts for the within-run and between-run contributions to the overall imprecision of the measurement procedure.