Ogni antibiotico è efficace in relazione a un determinato gruppo di microrganismi
comprare ampicillina online in italiain caso di infezioni oculari vengono scelte gocce ed unguenti.
Science.qxp
Received 11.18.05 Revisions Received 1.26.06 Accepted 2.2.06
Validating New Reagents:
Roadmaps Through the Wilderness
Roberta A. Martindale, BSc (MLS), MT(ASCP),1
George S. Cembrowski MD, PhD,1,2
Lucille J. Journault,1,2
Jennifer L. Crawford,
BSc (MLS),1,2
Chi Tran,1,2
Tammy L. Hofer, BSc (MLS), MBA,1,2
Bev J. Rintoul, BSc (MLS)1,2
Jean S. Der,1,2
Cathy W. Revers,
BSc (MLS),1,2
Cheryl A. Vesso,1,2
Carol E. Shalapay,1,2
Connie I. Prosser, PhD, FCACB,1,2
Donald F. LeGatt, PhD, FCACB1,2
( 1Department of Laboratory Medicine and Pathology, University of Alberta Hospitals, 2Capital Health Authority, Edmonton, Canada)
simply ignoring the QC shift. We offer a
variation. Depending on the test type, specific
One of the most frequent quality control issues
systematic approach to shifted quality control
information is gathered about the magnitude of
faced by laboratory professionals is how to
and/or patient data following a reagent lot
the shifts in either the QC and/or the patient
respond appropriately to a shift in quality
change. We divide laboratory tests into 3
data. The control mean is reset following an
control (QC) following a reagent lot change.
types, (1) tests for which the analysis of QC
isolated quality control shift. Evaluation of the
Possible actions include adjusting the control
specimens is sufficient, (2) tests which
shift in patient data is initiated by the
range, checking for shifts in patient data, or
demonstrate between reagent lot shifts
laboratory director when the shift exceeds a
infrequently, and (3) tests with between lot
multiple of the allowable error.
It is well known that reagent lot changes can cause significant
whenever a complete change of reagents occurs, "the laboratory
shifts in patient results. Mueller-Hinton agar lot changes can affect
. . demonstrate that changing reagent lot numbers does not
drug susceptibility results.1 In hematology, new lots of Simplate II
affect the range used to report patient test results, and control
have caused incorrect bleeding times,2 and new lots of hematology
values are not adversely affected by reagent lot number
reagent have affected automated complete blood counts.3 In the
changes."12 Soon after the enactment of CLIA ‘88, the require-
realm of clinical chemistry, reagent lot changes have affected im-
ment for lot validation was promulgated in the accreditation
munoassays more than general chemistry tests. Lot-to-lot variation
checklists of various professional organizations including that of
has been frequently implicated in shifts of patient and quality con-
the College of American Pathologists (CAP).
trol prostate specific antigen (PSA) values,4,5 probably because of
The rigor in fulfilling lot validation depends on the knowl-
the extensive application of PSA testing for screening and moni-
edge, confidence, and prior practices of the laboratory directors
toring of prostate cancer. Variation in reagent lots has resulted in
and the supervisory technologists. In preparing for our first CAP
significant variation in the testing of patients' hepatitis C
accreditation inspection last winter, our senior biochemistry staff
antibody,6 patients' human chorionic gonadotropin (hCG),7 and
and medical biochemistry supervisors spent well over 30 hours
theophylline quality control.8 Even point-of-care cholesterol
synthesizing 3 different, test-dependent lot validations. Being
tests9,10 are affected by reagent lot variation.
heavily influenced by our quality system, we present these vali-
In some analytical systems, reagent lot changes seem to
dations as flow charts. For one group of tests, we determined
primarily affect quality control measurements. The influence of
that the analysis of quality control materials was sufficient for
between lot variation on control product analysis is often as-
the workup of new reagent lots. For the other tests, the investi-
cribed to "matrix effects"; differences in constituent concentra-
gation depended on the history of QC and patient shifts with
tion and constituents in the control product and the plasma or
new reagent lots. With a stable method, quality control analysis
serum specimen that the control product is imitating. This
was usually adequate; with a method that frequently
phenomenon has been frequently observed in dry reagent sys-
demonstrated patient shifts with new reagent lots, we required
tems like that of the Vitros (Ortho-Clinical Diagnostics,
the analysis of retained patient specimens as well as quality con-
Rochester NY). Hill and colleagues have shown that slide gen-
trol specimens. This general approach is summarized in
Table 1.
eration changes in the Vitros can cause significant excursion in
Multiple quality control specimens must be run in order to
quality control measurements but little change in re-analyzed
detect the presence of a shift. To quantify a quality control shift,
patient specimens.11
we suggest that 4 measurements be made at each control level.
Prior to the 1992 enactment of CLIA ‘88,12 reagent lot val-
The shift is calculated by subtracting the usual control mean
idation practices were highly variable. General guidelines8 for
from the average of the controls. We suggest that the magnitude
measuring and responding to lot-related shifts in control and
of the QC shift be assessed by comparing the control shift to the
patient data were not widely applied and very few laboratories
method's stable standard deviation. If the magnitude of the QC
validated new reagent lots by re-analyzing retained patient speci-
shift exceeds 1 SD, we require recalculation and resetting of the
mens. Section 493.1255 of the CLIA ‘88 Standard specifies that
June 2006 䊏 Volume 37 Number 6 䊏
LABMEDICINE
To quantify the shift in patient data, we suggest that 10
different previously analyzed patient specimens be selected and
re-analyzed with the new reagents. If possible, the specimens
should be chosen to represent the usually measured concentra-
tion range. The shift is calculated by subtracting the average of
the initial results from the average of the new results. The
reanalysis of 10 specimens will result in greater than 60% of sig-
nificant shifts being discovered and corrected. (Personal commu-
nication, November 17, 2005, A. Srinivasan, LifeScan, Milpitas,
CA). The magnitude of the patient shift is assessed by compar-
ing the shift to a multiple of the allowable error (AE) of the
method. This allowable error may be the CLIA proficiency test
(PT) limit. As CLIA proficiency test limits are not available for
all analytes and are sometimes regarded as too broad, alternate
allowable errors based on physiologic variation are available.13
Table 2 shows the allowable errors that we use in our medical
biochemistry laboratory. We suggest that if the patient shift ex-
ceeds 0.5 x AE, then the method is judged as unacceptable and a
new reagent lot be obtained. Some laboratory professionals may
elect to use more stringent criteria for maximum allowable pa-
tient shift (eg, a maximum bias of 0.33 x AE). Some clinical lab-
oratories may require even tighter limits (eg, clinical trial
laboratories). These laboratories might attempt to use allowable
error limits derived from state of the art analytical performance.
Test-Specific Algorithms for Reagent
Validation
I. Tests where only QC is evaluated (Unstable analyte/
Figure 1_Tests where only QC is evaluated: Unstable analyte/Unstable
Unstable reagents/Insufficient material for retesting/Extremely
reagents/Insufficient material for retesting/Extremely tedious or
tedious or time-consuming)
There are at least 4 types of tests where we assess only the
shifts in quality control data, even when between lot variation inreagents may cause shifts in patient data. Some tests measurevery unstable analytes such as ACTH, insulin, vitamin A, and
the discovery of QC shifts exceeding 1 standard deviation (SD).
vitamin E. For these analytes, it would be misleading to reana-
The 4 replicate quality control measurements are averaged with
lyze previously analyzed specimens with alternate set of reagents.
their average compared to the usual QC average. If the reagents
Some tests use highly unstable reagents (eg, bile acids and free
are deemed unacceptable, reagents are remade if prepared in-
fatty acids). These reagents are so unstable that they need to be
house. Otherwise, manufacturer controls may be analyzed before
reconstituted daily. In order to validate such reagents with pa-
the manufacturer is notified.
tient specimens, we would need to measure the retained speci-mens daily. For other tests, there may be little or no specimen
II. QC-Based Reagent Lot Validation for Methods with
remaining (eg, tissue iron, tissue copper, etc). Finally, some tests
Usually Clinically Unimportant Lot-to-Lot Variation
are so laborious or time-consuming that we rarely would repeat
Some chemistry methods rarely demonstrate between lot
retained specimens with new reagent lots (eg, fecal fats).
variation for either control or patient results. We propose the
Figure 1 shows the algorithm for validating new reagent
following criterion for defining a method to be independent of
lots with only quality control analysis. This validation can occur
lot variation: a method is stable if the QC bias is less than 1 SD
during patient testing. Briefly, quality control specimens are run
for 3 successive reagent lot changes. The history of lot stability
in duplicate until there are 4 control observations at each level.
must be documented. Examples of stable methods include elec-
Trouble-shooting and/or recalibration follow out of range QC or
trolytes, calcium, phosphorous, total protein, albumin, urea, and
Table 1_General Approach to the Investigation of New Reagent Lots
Retained Patient Specimen Analysis
Laborious/Infrequently performed/Unstable analyte
4 control replicates, each level
Stable, generally no QC or patient shift with new reagent lots
4 control replicates, each level
10 retained patient specimens if control shift discovered
Sometimes demonstrates clinically important lot to lot variation in
4 control replicates, each level
10 retained patient specimens
patient specimens with new reagent lot
LABMEDICINE 䊏 Volume 37 Number 6 䊏 June 2006
Table 2_Allowable Error (AE) Criteria
Alternate allowable
Alternate allowable
error limit based on
error limit based on
physiologic variation
physiologic variation
Alpha-1 Antitrypsin
Human chorionic gonadotropin
Alanine aminotransferase
Alkaline phosphatase
Angiotensin converting enzyme
Lactate dehydrogenase
Apolipoprotein A1
Luteinizing hormone
Beta 2 microglobulin
Beta hydroxybutyrate
Bilirubin, direct
Carcinoembryonic antigen
Procainamide /N-acetyl
Cholesterol, total
Parathyroid hormone
Rheumatoid factor
Creatine kinase, MB
Sex hormone binding globulin
Creatinine, urine
C-reactive protein
Thyroid binding globulin
Thyroxine, free (FT4)
Triiodothyronine (T3)
Free testosterone
Thyroid stimulating hormone
Follicle stimulating hormone
June 2006 䊏 Volume 37 Number 6 䊏 LABMEDICINE
creatinine measured by the Beckman LX-20 and TSH measured
with alternate reagent lots. Some of our core chemistry labo-
by the Bayer ADVIA Centaur.
ratory assays demonstrate this variation: troponin, hCG,
For these reagent lot-independent methods, we recommend
and folate on the Bayer ADVIA Centaur and the enzyme
that only the quality control results be evaluated with the new
and turbidimetric tests on the Beckman LX-20. Each sec-
reagent before a new reagent lot is placed into service. For these
tion in medical biochemistry maintains a list of tests that
tests, it is acceptable to analyze quality control material just after
usually demonstrate large variation with alternate lots of
reagent lot change and then in the usual schedule. If a persistent
reagents. For these methods, before being placed into serv-
QC shift is detected in the 48 hours following reagent lot
ice, new reagent lots must evaluated for significant shifts in
change we then recommend that the magnitude of the patient
patient and quality control results.
bias also be evaluated.
Figure 3 shows the algorithm used to validate such un-
Figure 2 shows the algorithm used to validate such stable
stable tests. After the reagent lot change, quality control
tests. Because of the infrequent occurrence of significant lot de-
specimens are run in duplicate to more rapidly obtain 4
pendent variation, we suggest that this validation occur during
replicate observations at each level. If the QC has not
patient testing. Briefly, quality control specimens are run in the
shifted, 10 retained patient specimens are analyzed with the
usual manner after reagent lot change. Trouble-shooting and/or
new reagent lot and the size of the patient bias assessed. If
recalibration follows the violation of any quality control rule. In
the QC has shifted, trouble-shooting and/or recalibration
the case of unsuccessful trouble-shooting, 10 retained patient
are attempted. If these procedures do not restore the origi-
specimens or previously analyzed retained PT materials (in the
nal QC means (indicating a QC shift), the retained patient
absence of retained patient samples) are reanalyzed. If the patient
specimens are analyzed with the new reagent lot. If the pa-
or PT bias is too large, the clinical biochemist or pathologist is
tient bias is too large, the clinical biochemist or pathologist
consulted. Otherwise, the QC mean is reset if the QC has shifted
is consulted. Otherwise, the QC mean is reset if the QC
by more than 1 SD.
has shifted by more than 1 SD.
III. Patient-Based Reagent Lot Validation for Methods
With Significant Lot to Lot Variation
Some chemistry methods can demonstrate large
variations in quality control and/or patient specimen testing
Figure 2_QC-based reagent lot validation for methods with usually
Figure 3_Patient-based reagent lot validation for methods with signif-
clinically unimportant lot to lot variation.
icant lot to lot variation.
LABMEDICINE 䊏 Volume 37 Number 6 䊏 June 2006
Calculations and Record-Keeping
We designed a Microsoft Access program for entering, ana-
lyzing, and retrieving the required quality control and patient
replicate values. Figure 4 shows an output screen from this pro-
gram that summarizes the reagent information as well as the req-
uisite QC replicate data. Figure 5 shows an example of an input
screen for the entry of CK patient data (current and new lot).
The "drop-down" menu of analyte names is linked with the al-
lowable errors shown in Table 2 and permits easy evaluation of
the magnitude of the patient shift.
We have been using this new lot qualification system for
the last 16 months. For the LX-20 systems, we evaluated 103new reagent lots. Two lots of acetaminophen were judged unac-ceptable; the manufacturer has just narrowed its acceptance cri-teria for acetaminophen variation. With respect to the otherLX-20 analytes, all were acceptable; the following tests requiredquality control adjustments: alkaline phosphatase (2 lots), ala-nine transaminase (1), amylase (2), C-reactive protein (1), CSFprotein (4), gamma glutamyl transferase (1), lipase (1), microal-
Figure 4_Output screen showing evaluation of the control data.
bumin (2), salicylates (1), theophylline (2), and triglycerides (1).
Until recently, only troponin and vancomycin were tested withthe lot qualification system; troponin required quality controladjustments with 2 lots. We are adding more Centaurimmunoassay tests to our reagent qualification system.
Despite these efforts, we were unable to detect successive
increases in gamma glutamyl transferase patient results. Anothercity laboratory discovered our higher results with a patient com-parison study. We are now scrutinizing our gamma glutamyltransferase lot validations.
The system has provided us with defensible and logical cri-
teria for remaking new reagents and even returning "defective"
reagent lots. We have found that our QC adjustments are made
with increased confidence. As our chemistry laboratory is large
and run by 4 laboratory scientists, the flowcharts presented here
have standardized the evaluation of new reagents. The Access
data base program has greatly simplified our record keeping of
validation of new reagent lots. LM
Acknowledgement: We wish to acknowledge the initial
Figure 5_Input screen showing results of reagent lot comparisons using
patient specimens.
guidance that was provided by Ms. Elsa Quam of the Universityof Wisconsin Hospital Clinical Laboratories, Madison, WI.
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June 2006 䊏 Volume 37 Number 6 䊏 LABMEDICINE
Source: http://eqas.ir/pdf/validating%20new%20reagent.pdf
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