David L. Witte

Lack of specificity of cyclosporine immunoassays. Results of a College of American Pathologists Study.

OBJECTIVE To evaluate the cross-reactivity of the 6 most abundant cyclosporine A (CsA) metabolites in commonly used assays for CsA. DESIGN Whole blood samples containing either only 62 ng/mL CsA (A) or 62 ng/mL CsA and between 49 and 86 ng/mL of 1 of the 6 most abundant CsA metabolites (B) were lyophilized. One sample of A and 1 of B were mailed to each of the laboratories participating in the College of American Pathologists Proficiency Testing Program quarterly during a 3-year period (1999-2001). Method means and coefficients of variation were calculated for each mailing. RESULTS The study showed significant cross-reactivity of metabolites in all the immunoassay systems studied. Overall degree of interference decreased from Abbott TDx polyclonal > Abbott TDx monoclonal > DiaSorin > Syva EMIT. High-performance liquid chromatography methods gave results close to those found using mass spectrometric techniques. CONCLUSIONS Significant metabolite interference was found to occur with the immunoassay systems studied.

Biospecimens and Biorepositories for the Community Pathologist

Pathologists have long served as custodians of human biospecimens collected for diagnostic purposes. Rapid advancements in diagnostic technologies require that pathologists change their practices to optimize patient care. The proper handling of biospecimens creates opportunities for pathologists to improve their diagnoses while assessing prognosis and treatment. In addition, the growing need for high-quality biorepositories represents an opportunity for community pathologists to strengthen their role within the health care team, ensuring that clinical care is not compromised while facilitating research. This article provides a resource to community pathologists learning how to create high-quality biorepositories and participating in emerging opportunities in the biorepository field. While a variety of topics are covered to provide breadth of information, the intent is to facilitate a level of understanding that permits community pathologists to make more informed choices in identifying how best their skills and practice may be augmented to address developments in this field.

A longitudinal replicate study of immunosuppressive drugs: A College of American Pathologists Study

OBJECTIVE To identify the sources of analytical variation for cyclosporine and tacrolimus in a 3-year longitudinal study. DESIGN Two pools of whole blood were spiked with cyclosporine and tacrolimus, respectively. One aliquot of cyclosporine and 2 of the tacrolimus pool were distributed in the first and last mailing for years 1999 to 2001. For both drugs, the total variance for each method was partitioned into within- and between-laboratory components. SETTING The A and C mailings of the 1999, 2000, and 2001 AACC/CAP [American Association for Clinical Chemistry/College of American Pathologists] Immunosuppressive Drugs (CS) Monitoring Survey. MAIN OUTCOME MEASURES For each drug, total variance was partitioned into specimen, mailing, year, and interlaboratory effects for each analytical method. PARTICIPANTS The 292 laboratories for cyclosporine and 177 laboratories for tacrolimus enrolled in the survey from 1999 to 2001. RESULTS For both cyclosporine and tacrolimus, the major source of imprecision came from within-laboratory factors, which accounted for nearly 85% (range, 77% to 90%) of the total variance. For cyclosporine, the major component of within-laboratory variance was between-mailing, within-year effect, whereas for tacrolimus it was the between-year, within-laboratory variation. CONCLUSION The major source of long-term survey imprecision for cyclosporine and tacrolimus is within-laboratory factors. The finding that 85% of the total variance was due to within-laboratory variation is similar to other therapeutic drugs.

Sources of variability : A College of American Pathologists Therapeutic Drug Monitoring Survey Study

○ Objective.-To determine the magnitudes and sources of analytic variation in testing for therapeutic drugs. Specifically, among laboratories using the same analytic method, to compare the within-laboratory variation (including both short- and long-term variation) with the between-laboratory variation. Design.-Four identical challenges were prepared from a lyophilized pool of spiked sera and were sent in pairs 4 months apart to laboratories participating in a nationwide proficiency-testing program. For each of 25 drugs, the variability in reported results from laboratories using the same method was investigated using nested analysis of variance. Setting.-The first 2 mailings of the College of American Pathologists Therapeutic Drug Monitoring Survey, 1996, sets Z and ZM. Main Outcome Measures.-For each drug, total variance was partitioned into within- and between-laboratory components for common methods. The within-laboratory component was further partitioned into short- and long-term components. Participants.-The approximately 5000 laboratories enrolled in the survey. Results.-For the 25 drugs, the average percentages of the total variance due to short-term, within-laboratory variance; long-term, within-laboratory variance; between-laboratory variance; and total laboratory variance were 25.0% (range, 8.8-50.6%), 57.8% (35.3-73.7%), 17.3% (5.0-35.4%), and 82.7% (64.6-95.0%), respectively. Conclusion.-For all drugs tested, the within-laboratory component of variance was greater than the between-laboratory component of variance. Within laboratories, the magnitude of the long-term component was generally greater than the magnitude of the short-term component. This information will be helpful in determining the clinical utility of various drug assays and in evaluating the appropriateness of regulations involving therapeutic drug testing.

Frequency of unacceptable results in point-of-care testing.

K and associates1 show how the rich source of information available in the laboratory can be used to improve care processes. The ‘‘naturally concurrent’’ results from laboratory and point-of-care hematocrit measurements helped improve quality, and this concurrence exemplifies the real-time science of laboratory medicine. This article stimulates the search for similar improvement opportunities and suggests a practical research agenda. Kilgore et al did not differentiate common cause and special cause sources of variation.2 Common cause variation, usually modeled with the gaussian distribution, suggests that results beyond 3 SDs occur at a frequency of about 0.27%, or 2700 parts per million (ppm). Further, 4 SDs yield 63 ppm, 5 SDs yield 0.6 ppm, and 6 SDs yield 0.002 ppm, outlier rates in a gaussian distribution with no bias in the midpoint. Special cause variation is distinct from common cause and is believed to be attributable to unexpected sources of variation and is not modeled by the gaussian distribution.2 The figure presented by Kilgore et al suggests frequent special cause outliers in January and infrequent special cause variation plus perhaps smaller common cause variation in April. The authors defined a clinically significant difference as 5 hemat-