Development of nation-wide reference intervals using an indirect method and harmonized assays.

OBJECTIVES: For many years, clinical laboratories have either verified or estimated reference intervals (RI) for laboratory tests. Those calculations have largely been performed by direct sampling analysis of ostensibly healthy individuals or by post-analysis biochemical screening. Recently however, indirect calculations have come to the forefront as an IFCC endorsed method by using normal and abnormal patient data. DESIGN AND METHODS: Using a large database of patient test results from Laboratory Corporation of America, age and gender based RIs, inclusive of neonatal, pediatric, and geriatric populations, were determined using a modified indirect method of Hoffmann, and represent a diverse population distributed across the United States from a nation-wide system of laboratories and is unbiased with respect to age, gender, race or geography. RESULTS: The tabulation of RIs using big data by an indirect method represent 72 M patient test results. The table includes 266 individual analytes consisting of approximately 2,700 age categories, including tests across multiple medical disciplines. CONCLUSIONS: To our knowledge, this is the largest collection of RIs that were calculated by an indirect method representing clinical chemistry, endocrinology, coagulation, and hematology analytes that have been derived with very powerful "Ns" for each age bracket. This process provides more robust RIs and allows for the determination of pediatric and geriatric RIs that would otherwise be difficult to obtain using traditional direct RI determinations.

A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia.

Importance: Low-density lipoprotein cholesterol (LDL-C), a key cardiovascular disease marker, is often estimated by the Friedewald or Martin equation, but calculating LDL-C is less accurate in patients with a low LDL-C level or hypertriglyceridemia (triglyceride [TG] levels ≥400 mg/dL). Objective: To design a more accurate LDL-C equation for patients with a low LDL-C level and/or hypertriglyceridemia. Design, Setting, and Participants: Data on LDL-C levels and other lipid measures from 8656 patients seen at the National Institutes of Health Clinical Center between January 1, 1976, and June 2, 1999, were analyzed by the ß-quantification reference method (18 715 LDL-C test results) and were randomly divided into equally sized training and validation data sets. Using TG and non-high-density lipoprotein cholesterol as independent variables, multiple least squares regression was used to develop an equation for very low-density lipoprotein cholesterol, which was then used in a second equation for LDL-C. Equations were tested against the internal validation data set and multiple external data sets of either ß-quantification LDL-C results (n = 28 891) or direct LDL-C test results (n = 252 888). Statistical analysis was performed from August 7, 2018, to July 18, 2019. Main Outcomes and Measures: Concordance between calculated and measured LDL-C levels by ß-quantification, as assessed by various measures of test accuracy (correlation coefficient [R2], root mean square error [RMSE], mean absolute difference [MAD]), and percentage of patients misclassified at LDL-C treatment thresholds of 70, 100, and 190 mg/dL. Results: Compared with ß-quantification, the new equation was more accurate than other LDL-C equations (slope, 0.964; RMSE = 15.2 mg/dL; R2 = 0.9648; vs Friedewald equation: slope, 1.056; RMSE = 32 mg/dL; R2 = 0.8808; vs Martin equation: slope, 0.945; RMSE = 25.7 mg/dL; R2 = 0.9022), particularly for patients with hypertriglyceridemia (MAD = 24.9 mg/dL; vs Friedewald equation: MAD = 56.4 mg/dL; vs Martin equation: MAD = 44.8 mg/dL). The new equation calculates the LDL-C level in patients with TG levels up to 800 mg/dL as accurately as the Friedewald equation does for TG levels less than 400 mg/dL and was associated with 35% fewer misclassifications when patients with hypertriglyceridemia (TG levels, 400-800 mg/dL) were categorized into different LDL-C treatment groups. Conclusions and Relevance: The new equation can be readily implemented by clinical laboratories with no additional costs compared with the standard lipid panel. It will allow for more accurate calculation of LDL-C level in patients with low LDL-C levels and/or hypertriglyceridemia (TG levels, ≤800 mg/dL) and thus should improve the use of LDL-C level in cardiovascular disease risk management.

Automated Processing and Evaluation of Anti-Nuclear Antibody Indirect Immunofluorescence Testing.

Indirect immunofluorescence (IIF) is considered by the American College of Rheumatology (ACR) and the international consensus on ANA patterns (ICAP) the gold standard for the screening of anti-nuclear antibodies (ANA). As conventional IIF is labor intensive, time-consuming, subjective, and poorly standardized, there have been ongoing efforts to improve the standardization of reagents and to develop automated platforms for assay incubation, microscopy, and evaluation. In this study, the workflow and performance characteristics of a fully automated ANA IIF system (Sprinter XL, EUROPattern Suite, IFA 40: HEp-20-10 cells) were compared to a manual approach using visual microscopy with a filter device for single-well titration and to technologist reading. The Sprinter/EUROPattern system enabled the processing of large daily workload cohorts in less than 8 h and the reduction of labor hands-on time by more than 4 h. Regarding the discrimination of positive from negative samples, the overall agreement of the EUROPattern software with technologist reading was higher (95.6%) than when compared to the current method (89.4%). Moreover, the software was consistent with technologist reading in 80.6-97.5% of patterns and 71.0-93.8% of titers. In conclusion, the Sprinter/EUROPattern system provides substantial labor savings and good concordance with technologist ANA IIF microscopy, thus increasing standardization, laboratory efficiency, and removing subjectivity.

Changing the paradigm of laboratory quality control through implementation of real-time test results monitoring: For patients by patients.

OBJECTIVES: To develop and implement a quality control protocol using real-time patient data with immediate failure analysis and prevention of releasing results that exceed the allowable total error. DESIGN AND METHODS: Patient data are analyzed in real time using algorithms that incorporate moving medians and moving means for selected chemistry analytes. Simulation software was developed to determine optimal algorithms, establish error limits, and number of patient results for calculation of a single cumulative datum point. Algorithms for moving median (MovMed) and mean (MovMen) were chosen and validated for each analyte. Error limits (TEa) were established using biological and analytical variation with a goal of greater than 90% error detection rate during simulation runs. Middleware software was developed to prohibit the release of patient results upon error detection. RESULTS: A block size of 50 was determined to be the optimal number of patient results used in cumulative calculations. The application of MovMed and MovMen algorithms achieved 0% false rejection for 24 out of 28 tests (85.7%) during the simulation phase. Four tests had a false rejection rate ranging from 0.2 to 1.0%. Error detection rates of 100% were achieved for 16 out of 28 tests (57.1%). Twelve tests had error detection rates ranging from 94.5 to 99.8%. Traditional QC material utilization was reduced by approximately 75-85% and repeat analysis was reduced by approximately 50%. CONCLUSIONS: We successfully developed and implemented a real-time quality control protocol using patient results with true error detection and without release of erroneous results.

Reference intervals data mining: no longer a probability paper method.

OBJECTIVES: To describe the application of a data-mining statistical algorithm for calculation of clinical laboratory tests reference intervals. METHODS: Reference intervals for eight different analytes and different age and sex groups (a total of 11 separate reference intervals) for tests that are unlikely to be ordered during routine screening of disease-free populations were calculated using the modified algorithm for data mining of test results stored in the laboratory database and compared with published peer-reviewed studies that used direct sampling. The selection of analytes was based on the predefined criteria that include comparability of analytical methods with a statistically significant number of observations. RESULTS: Of the 11 calculated reference intervals, having upper and lower limits for each, 21 of 22 reference interval limits were not statistically different from the reference studies. CONCLUSIONS: The presented statistical algorithm is shown to be an accurate and practical tool for reference interval calculations.

Patient results and laboratory test accuracy.

PURPOSE: Traditional quality control materials used for monitoring the clinical laboratory test accuracy might be non-commutable with patient samples and may not detect systematic errors. The aim of this paper is to describe a method to monitor inter-instrument bias using result distributions that are independent of the control's commutability. DESIGN/METHODOLOGY/APPROACH: Serum calcium data collected within a laboratory network were assessed. A reference interval was calculated using a computerized, indirect Hoffmann's algorithm using all data across a laboratory network without excluding any results. Results outside the reference interval were considered as the zero-bias distribution. Three allowable bias levels were then calculated to determine the corresponding shift in abnormal results for each bias level in both directions from the zero-bias distribution. The observed result distributions in three laboratories within the network were compared for bias performance after one year of the reference interval study. FINDINGS: Performance levels for bias were: minimum allowable < 1.27 percent; desirable < 0.85 percent; and optimal < 0.42 percent. Zero bias result distribution above and below the reference interval for calcium was 3.92 percent and 2.53 percent respectively. All three laboratories performed within the desirable allowable bias level. ORIGINALITY/VALUE: Bias-monitoring process using patient result distributions allows managers to: assess systematic error between laboratory instruments; improve laboratory quality control; and strengthen patient risk management.

The ethics of refusing a request for off-label deep brain stimulation currently in clinical trial.

Physicians must ensure that patients understand that the principal aim of research is to increase generalizable knowledge. However, patients may hope for individual benefit as a secondary goal of participation. Highly motivated patients may request treatment off label if trial enrollment has ended, leading to ethical dilemmas for clinicians. This case uses early deep brain stimulation (DBS) as an example for exploring the ethically relevant questions related to the off-label use of medical devices.

Evaluation of HbA1c on the Roche COBAS Integra 800 closed tube system.

OBJECTIVES: Evaluate a new whole blood (WB) HbA1c immunoassay and system with closed tube sampling (CTS) capability. DESIGN AND METHODS: Compare the Tina-quant Haemoglobin A1c Gen.2 (A1C-2) application on the COBAS INTEGRA 800 (I800) and new I800 dedicated system with CTS capability to current Integra applications and a HbA1c method accurate with common haemoglobin (Hb) variants. RESULTS: CVs were < or =1.7%. Mean bias against National Glycohaemoglobin Standardization Program (NGSP) samples was 0.3 HbA1c %. Compared to the Hitachi Tina-quant(R) [a] HbA1c II (HbA1c II) assay (accurate with common Hb variants), mean bias was 0.04% and 0.21% HbA1c at 6% and 9%, respectively, with Hb AS variants; and -0.01% and 0.26% HbA1c at 6% and 9%, respectively, with Hb AC variants. CONCLUSIONS: The Integra A1C-2 application is precise, accurate against NGSP-assigned samples and the Hb variants tested; and, the I800 dedicated system with CTS capability offers increased throughput and reduced sample handling.

Lipoprotein-associated phospholipase A2: review and recommendation of a clinical cut point for adults.

Recently, several epidemiologic studies have demonstrated an association between plasma lipoprotein-associated phospholipase A2 (Lp-PLA2) concentration and risk of subsequent cardiovascular events. Several major commercial and reference laboratories across the United States are now offering Lp-PLA2 testing for clinical use to evaluate cardiovascular risk and as a guide to intensity of therapy in individuals at intermediate risk for developing coronary heart disease. Each laboratory has established its own cut points, or "decision values," for Lp-PLA2, which vary from the 50th to the 95th percentile values of individual populations tested at each site. Uniform reporting of cut points has not been achieved. The purpose of this manuscript is to recommend appropriate decision values for Lp-PLA2, endorsed by a consensus panel of laboratorians and clinicians from the major laboratories where the test is performed. These coauthors possess considerable experience with assessment of cardiovascular risk marker decision values in general and are familiar with the validation of the Lp-PLA2 immunoassay and the Lp-PLA2 clinical studies conducted thus far. An ideal risk marker, studied in an ideal population, might yield a consistent cut point associated with a sudden increase in cardiovascular risk. While acknowledging that additional studies will be required to test and refine the recommended decision value, this article reviews the most current information with which to provide guidance to practicing clinicians regarding Lp-PLA2 levels. Since several studies have demonstrated increased risk associated with the second and third tertiles vs. the first tertile for Lp-PLA2, the 50th percentile cut point (235 ng/mL) is recommended as a conservative cut point associated with increased risk for cardiovascular disease. This cut point is not proposed as a treatment target, but rather as a level above which clinicians should consider a patient to be at higher risk for cardiovascular events, independent of established risk factors, high- and low-density lipoprotein cholesterol, and high-sensitivity C-reactive protein.