Validation of the ADVIA Centaur® XP system for the determination of insulin and its application.

In this study, a direct chemiluminescent immunoassay for the determination of human serum insulin levels using the ADVIA Centaur® XP system was validated. Dilution recovery, linearity, precision, sensitivity, between analyzer variation, reference interval and stability were analyzed. The linear range of the insulin assay was from 0.64 to 277.27 mU/L. Intra- and inter-assay coefficients of variation were 3.67-7.96% and 4.66-8.69%, respectively. The lower and upper limits of quantification were 0.61 mU/L and 8872.64 mU/L, respectively. In terms of between analyzer variation, our study showed comparable results with a good correlation of r2 = 0.9934. The human serum insulin reference interval was in the range of 3.0-25.0 mU/L. Serum insulin can be kept for 7 days between 2-8 °C and 18-26 °C, and the corresponding results for -20 °C and -70 °C were 1 month and 6 months are reported. We proved that this insulin assay was robust and the analytical performance met the requirements. We successfully applied this insulin assay to a bioequivalence study of miglitol in 48 healthy Chinese subjects. The miglitol bioequivalence study was evaluated based on pharmacokinetic and pharmacodynamic parameter endpoints. The results demonstrated that the test formulation and the reference formulation were bioequivalent.

Precision, accuracy, cross reactivity and comparability of serum indices measurement on Abbott Architect c8000, Beckman Coulter AU5800 and Roche Cobas 6000 c501 clinical chemistry analyzers.

BACKGROUND: The aim of our study was to perform verification of serum indices on three clinical chemistry platforms. METHODS: This study was done on three analyzers: Abbott Architect c8000, Beckman Coulter AU5800 (BC) and Roche Cobas 6000 c501. The following analytical specifications were verified: precision (two patient samples), accuracy (sample with the highest concentration of interferent was serially diluted and measured values compared to theoretical values), comparability (120 patients samples) and cross reactivity (samples with increasing concentrations of interferent were divided in two aliquots and remaining interferents were added in each aliquot. Measurements were done before and after adding interferents). RESULTS: Best results for precision were obtained for the H index (0.72%-2.08%). Accuracy for the H index was acceptable for Cobas and BC, while on Architect, deviations in the high concentration range were observed (y=0.02 [0.01-0.07]+1.07 [1.06-1.08]x). All three analyzers showed acceptable results in evaluating accuracy of L index and unacceptable results for I index. The H index was comparable between BC and both, Architect (Cohen's κ [95% CI]=0.795 [0.692-0.898]) and Roche (Cohen's κ [95% CI]=0.825 [0.729-0.922]), while Roche and Architect were not comparable. The I index was not comparable between all analyzer combinations, while the L index was only comparable between Abbott and BC. Cross reactivity analysis mostly showed that serum indices measurement is affected when a combination of interferences is present. CONCLUSIONS: There is heterogeneity between analyzers in the hemolysis, icteria, lipemia (HIL) quality performance. Verification of serum indices in routine work is necessary to establish analytical specifications.

Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia.

BACKGROUND: Clinical guidelines specify that diagnosis of interstitial pulmonary fibrosis (IPF) requires identification of usual interstitial pneumonia (UIP) pattern. While UIP can be identified by high resolution CT of the chest, the results are often inconclusive, making surgical lung biopsy necessary to reach a definitive diagnosis (Raghu et al., Am J Respir Crit Care Med 183(6):788-824, 2011). The Envisia genomic classifier differentiates UIP from non-UIP pathology in transbronchial biopsies (TBB), potentially allowing patients to avoid an invasive procedure (Brown et al., Am J Respir Crit Care Med 195:A6792, 2017). To ensure patient safety and efficacy, a laboratory developed test (LDT) must meet strict regulatory requirements for accuracy, reproducibility and robustness. The analytical characteristics of the Envisia test are assessed and reported here. METHODS: The Envisia test utilizes total RNA extracted from TBB samples to perform Next Generation RNA Sequencing. The gene count data from 190 genes are then input to the Envisia genomic classifier, a machine learning algorithm, to output either a UIP or non-UIP classification result. We characterized the stability of RNA in TBBs during collection and shipment, and evaluated input RNA mass and proportions on the limit of detection of UIP. We evaluated potentially interfering substances such as blood and genomic DNA. Intra-run, inter-run, and inter-laboratory reproducibility of test results were also characterized. RESULTS: RNA content within TBBs preserved in RNAprotect is stable for up to 14 days with no detectable change in RNA quality. The Envisia test is tolerant to variation in RNA input (5 to 30 ng), with no impact on classifier results. The Envisia test can tolerate dilution of non-UIP and UIP classification signals at the RNA level by up to 60% and 20%, respectively. Analytical specificity studies utilizing UIP and non-UIP samples mixed with genomic DNA (up to 30% relative input) demonstrated no impact to classifier results. The Envisia test tolerates up to 22% of blood contamination, well beyond the level observed in TBBs. The test is reproducible from RNA extraction through to Envisia test result (standard deviation of 0.20 for Envisia classification scores on > 7-unit scale). CONCLUSIONS: The Envisia test demonstrates the robust analytical performance required of an LDT. Envisia can be used to inform the diagnoses of patients with suspected IPF.

Analytical Verification Performance of Afirma Genomic Sequencing Classifier in the Diagnosis of Cytologically Indeterminate Thyroid Nodules.

Background: Fine needle aspiration (FNA) cytology, a diagnostic test central to thyroid nodule management, may yield indeterminate results in up to 30% of cases. The Afirma® Genomic Sequencing Classifier (GSC) was developed and clinically validated to utilize genomic material obtained during the FNA to accurately identify benign nodules among those deemed cytologically indeterminate so that diagnostic surgery can be avoided. A key question for diagnostic tests is their robustness under different perturbations that may occur in the lab. Herein, we describe the analytical performance of the Afirma GSC. Results: We examined the analytical sensitivity of the Afirma GSC to varied input RNA amounts and the limit of detection of malignant signals with heterogenous samples mixed with adjacent normal or benign tissues. We also evaluated the analytical specificity from potential interfering substances such as blood and genomic DNA. Further, the inter-laboratory, intra-run, and inter-run reproducibility of the assay were examined. Analytical sensitivity analysis showed that Afirma GSC calls are tolerant to variation in RNA input amount (5-30 ng), and up to 75% dilution of malignant FNA material. Analytical specificity studies demonstrated Afirma GSC remains accurate in presence of up to 75% blood or 30% genomic DNA. The Afirma GSC results are highly reproducible across different operators, runs, reagent lots, and laboratories. Conclusion: The analytical robustness and reproducibility of the Afirma GSC test support its routine clinical use among thyroid nodules with indeterminant FNA cytology.

Analytical verification and method comparison of the ADVIA Centaur® Intact Parathyroid Hormone assay.

OBJECTIVES: This study is the first verification of the novel iPTH Siemens ADVIA Centaur® Intact Parathyroid Hormone (iPTHm) chemiluminescence immunoassay based on monoclonal antibodies. We also compared the iPTH results obtained using this assay with the previous ADVIA Centaur® Parathyroid Hormone assay (iPTHp) based on polyclonal antibodies. DESIGN AND METHODS: The analytical performance study of iPTHm assay included LoD, LoQ, intra- and inter-assay reproducibility, and linearity. A comparison study was performed on 369 routine plasma samples. The results were analyzed independently for patients with normal and abnormal GFR, as well as patients on hemodialysis. In addition, clinical concordance between assays was assessed. Finally, we studied PTH stability of plasma samples at 4°C. RESULTS: For the iPTHm assay LoD and LoQ were 0.03pmol/L and 0.10pmol/L, respectively. Intra- and inter-assay CV were between 2.3% and 6.2%. Linearity was correct in the range from 3.82 to 203.08pmol/L. Correlation studies showed a good correlation (r=0.99) between iPTHm and iPTHp, with bias of -2.55% (IC -3.48% to -1.62%) in the range from 0.32 to 117.07pmol/L. Clinical concordance, assessed by Kappa Index, was 0.874. The stability study showed that differences compared to basal iPTH concentration did not exceed 20% in any of the samples analyzed. CONCLUSIONS: The iPTHm assay demonstrated acceptable performance and a very good clinical concordance with iPTHp assay, currently used in our laboratory. Thus, the novel iPTHm assay can replace the previous iPTHp assay, since results provided by both assays are very similar. In our study, the stability of iPTH is not affected by storage up to 14days.

Analytical Performance of a Gene Expression Classifier for Medullary Thyroid Carcinoma.

BACKGROUND: The aim of this study was to demonstrate the analytical validity of an RNA classifier for medullary thyroid carcinoma (MTC). METHODS: Fresh-frozen tissue specimens were obtained from commercial sources, and MTC diagnoses were confirmed by histopathology review. De-identified patient fine-needle aspiration biopsies (FNABs) and whole blood from normal donors were obtained. Total RNA was extracted, amplified, and hybridized to custom microarrays for gene expression analysis. Gene expression data were normalized and classified via a machine learning algorithm. Positive control materials were produced from MTC tissues and tested across multiple experiments and laboratories. Twenty-seven MTC tissue specimens were used to evaluate the sensitivity of the MTC classifier. Gene expression data from tissues and FNABs were used to model classifier response to mixtures of MTC samples with normal thyroid tissue, a benign thyroid nodule, a Hürthle cell adenoma, and whole blood. Select mixture conditions were confirmed in vitro. Assay tolerance to RNA input variation (5-25 ng) and genomic DNA contamination (30% by mass) was evaluated. The intra- and inter-run reproducibility and inter-laboratory accuracy of MTC classifier results were characterized. RESULTS: The MTC classifier sensitivity of 96.3% [confidence interval 81.0-99.9%] was determined retrospectively using 27 MTC confirmed tissue specimens. One false-negative result in a necrotic tissue implicated sample necrosis in reduced classifier sensitivity. Dilution modeling of MTC samples with normal or benign tissues showed consistent detection of MTC down to 20% sample proportions, with in vitro confirmation of 20% analytical sensitivity. Classifier tolerance to RNA input variation (5-25 ng), genomic DNA contamination (30% by mass), and an interfering substance (blood) was demonstrated with 100% accurate classifier results under all tested conditions. The maximum observed run-to-run score difference for a single FNAB sample was ∼1 unit compared with the average score difference between 38 MTC and non-MTC FNABs of ∼32 units. MTC classifier results for 20 tissues processed from total RNA in two different laboratories showed 100% concordance. CONCLUSIONS: The MTC classifier, offered as part of the routine molecular testing of cytology-indeterminate thyroid nodules, demonstrates robust analytical sensitivity, specificity, accuracy, and reproducibility.