Citations

Abstract Background β-Quantification (BQ) is the reference method for low-density lipoprotein cholesterol (LDL-C) determination. It is not widely available, making it challenging for laboratories to assess the accuracy of LDL-C methods. Our goal was to develop an indirect graphical approach for comparing LDL-C test results to the BQ reference method. Methods BQ results from Mayo Medical Laboratories (n = 39 969) and the National Institutes of Health (n = 17 825) were used to investigate the interrelationships between lipid panel tests. A plot of LDL-C/non high-density lipoprotein cholesterol (nonHDL-C) vs (triglyceride (TG)/nonHDL-C)0.5 (lipid ratio plot) resulted in a negative linear regression line (y = −34.2x + 115). Based on simulation analysis, the minimum sample size for calculating its slope and intercept with a coefficient of variation of about 7.5% was 80. Results The regression lines for the lipid ratio plot of LDL-C calculated by the Sampson–NIH (y = −37.6x + 118) and enhanced Sampson–NIH (y = −33.1x + 116) equations closely overlapped with the BQ method. In contrast, the Martin–Hopkins equation showed a positive bias with an increasing TG/nonHDL-C ratio and exceeded the recommended bias limit of 4% on hypertriglyceridemic samples (y = −25.5x + 107). The Friedewald equation showed an even larger negative bias with hypertriglyceridemia (y = −47.5x + 126). Lipid ratio plots of the Roche direct assay revealed a fixed positive bias of approximately 4% (y = −33.9x + 120), whereas a much larger proportional positive bias was observed with increasing triglycerides for the Beckman direct assay (y = −14.6x + 97.8). Conclusions The lipid ratio plot is a simple graphical approach that can be readily performed by clinical laboratories for investigating the accuracy of LDL-C assays by calculation methods or direct assays.

Abstract Background Cardiovascular guidelines have long recommended low-density lipoprotein-cholesterol (LDL-C) as the primary target for lipid-lowering therapy. Recent guidelines have emphasized the importance of achieving low LDL-C levels; hence, the accurate measurement of low LDL-C is increasingly clinically relevant. Methods Using lipid panel test results from the Mayo Clinic (n = 24 590) and the FOURIER clinical trial of evolocumab (n = 9605), the following modified Sampson equation was developed by least-squares regression to match LDL-C (mg/dL) by the β-quantification reference method, by combining terms into non High Density Lipoprotein Cholesterol (nonHDLC = Total Cholesterol – High Density Lipoprotein Cholesterol) and forcing the coefficient to be one: Results The modified Sampson equation demonstrated significant improvement in its concordance to the reference method compared to other equations (the Lin Concordance Correlation Coefficient 0.992, P < 0.001). By overall kappa analysis, it showed the best agreement to the reference method at the 55 mg/dL cutpoint (1.4 mmol/L, 0.98 [P < 0.001], Sampson–NIH: 0.96, Martin–Hopkins: 0.96, Friedewald: 0.94) and the 70 mg/dL cutpoint (1.8 mmol/L, 0.97 [P < 0.001], Sampson–NIH: 0.94, Martin–Hopkins: 0.95, Friedewald: 0.92). The false classification rate of the modified Sampson equation was also significantly lower compared to the other equations at 55 mg/dL (15%, [P < 0.001], Sampson–NIH: 29%, Martin–Hopkins: 28%, Friedewald: 37%) and 70 mg/dL (18%, [P < 0.001]; Sampson–NIH: 30%, Martin–Hopkins: 28.%, Friedewald: 34%). The new equation increases the percentage of correctly classified patients with low LDL-C by approximately 10% to 20% over the other equations based on its net reclassification index. Conclusions The modified Sampson equation shows improved accuracy compared to other equations for low LDL-C. It more accurately identifies high-risk patients, who are not at their LDL-C goals and could benefit from more intensive lipid-lowering therapy.

Abstract New technologies enabling access to high-sensitivity cardiac troponin (hs-cTn) assays at the point of care (POC) are available for routine use. POC technology can accelerate cardiac troponin testing within the hospital setting and support testing in other healthcare environments. Pre-analytical and analytical issues unique to POC testing are discussed. The opportunities and the evidence needed to support the routine use of hs-cTn POC assays in clinical care are outlined. Based on recent developments, the potential impact of hs-cTn at the POC in multiple clinical settings is described, and a roadmap of the steps required for successful implementation is provided.

Abstract Background Cardiac troponin (cTn) levels exceeding the 99th percentile upper reference limit and a rise/fall pattern are key for diagnosing myocardial injury and infarction. Macrotroponins, formed by patient anti-cTn antibodies targeting cTn, can cause persistently elevated cTn levels without ongoing myocardial injury. The frequency and impact of macrotroponin interference on cTn 99th percentiles are unclear. This study compares sex-specific 99th percentiles for 2 cTn assays, before and after excluding macrotroponin-positive samples, focusing on the top 10% of cTn levels. Methods We examined 1058 plasma samples from healthy individuals previously used for Danish cTn 99th percentiles. Following International Federation of Clinical Chemistry and Laboratory Medicine educational recommendations, macrotroponin presence was assessed in the top 10% cTn samples using immunoglobulin G (IgG) depletion screening and a reference sucrose gradient, confirming macrotroponin when both methods concurred. Due to analytical dilution constraints, [the highest] 88 of 135 Siemens Atellica high-sensitivity cTnI (hs-cTnI) samples were analyzed with both methods. All 106 Roche hs-cTnT samples were negative using IgG depletion, and sucrose analysis was limited to the highest 70 samples. Results Macrotroponin was found in 76% (67/88) of Siemens samples but in none of the Roche samples (0/70). Excluding macrotroponin-affected samples lowered the Siemens 99th percentiles from 117 ng/L to 22 ng/L in men and from 37 ng/L to 9 ng/L in women. The 99th/50th percentile ratio for Siemens decreased from 12- to 29-fold to 3- to 7-fold, approaching the Roche ratios. Conclusions Macrotroponin significantly influenced the Siemens Atellica hs-cTnI 99th percentiles, suggesting important clinical implications that warrant further prospective studies. The 99th/50th percentile ratio may help evaluate macrotroponin interference in troponin assays.

BACKGROUND: Thresholds to define prognosis with hs-cTnI (high-sensitivity cardiac troponin I) have not been systematically addressed in wild-type transthyretin amyloid cardiomyopathy, in part because of the multiplicity of hs-cTnI assays. The aims of this study were: first, to assess the prognostic performance of hs-cTnI measured with different assays in patients with wild-type transthyretin amyloid cardiomyopathy and, second, to identify assay-specific hs-cTnI thresholds for prognosis that could be integrated into staging systems for risk stratification. METHODS: Observational multicenter study of stable wild-type transthyretin amyloid cardiomyopathy patients from different cohorts using the Abbott Architect Stat hs-cTnI assay and the Beckman Coulter Access hs-cTnI assay (testing cohorts) and the Siemens Centaur XPT hs-cTnI assay (validation cohort). Outcome was all-cause mortality. RESULTS: In the Abbott cohort (n=136; median follow-up 22 [13–41] months; 31 [23%] deaths) and Beckman cohort (n=98; median follow-up 19 [12–28] months; 16 [16%] deaths), natural log-transformed hs-cTnI was an independent predictor of mortality (age- and sex-adjusted hazard ratio, 1.62 [95% CI, 1.11–2.35]; P =0.012 and 2.47 [95% CI, 1.48–4.14]; P <0.001, respectively). The best hs-cTnI threshold for 18-month mortality of the combined Abbott/Beckman cohorts (n=234) was 81 ng/L, rounded to 80 ng/L for simplicity of clinical use. A 2-variable staging system (based on the Mayo Clinic system) using hs-cTnI (>80 ng/L) and NPs (natriuretic peptides; NT-proBNP [N-terminal pro-B-type natriuretic peptide] >3000 ng/L or BNP [B-type natriuretic peptide] >250 ng/L) identified 3 groups with progressively worse prognosis. The staging system (using hs-cTnI >80 ng/L and NT-proBNP>3000 ng/L) was then applied to an independent cohort evaluated with the hs-cTnI Siemens assay (n=345, median follow-up 32 [24-42] months, 119 [34%] deaths). The significant differences between the groups were maintained. CONCLUSIONS: In patients with wild-type transthyretin amyloid cardiomyopathy, hs-cTnI is a strong and independent predictor of mortality. A threshold of hs-cTnI of 80 ng/L for these 3 assays provides effective risk stratification alone and in a staging system with NP.

Abstract Background Cardiac troponin is the gold-standard biomarker for the evaluation of patients with suspected acute myocardial infarction (MI). Improvements in assay technology have led to high-sensitivity cardiac troponin assays that, when incorporated into accelerated diagnostic pathways, may rapidly diagnose or exclude acute MI more efficiently than conventional troponin assays. Content In this narrative review, we provide practical suggestions for implementing high-sensitivity cardiac troponin assays, review accelerated diagnostic pathways incorporating these assays, and review the impact of these assays on resource utilization and cost-effectiveness in relation to the evaluation of individuals with possible acute MI. Summary An increasing number of hospitals are transitioning to high-sensitivity cardiac troponin assays. This narrative review provides an overview of the potential benefits of this transition.

Background: Anaplastic large cell lymphomas (ALCLs) represent a heterogeneous group of T-cell lymphomas that currently are classified by the presence or absence of ALK tyrosine kinase (TK) fusion genes (ALK+ or ALK−) and clinical presentation (systemic, cutaneous, or breast implant-associated). Two overarching molecular types of ALCL recently were discovered, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. Fusions involving non-ALK TK genes occur in some ALK− cases, but the fusion landscape of ALCL remains incompletely characterized. Methods: Expert consensus pathology review was conducted in the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). RNAseq was performed and fusions were identified using FusionCatcher. Here, we focused on recurrent in-frame coding fusions. Previously unreported fusions were validated by RT-PCR. Type I/II was assigned using a previously validated gene expression-based model. Genes with adjusted (adj) P&lt;0.05 were considered differentially expressed. Overall survival (OS) was assessed for systemic ALCL, when available. Results: We evaluated 379 ALCLs (229M/150F; mean age, 56 y). Of 199 candidate fusions (excluding reciprocal events), 28 were recurrent and passed quality metrics. At least 1 of these 28 fusions was present in 150 cases (40%). ALK fusions were present in 106 ALK+ ALCLs (all Type I; P&lt;0.0001). Of these, NPM1::ALK was seen in 68/106 (64%). Alternate partners (X::ALK) included ATIC (N=24) and CTLC, COL1A2, MSN, MYH9, RNF213, SATB1, TFH, TPM3, and TRAF1 (1-3 cases each). X::ALK was associated with older age (mean, 52 y) than NPM1::ALK (32 y; P&lt;0.0001) and showed relative overexpression of 49 genes, including multiple activators of small GTPases such as CGNL1 (FC, 5.6; Padj=2.4×10-6), SRGAP1, ALS2, DOCK1, and NCKAP1. ALK expression was similar in cases with NPM1::ALK and X::ALK and there was no significant difference in OS. Non-ALK TK fusions were seen in 17/273 ALK− cases (6%), including TYK2 (N=9); JAK2 (N=6); and ROS1 (N=2). All were Type I ALCLs (P&lt;0.0001). ALK− cases with non-ALK TK fusions overexpressed 38 genes compared to ALK− cases without TK fusions, including cytokines involved in the IL17 signaling pathway such as CXCL6 (FC, 12.5; Padj=4.2×10-3), CXCL1, and CSF3. We then assessed the relationship between ALK− cases with non-ALK TK fusions and ALK+ cases by separately comparing each subset to ALK− cases without TK fusions. FC values for ALK− cases with non-ALK TK fusions were significantly correlated with FC values for ALK+ ALCLs over the set of expressed genes (R=0.54; P&lt;0.0001). At a median follow-up of 32 months, 0/4 systemic ALCL patients with non-ALK TK fusions had died, while 30% of those with ALK− ALCL without TK fusions had died, but this was not statistically significant (P=0.26). The other 13 ALK− cases with non-ALK TK fusions were either localized ALCLs or did not have outcome data available. Of 20 TP63 fusions, 17 (85%) were TBL1XR1::TP63 and 3 were X::TP63. As previously reported, TP63 fusions were associated with poor OS (median OS, 10 months; not reached for other ALK− ALCLs; P=0.007). Four ALCLs had a novel NCL::UBTF fusion involving genes encoding the nucleolar proteins nucleolin and nucleolar (upstream binding) transcription factor-1. Four cases each had PARG::BMS1 and TNK1::GPS2 (the latter seen only in Type I ALCLs). Conclusions: This large consortium-based analysis of coding fusions further elucidates the molecular distinction between Type I and Type II ALCLs. Both ALK and non-ALK TK fusions were seen exclusively in Type I ALCLs, which we have shown previously are enriched for JAK-STAT3 pathway genes and correlate strongly with pSTAT3Y705 positivity by immunohistochemistry. These fusions were not identified in Type II ALCLs, which previous data suggest are associated with epigenetic alterations. ALK+ ALCLs with NPM1::ALK and X::ALK showed differences in gene expression, suggesting biological differences. Furthermore, ALCLs with non-ALK TK fusions shared gene expression features with ALK+ ALCL. Clinical fusion detection could enhance molecular classification of Type I and Type II ALCLs and may guide precision therapy.

Introduction: HIV-associated diffuse large B-cell lymphoma (HIV-DLBCL) is a significant complication in HIV-positive individuals, presenting unique clinical challenges and a poorer prognosis compared to patients with de novo DLBCL. Epstein-Barr Virus (EBV) status is a critical factor influencing the pathogenesis, clinical behavior, and therapeutic responses in these lymphomas. Plasmablastic lymphomas (PBL) have shared some overlapping genomic abnormalities with HIV-DLBCL including MYC rearrangements. This study aims to elucidate the differences in the genetic profiles and pathway activations between EBV(+) and EBV(-) HIV-DLBCL through comprehensive genomic profiling. Methods: Cases of DLBCL were identified in patients living with HIV from a multi-institute cooperative group. Cases of Burkitt lymphoma and PBL were excluded. We performed whole exome sequencing (WES) on 106 tumors of HIV-DLBCL and RNA sequencing on 39 tumors and mapped the reads to hg38 reference genome using BWA and STAR, respectively. EBV status of cases was determined by in situ hybridization and/or reads mapped on EBV genome in sequencing data. Somatic mutations were identified using variant callers (Strelka2, Mutect2) with WES data. For those mutated genes in COSMIC, allele frequency cutoff was set at 0.03. Mutations with an artifact score larger than 0.7 in SOBDetector and those located in segmental duplications were further removed. They were annotated with Ensembl Variant Effect Predictor, manually checked, and plotted with maftools. RNAseq read counts aligned to each gene were obtained by featureCounts and DEseq2 was used for differential expression (DE) analysis between EBV positive and negative groups. Pathway analysis with the DE genes was performed using GSEA. FISH analysis was performed using MYC, BCL2, and BCL6 break-apart probes. Results: There were 41 cases of EBV(+) HIV-DLBCL and 65 cases of EBV(-) HIV-DLBCL. FISH of EBV(+) HIV-DLBCL identified 42% (3/7) with MYC rearrangement (MYCr), none with BCL2 rearrangements (BCL2r) (0/6), and 33% (2/6) positive for BCL6 rearrangement (BCL6r) with 1 tumor having a MYCr/BCL6r. For EBV(-) HIV-DLBCL, there were 35% with a MYCr (6/17), 18% with BCL2r (2/11), and 27% with a BCL6r (3/11) with 2 tumors with MYCr/BCL6r, and 1 tumor with MYCr/BCL2r/BCL6r. The most frequent mutations seen in EBV(+) HIV-DLBCL were STAT3 (32%), DDX3X (22%), and TP53 (15%). For EBV(-) HIV-DLBCL, the most frequent mutations were KMT2D (25%), TP53 (23%), GNA13 (22%), and TET2 (22%). Pathways that were most commonly associated with EBV(+) HIV-DLBCL were JAK/STAT (42%) (STAT3, JAK1) and NF-kB (39%)(DDX3X, TNFAIP3) while EBV(-) HIV-DLBCL was associated with epigenetic modifiers (62%)(KMT2D, TET2, EP300), JAK/STAT (45%)(SOCS1, JAK3) and PI3K/mTOR (40%)(GNA13, MTOR). Significant disparities between EBV(+) and EBV(-) were KMT2D (24% vs 50%, P=0.0025), TET2 (10% vs 26%, P=0.008), SOCS1 (29% vs 39%, P=0.04), DDX3X (15% vs 5%, P=0.03), and GNA13 (5% vs 24%, P=0.001). RAS mutations (KRAS, NRAS) were infrequent in HIV-DLBCL (EBV(+), 12%; EBV(-), 6%), in contrast to prior studies of PBL. Gene expression profiling showed enrichment of MYC targets, oxidative phosphorylation, and the mTORC pathway in EBV(+) as compared to EBV(-) HIV-DLBCL. Conclusion: EBV(+) HIV-DLBCL show a distinct mutational profile compared to EBV(-) HIV-DLBCL, with EBV(+) cases showing frequent mutations with STAT3 and DDX3X in contrast to EBV(-) cases with frequent mutations associated with epigenetic modification pathways (KMT2D, TET2). These genetic profiles underscore the need for tailored therapeutic approaches depending on EBV status. Although the analysis is limited and requires confirmation in a larger cohort, this is the largest study at present evaluating these tumors.