Journal of Applied Laboratory Medicine最新文献

Background: Cancer immunotherapy research, immune microenvironment exploration, and biomarker discovery are key application areas of immune checkpoint analysis. PD-1 and CD28 are crucial receptors expressed on the surface of T cells, playing vital roles in regulating T cell activation and immune response. Accurate detection of these immune checkpoints, such as PD-1 and CD28 on lymphocytes, is essential for understanding immune responses, particularly in clinical contexts such as cancer immunotherapy. Flow cytometry offers a precise approach to detect these markers in whole blood samples.

Methods: This study developed and optimized a flow cytometry-based detection method utilizing the CYTEK NL-CLC flow cytometer to quantitatively assess the expression of PD-1 and CD28 on lymphocytes. A detailed protocol was established and validated, focusing on key performance parameters.

Results: Our method showed high sensitivity and specificity, providing a powerful tool for immune monitoring and treatment decision-making. Validation results, including precision, dilution linearity, fluorescence stability, reference interval, and accuracy, all met acceptable criteria and have been reviewed and approved for clinical testing.

Conclusions: The CYTEK NL-CLC flow cytometer is positioned as a reliable and effective platform for immune checkpoint analysis in both clinical and research settings, supporting its integration into cancer immunotherapy workflows and personalized medicine strategies.

Background: Increases in obesity and hypertriglyceridemia worldwide, together with lower LDL cholesterol (LDL-c) values from new lipid-lowering agents, prompted the development of new estimation formulas including Martin (M-LDL-c), extended Martin (ME-LDL-c), and Sampson (S-LDL-c) equations. These require validation in different populations.

Methods: Lipid profiles with direct LDL-c (D-LDL-c) by homogeneous assay were collected from 22 748 patients in Argentina. Friedewald (F-LDL-c), S-LDL-c, M-LDL-c, and ME-LDL-c were calculated. Patients were classified into treatment categories using both D-LDL-c and each formula independently. Datasets were subdivided by triglycerides (TG). Lipid ratio plot (LRP) provided indirect comparison to beta quantification (BQ). Passing-Bablok, Bland-Altman, and clinical concordance (kappa index) analyses assessed formula performance against D-LDL-c.

Results: LRP analysis showed S-LDL-c had the closest agreement with BQ surrogate line, followed by D-LDL-c. All formulas showed good correlation with D-LDL-c (r > 0.95) and moderate concordance (kappa > 0.6). M-LDL-c and ME-LDL-c demonstrated the best clinical concordance with D-LDL-c overall. Performance decreased with increasing TG for all formulas. F-LDL-c deteriorated from 200 mg/dL (2.28 mmol/L) TG, while S-LDL-c, M-LDL-c, and ME-LDL-c maintained acceptable performance up to 400 mg/dL (4.56 mmol/L) TG.

Conclusion: S-LDL-c, M-LDL-c, and ME-LDL-c showed better agreement with D-LDL-c than F-LDL-c in this South American population. LRP analysis suggests S-LDL-c may provide most accurate estimation vs gold standard BQ, particularly in hypertriglyceridemia. These findings support the adoption of newer equations in clinical practice.

Background: Acute graft-versus-host disease (aGVHD) is a common complication of allogenic hematopoietic cell transplantation (HCT). The aGVHD presymptomatic algorithm is comprised of 2 serum biomarkers, suppression of tumorigenicity 2 and regenerating islet-derived 3-alpha. This test was developed to predict severe aGVHD and 6-month nonrelapse mortality (NRM) in allogeneic HCT recipients.

Methods: The medical records of 223 patients tested with the aGVHD presymptomatic algorithm between January 2020 and June 2024 were retrospectively reviewed. Sensitivity and specificity for the prediction of severe aGVHD (grade III or IV) and 6-month NRM were determined. Logistic regression modeling was used to assess the odds ratios of risk factors for severe aGVHD and 6-month NRM. The likelihood ratio test was used to evaluate whether the addition of the aGVHD presymptomatic algorithm improved model fit.

Results: Severe aGVHD occurred in 8.5% of patients, and 6-month NRM was 7.2%. The aGVHD presymptomatic algorithm demonstrated a sensitivity of 21.1% (95% CI, 8.0%-43.9%) and specificity of 83.3% (95% CI, 77.6%-87.9%) for severe aGVHD and a sensitivity of 43.8% (95% CI, 23.1%-66.8%) and specificity of 85.0% (95% CI, 79.5%-89.3%) for 6-month NRM. The addition of results from the aGVHD presymptomatic algorithm to conventional risk factors did not improve prediction of aGVHD but improved prediction of 6-month NRM.

Conclusions: The aGVHD presymptomatic algorithm was suboptimal for routine clinical use. Further development of predictive aGVHD biomarkers may be required to aid in the management of allogeneic HCT recipients.

Background: Health literacy and numeracy are broad terms that relate to a patient's understanding of their health information. While there is a substantial amount of research on this topic in a general sense as well as in relation to how deficiencies in these skills impact patients' understanding of laboratory results, little is known regarding the extent to which underlying factors, which are impacted by health literacy/numeracy, affect how patients interpret their results. This literature review attempts to shed light on the current literature on this more focused and narrow issue, including recommendations to address these barriers.

Content: To perform this review, the key terms "health literacy AND numeracy," "health literacy AND laboratory results," and "patient understanding of laboratory test results" were searched in the PubMed Central, Health Source: Nursing/Academic Edition, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases. After reviewing articles for inclusion and exclusion criteria, a total of 16 articles were included. Major themes from the articles utilized were (a) the impact of the laboratory, (b) factors that affect health literacy and numeracy of laboratory data, and (c) recommendations to improve patient understanding and comprehension of their test results.

Summary: Many factors affect patients' comprehension of laboratory data, such as access to this information, data presentation, and holistic influences. Recommendations for improving patient health numeracy of laboratory information are to improve how data is presented to patients and to increase access to supplemental resources via patient portals.

Background: Rapid, accurate diagnosis in acute and emergent care remains a major challenge, with delays directly impacting patient outcomes. Extracellular vesicles (EVs), nanoscale membranous particles secreted by all cell types and found in virtually all biological fluids, have the potential to transform acute diagnostics as minimally invasive biomarkers. As key intercellular messengers and carriers of biological cargo, EVs reflect the physiological and pathological states of their parent cells. While EV research has largely focused on chronic diseases such as cancer and neurodegeneration, their role in acute pathologies remains under-investigated.

Content: This review describes the current landscape of EVs in laboratory medicine, with a focus on their potential for acute and emergent conditions, including sepsis, stroke, traumatic brain injury, and myocardial infarction. We examine advances in EV isolation and characterization techniques and discuss the unique challenges of implementing these approaches in a clinical setting. In particular, we highlight emerging technologies that aim to address existing barriers, including lack of standardization, long processing times, and limited clinical scalability.

Summary: By summarizing existing knowledge and identifying critical research gaps, this review intends to refocus attention toward EV applications for acute care. As EV-based diagnostics continue to advance, their successful integration into clinical work flows has the potential to significantly transform healthcare delivery, enabling real-time, personalized diagnostics and improving health outcomes across a wide range of settings.

Background: Bicarbonate concentration is widely used to assess acid-base disorders in patients, and the concentration can be directly measured or calculated. When discrepant results between measured bicarbonate (mHCO3-) and calculated bicarbonate (cHCO3-) are observed, it can lead to confusion among clinicians and potential for misdiagnosis. Here we assessed the agreement between cHCO3- from the Radiometer blood gas analyzer and mHCO3- from 3 different chemistry instruments.

Methods: Three institutions that measure bicarbonate using chemistry analyzers from 3 different manufacturers and derive bicarbonate on Radiometer blood gas analyzers participated in this study. De-identified patient data include plasma mHCO3- and blood gas cHCO3- results (arterial and venous) collected within +/- 20 min. Correlations and biases were determined.

Results: Deming regression analysis showed good correlations between cHCO3- and mHCO3-. Bland-Altman analysis revealed the greatest bias between Radiometer and Abbott Architect (-2.63 mmol/L), followed by Siemens Advia (0.49 mmol/L) and Beckman AU680 (-0.45 mmol/L).

Conclusions: This is the first study to compare cHCO3- from the Radiometer blood gas analyzer against mHCO3- results from multiple chemistry analyzers. Our results suggest that the Radiometer blood gas analyzer, Siemens Advia, and Beckman AU680 agree well with each other. However, bicarbonate results may be negatively biased when measured on the Abbott Architect compared with the other methods.

Background: Determination of steroid hormones by mass spectrometry (MS) offers several advantages over immunoassays. Modern MS instruments have high selectivity and sensitivity and permit measurements of several compounds at picomolar concentrations in one sample volume, which is advantageous when conducting biobank studies.

Methods: We developed a LC-MS/MS method for the determination of 17β-estradiol, 17α-ethinylestradiol, estrone, estrone 3-sulfate, estriol, progesterone, testosterone, dehydroepiandrosterone sulfate, aldosterone, cortisone, and cortisol in 300 μL human serum. Samples were subjected to robotized protein precipitation with acetonitrile and liquid-liquid extraction with ethyl acetate/heptane, and the aqueous and organic phases were used to determine conjugated and unconjugated steroids, respectively. The steroids were separated from isobars and compounds with similar mass (M + 2) on a C18 reversed phase column. Ammonium hydroxide was infused post-column to enhance ionization, and ions were measured in multiple reaction monitoring negative and positive mode.

Results: The lower limits of quantification for 17β-estradiol and estrone were 3.6 (0.98 pg/mL) and 2.1 pmol/L (0.57 pg/mL), respectively. For medium concentrations of steroid hormones, total CVs were in the range 2.3% to 10.5%, and accuracies were 97% to 109%. The method was validated in terms of linearity (r2 ≥ 0.9779) and assay recovery (83%-114%), and certified control sera were analyzed. Steroid profiles were obtained in 921 women with a mean age of 56 years (range 44-66 years) from the European Community Respiratory Health Survey.

Conclusions: We developed a selective and sensitive LC-MS/MS method for 11 steroids in human serum. It is suitable for biobank studies.

Background: JAK2, CALR, and MPL mutations are defining features of myeloproliferative neoplasms (MPNs). Molecular testing for variants in these genes is standard of care in the diagnosis of MPNs. A high reimbursement denial rate led to review of ordering practices and test utilization to identify potential areas for optimization, education, or triage to improve laboratory stewardship.

Methods: MPN panel orders placed between January 1, 2023 and December 31, 2023 were analyzed by ordering provider, complete blood count (CBC) values, demographics, test results, and International Classification of Diseases, 10th revision (ICD10) code. Laboratory staff manually review orders prior to testing. Clinical appropriateness was defined as unexplained cytosis or atypical thrombosis.

Results: Orders for 257 unique patients were included for analysis. Most orders were placed by hematology/oncology providers (79.0%). Of orders, 72.8% had a cytosis-related ICD10 code, and 11.7% a thrombosis-related ICD10 code. MPN panel results were negative in 76.3% of patients and positive (pathogenic mutations in JAK2/CALR/MPL) in 13.2%. A χ2 test did not show a statistically significant association between ICD10 category and positive results. Of patients with positive results, 79.4% had thrombocytosis on CBC, but 70.6% had normal or low hemoglobin.

Conclusions: Orders for our institution's MPN panel are generally appropriate and placed correctly. Our findings do not support additional interventions or clinical decision support, utilizing features such as the patient's CBC values or ICD10 codes, as likely to be of significant benefit. The limited reimbursement remains challenging, but we will continue to engage stakeholders to advocate for continued access.