International journal of laboratory hematology最新文献

Introduction: Minimal/measurable residual disease (MRD) is a key prognostic factor in B-lymphoblastic leukemia/lymphoma (B-ALL/LBL), commonly assessed via multiparametric flow cytometry (MFC). This study evaluated 12 leukemia-associated immunophenotype (LAIP) markers-CD81, CD86, CD123, CD58, CD9, CD73, CD13/CD33, CD44, CD97, CD66c, CD49f, and CD304-to determine their suitability for MRD detection.

Methods: Marker expression was analyzed in 103 B-ALL cases at diagnosis, and 54 post-therapy follow-up samples, including 16 MRD-positive cases. Additionally, 25 non-B-ALL bone marrow samples were examined for marker expression in hematogones. Clinical and genetic correlation was also performed.

Results: Median age of patients was 9 years (range: 0.3-89), with male: female ratio of 1:1. We found that CD97, CD73, CD86, and CD58 are excellent markers for MRD analysis in B-ALL, as they are expressed in more than 85% of cases at baseline, and their expression is preserved in more than 75% of cases post-therapy. Two other extremely promising markers are CD81 and CD49f, both of which are expressed as LAIP in more than 50% of B-ALL cases, with retention of expression in more than 85% of cases post-therapy, and importantly, expression as LAIP in some post-therapy samples despite their absence at baseline. Hyperdiploidy was significantly associated with expression of CD86, CD97, CD123, CD66c, and CD9; BCR::ABL1 fusion was associated with CD49f, CD81, and CD66c.

Conclusion: CD97, CD73, CD86, and CD58 are the best amongst newer markers in B-ALL MRD assessment. Our findings support integrating these into MRD panels to enhance post-therapy MRD detection, thus improving prognostication and guiding treatment decisions.

CBL syndrome is caused by a heterozygous germline mutation in the CBL gene. It is a rare RASopathy that shares many clinical features with mild forms of Noonan syndrome. These patients have a higher risk of developing juvenile myelomonocytic leukaemia (JMML) during early childhood. Here we report a case of an 11-month-old infant with JMML and CBL syndrome. It was caused by a heterozygous de novo germline mutation in the CBL gene and acquired biallelic inactivation of the gene through copy-neutral loss of heterozygosity (CN-LOH) in haematological cells. CBL mutation was not found in parents and siblings. CN-LOH was confirmed by single nucleotide polymorphism array. This patient presented with an aggressive clinical course and required an allogeneic stem cell transplant.

Background: Direct oral anticoagulants (DOACs) have simplified anticoagulant therapy, but plasma level testing (i.e., anti-Xa and anti-IIa activities) remains important in specific clinical situations (e.g., emergency surgery, bleeding, renal impairment, or suspected non-adherence). However, the impact of sample storage on assay reliability is not well defined. This study evaluated the stability and potential systematic errors in DOACs (apixaban, rivaroxaban, edoxaban, dabigatran) plasma levels after 24 h storage under different conditions.

Methods: We enrolled 182 patients on one of the four DOACs. Blood samples were collected in duplicate citrated tubes. The first tube was processed within 4 h to obtain baseline values, with plasma successively stored at room temperature, 4°C, and -20°C for 24 h. The second tube was stored as whole blood at room temperature before measuring DOACs concentrations. DOACs were measured using dedicated clotting or chromogenic assays. Stability was assessed using non-parametric statistics, Passing-Bablok regression, and Bland-Altman analysis, with Acceptable Change Limits based on assay variability.

Results: All DOACs showed good stability across conditions, with median recoveries ranging from 93% to 102%. No significant proportional errors were observed. Minor constant biases were observed for apixaban (at 4°C and -20°C), and more consistently for rivaroxaban and edoxaban. Dabigatran showed no significant bias. Variability was generally low (< 7%), and most measurements near clinical thresholds remained accurate.

Conclusion: DOACs plasma levels remain stable after 24 h storage under various conditions. While minor biases exist, particularly for rivaroxaban and edoxaban, they are unlikely to affect clinical interpretation in most cases. Whenever needed, DOACs measurement can be deferred after blood drawing without jeopardizing results interpretation.

Introduction: Erythrocyte sedimentation rate (ESR) is a widely used inflammation marker. VISION Pro (Shenzhen YHLO Biotech Co. LTD, Shenzhen, China) is a fully automated ESR analyzer. This study verified its analytical performance and comparability to the manual Westergren method.

Methods: Inter- and intra-run precision study was assessed using control and patient samples at low, medium, and high ESR levels. Accuracy was evaluated by comparing 240 K₂EDTA (ethylenediaminetetraacetic acid) whole blood samples with the Westergren method in citrate divided by ESR subgroups (< 40, 40-80, > 80 mm). Sample stability was tested in 8 samples at room temperature and 2°C-8°C over 24 h. Reference range verification included 40 healthy individuals (20 male, 20 female). The effects of testing order for ESR and complete blood count (CBC) (ESR/CBC/ESR vs. CBC/ESR/CBC) and analysis modes (Cycle, Random, Mixer+Random) were also explored.

Results: Inter- and intra-run precision were acceptable at medium and high ESR levels without temperature correction, while low levels exceeded acceptable criteria (e.g., CV = 24.4% vs. criterion 11.3%). Agreement with Westergren was excellent, with no significant differences (intercept = 1.1 [95% CI: 0.0-1.4]; slope = 1.0 [95% CI: 0.9-1.0]), while temperature-corrected results showed unsatisfactory agreement (intercept = -0.1 [95% CI: -0.7 to 0.4]; slope = 0.8 [95% CI: 0.7-0.8]). Sample stability was maintained for up to 3 h at room temperature and up to 10 h at 2°C-8°C. Reference range verification demonstrated all 20 samples within limits for men and 19/20 for women, while only 17/20 for temperature-corrected results for women. ESR/CBC/ESR order minimally affected the results (14/15 acceptable), while CBC/ESR/CBC order influenced CBC parameters (predominantly MPV). No significant differences occurred between measurement modes (p = 0.093).

Conclusion: VISION Pro analyzer demonstrated acceptable ESR measurement performance without temperature correction and is suitable for routine laboratory use. Temperature-corrected results showed inconsistent performance and require cautious interpretation.

Background: The peripheral blood film (PBF) analysis traditionally relies on manual microscopy (MM), a labour-intensive method with inter-observer variability. This study evaluates Blade (a semi-supervised AI model) and CellaVision DM9600 (commercial benchmark) against MM in automated leukocyte classification.

Methods: PBFs from 168 patients were prepared using automated staining and scanned digitally. Blade, trained on 185 412 cells (75 435 labelled, 109 977 unlabelled) via ResNet34 and RetinaNet architectures, underwent pseudo-labelling and AdamW optimisation. Performance was evaluated on 1675 cells against MM using the concordance correlation coefficient (CCC), Bland-Altman analysis, Deming/Passing-Bablok regression and diagnostic accuracy measures across nine leukocyte subtypes.

Results: When evaluated individually against MM, both systems showed high agreement. Blade achieved excellent correlation for common cells (neutrophils: ccc = 0.988; lymphocytes: ccc = 0.985; eosinophil: ccc = 0.953) and comparable results to CellaVision for monocytes (ccc = 0.852 vs. 0.847) and basophils (ccc = 0.762 vs. 0.794). Blade performed better for metamyelocytes (ccc = 0.905 vs. 0.756) and showed higher sensitivity for monocytes (75% vs. 63%) and myelocytes (87% vs. 74%). Regression analysis showed slopes close to 1.0 for most cell types, with Blade displaying narrower Limits of Agreement in Bland-Altman analysis. Both systems achieved 100% sensitivity for blasts and reactive lymphocytes. Overall macro-averaged performance was comparable between Blade (sensitivity 89.2%, specificity 96.3%) and CellaVision (86.3% and 96.7%).

Conclusion: Blade and CellaVision demonstrated strong concordance with MM, validating their clinical utility. Blade's semi-supervised learning confers marginal advantages in rare cell detection and stability, highlighting AI's potential to enhance diagnostic accuracy. While both systems reduce labour and variability, Blade's performance has potential for integration into haematology workflows. Future validation in diverse cohorts is recommended.