International journal of laboratory hematology最新文献

Background: Limited availability of diagnostic tests in low-resource settings hampers the diagnosis and classification of diffuse large B-cell lymphoma (DLBCL). A study was performed to assess the use of resources for classifying DLBCL in South Africa (SA) using 'essential' and 'desirable' investigations as per published guidelines.

Methods: A record review was performed of 74 patients newly diagnosed with DLBCL by tissue biopsy at the National Health Laboratory Service (NHLS) in Johannesburg between 1 January 2019 and 31 December 2022. The immunohistochemistry (IHC) and/or molecular work-up performed for the primary diagnosis of DLBCL and the associated costs were recorded.

Results: The primary diagnosis of DLBCL was based on 34 (45.9%) nodal and 40 (54.1%) extra-nodal biopsy sections. Overall, 60 (81.1%) were from participants living with human immunodeficiency virus (HIV) infection. 'Essential' IHC for CD3, CD10, CD20, Ki-67, BCL-2, BCL-6, MUM-1 and 'desirable' fluorescence in situ hybridisation (FISH) for MYC gene rearrangement were most requested for diagnosis. 'Essential' IHC for c-MYC was not performed because of non-availability of the testing. The 'essential' IHC was diagnostic in 97.3%. 'Desirable' FISH for MYC rearrangement was done in 56 (79.7%) cases, with additional FISH for BCL2 and BCL6 rearrangement performed in cases positive for MYC rearrangement. The average cost of diagnosis at the NHLS was half that of the recommended diagnostic testing.

Conclusion: The advocated 'essential' investigations, in addition to 'desirable' tests where necessary, enabled the accurate and cost-effective diagnosis of DLBCL in SA and are recommended for other parts of the world with limited resources.

Introduction: Malaria is a common and life-threatening infection. Malaria diagnosis needs to be fast and reliable. Although malaria microscopy is currently the gold standard, it is laborious, requires extensive training, and relies heavily on the proficiency of microscopists. Though malaria rapid tests are widely used, they show poor sensitivity at low parasitemia levels, are affected by gene deletions, and offer only qualitative results. There is a need to explore new techniques for the diagnosis of malaria.

Methodology: A single-center, cross-sectional study evaluated the diagnostic performance of the Sysmex XN-31 automated analyzer for detecting malaria parasites compared to expert microscopy. The primary objective was to assess the XN-31's sensitivity, specificity, and ability to quantify malaria parasites relative to microscopy, the current gold standard. Blood samples from 310 adult patients undergoing routine malaria testing in a hospital setting were used. This included 118 confirmed malaria-positive cases. The Sysmex XN-31 results were compared to blinded expert microscopy on the same samples. Dried blood spot samples were collected for any discrepancies and resolved using molecular testing.

Results: This study analyzed 310 patient samples for malaria using both microscopy and the XN-31 analyzer. Microscopy identified 122 positive samples (39%), with P. falciparum being the most prevalent species. Expert malaria microscopy demonstrated a sensitivity of 97.6% and a specificity of 100%. The XN-31 analyzer showed a sensitivity of 100% and a specificity of 99.46%. In malaria speciation, the XN-31 correctly flagged P. falciparum in 116 out of 117 cases (99.1%) among 125 positive cases. Additionally, five nonfalciparum malaria cases (Plasmodium malariae-four cases and Plasmodium ovale-one case) were accurately flagged as 'Malaria (Others).' However, five P. falciparum cases were incorrectly flagged as 'Malaria (Others),' highlighting limitations in malaria speciation by the analyzer. Statistical analysis revealed a strong correlation (Spearman coefficient of 0.8) between the parasite density measured via microscopy and the XN-31. Passing-Bablok regression indicated a strong linear relationship between these two methods.

Conclusion: The Sysmex XN-31 analyzer provides a quick and accurate method for the diagnosis of malaria. It detects, quantifies, and speciates plasmodium infections in less than 1 minute. Our study showed that the analyzer shows high sensitivity and specificity comparable to those of expert microscopy in detecting Plasmodium species, making it a promising alternative to current diagnostic methods. By overcoming the numerous limitations of existing tests, the XN-31 proves to be well-suited for malaria testing, especially in malaria-endemic regions.

Introduction: Von Willebrand factor (VWF) multimer analysis is essential for diagnosing and classifying von Willebrand disease (VWD) but requires expert interpretation and is subject to inter-rater variability. We developed an automated image analysis pipeline using deep learning to improve the reproducibility and efficiency of VWF multimer pattern classification.

Methods: We trained a YOLOv8 deep learning model on 514 gel images (6168 labeled instances) to classify VWF multimer patterns into 12 classes. The model was validated on 192 images (2304 instances) and tested on an independent set of 94 images (1128 instances). Images underwent preprocessing, including histogram equalization, contrast enhancement, and gamma correction. Two expert raters provided ground truth classifications.

Results: The model achieved 91% accuracy compared to Expert 1 (macro-averaged precision = 0.851, recall = 0.757, F1-score = 0.786) and 87% accuracy compared to Expert 2 (macro-averaged precision = 0.653, recall = 0.653, F1-score = 0.641). Inter-rater agreement was very high between experts (κ = 0.883), with strong agreement between the model and Expert 1 (κ = 0.845) and good agreement with Expert 2 (κ = 0.773). The model performed exceptionally well on common patterns (F1 > 0.93) but showed lower performance on rare subtypes.

Conclusion: Automated VWF multimer analysis using deep learning demonstrates high accuracy in pattern classification and could standardize the interpretation of VWF multimer patterns. While not replacing expert analysis, this approach could improve the efficiency of expert human review, potentially streamlining laboratory workflow and expanding access to VWF multimer testing.

Introduction: Formalin-fixed paraffin-embedded (FFPE) tumor biopsy is the current mainstay of genotyping, but is limited by its invasiveness and tumor heterogeneity. Plasma cell-free DNA (cfDNA) constitutes a minimally invasive alternative that may better capture tumor-derived profiles from circulating tumor DNA (ctDNA). This study compares the performance and genomic concordance of cfDNA and FFPE tumor DNA in aggressive non-Hodgkin large B-cell lymphoma.

Methods: Paired diagnostic FFPE tissue and plasma samples from 15 patients were sequenced with a custom 53-gene panel.

Results: Detection thresholds were empirically guided at 1% variant allele frequency (VAF) for cfDNA and 10% for unpaired FFPE DNA. The median number of cfDNA variants was 6 (interquartile range (IQR): 2-11) versus 63 (IQR: 15-250) in FFPE DNA at 1% VAF. Collectively, 102 somatic variants were shared between cfDNA and FFPE DNA with a median of 5 (range: 0-23). cfDNA showed a five-fold lower median VAF for shared variants than FFPE DNA (7% vs. 36%, p < 0.0001). Eighty percent of patients harbored at least one cfDNA variant. A maximum cfDNA recall rate of 83% was observed at FFPE DNA VAF > 50%. COSMIC database overlap was twice as high for cfDNA compared to FFPE DNA (22% vs. 11%) at 10% VAF.

Conclusion: cfDNA has superior specificity for somatic mutation detection but lower sensitivity than FFPE DNA. Modest concordance was demonstrated between the two compartments. Our results support a complementary role of ctDNA in mutational profiling at a 1% VAF threshold in a pragmatic and clinically applicable setup.

Introduction: Measurable residual disease (MRD) in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) following anti-CD19 targeted therapies requires specific strategies to identify residual blast cells due to loss or reduced CD19 expression that makes it inconsistent as a primitive marker for B-cell gating.

Objective: Due to the increased access of BCP-ALL patients to therapies with CD3/CD19 bispecific T-cell engagers (BiTe) and CD19-targeted chimeric antigen receptor T-Cell (CAR-T), it is essential that flow cytometry laboratories are prepared to evaluate therapeutic responses.

Material and methods: Here, validated strategies for MRD detection in the context of anti-CD19 therapies are described, accessible to flow cytometry laboratories according to their different facilities. The paper includes an 8-color flow cytometry (FC) strategy for BCP-ALL MRD based on alternative gating without the use of additional markers (Euroflow protocol), as well as other strategies using alternative markers to CD19, comprising 2 protocols using 8 colors, one using 10 colors and another 14 colors/15 markers.

Conclusion: Different strategies are needed to detect MRD without using CD19 for B-cell population gating after CD19-targeted therapies. However, it is essential that validated protocols are used according to the available resources to ensure reliable results for clinical decision-making.

Background/objectives: Infant BCP-ALL is classified into KMT2A-r and KMT2A-wt groups, both showing heterogeneity. KMT2A rearrangements indicate poor prognosis, but outcomes vary by fusion partner. The KMT2A-wt group includes cases in the B-other ALL subgroup, with unclear prognostic significance. We aim to improve understanding of molecular subtypes in KMT2A-r and KMT2A-wt, focusing on NUTM1 and PAX5 rearrangements.

Methods: We analyzed 175 infants (aged 0-365 days) diagnosed with BCP-ALL from 2010 to 2023 at the Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology. Genomic aberrations were identified by karyotyping, FISH and RNA-seq. RNA-seq was performed using the Illumina, and gene fusions were validated by Sanger sequencing.

Results: There was no difference in survival based on KMT2A partner genes. The KMT2A::AFF1 group showed similar outcomes to other partners, with 2-year EFS of 36% (95% CI, 21%-59%) versus 37% (95% CI, 23%-60%) (log-rank test, p = 0.9). In the KMT2A-wt group (n = 33, 17.7% of cases), NUTM1-r (n = 9) and PAX5-r (n = 10) accounted for 27% and 30.3%, respectively. The NUTM1-r and PAX5-r groups showed excellent survival rates, with 2-year EFS of 80% (95% CI, 52%-100%) and 100% (95% CI, 100%-100%), respectively, but the small cohort size limit the statistical power of the analysis (log-rank test, p = 0.9).

Conclusions: Survival in the KMT2A-r group did not differ by fusion partner. NUTM1 rearrangements showed a favorable prognosis, and PAX5-rearranged patients had better outcomes than previously reported. In the NUTM1-r group, the most common fusion, BRD9:NUTM1, showed variability in breakpoints (Exons 3, 8, and 14 of BRD9).

Background: Long noncoding RNAs (lncRNAs) have emerged as key regulators of cancer; in addition, they have been identified as novel therapeutic targets and biomarkers for several cancers, including diffuse large B-cell lymphoma (DLBCL).

Methods: A total of 75 DLBCL patients and 30 control subjects with active lymph nodes were enrolled into our study. The baseline expression levels of lncRNAs HOTAIR, MALAT1, and PANDA in paraffin-embedded blocks of lymph nodes from DLBCL patients and controls were evaluated using reverse transcription quantitative real-time PCR (RTqPCR) technique.

Results: The expression levels of HOTAIR and MALAT1 were increased while PANDA expression level was decreased in DLBCL patients when compared to controls and in R-CHOP-resistant patients when compared to responder ones. Also, HOTAIR, MALAT1, and PANDA baseline expression levels were significantly correlated with the different clinical parameters in this study. As diagnostic and prognostic tools, the results obtained from the ROC curve revealed that the PANDA baseline expression level was the best one as the diagnostic biomarker could differentiate DLBCL disease and the prognostic biomarker predicts R-CHOP resistance.

Conclusion: In conclusion, the integrated approach reveals that lncRNAs HOTAIR and MALAT1 were upregulated, while lncRNA PANDA was downregulated in DLBCL patients compared with controls, and the three lncRNAs closely associated with clinical prognosis. This study warrants future studies in clinical trials for the treatment of R-CHOP-resistant DLBCL patients.

Introduction: The PNH working group was created in 2010 to initiate a workshop on testing white blood cells to share international recommendations.

Methods: Thirty-five French and Belgian laboratories equipped with 2- or 3-laser cytometers applied three different panels with or without FLAER reagent in 305 samples. This multicenter study demonstrated the interplatform applicability of setting harmonization and the benefits of using a harmonized gating method. A 10^-4 limit of detection was achieved with harmonized multiparametric approaches in both six-color combinations, as well as a robust quantification of minor PNH clones.

Results: Following this workshop, the group has developed a quality control scheme since 2013 to improve PNH diagnosis practices. This annual program includes two surveys, a virtual one and one based on fresh whole-blood sample analysis. Over the last 10 years, the regular participation of the French-speaking registered centers has demonstrated their strong commitment to our program, which offers various PNH clinical situations. Alongside, the conformity of the final reports provided by the participants has increased to 96%.

Conclusion: In 2016, our PNH working group initiated a nationwide multicenter prospective observational study, collecting all PNH cases or GPI-deficient cells above 0.01% to monitor the long-term evolution of minor PNH clones < 1% and to further investigate the relevance of classifying type II and type III PNH cells in WBCs in clones > 1%. The strong network of cytometrists built led us to create in 2018 the French-speaking flow cytometry association in Hematology, namely CytHem, to harmonize the diagnostic practices in various hematological diseases.

Objective: To develop a novel predictive model based on demographics and complete blood count (CBC) parameters to quickly identify suspicious features of myeloproliferative neoplasms (MPN), enabling prompt initiation of further investigations and referrals.

Methods: 426 patients with elevated peripheral blood cell counts were referred to the Hematology Department of Ruijin Hospital from 2017 to 2023. Among them, 215 patients were diagnosed with MPN, while the remaining 211 patients formed the non-MPN group. The patients were randomly divided into a training cohort and a validation cohort. Demographic characteristics, CBC data, and other relevant laboratory information were collected. By univariable and multivariable logistic regression, significant indicators independently associated with MPN were identified and included in the nomogram. The model was evaluated by measuring the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) curve.

Results: Five indicators were identified as independently associated with MPN, including onset age, monocyte fraction, basophil fraction, red blood cell distribution width, and platelet count. The AUC values for the training and validation cohorts were 0.912 and 0.928, respectively. The calibration curves showed good agreement between the predicted risk by the nomogram and the actual outcomes. The DCA for the training and the validation datasets revealed net benefits of 0.9026 and 0.9303, respectively.

Conclusion: We have developed and validated a prediction model for MPN based on demographics and CBC data. The model could assist general practitioners in quickly identifying patients with potential MPN and in initiating timely further investigations and referrals.