BackgroundKnowledge concerning the clinical and biological presentation, as well as the outcome of treatment, of biphenotypic acute leukemia in children is limited. Design and MethodsThis retrospective review analyzes the clinical features and outcome of children with biphenotypic acute leukemia diagnosed and treated over an 8-year period. According to the EGIL scoring system 24 (3.7%) of 633 patients with acute leukemia were classified as having biphenotypic acute leukemia. The diagnostic work-up and results were reviewed specifically for this study in the light of the newly published WHO criteria for the diagnosis of leukemia of ambiguous lineage. Based on these criteria, 11 (1.7%) patients were categorized according to the new nomenclature as having mixed phenotype acute leukemia. The majority of the patients (58.3%) had a B-lymphoid/myeloid phenotype, followed by the T-lymphoid/myeloid phenotype. The most frequent chromosomal abnormality involved the 14q32 locus. Patients received therapy based on a treatment regimen for acute lymphocytic leukemia regimen, which included myeloid-effective agents. ResultsAt a median follow up of 4 years (range, 6 month -7 years) the overall survival rate was 75.7% and the event-free survival rate was 73.5%. The survival of those patients who underwent hematopoietic stem cell transplantation in first complete remission was not different from that of the patients who were treated with chemotherapy alone (overall survival: 70.1% versus 81.1%, respectively, p=0.39; event-free survival: 70.1% versus 76.2%, respectively, p=0.75). The outcome of the 11 patients who were retrospectively classified as having mixed phenotype acute leukemia according to the new WHO criteria was excellent, with no relapses or deaths occurring among these patients. ConclusionsAn acute lymphocytic leukemia type of induction therapy, using agents that are active against lymphoid and myeloid leukemias, appears to be more effective in achieving and maintaining complete remissions regardless of whether the patients are classified according to EGIL criteria or the new WHO criteria. Hematopoietic stem cell transplantation may not be necessary for all patients in first complete remission.Key words: biphenotypic acute leukemia, diagnosis, therapy, immunophenotyping, stem cell transplant.Citation: Al-Seraihy AS, Owaidah TM, Ayas M, El-Solh H, Al-Mahr M, Al-Ahmari A, and Belgaumi AF. Clinical characteristics and outcome of children with biphenotypic acute leukemia. Haematologica 2009; 94:1682-1690. doi:10.3324/haematol.2009

Biphenotypic acute leukemia (BAL) is a rare, difficult to diagnose entity. Its identification is important for risk stratification in acute leukemia (AL). The scoring proposal of the European Group for the Classification of Acute Leukemia (EGIL) is useful for this purpose, but its performance against objective benchmarks is unclear. Using the EGIL system, we identified 23 (3.4%) BAL from among 676 newly diagnosed AL patients. Mixed, small and large blast cells predominated, with FAB M2 and L1 constituting the majority. All patients were positive for myeloid (M) markers and either B cell (B) (17 or 74%) or T cell (T) (8 or 34%) markers with two exceptional patients demonstrating trilineage phenotype. Six (50%) of studied M-B cases were positive for both IGH and TCR. In six (26%) patients myeloid lineage commitment was also demonstrable by electron cytochemistry. Abnormal findings were present in 19 (83%) patients by cytogenetics/FISH/molecular analysis as follows: t(9;22) (17%); MLL gene rearrangement (26%); deletion(6q) (13%); 12p11.2 (9%); numerical abnormalities (13%), and three (13%) new, previously unreported translocations t(X;6)(p22.3;q21); t(2;6)(q37;p21.3); and t(8;14)(p21;q32). In conclusion, the EGIL criteria for BAL appear robust when compared against molecular techniques that, if applied routinely, could aid in detecting BAL and help in risk stratification.

Genetic screening is an important tool to control, minimize, and prevent genetic disorders. Saudi Arabia started the first national premarital screening (PMS) program to control inherited hemoglobin (Hb) disorders that are the most commonly inherited genetic disorders in the Kingdom of Saudi Arabia. The aim of this study was to assess the knowledge, perception, and attitude among the Saudi population about the PMS program through a questionnaire-based survey. A total of 1,047 candidates were included, divided into three groups. Group A represented the general population, group B was composed of couples presenting for PMS, and group C represented couples who had received their results. There was a fair knowledge among participants of the three groups about the nature of the tests and the targeted disorders, with more than 80% believing that it should include both sexually and genetically transmitted diseases. The concept of genetic counseling was liked by most of the participants. There was a positive attitude toward the program and the majority agreed to apply the PMS program to all couples in all country regions. More than 60% of all the participants were in favor of preventing at-risk marriages.

Augmented human intelligence (AHI) and artificial intelligence (AI) tools might shape the future of medical practice. The expansion of data generated by our systems, medical literature, and the inefficiencies of healthcare systems will necessitate utilizing the power of AI tools. 1,2 The integration of AHI tools into medical practice, including machine learning (ML) and deep learning algorithms, has begun. For instance, the United States food and drug administration (US-FDA) has approved many AI-based softwares since 2017 for medical use. 2,3 The introduction of digital pathology has brought many opportunities to the field of pathology, such as telemedicine. 4,5 Recently, the use of digital pathology has allowed for the use of ML (including deep learning algorithms) in the automation of pathological diagnosis. 6,7 The challenges facing the use of ML in pathology are many, including digitalizing slides, labeling in case of Abstract Machine learning (ML) offers opportunities to advance pathological diagnosis, especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is time-consuming and challenging in many areas globally and there is a growing trend in utilizing ML techniques for its diagnosis. In this review, we aimed to describe the literature of ML utilization in the diagnosis of the four common types of leukemia: acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), acute myeloid leukemia (AML), and chronic myelogenous leukemia (CML). Using a strict selection criterion, utilizing MeSH terminology and Boolean logic, an electronic search of MEDLINE and IEEE Xplore Digital Library was performed. The electronic search was complemented by handsearching of references of related studies and the top results of Google Scholar. The full texts of 58 articles were reviewed, out of which, 22 studies were included. The number of studies discussing ALL, AML, CLL, and CML was 12, 8, 3, and 1, respectively. No studies were prospectively applying algorithms in real-world scenarios. Majority of studies had small and homogenous samples and used supervised learning for classification tasks. 91% of the studies were performed after 2010, and 74% of the included studies applied ML algorithms to microscopic diagnosis of leukemia. The included studies illustrated the need to develop the field of ML research, including the transformation from solely designing algorithms to practically applying them clinically. K E Y W O R D S diagnosis, digital, leukemia, machine learning, pathology How to cite this article: Salah HT, Muhsen IN, Salama ME, Owaidah T, Hashmi SK. Machine learning applications in the diagnosis of leukemia: Current trends and future directions. Int J Lab Hematol. 2019;41:717-725. https ://doi.

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This study showed some early benefits of the PMS in prevention of the targeted diseases and the program helped in early detection of the disease in their offspring.

Positivity for both leukemia-associated antigens CD66c and CD25 in combination can predict the presence of BCR/ABL rearrangement in pre-B cell ALL. While this finding does not replace the detection of BCR/ABL abnormality by cytogenetic or molecular techniques, it does provide an early and handy tool for prediction and management of high-risk cases of pre-B cell ALL, especially in centers with limited laboratory facilities.

There is unmet need for prediction of treatment response for chronic myeloid leukemia (CML) patients. The present study aims to identify disease-specific/disease-associated protein biomarkers detectable in bone marrow and peripheral blood for objective prediction of individual’s best treatment options and prognostic monitoring of CML patients. Bone marrow plasma (BMP) and peripheral blood plasma (PBP) samples from newly-diagnosed chronic-phase CML patients were subjected to expression-proteomics using quantitative two-dimensional gel electrophoresis (2-DE) and label-free liquid chromatography tandem mass spectrometry (LC-MS/MS). Analysis of 2-DE protein fingerprints preceding therapy commencement accurately predicts 13 individuals that achieved major molecular response (MMR) at 6 months from 12 subjects without MMR (No-MMR). Results were independently validated using LC-MS/MS analysis of BMP and PBP from patients that have more than 24 months followed-up. One hundred and sixty-four and 138 proteins with significant differential expression profiles were identified from PBP and BMP, respectively and only 54 proteins overlap between the two datasets. The protein panels also discriminates accurately patients that stay on imatinib treatment from patients ultimately needing alternative treatment. Among the identified proteins are TYRO3, a member of TAM family of receptor tyrosine kinases (RTKs), the S100A8, and MYC and all of which have been implicated in CML. Our findings indicate analyses of a panel of protein signatures is capable of objective prediction of molecular response and therapy choice for CML patients at diagnosis as ‘personalized-medicine-model’.