Race/ethnicity and the risk of childhood leukaemia: a case-control study in California.

BackgroundWe conducted a large registry-based study in California to investigate the association between race/ethnicity and childhood leukaemia focusing on two subtypes: acute lymphoblastic leukaemia (ALL) and acute myeloid leukaemia (AML).MethodsWe obtained information on 5788 cases and 5788 controls by linking California cancer and birth registries. We evaluated relative risk of childhood leukaemia by race and ethnicity of the child and their parents using conditional logistic regression, with adjustment for potential confounders.ResultsCompared with Whites, Black children had lower risk of ALL (OR=0.54, 95% CI 0.45 to 0.66) as well as children of Black/Asian parents (OR=0.31, 95% CI 0.10 to 0.94). Asian race was associated with increased risk of AML with OR=1.643, 95% CI 1.10 to 2.46 for Asian vs Whites; and OR=1.67, 95% CI 1.04 to 2.70 for Asian/Asian vs White/White. Hispanic ethnicity was associated with increased risk of ALL (OR=1.37, 95% CI 1.22 to 1.52). A gradient in risk of ALL was observed while comparing Hispanic children with both parents Hispanic, one parent Hispanic and non-Hispanic children (p Value for trend <0.0001). The highest risk of ALL was observed for children with a combination of Hispanic ethnicity and White race compared with non-Hispanic whites (OR=1.27, 95% CI 1.12 to 1.44). The lowest risk was observed for non-Hispanic blacks (OR=0.46, 95% CI 0.36 to 0.60). Associations for total childhood leukaemia were similar to ALL.ConclusionsOur results confirm that there are ethnic and racial differences in the incidence of childhood leukaemia. These differences indicate that some genetic and/or environmental/cultural factors are involved in aetiology of childhood leukaemia

Fuzzy Inspired Case based Reasoning for Hematology Malignancies Classification

Conventional approaches for collecting and reporting hematological data as well as diagnosing hematologic malignancies such as leukemia, anemia, e.t.c are based on subjective professional physician personal opinions or experiences which are influenced by human error, dependent on human-to-human judgments, time consuming processes and the blood results are non-reproducible. In the light of those human limitations identified, an automatic or semi-automatic classification and corrective method is required because it reduces the load on human observers and accuracy is not affected due to fatigue. Case-Based Reasoning (CBR) as a multi-disciplinary subject that focuses on the reuse of past experiences or cases to proffer solution to new cases was adopted and combined with the power of Fuzzy logic to design a software model that will effectively mine hematology data. This study aim at helping the medical practitioners to diagnose and provide corrective treatment to both normal patients and patients with hematology disorder at the early stage which can reduce the number of deaths. This aim is achievable by developing an intelligent expert system based on fuzzy logic and case-based reasoning for classification of hematology malignancy

Case-based retrieval framework for gene expression data

© the authors, publisher and licensee Libertas academica Limited. Background: The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process.Methods: This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. Results: The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children’s Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. Conclusion: The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps

A case-based reasoning framework for prediction of stroke

© Springer Nature Singapore Pte Ltd. 2018. Case-based reasoning (CBR) has been a popular method in health care sector from the last two decades. It is used for analysis, prediction, diagnosis and recommending treatment for patients. This research purposes a conceptual CBR framework for stroke disease prediction that uses previous case-based knowledge. The outcomes of this approach not only assist in stroke disease decision-making, but also will be very useful for prevention and early treatment of patients

Selinexor-Based Triplet Regimens in Patients With Multiple Myeloma Previously Treated With Anti-CD38 Monoclonal Antibodies

High-risk; Oral selective inhibitor of nuclear export; Relapsed/refractoryAlto riesgo; Inhibidor selectivo oral de la exportación nuclear; Recaída/refractarioAlt risc; Inhibidor selectiu oral de l'exportació nuclear; Recaiguda/refractariBackground The increasing use of anti-CD38 monoclonal antibodies (αCD38 mAbs) for newly diagnosed or early relapsed multiple myeloma (MM), especially in non-transplant eligible patients, may lead to more patients developing αCD38 mAb-refractory disease earlier in the treatment course with fewer treatment options. Patients and methods We analyzed the efficacy and safety of selinexor-based triplets (selinexor+dexamethasone [Sd] plus pomalidomide [SPd, n = 23], bortezomib [SVd, n = 16] or carfilzomib (SKd, n = 23]) in a subset of STOMP (NCT02343042) and BOSTON (NCT03110562) study patients treated previously with αCD38 mAbs. Results Sixty-two patients (median 4 prior therapies, range 1 to 11, 90.3% refractory to αCD38 mAb) were included. Overall response rates (ORR) in the SPd, SVd and SKd cohorts were 52.2%, 56.3%, and 65.2%, respectively. Overall response rate was 47.4% among patients who had MM refractory to the third drug reintroduced in the Sd-based triplet. Median progression-free survival in the SPd, SVd, and SKd cohorts was 8.7, 6.7, and 15.0 months, respectively, and median overall survival was 9.6, 16.9, and 33.0 months, respectively. Median time to discontinuation in the SPd, SVd, and SKd cohorts was 4.4, 5.9, and 10.6 months, respectively. The most common hematological adverse events were thrombocytopenia, anemia, and neutropenia. Nausea, fatigue, and diarrhea were primarily grade 1/2. Adverse events were generally manageable with standard supportive care and dose modifications. Conclusion Selinexor-based regimens may offer effective and well-tolerated therapy to patients with relapsed and/or refractory MM who had disease previously exposed or refractory to αCD38 mAb therapy and could help address the unmet clinical need in these high-risk patients

Combining carfilzomib and panobinostat to treat relapsed/refractory multiple myeloma: results of a Multiple Myeloma Research Consortium Phase I Study

Key points CarPan is a highly active, steroid-sparing regimen, effective in both bortezomib-sensitive and refractory patients.The safety profile of CarPan, particularly thrombocytopenia and gastrointestinal adverse events, compares favorably with that of panobinostat and bortezomib

ANMM4CBR: a case-based reasoning method for gene expression data classification

<p>Abstract</p> <p>Background</p> <p>Accurate classification of microarray data is critical for successful clinical diagnosis and treatment. The "curse of dimensionality" problem and noise in the data, however, undermines the performance of many algorithms.</p> <p>Method</p> <p>In order to obtain a robust classifier, a novel Additive Nonparametric Margin Maximum for Case-Based Reasoning (ANMM4CBR) method is proposed in this article. ANMM4CBR employs a case-based reasoning (CBR) method for classification. CBR is a suitable paradigm for microarray analysis, where the rules that define the domain knowledge are difficult to obtain because usually only a small number of training samples are available. Moreover, in order to select the most informative genes, we propose to perform feature selection via additively optimizing a nonparametric margin maximum criterion, which is defined based on gene pre-selection and sample clustering. Our feature selection method is very robust to noise in the data.</p> <p>Results</p> <p>The effectiveness of our method is demonstrated on both simulated and real data sets. We show that the ANMM4CBR method performs better than some state-of-the-art methods such as support vector machine (SVM) and <it>k </it>nearest neighbor (<it>k</it>NN), especially when the data contains a high level of noise.</p> <p>Availability</p> <p>The source code is attached as an additional file of this paper.</p

A randomized phase III study of carfilzomib vs low-dose corticosteroids with optional cyclophosphamide in relapsed and refractory multiple myeloma (FOCUS)

This randomized, phase III, open-label, multicenter study compared carfilzomib monotherapy against low-dose corticosteroids and optional cyclophosphamide in relapsed and refractory multiple myeloma (RRMM). Relapsed and refractory multiple myeloma patients were randomized (1:1) to receive carfilzomib (10-min intravenous infusion; 20 mg/m(2) on days 1 and 2 of cycle 1; 27 mg/m(2) thereafter) or a control regimen of low-dose corticosteroids (84 mg of dexamethasone or equivalent corticosteroid) with optional cyclophosphamide (1400 mg) for 28-day cycles. The primary endpoint was overall survival (OS). Three-hundred and fifteen patients were randomized to carfilzomib (n=157) or control (n=158). Both groups had a median of five prior regimens. In the control group, 95% of patients received cyclophosphamide. Median OS was 10.2 (95% confidence interval (CI) 8.4-14.4) vs 10.0 months (95% CI 7.7-12.0) with carfilzomib vs control (hazard ratio=0.975; 95% CI 0.760-1.249; P=0.4172). Progression-free survival was similar between groups; overall response rate was higher with carfilzomib (19.1 vs 11.4%). The most common grade ⩾3 adverse events were anemia (25.5 vs 30.7%), thrombocytopenia (24.2 vs 22.2%) and neutropenia (7.6 vs 12.4%) with carfilzomib vs control. Median OS for single-agent carfilzomib was similar to that for an active doublet control regimen in heavily pretreated RRMM patients