Clinical Outcomes of Patients with Chronic Myeloid Leukemia and COVID-19 Infection-A Single Center Survey.

Background: Previous research has shown different effects of hematological malignancies on the outcome of patients with COVID-19 infection depending on the type of disease and the treatment received. This research was aimed at examining the clinical outcome of COVID-19 infection in positive patients with chronic myeloid leukemia treated with tyrosine kinase inhibitors. Methods: We collected retrospective information on chronic myeloid leukemia patients who were treated and monitored in our institution during the pandemic period. Within this cohort, we recorded COVID-19 positive symptomatic patients and analyzed their basic characteristics, symptoms, severity, and outcome. Results: In the study cohort when COVID-19 was diagnosed, 86.7% of patients were on first-generation tyrosine kinase inhibitors therapy-imatinib. At the time of infection, 70% of patients were in molecular remission, 23.4% in complete cytogenetic remission, and 3.3% in complete hematological response. Most patients had symptomatic disease. Within the analyzed group, 56.7% of patients had asymptomatic/mild COVID-19 infection, 23.3% of patients had moderate symptoms which did not require hospitalization, and 20% of patients had severe/critical symptoms that required admission to the intensive care unit. More than half of the patients interrupted treatment with tyrosine kinase inhibitors temporarily during COVID-19. There were no deaths due to COVID-19 infection. Conclusions: In compliance with other larger clinical studies, analysis of the clinical outcome of COVID-19 infection in patients with chronic myeloid leukemia on tyrosine kinase inhibitors therapy in this study showed that they do not have an increased risk for COVID-19 infection and that they have a mild course of the disease with recovery.

The significance of angiogenesis for predicting optimal therapeutic response in chronic myeloid leukaemia patients.

In this study the correlation and the prognostic value of the morphometric parameters of angiogenesis for optimal therapeutic response to tyrosine kinase inhibitor (TKI) therapy in patients with chronic myeloid leukaemia (CML), i.e. complete cytogenetic response (CCgR) and major molecular response (MMoR), were investigated. Microvascular density (MVD) and a number of different size- and shape-related morphometric parameters of microvessels of bone marrow biopsy from 40 CML patients and 20 controls were examined. Microvessels of bone marrow were examined by using immunohistochemical staining for CD34 and quantified in the region of the most intense vascularisation by using image analysis. CML patients had significantly higher angiogenesis parameters when compared with controls. A statistically significant correlation was found between some parameters of angiogenesis and evaluated CCgR and MMoR. For achievement of CCgR, lower values of MVD, minor axis, area, circularity, and roundness and higher value of aspect ratio, while for achievement of MMoR only lower values of MVD have been identified as positive prognostic factors. Besides confirming increased angiogenesis in CML patients, this study also demonstrated prognostic significance of the degree of angiogenesis for the clinical outcome and identified angiogenic predictive factors for achieving optimal response on TKIs therapy.

Impact of quality of response on survival outcomes among multiple myeloma patients treated with novel agents - a retrospective analysis.

BACKGROUND: In this era of target therapies, novel data on the correlation between response endpoints and survival outcomes in multiple myeloma have arisen. OBJECTIVE: To determine the impact of quality of response on clinical outcomes, using first-line treatment, and identify risk factors influencing progression-free survival (PFS) and overall survival (OS) among myeloma patients. DESIGN AND SETTING: Retrospective analysis on myeloma patients who were treated at the Clinic of Hematology and Clinical Immunology, University Clinical Centre, Nis, Serbia, over a four-year period. METHODS: A total of 108 newly diagnosed patients who received first-line therapy consisting of conventional chemotherapy or novel agent-based regimens were included in this analysis. RESULTS: The quality of response to first-line therapy for the whole cohort was classified as follows: complete response (CR) in 19%; very good partial response (VGPR) in 23%; partial response (PR) in 38%; and less than PR for the remaining patients. After a median follow-up of 25.4 months, the three-year PFS and OS for the entire study population were 47% and 70%, respectively. Achievement of CR was the main factor associated with significantly prolonged PFS and OS, in comparison with patients who reached VGPR and PR. Likewise, addition of the new drugs bortezomib and thalidomide to standard chemotherapy led to considerably extended PFS and OS, compared with conventional therapy alone. CONCLUSIONS: This analysis demonstrated that the quality of response after application of first-line treatment using novel agent-based regimens among multiple myeloma patients was a prognostic factor for PFS and OS, which are the most clinically relevant outcomes.

Generic Imatinib in Chronic Myeloid Leukemia Treatment: Long-Term Follow-up.

BACKGROUND: Similar to the application of other generic drugs, the use of generic imatinib in the treatment of chronic myeloid leukemia (CML) leads to significant cost savings, but it also raises issues related to efficacy, safety, and quality. This study assessed the long-term outcome of CML patients after administration of generic imatinib. PATIENTS AND METHODS: The cohort of 83 patients was divided into 2 groups depending on whether generic imatinib was applied in the front-line setting or after switching from original imatinib. The groups were compared regarding rates of optimal treatment response, adverse events, and survival. RESULTS: In the first group, at the time of switching, rates of complete cytogenetic response experienced, and major molecular response were 95% and 87.5% of patients in the front-line generic imatinib group and the group that switched from original to generic imatinib, respectively. After 24 months of treatment with generic imatinib, the rates of sustained, lost, and experienced major molecular response were 72.5%, 15%, and 12.5%, respectively. In the group treated with front-line generic imatinib at 6 months, 67.4% experienced complete cytogenetic response, while for major molecular response at 12 and 24 months, it was 58.1% and 69.8%, respectively. Estimated 5-year overall survival in the group treated with front-line generic imatinib was 86.1%, while 10-year overall survival in the group treated with second-line generic imatinib was 93.8%. CONCLUSION: Results of this study with long-term follow-up are further evidence that generic imatinib is at least noninferior to original imatinib regarding efficacy and survival, both when provided initially and as a subsequent replacement for original imatinib.

Impact of quality of response on survival outcomes among multiple myeloma patients treated with novel agents - a retrospective analysis

Abstract BACKGROUND: In this era of target therapies, novel data on the correlation between response endpoints and survival outcomes in multiple myeloma have arisen. OBJECTIVE: To determine the impact of quality of response on clinical outcomes, using first-line treatment, and identify risk factors influencing progression-free survival (PFS) and overall survival (OS) among myeloma patients. DESIGN AND SETTING: Retrospective analysis on myeloma patients who were treated at the Clinic of Hematology and Clinical Immunology, University Clinical Centre, Niš, Serbia, over a four-year period. METHODS: A total of 108 newly diagnosed patients who received first-line therapy consisting of conventional chemotherapy or novel agent-based regimens were included in this analysis. RESULTS: The quality of response to first-line therapy for the whole cohort was classified as follows: complete response (CR) in 19%; very good partial response (VGPR) in 23%; partial response (PR) in 38%; and less than PR for the remaining patients. After a median follow-up of 25.4 months, the three-year PFS and OS for the entire study population were 47% and 70%, respectively. Achievement of CR was the main factor associated with significantly prolonged PFS and OS, in comparison with patients who reached VGPR and PR. Likewise, addition of the new drugs bortezomib and thalidomide to standard chemotherapy led to considerably extended PFS and OS, compared with conventional therapy alone. CONCLUSIONS: This analysis demonstrated that the quality of response after application of first-line treatment using novel agent-based regimens among multiple myeloma patients was a prognostic factor for PFS and OS, which are the most clinically relevant outcomes.

Intelligent Flow Friction Estimation.

Nowadays, the Colebrook equation is used as a mostly accepted relation for the calculation of fluid flow friction factor. However, the Colebrook equation is implicit with respect to the friction factor (λ). In the present study, a noniterative approach using Artificial Neural Network (ANN) was developed to calculate the friction factor. To configure the ANN model, the input parameters of the Reynolds Number (Re) and the relative roughness of pipe (ε/D) were transformed to logarithmic scales. The 90,000 sets of data were fed to the ANN model involving three layers: input, hidden, and output layers with, 2, 50, and 1 neurons, respectively. This configuration was capable of predicting the values of friction factor in the Colebrook equation for any given values of the Reynolds number (Re) and the relative roughness (ε/D) ranging between 5000 and 10(8) and between 10(-7) and 0.1, respectively. The proposed ANN demonstrates the relative error up to 0.07% which had the high accuracy compared with the vast majority of the precise explicit approximations of the Colebrook equation.

Artificial neural networks based prediction of cerebral palsy in infants with central coordination disturbance.

BACKGROUND: In a previous study we demonstrated that heart variability parameters (HRV) could be helpful clinically as well as a prognostic tool in infants with central coordination disturbance (CCD). In recent years, outcome predictions using artificial neural networks (ANN) have been developed in many areas of health care research, but there are no published studies considered ANN models for prediction of cerebral palsy (CP) development. OBJECTIVE: To compare the results of an ANN analysis with results of regression analysis, using the same data set and the same clinical and HRV parameters. METHODS: The study included 35 infants with CCD and 37 healthy age and sex-matched controls. Time-domain HRV indices were analyzed from 24h electrocardiography recordings. Clinical parameters and selected time domain HRV parameters are used to predict CP by logistic regression, and then an ANN analysis was applied to the same data set. Input variables were age, gender, postural responses, heart rate parameters (minimum, maximum and average), and time domain parameters of HRV (SDNN, SDANN and RMSSD). For each of one the pairs of ANN and clinical predictors, the area under the receiver operating characteristic (ROC) curves with test accuracy parameters were calculated and compared. RESULTS: In the observed dataset, ANN model overall correctly classified all infants, compared with 86.11% correct classification for the logistic regression model, and compared with 67.65% and 77.14% for SDANN and SDNN respectively. CONCLUSIONS: ANN model, based on clinical and HRV data can predict development of CP in patients with CCD with accuracy greater than 90%. Our results strongly indicate that a well-validated ANN may have a role in the clinical prediction of CP in infants with CCD.

Artificial neural networks based early clinical prediction of mortality after spontaneous intracerebral hemorrhage.

Numerous outcome prediction models have been developed for mortality and functional outcome after spontaneous intracerebral haemorrhage (ICH). However, no outcome prediction model for ICH has considered the impact of care restriction. To develop and compare results of the artificial neural networks (ANN) and logistic regression (LR) models, based on initial clinical parameters, for prediction of mortality after spontaneous ICH. Analysis has been conducted on consecutive dataset of patients with spontaneous ICH, over 5-year period in tertiary care academic hospital. Patients older than 18 years were eligible for inclusion if they had been presented within 6 h from the start of symptoms and had evidence of spontaneous supratentorial ICH on initial brain computed tomography within 24 h. Initial clinical parameters have been used to develop LR and ANN prediction models for hospital mortality as outcome measure. Models have been accessed for discrimination and calibration abilities. We have analyzed 411 patients (199 males and 212 females) with spontaneous ICH, medically treated and not withdrawn from therapy, with average age of 67.35 years. From them, 256 (62.29%) patients died during hospital treatment and 155 (37.71%) patients survived. In the observed dataset, ANN model overall correctly classified outcome in 93.55% of patients, compared with 79.32% of correct classification for the LR model. Discrimination and calibration parameters indicate that both models show an adequate fit of expected and observed values, with superiority of ANN model. Our results favour the ANN model for prediction of mortality after spontaneous ICH. Further studies of the strengths and limitations of this method are needed with larger prospective samples.