Low-risk polycythemia vera treated with phlebotomies: clinical characteristics, hematologic control and complications in 453 patients from the Spanish Registry of Polycythemia Vera

Myelofibrosis; Phlebotomies; ThrombosisMielofibrosi; Flebotomies; TrombosiMielofibrosis; Flebotomías; TrombosisHematological control, incidence of complications, and need for cytoreduction were studied in 453 patients with low-risk polycythemia vera (PV) treated with phlebotomies alone. Median hematocrit value decreased from 54% at diagnosis to 45% at 12 months, and adequate hematocrit control over time ( 60 years, and microvascular symptoms constituted the main indications for starting cytoreduction. Median duration without initiating cytoreduction was significantly longer in patients younger than 50 years (< 0.0001). The incidence rate of thrombosis under phlebotomies alone was 0.8% per year and the estimated probability of thrombosis at 10 years was 8.5%. The probability of arterial thrombosis was significantly higher in patients with arterial hypertension whereas there was a trend to higher risk of venous thrombosis in cases with high JAK2V617F allele burden. Rates of major bleeding and second primary neoplasm were low. With a median follow-up of 9 years, survival probability at 10 years was 97%, whereas the probability of myelofibrosis at 10 and 20 years was 7% and 20%, respectively. Progression to acute myeloid leukemia was documented in 3 cases (1%). Current management of low-risk PV patients is associated with low rate of thrombosis and long survival. New treatment strategies are needed for improving hematological control and, in the long term, reducing progression to myelofibrosis.This work was supported by PI18/01472, PI18/00205, and PI21/00231 from the Instituto de Salud Carlos III (ISCIII), through the Plan Estatal de Investigación Científica y Técnica y de Innovación. GEMFIN received a grant from Novartis for the development of the Spanish Registry of Polycythemia Vera and for conducting the present project

Real-world analysis of main clinical outcomes in patients with polycythemia vera treated with ruxolitinib or best available therapy after developing resistance/intolerance to hydroxyurea

Hemorrhage; Polycythemia vera; RuxolitinibHemorràgia; Policitèmia vera; RuxolitinibHemorragia; Policitemia vera; RuxolitinibBackground Ruxolitinib is approved for patients with polycythemia vera (PV) who are resistant/intolerant to hydroxyurea, but its impact on preventing thrombosis or disease-progression is unknown. Methods A retrospective, real-world analysis was performed on the outcomes of 377 patients with resistance/intolerance to hydroxyurea from the Spanish Registry of Polycythemia Vera according to subsequent treatment with ruxolitinib (n = 105) or the best available therapy (BAT; n = 272). Survival probabilities and rates of thrombosis, hemorrhage, acute myeloid leukemia, myelofibrosis, and second primary cancers were calculated according to treatment. To minimize biases in treatment allocation, all results were adjusted by a propensity score for receiving ruxolitinib or BAT. Results Patients receiving ruxolitinib had a significantly lower rate of arterial thrombosis than those on BAT (0.4% vs 2.3% per year; P = .03), and this persisted as a trend after adjustment for the propensity to have received the drug (incidence rate ratio, 0.18; 95% confidence interval, 0.02-1.3; P = .09). There were no significant differences in the rates of venous thrombosis (0.8% and 1.1% for ruxolitinib and BAT, respectively; P = .7) and major bleeding (0.8% and 0.9%, respectively; P = .9). Ruxolitinib exposure was not associated with a higher rate of second primary cancers, including all types of neoplasia, noncutaneous cancers, and nonmelanoma skin cancers. After a median follow-up of 3.5 years, there were no differences in survival or progression to acute leukemia or myelofibrosis between the 2 groups. Conclusions The results suggest that ruxolitinib treatment for PV patients with resistance/intolerance to hydroxyurea may reduce the incidence of arterial thrombosis.This work was supported by the Instituto de Salud Carlos III through a National Plan for Scientific and Technical Research and Innovation Innovación (PI18/01472, PI18/00205, and PI21/00231). The Spanish Group of Myeloproliferative Neoplasms (GEMFIN) received a grant from Novartis for developing the Spanish Registry of Polycythemia Vera and for conducting the current project

Applying data mining to software development projects : a case study

One of the main challenges that the project managers have during the building process of a software development project (SDP) is to optimise the values of the parameters that measure the viability of the final process. The accomplishment of this task, something that was not easy at the beginning, was helped with the appearance of dynamic models and simulation environments. The application of data mining techniques to the managing of Software Development Projects (SDP) is not an uncommon phenomenon, as in any other productive process that generates information in the way of input data and output variables. In this paper, we present and analyze the results obtained from a tool, developed by the authors, based on a Knowledge Discovery in Databases (KDD) technique. One of the most important contributions of these techniques to the software engineering field is the possibility of improving the management process of an SDP. The purpose is to provide accurate decision rules in order to help the project manager to take decisions during the development

Visualization techniques of management rules for software development projects

The application of data mining techniques to the managing of software development projects (SDP) is not an uncommon phenomenon, as in any other productive process that generates information in the way of input data and output variables. In this paper, a set of tools developed by the authors, that generate, in a visual way, managing rules suitable to cover minimum goals in a SDP are presented. Although the techniques used are able to generate quantitative rules, giving numeric values suitable for these goals, the visual representation of these rules helps their easy and quick understanding by a manager of a SDP. The application to a database generated from the simulation of a project allows to establish a profitable comparison and to demonstrate the validity of the techniques

R e troalimentación biológica y relajación en pacientes con enfermedad renal crónica terminal en tratamiento de hemodiálisis

El objetivo de este estudio fue evaluar la utilidad de la retroalimentación biológica y la relajación para reducir ansiedad y estrés en pacientes que se encontraban en tratamiento médico de hemodiálisis por enfermedad renal crónico terminal (ERCT) utilizando estrategias derivadas del modelo cognitivo conductual. Participaron ocho pacientes del servicio de Nefrología del Hospital Juárez de México a los que se les aplicaron el inventario de ansiedad IDARE y una escala subjetiva de estrés antes y después de realizar el programa. El diseño fue de caso único con línea base retrospectiva y replicación intrasujeto. Se trabajó con cada paciente durante ocho sesiones en las que se les instruyó sobre el propósito de la retroalimentación y recibieron instrucciones para relajarse ofreciéndoles de manera visual sus cifras de presión arterial y frecuencia cardiaca. Cada paciente disminuyó sus cifras de presión arterial sistólica y diastólica, siendo estas reducciones estadísticamente significativas. Se compararon los puntajes de las escalas de ansiedad y estrés antes y después del tratamiento existiendo reducción en los puntajes de ambas para cada sujeto, siendo estas reducciones estadísticamente significativas, concluyendo que el uso de relajación combinada con retroalimentación biológica resultó eficaz.Palabras clave: Ansiedad, Estrés, Relajación, Retroalimentación biológica (biofeedback), Enfermedad Renal Crónica

Innovaemprende

El proyecto INNOVAEMPRENDE se ha desarrollado en el contexto del Máster en Biotecnología Industrial y Ambiental, dentro de la asignatura del módulo fundamental “Organización y Seguridad Industrial” con el objetivo general de contribuir a la formación de los alumnos del Máster en la cultura del emprendimiento, favoreciendo la conciencia del valor del conocimiento dentro del ámbito de la biotecnología, sector en crecimiento que, en el contexto global de una economía cada vez más fundamentada en la I+D+i, ha demostrado su importancia e impacto económico, siendo uno de los nuevos yacimientos de riqueza económica y de empleo

Evaluación de la respuesta inmune en lenguado senegalés conferida por una vacuna inactivada frente a Betanodavirus

La necrosis nerviosa viral es una enfermedad que afecta a peces cultivados en todo el mundo. Su agente etiológico es el virus de la necrosis nerviosa, género Betanodavirus, familia Nodaviridae, que presenta un genoma compuesto por dos segmentos de RNA monocatenario. Los betanodavirus se clasifican en cuatro especies, Striped Jack-, Tiger puffer-, Redspotted grouper- y Barfin flonder nervous necrosis virus (SJNNV, TPNNV, RGNNV y BFNNV, respectivamente). En el sur de Europa se han descrito recombinantes de los segmentos genómicos de las especies SJNNV y RGNNV como agentes causantes de epizootías en lenguado senegalés y dorada. El control de esta enfermedad es de gran importancia para la acuicultura europea y la vacunación es una de las estrategias más prometedoras. Sin embargo, solo existen vacunas comercializadas contra la especie RGNNV las cuales no protegen frente a los aislados recombinantes, por lo que se ha desarrollado una vacuna inactivada utilizando el aislado recombinante SpSsIAusc160.03 que produce una moderada protección frente a la infección vírica en lenguado (Valero et al., 2021). El objetivo de este estudio es evaluar la capacidad de dicha vacuna de inducir una respuesta inmune eficaz en lenguado (Solea senegalensis). Se tomaron muestras de cerebro y riñón cefálico de lenguados vacunados y sin vacunar a 2, 3 y 7 días post-vacunación (dpv), analizándose la expresión de 106 inmunogenes mediante la plataforma OpenArray® (Gémez et al., 2020). Se detectó una respuesta inmune temprana en muestras de riñón, expresándose diferencialmente 39 y 29 genes a 2 y 3 dpv, respectivamente. Esta modulación fue significativamente menor a 7 dpv, con solo 3 genes expresados diferencialmente (DEG). En muestras de cerebro, tejido diana de la infección, se observó una menor modulación génica, detectándose expresión diferencial exclusivamente a 2 y 3 dpv (5 y 12 DEG, respectivamente). Financiación: Proyecto RTI2018-094687-B-C21/C22 del MICIU cofinanciado por FEDER.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Riesgo quirúrgico tras resección pulmonar anatómica en cirugía torácica. Modelo predictivo a partir de una base de datos nacional multicéntrica

Introduction: the aim of this study was to develop a surgical risk prediction model in patients undergoing anatomic lung resections from the registry of the Spanish Video-Assisted Thoracic Surgery Group (GEVATS). Methods: data were collected from 3,533 patients undergoing anatomic lung resection for any diagnosis between December 20, 2016 and March 20, 2018. We defined a combined outcome variable: death or Clavien Dindo grade IV complication at 90 days after surgery. Univariate and multivariate analyses were performed by logistic regression. Internal validation of the model was performed using resampling techniques. Results: the incidence of the outcome variable was 4.29% (95% CI 3.6-4.9). The variables remaining in the final logistic model were: age, sex, previous lung cancer resection, dyspnea (mMRC), right pneumonectomy, and ppo DLCO. The performance parameters of the model adjusted by resampling were: C-statistic 0.712 (95% CI 0.648-0.750), Brier score 0.042 and bootstrap shrinkage 0.854. Conclusions: the risk prediction model obtained from the GEVATS database is a simple, valid, and reliable model that is a useful tool for establishing the risk of a patient undergoing anatomic lung resection

Machine Learning Improves Risk Stratification in Myelofibrosis: An Analysis of the Spanish Registry of Myelofibrosis

Myelofibrosis (MF) is a myeloproliferative neoplasm (MPN) with heterogeneous clinical course. Allogeneic hematopoietic cell transplantation remains the only curative therapy, but its morbidity and mortality require careful candidate selection. Therefore, accurate disease risk prognostication is critical for treatment decision-making. We obtained registry data from patients diagnosed with MF in 60 Spanish institutions (N = 1386). These were randomly divided into a training set (80%) and a test set (20%). A machine learning (ML) technique (random forest) was used to model overall survival (OS) and leukemia-free survival (LFS) in the training set, and the results were validated in the test set. We derived the AIPSS-MF (Artificial Intelligence Prognostic Scoring System for Myelofibrosis) model, which was based on 8 clinical variables at diagnosis and achieved high accuracy in predicting OS (training set c-index, 0.750; test set c-index, 0.744) and LFS (training set c-index, 0.697; test set c-index, 0.703). No improvement was obtained with the inclusion of MPN driver mutations in the model. We were unable to adequately assess the potential benefit of including adverse cytogenetics or high-risk mutations due to the lack of these data in many patients. AIPSS-MF was superior to the IPSS regardless of MF subtype and age range and outperformed the MYSEC-PM in patients with secondary MF. In conclusion, we have developed a prediction model based exclusively on clinical variables that provides individualized prognostic estimates in patients with primary and secondary MF. The use of AIPSS-MF in combination with predictive models that incorporate genetic information may improve disease risk stratification