57 research outputs found
Estudio de los Síndromes Mielodisplásicos en la población gallega: análisis descriptivo y pronóstico
Los principales objetivos de la presente tesis doctoral son tres: describir la
epidemiología de los Síndromes Mielodisplásicos (SMD) en la población gallega a estudio,
validar y comparar el nuevo índice pronóstico IPSS-R frente al estándar IPSS, utilizado
actualmente sobre nuestra población, y analizar la capacidad de predicción de nuevos factores
pronósticos (LDH, transfusiones previas, ferritina, índice de comorbilidades) incorporándolos a
este nuevo IPSS-R.
A partir de la base de datos de estudios citogenéticos de la Fundación Pública Galega
de Medicina Xenómica seleccionamos los pacientes diagnosticados de SMD según criterios de
la clasificación FAB, OMS 2001 u OMS 2008, entre enero de 2007 y diciembre de 2011 de
SMD. Los pacientes procedían de todos Centros Hospitalarios de la CCAA excepto del
CHUAC y POVISA por no disponer de estos datos. Cumplieron criterios de inclusión en el
estudio 339 pacientes. El seguimiento se realizó a través del programa de gestión clínica del
SERGAS (IANUS) o en la historia clínica física en cada centro hospitalario. El periodo de
seguimiento mínimo de los pacientes vivos incluidos en el estudio fue de un año (rango 2 - 2148
días).
Inicialmente describimos las variables epidemiológicas de los SMD en nuestra
población a estudio. Nuestros resultados muestran una población más envejecida, con menor
incidencia y misma distribución por sexo respecto a las grandes poblaciones de SMD de la
literatura. Nuestra población se distribuye en subgrupos de diagnóstico según la clasificación
OMS 2001 y 2008 de forma similar a las grandes series publicadas.
Posteriormente describimos las variables que forman el índice pronóstico para la
supervivencia y el riesgo de transformación a leucemia mieloblástica aguda más ampliamente
utilizado, el IPSS, y tratamos de validar su reciente propuesta revisada, el IPSS-R en nuestra
población. Comparamos dichas variables con las descritas en las grandes series de pacientes con
SMD de la literatura, observando similitud con las mismas, permitiéndonos realizar la
validación del IPSS-R en nuestra muestra.
Con estos datos clasificamos a nuestros pacientes según los grupos de riesgo de uno y
otro índice, y analizamos la capacidad de predecir la supervivencia y el riesgo de evolución a
Leucemia Aguda Mieloblástica (LMA). Posteriormente observamos la redistribución de los
pacientes incluídos en los subgrupos del antiguo índice en nuevo índice revisado. los resultados
obtenidos de la reclasificación, aplicando el IPSS-R evidencia una mayor capacidad de predecir
la supervivencia de estos pacientes que el IPSS. Cada uno de los grupos del IPSS es
redistribuído con el IPSS-R en grupos de riesgo más ajustados a la supervivencia real de los
pacientes. Este hecho es más evidente en el grupo intermedio-1 del IPSS.
Por último, añadimos nuevas variables al índice revisado (IPSS-R), tratando de mejorar
su capacidad predictiva de la supervivencia. al añadir las dos nuevas variables estadísticamente
significativas por nosotros propuestas (índice de comorbilidades y transfusiones previas) al
IPSS-R, observamos que la capacidad de este nuevo índice, para predecir la supervivencia, se ve
notablemente mejorada.
La aplicación del nuevo índice IPSS-R a nuestra población gallega a estudio, también
mustra una mayor capacidad de predecir el riesgo de transformación a Leucemia Mieloblástica
Aguda
Time to Treatment Prediction in Chronic Lymphocytic Leukemia Based on New Transcriptional Patterns
Chronic lymphocytic leukemia (CLL) is the most frequent lymphoproliferative syndrome in
western countries. CLL evolution is frequently indolent, and treatment is mostly reserved
for those patients with signs or symptoms of disease progression. In this work, we used
RNA sequencing data from the International Cancer Genome Consortium CLL cohort
to determine new gene expression patterns that correlate with clinical evolution.We
determined that a 290-gene expression signature, in addition to immunoglobulin heavy
chain variable region (IGHV) mutation status, stratifies patients into four groups with
notably different time to first treatment. This finding was confirmed in an independent
cohort. Similarly, we present a machine learning algorithm that predicts the need for
treatment within the first 5 years following diagnosis using expression data from 2,198
genes. This predictor achieved 90% precision and 89% accuracy when classifying
independent CLL cases. Our findings indicate that CLL progression risk largely correlates
with particular transcriptomic patterns and paves the way for the identification of high-risk
patients who might benefit from prompt therapy following diagnosis.S
The association of germline variants with chronic lymphocytic leukemia outcome suggests the implication of novel genes and pathways in clinical evolution
Background
Chronic Lymphocytic Leukemia (CLL) is the most frequent lymphoproliferative disorder in western countries and is characterized by a remarkable clinical heterogeneity. During the last decade, multiple genomic studies have identified a myriad of somatic events driving CLL proliferation and aggressivity. Nevertheless, and despite the mounting evidence of inherited risk for CLL development, the existence of germline variants associated with clinical outcomes has not been addressed in depth.
Methods
Exome sequencing data from control leukocytes of CLL patients involved in the International Cancer Genome Consortium (ICGC) was used for genotyping. Cox regression was used to detect variants associated with clinical outcomes. Gene and pathways level associations were also calculated.
Results
Single nucleotide polymorphisms in PPP4R2 and MAP3K4 were associated with earlier treatment need. A gene-level analysis evidenced a significant association of RIPK3 with both treatment need and survival. Furthermore, germline variability in pathways such as apoptosis, cell-cycle, pentose phosphate, GNα13 and Nitric oxide was associated with overall survival.
Conclusion
Our results support the existence of inherited conditionants of CLL evolution and points towards genes and pathways that may results useful as biomarkers of disease outcome. More research is needed to validate these findings.S
Measurement of the cosmic ray spectrum above eV using inclined events detected with the Pierre Auger Observatory
A measurement of the cosmic-ray spectrum for energies exceeding
eV is presented, which is based on the analysis of showers
with zenith angles greater than detected with the Pierre Auger
Observatory between 1 January 2004 and 31 December 2013. The measured spectrum
confirms a flux suppression at the highest energies. Above
eV, the "ankle", the flux can be described by a power law with
index followed by
a smooth suppression region. For the energy () at which the
spectral flux has fallen to one-half of its extrapolated value in the absence
of suppression, we find
eV.Comment: Replaced with published version. Added journal reference and DO
Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory
The Auger Engineering Radio Array (AERA) is part of the Pierre Auger
Observatory and is used to detect the radio emission of cosmic-ray air showers.
These observations are compared to the data of the surface detector stations of
the Observatory, which provide well-calibrated information on the cosmic-ray
energies and arrival directions. The response of the radio stations in the 30
to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of
the incoming electric field. For the latter, the energy deposit per area is
determined from the radio pulses at each observer position and is interpolated
using a two-dimensional function that takes into account signal asymmetries due
to interference between the geomagnetic and charge-excess emission components.
The spatial integral over the signal distribution gives a direct measurement of
the energy transferred from the primary cosmic ray into radio emission in the
AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air
shower arriving perpendicularly to the geomagnetic field. This radiation energy
-- corrected for geometrical effects -- is used as a cosmic-ray energy
estimator. Performing an absolute energy calibration against the
surface-detector information, we observe that this radio-energy estimator
scales quadratically with the cosmic-ray energy as expected for coherent
emission. We find an energy resolution of the radio reconstruction of 22% for
the data set and 17% for a high-quality subset containing only events with at
least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO
Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy
We measure the energy emitted by extensive air showers in the form of radio
emission in the frequency range from 30 to 80 MHz. Exploiting the accurate
energy scale of the Pierre Auger Observatory, we obtain a radiation energy of
15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV
arriving perpendicularly to a geomagnetic field of 0.24 G, scaling
quadratically with the cosmic-ray energy. A comparison with predictions from
state-of-the-art first-principle calculations shows agreement with our
measurement. The radiation energy provides direct access to the calorimetric
energy in the electromagnetic cascade of extensive air showers. Comparison with
our result thus allows the direct calibration of any cosmic-ray radio detector
against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI.
Supplemental material in the ancillary file
Correction : Chaparro et al. Incidence, Clinical Characteristics and Management of Inflammatory Bowel Disease in Spain: Large-Scale Epidemiological Study. J. Clin. Med. 2021, 10, 2885
The authors wish to make the following corrections to this paper [...]
Incidence, Clinical Characteristics and Management of Inflammatory Bowel Disease in Spain : Large-Scale Epidemiological Study
(1) Aims: To assess the incidence of inflammatory bowel disease (IBD) in Spain, to describe the main epidemiological and clinical characteristics at diagnosis and the evolution of the disease, and to explore the use of drug treatments. (2) Methods: Prospective, population-based nationwide registry. Adult patients diagnosed with IBD-Crohn's disease (CD), ulcerative colitis (UC) or IBD unclassified (IBD-U)-during 2017 in Spain were included and were followed-up for 1 year. (3) Results: We identified 3611 incident cases of IBD diagnosed during 2017 in 108 hospitals covering over 22 million inhabitants. The overall incidence (cases/100,000 person-years) was 16 for IBD, 7.5 for CD, 8 for UC, and 0.5 for IBD-U; 53% of patients were male and median age was 43 years (interquartile range = 31-56 years). During a median 12-month follow-up, 34% of patients were treated with systemic steroids, 25% with immunomodulators, 15% with biologics and 5.6% underwent surgery. The percentage of patients under these treatments was significantly higher in CD than UC and IBD-U. Use of systemic steroids and biologics was significantly higher in hospitals with high resources. In total, 28% of patients were hospitalized (35% CD and 22% UC patients, p < 0.01). (4) Conclusion: The incidence of IBD in Spain is rather high and similar to that reported in Northern Europe. IBD patients require substantial therapeutic resources, which are greater in CD and in hospitals with high resources, and much higher than previously reported. One third of patients are hospitalized in the first year after diagnosis and a relevant proportion undergo surgery
Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis
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