Revistas
Revista:
JOURNAL OF UROLOGY
ISSN:
0022-5347
Año:
2023
Vol.:
209
N°:
1
Págs.:
261 - 270
Revista:
CLINICAL AND TRANSLATIONAL ONCOLOGY
ISSN:
1699-048X
Año:
2023
Vol.:
25
N°:
5
Págs.:
1268 - 1276
Introduction: A rapid deploy of unexpected early impact of the COVID pandemic in Spain was described in 2020. Oncology practice was revised to facilitate decision-making regarding multimodal therapy for prevalent cancer types amenable to multidisciplinary treatment in which the radiotherapy component searched more efficient options in the setting of the COVID-19 pandemic, minimizing the risks to patients whilst aiming to guarantee cancer outcomes.
Methods: A novel Proton Beam Therapy (PBT), Unit activity was analyzed in the period of March 2020 to March 2021. Institutional urgent, strict and mandatory clinical care standards for early diagnosis and treatment of COVID-19 infection were stablished in the hospital following national health-authorities' recommendations. The temporary trends of patients care and research projects proposals were registered.
Results: 3 out of 14 members of the professional staff involved in the PBR intra-hospital process had a positive test for COVID infection. Also, 4 out of 100 patients had positive tests before initiating PBT, and 7 out of 100 developed positive tests along the weekly mandatory special checkup performed during PBT to all patients. An update of clinical performance at the PBT Unit at CUN Madrid in the initial 500 patients treated with PBT in the period from March 2020 to November 2022 registers a distribution of 131 (26%) pediatric patients, 63 (12%) head and neck cancer and central nervous system neoplasms and 123 (24%) re-irradiation indications. In November 2022, the activity reached a plateau in terms of patients under treatment and the impact of COVID pandemic became sporadic and controlled by minor medical actions. At present, the clinical data are consistent with an academic practice prospectively (NCT05151952). Research projects and scientific production was adapted to the pandemic evolution and its influence upon professional time availability. Seven research projects based in public funding were activated in this period and preliminary data on molecular imaging guided proton therapy in brain tumors and post-irradiation patterns of blood biomarkers are reported.
Conclusions: Hospital-based PBT in European academic institutions was impacted by COVID-19 pandemic, although clinical and research activities were developed and sustained. In the post-pandemic era, the benefits of online learning will shape the future of proton therapy education.
Autores:
Farina, B. (Autor de correspondencia); Ramos-Guerra, A. D.; Bermejo-Peláez, D.; et al.
Revista:
JOURNAL OF TRANSLATIONAL MEDICINE
ISSN:
1479-5876
Año:
2023
Vol.:
21
N°:
1
Págs.:
174
BackgroundIdentifying predictive non-invasive biomarkers of immunotherapy response is crucial to avoid premature treatment interruptions or ineffective prolongation. Our aim was to develop a non-invasive biomarker for predicting immunotherapy clinical durable benefit, based on the integration of radiomics and clinical data monitored through early anti-PD-1/PD-L1 monoclonal antibodies treatment in patients with advanced non-small cell lung cancer (NSCLC).MethodsIn this study, 264 patients with pathologically confirmed stage IV NSCLC treated with immunotherapy were retrospectively collected from two institutions. The cohort was randomly divided into a training (n = 221) and an independent test set (n = 43), ensuring the balanced availability of baseline and follow-up data for each patient. Clinical data corresponding to the start of treatment was retrieved from electronic patient records, and blood test variables after the first and third cycles of immunotherapy were also collected. Additionally, traditional radiomics and deep-radiomics features were extracted from the primary tumors of the computed tomography (CT) scans before treatment and during patient follow-up. Random Forest was used to implementing baseline and longitudinal models using clinical and radiomics data separately, and then an ensemble model was built integrating both sources of information.ResultsThe integration of longitudinal clinical and deep-radiomics data significantly improved clinical durable benefit prediction at 6 and 9 months after treatment in the independent test set, achieving an area under the receiver operating characteristic curve of 0.824 (95% CI: [0.658,0.953]) and 0.753 (95% CI: [0.549,0.931]). The Kaplan-Meier survival analysis showed that, for both endpoints, the signatures significantly stratified high- and low-risk patients (p-value< 0.05) and were significantly correlated with progression-free survival (PFS6 model: C-index 0.723, p-value = 0.004; PFS9 model: C-index 0.685, p-value = 0.030) and overall survival (PFS6 models: C-index 0.768, p-value = 0.002; PFS9 model: C-index 0.736, p-value = 0.023).ConclusionsIntegrating multidimensional and longitudinal data improved clinical durable benefit prediction to immunotherapy treatment of advanced non-small cell lung cancer patients. The selection of effective treatment and the appropriate evaluation of clinical benefit are important for better managing cancer patients with prolonged survival and preserving quality of life.
Revista:
JOURNAL OF UROLOGY
ISSN:
0022-5347
Año:
2023
Vol.:
209
N°:
1
Págs.:
270
Revista:
EUROPEAN JOURNAL OF VASCULAR AND ENDOVASCULAR SURGERY
ISSN:
1078-5884
Año:
2022
Vol.:
63
N°:
1
Págs.:
163 - 164
Autores:
Bermejo-Peláez, D.; San José Estépar, R.; Fernández-Velilla, M.; et al.
Revista:
SCIENTIFIC REPORTS
ISSN:
2045-2322
Año:
2022
Vol.:
12
N°:
1
Págs.:
9387
The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performance with respect to human reader severity assessment and whole lung radiomics. We propose a deep learning based scheme to automatically segment the different lesion subtypes in nonenhanced CT scans. The automatic lesion quantification was used to predict clinical outcomes. The proposed technique has been independently tested in a multicentric cohort of 103 patients, retrospectively collected between March and July of 2020. Segmentation of lesion subtypes was evaluated using both overlapping (Dice) and distance-based (Hausdorff and average surface) metrics, while the proposed system to predict clinically relevant outcomes was assessed using the area under the curve (AUC). Additionally, other metrics including sensitivity, specificity, positive predictive value and negative predictive value were estimated. 95% confidence intervals were properly calculated. The agreement between the automatic estimate of parenchymal damage (%) and the radiologists' severity scoring was strong, with a Spearman correlation coefficient (R) of 0.83. The automatic quantification of lesion subtypes was able to predict patient mortality, admission to the Intensive Care Units (ICU) and need for mechanical ventilation with an AUC of 0.87, 0.73 and 0.68 respectively. The proposed artificial intelligence system enabled a better prediction of those clinically relevant outcomes when compared to the radiologists' interpretation and to whole lung radiomics. In conclusion, deep learning lesion subtyping in COVID-19 pneumonia from noncontrast chest CT enables quantitative assessment of disease severity and better prediction of clinical outcomes with respect to whole lung radiomics or radiologists' severity score.
Autores:
Timmerman, D. (Autor de correspondencia); Planchamp, F.; Bourne, T.; et al.
Revista:
ULTRASOUND IN OBSTETRICS AND GYNECOLOGY
ISSN:
0960-7692
Año:
2021
Vol.:
58
N°:
1
Págs.:
148 - 168
The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumors, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements.
Autores:
Timmerman, D. (Autor de correspondencia); Planchamp, F.; Bourne, T.; et al.
Revista:
FACTS, VIEWS & VISION IN OBGYN
ISSN:
2032-0418
Año:
2021
Vol.:
13
N°:
2
Págs.:
107 - 130
The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumours, including imaging techniques, biomarkers and prediction models.
ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumours and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised.
Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements.
This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumours and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.
Autores:
Carabaño Aguado, I. (Autor de correspondencia); La Orden Izquierdo, E.; Pelayo Baeza, F. J.; et al.
Revista:
PEDIATRIA ATENCION PRIMARIA
ISSN:
1139-7632
Año:
2012
Vol.:
13
N°:
52
Págs.:
595-600
La retención urinaria aguda en niños está poco descrita en la bibliografía médica. No hay un claro predominio de afectación por sexo, y su mediana de edad es cuatro años. Puede ser primaria (si aparece en relación con problema nefrourológicos) o secundaria a diversos procesos (cirugía, inmovilidad, trastornos neurológicos crónicos, retraso mental, consumo de drogas, anticolinérgicos, estreñimiento). Clínicamente, puede recordar a una invaginación intestinal, y cursar con dolor abdominal intenso e irritabilidad. Su tratamiento consiste en la evacuación de la orina mediante sondaje. Conviene hacer esta por etapas, si el volumen de la vejiga es muy alto, para evitar la hematuria ex vacuo.
Revista:
PEDIATRIA ATENCION PRIMARIA
ISSN:
1139-7632
Año:
2012
Vol.:
14
N°:
56
Págs.:
289-291