To switch or not to switch? A real-life experience using dexamethasone in combination with abiraterone

The recently published phase II prospective SWITCH trial evaluated whether patients with metastatic castration-resistant prostate cancer (mCRPC) treated with abiraterone acetate could benefit from a 'steroid switch' from prednisone to dexamethasone. A total of 26 patients, both chemonaive (14 patients) or pretreated with docetaxel (12 patients), with biochemical and/or limited radiological progression, were enrolled in this trial. Primary endpoint was prostate specific antigen (PSA) 30 defined as the proportion of patients with a PSA level decline 30% or more after 6 weeks of treatment with abiraterone acetate + dexamethasone. Secondary endpoints were: a PSA50 rate (defined as the proportion of patients with PSA decline of 50% or more after 12 weeks on abiraterone acetate + dexamethasone), biochemical and radiological progression-free survival (bPFS and rPFS, respectively), benefit from subsequent treatment and identification of biomarkers of response. Primary endpoint was reached in 46.2% of patients (12 patients), and two patients had an objective partial response on computed tomography scan. Median bPFS and rPFS were 5.3 months and 11.8 months. We present a case series of 11 patients who were consecutively treated with a steroid switch at our institution from January 2016 to August 2018 to investigate if this strategy could be used in a 'real-life' setting. We observed a PSA30 response in two patients (18%), median bPFS was 4.77 months (95% confidence interval [CI] 2.5-14.6) and median rPFS was 7.2 months (95% CI 3.8-15.5). Seven patients had a radiological stable disease as best response to steroid switch. Three patients were being still treated with abiraterone acetate + dexamethasone at data cut-off time. Our case series confirms that switching from prednisone to dexamethasone during abiraterone acetate treatment produces biochemical and radiological responses in both a predocetaxel and a postdocetaxel setting, providing a clinical benefit in mCRPC patients. However, to date, there is no clear indication as to which patient could benefit most from this kind of strategy

BRCA Mutations in Prostate Cancer: Prognostic and Predictive Implications

Despite chemotherapy and novel androgen-receptor signalling inhibitors (ARSi) have been approved during the last decades, metastatic castration-resistant prostate cancer (mCRPC) remains a lethal disease with poor clinical outcomes. Several studies found that germline or acquired DNA damage repair (DDR) defects affect a high percentage of mCRPC patients. Among DDR defects, BRCA mutations show relevant clinical implications. BRCA mutations are associated with adverse clinical features in primary tumors and with poor outcomes in patients with mCRPC. In addition, BRCA mutations predict good response to poly-ADP ribose polymerase (PARP) inhibitors, such as olaparib, rucaparib, and niraparib. However, concerns still remain on the role of extensive mutational testing in prostate cancer patients, given the implications for patients and for their progeny. The present comprehensive review attempts to provide an overview of BRCA mutations in prostate cancer, focusing on their prognostic and predictive roles

Multimodality Imaging of Sudden Cardiac Death and Acute Complications in Acute Coronary Syndrome

Sudden cardiac death (SCD) is a potentially fatal event usually caused by a cardiac arrhythmia, which is often the result of coronary artery disease (CAD). Up to 80% of patients suffering from SCD have concomitant CAD. Arrhythmic complications may occur in patients with acute coronary syndrome (ACS) before admission, during revascularization procedures, and in hospital intensive care monitoring. In addition, about 20% of patients who survive cardiac arrest develop a transmural myocardial infarction (MI). Prevention of ACS can be evaluated in selected patients using cardiac computed tomography angiography (CCTA), while diagnosis can be depicted using electrocardiography (ECG), and complications can be evaluated with cardiac magnetic resonance (CMR) and echocardiography. CCTA can evaluate plaque, burden of disease, stenosis, and adverse plaque characteristics, in patients with chest pain. ECG and echocardiography are the first-line tests for ACS and are affordable and useful for diagnosis. CMR can evaluate function and the presence of complications after ACS, such as development of ventricular thrombus and presence of myocardial tissue characterization abnormalities that can be the substrate of ventricular arrhythmias

Acute Delta Hepatitis in Italy spanning three decades (1991–2019): Evidence for the effectiveness of the hepatitis B vaccination campaign

Updated incidence data of acute Delta virus hepatitis (HDV) are lacking worldwide. Our aim was to evaluate incidence of and risk factors for acute HDV in Italy after the introduction of the compulsory vaccination against hepatitis B virus (HBV) in 1991. Data were obtained from the National Surveillance System of acute viral hepatitis (SEIEVA). Independent predictors of HDV were assessed by logistic-regression analysis. The incidence of acute HDV per 1-million population declined from 3.2 cases in 1987 to 0.04 in 2019, parallel to that of acute HBV per 100,000 from 10.0 to 0.39 cases during the same period. The median age of cases increased from 27 years in the decade 1991-1999 to 44 years in the decade 2010-2019 (p < .001). Over the same period, the male/female ratio decreased from 3.8 to 2.1, the proportion of coinfections increased from 55% to 75% (p = .003) and that of HBsAg positive acute hepatitis tested for by IgM anti-HDV linearly decreased from 50.1% to 34.1% (p < .001). People born abroad accounted for 24.6% of cases in 2004-2010 and 32.1% in 2011-2019. In the period 2010-2019, risky sexual behaviour (O.R. 4.2; 95%CI: 1.4-12.8) was the sole independent predictor of acute HDV; conversely intravenous drug use was no longer associated (O.R. 1.25; 95%CI: 0.15-10.22) with this. In conclusion, HBV vaccination was an effective measure to control acute HDV. Intravenous drug use is no longer an efficient mode of HDV spread. Testing for IgM-anti HDV is a grey area requiring alert. Acute HDV in foreigners should be monitored in the years to come

The Potential of Satellite Interferometry for Geohazard Assessment in Cultural Heritage Sites

[EN] A continuous monitoring system of ground deformation, based on radar images acquired by ESA (European Space Agency) Sentinel-1 constellation, is active over the Tuscany Region (Central Italy). The potential of repeat-pass satellite SAR (Synthetic Aperture Radar) interferometry has been exploited to investigate spatial patterns and temporal evolution of regional and local ground deformation that affect cultural heritage sites. With millions of measurement points, ground deformation maps for Tuscany Region provide information that can be exploited to scan wide areas and to flag ground instabilities. These areas become targets for detailed analysis with high resolution sensors (e.g., COSMO-SkyMed satellites of the Italian Space Agency) to create a virtual constellation, in which different satellite data sources are synergically used to create a more effective and robust Earth Observation system. The potential of a virtual constellation is presented and discussed through the case study of Pistoia, a city whose origins date back to the Etruscan civilization.The ground deformation monitoring system presented in this paper has been requested, founded and supported by the Regional government of Tuscany, under the agreement “Monitoring ground deformation in the Tuscany Region with satellite radar data”.Peer reviewe

Unsupervised detection of InSAR time series patterns based on PCA and K-means clustering

The need for implementing efficient value-adding tools able to optimise Earth Observation data usage, compels the scientific community to find innovative solutions for the downstream of Earth Observation information. In this paper we present an unsupervised and automated approach based on Principal Component Analysis (PCA) and K-means clustering to detect patterns of natural or anthropogenic ground deformation from Interferometric Synthetic Aperture Radar (InSAR) Time Series. For our proof-of-concept, we focus on the Valle d’Aosta region (Northwest Italy) where mass wasting processes frequently occurs, interacting with human activities and infrastructures. The large volumes of Sentinel-1 data produced allows for retrieving horizontal and vertical Time Series from multi-geometry data fusion of Line-of-Sight (LOS) InSAR measurements. The added benefit of combining ascending/descending InSAR data and interpolating displacements in time at different time steps is here explored prior to data dimensionality reduction and feature extraction through PCA. The retrieved principal components serve as a continuous solution for cluster membership indicators in the K-means clustering method, allowing to define spatially and temporally coherent displacement phenomena. The signal of the ground deformation clusters is then deconstructed into the underlying trend and seasonality components to enhance the interpretability of the classified satellite InSAR features. Using InSAR Time series data spanning 2014–2020, the proposed approach detects several slope movements and anthropogenic deformations with both linear and seasonal displacement behaviours. The results demonstrate the potential applicability of our transferable approach to the development of automated ground motion analysis systems

De novo Metastatic Breast Cancer Arising in Young Women: Review of the Current Evidence

Women with metastatic breast cancer remains a heterogeneous group of patients with different prognostic outcomes and therapeutic needs. Young women with de novo metastatic breast cancer (dnMBC) represent a peculiar population with respect to tumor biology, prognosis, clinical management and survivorship issues. Overall, these patients are able to attain long-term survival with a proper management of both primary tumor and distant metastases. On the other hand, they are also at higher risk of experiencing a deterioration in their quality of life (QoL) due to primary cancer-related side effects. Young women are also likely to harbor germline pathogenic variants in cancer predisposition genes which could affect treatment decisions and have a direct impact on the lives of patients’ relatives. The loco-regional management of the primary tumor represents another thorny subject, as the surgical approach has shown controversial effects on the survival and the QoL of these patients. This review aims to provide an update on these issues to better inform the clinical management of dnMBC in young women.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Update on the Management of Breast Cancer during Pregnancy

The diagnosis of breast cancer during pregnancy represents a challenging situation for the patient, her caregivers and physicians. Pregnancy adds complexity to oncological treatment planning, as many therapies can be potentially dangerous to the fetus. Therefore, a multidisciplinary approach is needed to offer a proper care for obtaining the best possible outcomes for the mother and the future child. Breast surgery is feasible throughout the pregnancy while radiotherapy should be postponed after delivery. Administration of chemotherapy is considered safe and can be given during the second and third trimesters, while it is contraindicated in the first trimester due to the high risk of fetal malformations. Endocrine therapy and targeted agents are not recommended during the whole pregnancy period; however, limited data are available on the use of the majority of new anticancer drugs in this context. The aim of the current review is to provide an update on the current state of art about the management of women diagnosed with breast cancer during pregnancy

Automated classification of A-DInSAR-based ground deformation by using random forest

Wide-area ground motion monitoring is nowadays achievable via advanced Differential Interferometry SAR (A-DInSAR) techniques which benefit from the availability of large sets of Copernicus Sentinel-1 images. However, it is of primary importance to implement automated solutions aimed at performing integrated analysis of large amounts of interferometric data. To effectively detect high-displacement areas and classify ground motion sources, here we explore the feasibility of a machine learning-based approach. This is achieved by applying the random forest (RF) technique to large-scale deformation maps spanning 2015–2018. Focusing on the northern part of Italy, we train the model to identify landslide, subsidence, and mining-related ground motion with which to construct a balanced training dataset. The presence of noisy signals and other sources of deformation is also tackled within the model construction. The proposed approach relies on the use of explanatory variables extracted from the A-DInSAR datasets and from freely accessible informative layers such as Digital Elevation Model (DEM), land cover maps, and geohazard inventories. In general, the model performance is very promising as we achieved an overall accuracy of 0.97, a true positive rate of 0.94 and an F1-Score of 0.93. The obtained outcomes demonstrate that such transferable and automated approach may constitute an asset for stakeholders in the framework of geohazards risk management