The Italian Version of the Borderline Personality Disorder Severity Index IV:Psychometric Properties, Clinical Usefulness, and Possible Diagnostic Implications

Borderline personality disorder (BPD) has a core embodied in affective and behavioral dysregulations, impulsivity, and relational disturbance. Clinical presentation might be heterogeneous due to a combination of different symptoms listed in the DSM-5. Clinical diagnosis and assessment of the severity of manifestations might be improved through the administration of structured interviews such as the Borderline Personality Disorder Severity Index, 4th edition (BPDSI-IV). The psychometric properties of the Italian version of the BPDSI-IV were examined for the first time in 248 patients affected by BPD and 113 patients affected by bipolar disorder, proving to be a valid and accurate instrument with good internal consistency and high accuracy. The Italian version also demonstrates significant validity in the discrimination between these clinical groups (p < .001)

Combination of baseline LDH, performance status and age as integrated algorithm to identify solid tumor patients with higher probability of response to anti PD-1 and PD-l1 monoclonal antibodies

Predictive biomarkers of response to immune-checkpoint inhibitors (ICIs) are an urgent clinical need. The aim of this study is to identify manageable parameters to use in clinical practice to select patients with higher probability of response to ICIs. Two-hundred-and-seventy-one consecutive metastatic solid tumor patients, treated from 2013 until 2017 with anti-Programmed death-ligand 1 (PD-L1)/programmed cell death protein 1 (PD-1) ICIs, were evaluated for baseline lactate dehydrogenase (LDH) serum level, performance status (PS), age, neutrophil-lymphocyte ratio, type of immunotherapy, number of metastatic sites, histology, and sex. A training and validation set were used to build and test models, respectively. The variables\u2019 effects were assessed through odds ratio estimates (OR) and area under the receive operating characteristic curves (AUC), from univariate and multivariate logistic regression models. A final multivariate model with LDH, age and PS showed significant ORs and an AUC of 0.771. Results were statistically validated and used to devise an Excel algorithm to calculate the patient\u2019s response probabilities. We implemented an interactive Excel algorithm based on three variables (baseline LDH serum level, age and PS) which is able to provide a higher performance in response prediction to ICIs compared with LDH alone. This tool could be used in a real-life setting to identify ICIs in responding patients

The Brief Negative Symptom Scale (BNSS): Independent validation in a large sample of Italian patients with schizophrenia

BACKGROUND: The Brief Negative Symptom Scale (BNSS) was developed to address the main limitations of the existing scales for the assessment of negative symptoms of schizophrenia. The initial validation of the scale by the group involved in its development demonstrated good convergent and discriminant validity, and a factor structure confirming the two domains of negative symptoms (reduced emotional/verbal expression and anhedonia/asociality/avolition). However, only relatively small samples of patients with schizophrenia were investigated. Further independent validation in large clinical samples might be instrumental to the broad diffusion of the scale in clinical research. METHODS: The present study aimed to examine the BNSS inter-rater reliability, convergent/discriminant validity and factor structure in a large Italian sample of outpatients with schizophrenia. RESULTS: Our results confirmed the excellent inter-rater reliability of the BNSS (the intraclass correlation coefficient ranged from 0.81 to 0.98 for individual items and was 0.98 for the total score). The convergent validity measures had r values from 0.62 to 0.77, while the divergent validity measures had r values from 0.20 to 0.28 in the main sample (n=912) and in a subsample without clinically significant levels of depression and extrapyramidal symptoms (n=496). The BNSS factor structure was supported in both groups. CONCLUSIONS: The study confirms that the BNSS is a promising measure for quantifying negative symptoms of schizophrenia in large multicenter clinical studies