Publications by authors named "Sara Urru"
Background: Over the last few years, many efforts have been made to leverage historical information in clinical trials. Incorporating historical data into current trials allows for a more efficient design, smaller studies, or shorter duration and may potentially increase the relative amount of information on efficacy and safety. Despite these advantages, it is crucial to select external data sources appropriately to avoid introducing potential bias into the new study.
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- The study explores the effects of internet-based mindfulness interventions (e-MBIs) on reducing anxiety, depression, and stress in cancer patients, specifically those with prostate or breast cancer.
- It assesses how the variety and frequency of mindfulness practices, along with factors like personality traits and sociodemographic characteristics, relate to symptom improvements.
- Results indicate that participants who practiced mindfulness more diversely and consistently showed significant symptom reduction, with male, married, and educated individuals more likely to engage in these practices.
Article Synopsis
- The Sinclair Compassion Questionnaire (SCQ) was developed to assess patients' experiences of compassion in palliative care, specifically for those with terminal illnesses.
- The validation study of the Italian version, SCQit, confirmed its reliability and identified factors such as hospital setting and religious faith that influence compassion experiences among patients.
- This validated tool can be utilized in clinical practice and research to enhance compassionate care for terminally ill cancer patients and improve healthcare professional training.
Information extraction from medical case reports using OpenAI InstructGPT.
Comput Methods Programs Biomed
October 2024
Background And Objective: Researchers commonly use automated solutions such as Natural Language Processing (NLP) systems to extract clinical information from large volumes of unstructured data. However, clinical text's poor semantic structure and domain-specific vocabulary can make it challenging to develop a one-size-fits-all solution. Large Language Models (LLMs), such as OpenAI's Generative Pre-Trained Transformer 3 (GPT-3), offer a promising solution for capturing and standardizing unstructured clinical information.
View Article and Find Full Text PDFBackground: The prognostic impact of catheter ablation (CA) of atrial fibrillation (AF) in hypertrophic cardiomyopathy (HCM) patients has not yet been satisfactorily elucidated.
Objectives: The aim of the study was to assess the impact of CA of AF on clinical outcomes in a large cohort of HCM patients.
Methods: In this retrospective multicenter study, 555 HCM patients with AF were enrolled, 140 undergoing CA and 415 receiving medical therapy.
Introduction: Differentiated vulvar intraepithelial neoplasia (dVIN) is a high-risk preinvasive vulvar lesion and precursor of human papillomavirus-independent vulvar squamous cell carcinoma (VSCC). Due to its rarity, literature data on its malignant potential are scant. The aim of the study is to assess the risk of developing VSCC in patients surgically treated for dVIN not associated with VSCC (solitary dVIN) and the risk of VSCC recurrence in patients treated for dVIN associated with VSCC (dVIN-VSCC) at first diagnosis.
View Article and Find Full Text PDFR-CHOP standard chemotherapy is successful in about 60% of diffuse large B-cell lymphoma (DLBCL) patients. Unresponsive patients have a poor prognosis, and predictive biomarkers of response to R-CHOP are lacking. We conducted the first prospective GWAS study aimed at exploring constitutional biomarkers predictive of R-CHOP efficacy and toxicity.
View Article and Find Full Text PDFContext: Because of the rarity of adrenocortical cancer (ACC), only a few population-based studies are available, and they reported limited details in the characterization of patients and their treatment.
Objective: To describe in a nationwide cohort the presentation of patients with ACC, treatment strategies, and potential prognostic factors.
Methods: Retrospective analysis of 512 patients with ACC, diagnosed in 12 referral centers in Italy from January 1990 to June 2018.
Objective: In the past 2 years, the number of scientific publications has grown exponentially. The COVID-19 outbreak hugely contributed to this dramatic increase in the volume of published research. Currently, text mining of the volume of SARS-CoV-2 and COVID-19 publications is limited to the first months of the outbreak.
View Article and Find Full Text PDFBackground: Breast cancer (BC) is the most frequently diagnosed cancer among women. Numerous studies explored cell-free circulating microRNAs as diagnostic biomarkers of BC. As inconsistent and rarely intersecting microRNA panels have been reported thus far, we aim to evaluate the overall diagnostic performance as well as the sources of heterogeneity between studies.
View Article and Find Full Text PDFBackground: In a randomized controlled trial (RCT) with binary outcome the estimate of the marginal treatment effect can be biased by prognostic baseline covariates adjustment. Methods that target the marginal odds ratio, allowing for improved precision and power, have been developed.
Methods: The performance of different estimators for the treatment effect in the frequentist (targeted maximum likelihood estimator, inverse-probability-of-treatment weighting, parametric G-computation, and the semiparametric locally efficient estimator) and Bayesian (model averaging), adjustment for confounding, and generalized Bayesian causal effect estimation frameworks are assessed and compared in a simulation study under different scenarios.