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BACKGROUND: Understanding stakeholders' perception of cure in prostate cancer (PC) is essential to preparing for effective communication about emerging treatments with curative intent. This study used artificial intelligence (AI) for landscape review and linguistic analysis of definition, context and value of cure among stakeholders in PC. MATERIALS AND METHODS: Subject-matter experts (SMEs) selected cure-related key words using Elicit, a semantic literature search engine, and extracted hits containing the key words from Medline, Sermo and Overton, representing academic researchers, health care providers (HCPs) and policymakers, respectively. NetBase Quid, a social media analytics and natural language processing tool, was used to carry out key word searches in social media (representing the general public). NetBase Quid analysed linguistics of key word-specific hit sets for key word count, geolocation and sentiments. SMEs qualitatively summarised key word-specific insights. Contextual terms frequently occurring with key words were identified and quantified. RESULTS: SMEs identified seven key words applicable to PC (number of acquired hits) across four platforms: Cure (12429), Survivor (6063), Remission (1904), Survivorship (1179), Curative intent (432), No evidence of disease (381) and Complete remission (83). Most commonly used key words were Cure by the general public and HCPs (11815 and 224 hits), Survivorship by academic researchers and Survivor by policymakers (378 hits each). All stakeholders discussed Cure and cure-related key words primarily in early-stage PC and associated them with positive sentiments. All stakeholders defined cure differently but communicated about it in relation to disease measurements (e.g. prostate-specific antigen) or surgery. Stakeholders preferred different terms when discussing cure in PC: Cure (academic researchers), Cure rates (HCPs), Potential cure and Survivor/Survivorship (policymakers) and Cure and Survivor (general public). CONCLUSION: This human-led, AI-assisted large-scale qualitative language-based research revealed that cure was commonly discussed by academic researchers, HCPs, policymakers and the general public, especially in early-stage PC. Stakeholders defined and contextualised cure in their communications differently and associated it with positive value.
Asunto(s)
Inteligencia Artificial , Neoplasias de la Próstata , Medios de Comunicación Sociales , Humanos , Masculino , Neoplasias de la Próstata/terapia , Lingüística/métodos , Política de Salud , Percepción , Procesamiento de Lenguaje NaturalRESUMEN
PURPOSE: The purpose of this study was to analyze the therapeutic strategies and estimate the health care resource consumption in patients with psoriatic arthritis (PsA). PATIENTS AND METHODS: An observational retrospective cohort analysis of administrative databases of six Italian Local Health Units was performed. Patients ≥18 years with a hospitalization discharge diagnosis of PsA (International Classification of Diseases, Ninth Revision code: 696.0) or exemption code (045.696.0) for PsA from January 1, 2010 to December 31, 2015 (inclusion period), with at least one prescription of any therapy used for PsA were included. The index date (ID) was the first date matching with at least one of the inclusion criteria during the inclusion period. All patients were followed up after the ID until the end of data availability. Baseline C-reactive protein (CRP) levels (±6 months in relation to the ID) were also analyzed. RESULTS: A total of 2,408 (prevalence 0.83 per 1,000) patients with PsA (male 52%; median age 54 years) were included in the study; patients were already treated for PsA in 42.4% of cases. At 1 year of follow-up, 73% of the patients received one systemic drug, while 22% of patients received two systemic drugs; in addition, our results show an increase in the number of add-on or switches in a longer follow-up period. The utilization of biologic agents was higher among patients with previous PsA treatment, showing a progression of the pathology. Overall, a medium/high level of CRP at baseline was observed among more than half of the overall sample, with slight changes across subgroups in analysis. The average health care costs were 1,966.4 and 13,914 per year for patients treated with conventional systemic therapy and biological agents, respectively. CONCLUSION: A better knowledge of prescription therapeutic scheme and economic burden of PsA could stimulate the rational development of health programs aimed at potentiating services for its management.
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BACKGROUND: Daclatasvir (DCV) combinated with Sofosbuvir (SOF) has shown good efficacy and safety profile for HCV patients. The aim was to evaluate the cost-effectiveness of DCV/SOF regimen versus HCV alternative treatments for patients who failed to achieve the SVR12 after a first DAA treatment from Italian perspective (PITER cohort). METHODS: A Markov model of HCV chronically infected patients was used to develop two scenarios: 1) DCV+ SOF versus Ledipasvir (LDV)+ SOF in Genotype (Gt)1 and Gt4; 2) DCV+ SOF versus no retreatment option in Gt1, Gt3, and Gt4. The percentage of patients who failed the first line with SOF/Simeprevir/Ribavirin (RBV) or SOF/RBV and were retreated or not according to evidences from PITER cohort, were used to populate the model. HCV resources consumption and SVR rates were quantified using PITER data. Transition probabilities and utility rates were derived from the literature. The outcomes were expressed in terms of Quality adjusted life years (QALYs). Probabilistic sensitivity analysis (PSA) was performed considering a cost-effectiveness threshold of 30,000/QALY. RESULTS: In the base-case analysis, DCV+ SOF represents a cost-effectiveness therapy with ICERs lower than the threshold. The PSA showed robust results, ICERs remain below the threshold in 94% and 99% simulations in Scenario 1 and 2, respectively.