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Povzetek: EGFR exon 20 (EGFR Ex20) insertion mutations in non-small cell lung cancer (NSCLC) are insensitive to traditional EGFR tyrosine kinase inhibitors (TKIs). Mobocertinib is the only approved TKI specifically designed to target EGFR Ex20. We performed an international, real-world safety and efficacy analysis on patients with EGFR Ex20-positive NSCLC enrolled in a mobocertinib early access program. We explored the mechanisms of resistance by analyzing postprogression biopsies, as well as cross-resistance to amivantamab. Data from 86 patients with a median age of 67 years and a median of two prior lines of treatment were analyzed. Treatment-related adverse events (TRAEs) occurred in 95% of patients. Grade ≥3 TRAEs were reported in 38% of patients and included diarrhea (22%) and rash (8%). In 17% of patients, therapy was permanently discontinued, and two patients died due to TRAEs. Women were seven times more likely to discontinue treatment than men. In the overall cohort, the objective response rate to mobocertinib was 34% (95% CI, 24–45). The response rate in treatment-naïve patients was 27% (95% CI, 8–58). The median progression-free and overall survival was 5 months (95% CI, 3.5–6.5) and 12 months (95% CI, 6.8–17.2), respectively. The intracranial response rate was limited (13%), and one-third of disease progression cases involved the brain. Mobocertinib also showed antitumor activity following EGFR Ex20-specific therapy and vice versa. Potential mechanisms of resistance to mobocertinib included amplifications in MET, PIK3CA, and NRAS. Mobocertinib demonstrated meaningful efficacy in a real-world setting but was associated with considerable gastrointestinal and cutaneous toxicity.
Ključne besede: medicina, non-small cell lung cancer, EGFR exon 20 inhibitors, mobocertinib, real-world data, exon 20 insertion
Objavljeno v DiRROS: 19.06.2024; Ogledov: 161; Prenosov: 102
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Povzetek: Despite numerous attempts to integrate dream research into a vast array of sci-entific disciplines, there appears to be no consensus on why and how we dream. This millennia-old universal human phenomenon appears to be too elusive to be thoroughly understood by a single scientific discipline and too complex and data--rich to be studied only theoretically. However, another dimension to dreams and dreaming could promise an integrative approach: the culture-historical compo-nent that merges with recent advances in artificial Intelligence. This paper briefly examines conceptual understandings of dreams before the dawn of modern science – specifically, the Native american, Mesopotamian, ancient Greek, and Hippocra-tic principles of dream practices and knowledge – in an attempt to understand the contemporary dream research field better and to outline future avenues for a data-driven approach while remaining grounded in its epistemological foundation.
Ključne besede: ancient dreaming, archetypes, artificial intelligence, dream data, cross-cultural dream analysis
Objavljeno v DiRROS: 13.05.2024; Ogledov: 214; Prenosov: 150
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Povzetek: Two approaches to clustering and blockmodeling of temporal networks are presented: the first is based on an adaptation of the clustering of symbolic data described by modal values and the second is based on clustering with relational constraints. Different options for describing a temporal block model are discussed.
Ključne besede: social networks, network analysis, blockmodeling, symbolic data analysis, clustering with relational constraints
Objavljeno v DiRROS: 08.04.2024; Ogledov: 287; Prenosov: 126
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Povzetek: The effects of data governance (as a means to maximize big data value creation in fire risk management) performance on fire risk was analyzed based on multi-source statistical data of 105 cities in China from 2016 to 2018. Specifically, data governance was first quantified with ten detailed indicators, which were then selected for explaining urban fire risk through correlation analysis. Next, the sample cities were clustered in terms of major socio-economic characteristics, and then the effects of data governance were examined by constructing multivariate regression models for each city cluster with ordinary least squares (OLS). The results showed that the constructed regression models produced good interpretation of fire risk in different types of cities, with coefficient of determination (R2) in each model exceeding 0.65. Among the indicators, the development of infrastructures (e.g. data collection devices and data analysis platforms), the level of data use, and the updating of fire risk related data were proved to produce significant effects on the reduction of fire frequency and fire consequence. Moreover, the organizational maturity of data governance was proved to be helpful in reducing fire frequency. For the cities with large population, the cross-department sharing of high-value data was found to be another important determinant of urban fire frequency. In comparison with existing statistical models which interpreted fire risk with general social factors (with the highest R2 = 0.60), these new regression models presented a better statistical performance (with the average R2 = 0.72). These findings are expected to provide decision support for the local governments of China and other jurisdictions to facilitate big data projects in improving fire risk management.
Ključne besede: urban fire risk, fire risk management, big data technologies, data governance, socio-economic factors, city-wide analysis
Objavljeno v DiRROS: 09.01.2024; Ogledov: 329; Prenosov: 114
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Povzetek: The analysis of the current state of fire statistics and data collection in Europe and other countries is needed to increase awareness of how fire incidents affect buildings and to support pan-European fire prevention and fire mitigation mea- sures. The terminology and data collected regarding fire incidents in buildings in the EU Member States were mapped to obtain meaningful datasets to determine common terminology, collection methodology, and data interpretation system. An extensive literature review showed that fire data collection systems have been instrumental in informing firefighting strategies, evidence-based planning, prevention, and educational programmes. Differences and similarities between fire data collection systems were also investigated. The amount and quality of the information in fire statistical recording systems appear to be influenced by the complexity and structure with which the data are collected. The analysis also examined the existing fire statistics in the EU Member States and a few other countries. Finally, a detailed investigation of the number of fires, fire deaths, and injuries from 2009 to 2018 in several countries was examined based on data from a report by CTIF. The trends showed differences attributable to the existing fire statistical practices in terms of terminology and data collection, and interpretation. Part II proposes a common terminology for selected fire statistical variables. The results provide relevant information regarding fire safety at the European level and should be used to guide the development of more uniform fire statistics across Europe.
Ključne besede: fire statistics, fire incidents, fire statistical variable, terminology, data collection, data interpretation
Objavljeno v DiRROS: 13.11.2023; Ogledov: 605; Prenosov: 189
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