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The development and implementation of health technology assessment (HTA) methods is a process needed for improving HTA quality, in response to emerging novel health technologies and the variety in HTA practices. However, some general problems that negatively affected method development or implementation have occurred over time, such as the lack of a clear overview of the needs from HTA stakeholders and lack of expertise on the HTA methods. To address the problems related to HTA method development or implementation, in Chapter 2, we first provided a conceptual framework to facilitate a general understanding of the process of innovating HTA methods and the stakeholder roles involved. Also, in Chapter 3, we explored the applicability of this conceptual framework in three cases of innovating quantitative methods in various disease fields (such as diabetes and head and neck cancer), and improved the framework applicability by designing a roadmap. In addition to providing a conceptual framework, in Chapter 4-8, we investigated specific research questions related to development or implementation of qualitative and quantitative HTA methods using real-world data (RWD). More specifically, in Chapter 4,5, and 6, we focused on methods used for assessing quality of studies using RWD; in Chapter 7 and 8, we focused on methods used for merging randomized-controlled trials and RWD in (network) meta-analyses. This thesis showed that, the use of the framework may lead to increased awareness that not only researchers, but also all HTA stakeholders (e.g. patients, clinician and health technology developers) have the potential to contribute to the development or implementation of HTA methods. Also, in this thesis, we have offered some potential solutions to the challenges of HTA method innovation. For example, given the lack of skills to implement a method in the HTA context, we recommend developers to inform practitioners and beneficiaries of the contexts where using a method is approp

INTRODUCTION: Brodalumab is a human interleukin-17 receptor A antagonist indicated for the treatment of moderate-to-severe plaque psoriasis in adult patients who are candidates for systemic therapy or phototherapy and have failed to respond or have lost response to other systemic therapies. Although the US prescribing information for brodalumab includes a boxed warning regarding suicidal ideation and behavior, no causal association has been demonstrated. Here, we summarize 5 years of pharmacovigilance data, from August 15, 2017, through August 14, 2022, reported to Ortho Dermatologics by US patients and healthcare providers. METHODS: Prevalence of the most common adverse events (AEs) listed in the brodalumab package insert (incidence ≥ 1%) and AEs of special interest are described. Brodalumab exposure was estimated as the time from the first to last prescription-dispensing authorization dates. Data were collected from 4744 patients in the USA, with an estimated exposure of 5815 patient-years. RESULTS: Over 5 years, 11 cases of adjudicated major adverse cardiovascular events were reported (0.23 events/100 patients), a rate lower than that experienced by patients in the international Psoriasis Longitudinal Assessment and Registry. There were 106 serious infections. No serious fungal infections were reported. There were 40 confirmed and 2 suspected COVID-19 cases, with no new COVID-19-related deaths. Of 49 reported malignancies among 42 patients, 3 were deemed possibly related to brodalumab. No completed suicides and no new suicidal attempts were reported. CONCLUSION: Five-year pharmacovigilance data are consistent with the established safety profile reported in long-term clinical trials and previous pharmacovigilance reports, with no new safety signals.

Process mining (PM) is a novel technique that allows to derive insights about business processes based on data already available in today’s information systems. PM offers a wide variety of possibilities, such as as is process discovery, or the automatic comparison of as-is and to-be processes. Especially in manufacturing, the individuality of manufacturing processes further prevents the identification of possible usages. However, for the success of PM it is essential to work on the right use cases. While numerous solutions on the detailing and assessment of PM use cases have been defined, none deals with the structured identification of possible use cases. In this paper, we develop a method to systematically identify PM use cases in manufacturing organizations in collaboration with two-real world organizations. We apply the final method to one organization. The method is two-fold: first, we present a workshop method that guides practitioners through the ideation and concretization of PM use cases. We show that manufacturing organizations are best off by posing questions about their process. Consequently, our second contribution is a template of possible questions to answer, drawing from typical process improvement initiatives in manufacturing, such as lean management. Our contribution especially helps organizations with little experience in PM, and can serve as good workshop concept for kicking off new PM initiatives.

This study introduces a novel systematic approach to address the challenge of labeled data scarcity for fault detection and diagnosis (FDD) in District Heating (DH) systems. To replicate real-world DH fault scenarios, we have created a controlled laboratory emulation of a generic DH substation integrated with a climate chamber. Furthermore, we present an FDD pipeline using an isolation forest and a one-class support vector machine for fault detection alongside a random forest and a support vector machine for fault diagnosis. Our research analyzed the impact of data sampling frequencies on the FDD models, revealing that shorter intervals, such as 1-min and 5-min, significantly improve FDD performance. We provide detailed information on six scenarios, including normal operation, a minor valve leak, a valve leak, a stuck valve, a high heat curve, and a temperature sensor deviation. For each scenario, we present their signature, quantifying their unique behavior and providing deeper insights into the operational implications. The signatures suggest that, while variable, faults have a consistent pattern seen in the generic DH substation. While this work contributes directly to the DH field, our methodology also extends its applicability to a broader context where labeled data is scarce. © 2024 The Authors

Quality inspections are essential in almost all manufacturing processes and can be undertaken using an automatic vision system. The main challenge when using AI-based vision systems is gathering enough training data for the AI to perform well. This study investigates the use of simulationgenerated data to address this challenge. A real-world industrial case study evaluates the feasibility of simulationgenerated images for training an AI to be used in an industrial vision system for quality inspection. Results from the study show that the approach has potential, but that simulationgenerated images cannot be used solely. However, real-world images must be mixed into the training data set to achieve satisfactory results., © 2024, EUROSIS-ETI. All rights reserved.

Several real-world applications introduce derivativefree optimization problems, called variable dimension problems, where the problem's dimension is not known in advance. Despite their importance, no unified framework for developing, comparing, and benchmarking variable dimension problems exists. The robot arm controlling problem is a variable dimension problem where the number of joints to optimize defines the problem's dimension. For a holistic study of global optimization methods, we studied 14 representative methods from 4 different categories, i.e., (i) local search optimization techniques with random restarts, (ii) state-of-the-art DIRECT-type methods, (iii) established Evolutionary Computation approaches, and (iv) state-of-the-art Evolutionary Computation approaches. To investigate the effect of the problem's dimensionality on the solution we generated 20 instances of various combinations among the number of predefined and open decision variables, and we performed experiments for various computational budgets. The results attest that the robot arm controlling problem provides a proper benchmark for variable dimensions. Furthermore, methods in-corporating local search techniques have dominant performance for higher dimensionalities of the problem, while state-of-the-art EC methods dominate in the lower dimensionalities.

Despite the advancements in artificial lighting technology, such as LEDs, a gap persists between expected and actual performance outcomes, attributed to conventional reliability evaluation methods that inadequately mirror real-world operational conditions. This study explores the crucial roles of failure analysis and fault diagnosis in improving lighting source reliability. It reveals a focus on LED lighting failure analysis based on test data, highlighting a disconnect from operational fault diagnosis. By detailing fault types and diagnostic tools, the study proposes a practical fault diagnosis framework. This framework aims to enhance lighting reliability by incorporating diagnostic insights back into the design and manufacturing stages, creating a closed-loop system between failure analysis and fault diagnosis. This approach bridges the gap between theory and practice, advancing lighting reliability in public libraries. However, the insights into failure analysis and fault diagnosis can be applied to other scenarios.

Purpose: The aim of this multi-center, retrospective/prospective cohort observational study was to evaluate outcomes in routine clinical practice of first-line chemo-immunotherapy with cis/carboplatin, pemetrexed and pembrolizumab in patients with advanced non-squamous non-small cell lung cancer (NSCLC) in 33 Italian centers. Methods: The outcome measure was to evaluate overall survival (OS) in a real-world patient population. Secondary endpoints were: progression-free survival (PFS), objective response rate (ORR), duration of response (DoR) and incidence of treatment-related adverse events (AEs). Results: 1068 patients were enrolled at the time of data cut-off (January 31st, 2023), and 812 (76.0%) belonged to the retrospective cohort. Median age was 66 years (27−85), ECOG PS was ≥ 2 in 91 (8.6%) patients; 254 (23.8%) patients had brain metastases at baseline; 38 (3.6%) patients had tumor with PD-L1 expression ≥ 50%. After a median follow-up of 17.0 months (95% CI, 16.1–17.9), median OS was 16.1 months (95% CI, 14.4–18.8) and PFS was 9.9 months (95% CI, 8.8–11.2). Median DoR (n = 493) was 14.7 months (95% CI, 13.6–17.1). ORR was 43.4% (95% CI, 40.4–46.4). Any-grade AEs occurred in 636 (59.6%) patients and grade ≥ 3 in 253 (23.7%) patients. Most common grade ≥ 3 AEs were neutropenia (6.3%) and anemia (6.3%). Conclusions: First-line chemo-immunotherapy was effective and tolerable in this large, real-world Italian study of patients with advanced non-squamous NSCLC. Our results were in line with the KEYNOTE-189 registration study, also considering the low number of PD-L1 ≥ 50% patients included in our study.

Biological drugs have dramatically changed the approach to treating moderate-to-severe plaque psoriasis, achieving excellent skin clearance and safety outcomes. However, the management of difficult-to-treat areas (e.g., scalp, palms/soles, nails, and genitalia) still represents a challenge in psoriasis treatment. Data in the literature on difficult-to-treat sites are limited and, frequently, no specific analysis is performed during clinical trials. We conducted a 52-week, retrospective study to evaluate the effectiveness of ixekizumab in 120 patients with moderate-to-severe plaque psoriasis of at least one difficult-to-treat area (scalp, palmoplantar surfaces, nails, and genitalia). Ninety-nine patients had scalp psoriasis, 35 had involvement of the palms or soles, 27 were affected by genital psoriasis, and 22 patients reported involvement of the nails. After 1 year of treatment, 96% of patients with scalp involvement, 95.6% of patients with palmoplantar psoriasis, 95.2% of patients with genital psoriasis, and 85% of patients with nail involvement achieved a site-specific Physician's Global Assessment of 0 or 1 (clear or almost clear). No serious adverse events were observed during the study. Our study supports the effectiveness of ixekizumab in plaque psoriasis involving difficult-to-treat sites.

Aim: To investigate changes in treatment patterns in extensive-stage small-cell lung cancer (ES-SCLC) in France, Germany, Italy, Spain and the UK (EU5) between 2018 and 2021. Methods: Cross-sectional data from an oncology database were analyzed retrospectively. Results: Of 5832 eligible patients, 88.4% had stage IV disease at diagnosis. Among patients receiving first-line treatment, 91.8% (1079 /1176) received the platinum-etoposide (PE) combination in 2018 which decreased to 42.3% (509/1203) by 2021. Usage of the PE-atezolizumab combination increased from 0 to 41.2% during the same timeframe. Topotecan monotherapy remained the most widely used second-line treatment regardless of patients' platinum sensitivity. Conclusion: The first-line standard of care for ES-SCLC has evolved in EU5 with the PE-atezolizumab/durvalumab combination gradually superseding PE usage.

Background: Australia has one of the highest rates of asbestos-associated diseases. Mesothelioma remains an area of unmet need with a 5-year overall survival of 10%. First-line immunotherapy with ipilimumab and nivolumab is now a standard of care for unresectable pleural mesothelioma following the CheckMate 743 trial, with supportive data from the later line single-arm MAPS2 trial. RIOMeso evaluates survival and toxicity of this regimen in real-world practice. Methods: Demographic and clinicopathologic data of Australian patients treated with ipilimumab and nivolumab in first- and subsequent-line settings for pleural mesothelioma were collected retrospectively. Survival was reported using the Kaplan-Meier method and compared between subgroups with the log-rank test. Toxicity was investigator assessed using Common Terminology Criteria for Adverse Events version 5.0. Results: A total of 119 patients were identified from 11 centers. The median age was 72 years, 83% were male, 92% had Eastern Cooperative Oncology Group less than or equal to 1, 50% were past or current smokers, and 78% had known asbestos exposure. In addition, 50% were epithelioid, 19% sarcomatoid, 14% biphasic, and 17% unavailable. Ipilimumab and nivolumab were used first line in 75% of patients. Median overall survival (mOS) was 14.5 months (95% confidence interval [CI]: 13.0–not reached [NR]) for the entire cohort. For patients treated first line, mOS was 14.5 months (95% CI: 12.5–NR) and in second- or later-line patients was 15.4 months (95% CI: 11.2–NR). There was no statistically significant difference in mOS for epithelioid patients compared with nonepithelioid (19.1 mo [95% CI: 15.4–NR] versus 13.0 mo [95% CI: 9.7–NR], respectively, p = 0.064). Furthermore, 24% of the patients had a Common Terminology Criteria for Adverse Events grade greater than or equal to 3 adverse events, including three treatment-related deaths. Colitis was the most frequent adverse event. Conclusions: Combination immunothe

Purpose: The TRITRIAL study assessed the effects of beclometasone dipropionate/formoterol fumarate/glycopyrronium (BDP/FF/G) fixed combination in patients with chronic obstructive pulmonary disease (COPD) in a real-world setting, focusing on patient's experience and perspective through the use of patients reported outcomes. Patients and methods: TRITRIAL was a multicenter, prospective, observational study conducted on patients with moderate-severe COPD treated with BDP/FF/G fixed therapy for 12 months. The main objective was to evaluate the impact of BDP/FF/G on health status through the COPD Assessment Test (CAT) score. Additional assessments included adherence and satisfaction, measured by the TAI-10/12 questionnaire and a specifically designed eight-item questionnaire, quality of life through the EQ-5D-5L test, sleep quality through the COPD and Asthma Sleep Impact Scale (CASIS), as well as safety and disease-related outcomes. Results: Data from 655 patients were analyzed in the study. The mean total CAT score significantly improved (from 22.8 at baseline to 18.1 at 6 months and 16.5 at 12 months; p < 0.0001), as well as all the eight CAT sub-items, which decreased on average by 0.5-0.9 points during the study. Adherence and usability of the inhaler also improved during the study, with a decrease in poor compliance (from 30.1% to 18.3%) and an increase in good compliance (from 51.8% to 58.3%) according to the TAI score. Patients also benefited from significantly improved quality of life (EQ Index from 0.70 to 0.80; EQ-5D VAS score from 55.1 to 63.1) and sleep quality (CASIS score from 41.1 to 31.8). Finally, patients reported a significant reduction in exacerbation during the study. Conclusion: TRITRIAL showed that the BDP/FF/G fixed combination is effective and safe in patients with moderate-severe COPD and poorly controlled disease, improving patients' HRQoL, sleep quality, adherence and inhaler usability and reducing COPD symptoms and the risk of exacerbati

Manufacturers install and rely on a large number of sensors to operate and control their processes. However, the collected sensor data is rarely used to analyse and improve the higher-level, aggregated business processes. Process mining (PM) appears to be a promising solution, with the ability to automatically generate and analyse business process models based on data. However, the atomic events of sensor measurements need to be refined, aggregated, and enriched to properly represent a business process. In this paper, we propose a novel framework to make manufacturing sensor data analysable with PM. The framework allows manufacturers with batch and continuous processes (BCP) to systematically enrich their sensor data to use it for optimization purposes. Following the action design research, we demonstrate the applicability of the framework in a use case study using sensor data from a BCP beverage production.

Introduction. There is a knowledge gap concerning patients with acute myeloid leukemia (AML) who are not eligible for intensive induction chemotherapy; this, together with a recent increase in the incidence in Latin America, encloses a need. Through real-world evidence, we describe and compare the results of the different treatment strategies within this context. Methodology. This is a longitudinal, descriptive, retrospective study of a cohort of Latin American patients with AML not eligible for intensive induction chemotherapy, treated with low-intensity chemotherapy or with the best supportive care alone between January 1, 2015, to December 31, 2018. Results. Of a total of 125 patients (median age 74.8 years), the majority received low-intensity chemotherapy (78.4%). The median time in months of overall survival (9.2), progression-free survival (4.8), and time to treatment failure (3.8) were longer in patients receiving hypomethylating agents. Additionally, better results were observed with low-intensity chemotherapy (complete response 11.2% and stable disease 17.3%) compared to the best supportive care alone. Conclusion. We deliver a real-world standpoint of Latin American patients with AML who are not eligible for intensive induction chemotherapy. Our findings pave the first steps of the way to describe, understand, and support informed decision-making processes in our region.

INTRODUCTION: In addition to clinical trials, real-world data is needed to verify the effectiveness of the CDK 4/6 inhibitor palbociclib. The primary aim was to examine real-world variation in treatment modification strategies for neutropenia and its relation to progression-free survival (PFS). The secondary aim was to assess if there is a gap between real-world and clinical trial outcomes.MATERIALS AND METHODS: In this multicenter, retrospective observational cohort study 229 patients were analyzed who started palbociclib and fulvestrant as second- or later-line therapy for HR-positive, HER2-negative metastatic breast cancer in the Santeon hospital group in the Netherlands between September 2016 and December 2019. Data were manually retrieved from patients' electronic medical records. PFS was examined using the Kaplan-Meier method to compare neutropenia-related treatment modification strategies within the first three months after neutropenia grade 3 - 4 occurred, as well as patients' eligibility to have participated in the PALOMA-3 clinical trial or not.RESULTS: Even though treatment modification strategies differed from those in PALOMA-3 (dose interruptions: 26 vs 54%, cycle delays: 54 vs 36%, and dose reductions: 39 vs 34%), these did not influence PFS. Patients who were PALOMA-3 ineligible experienced a shorter median PFS than those who were eligible (10.2 vs. 14.1 months; HR 1.52; 95% CI 1.12 - 2.07). An overall longer median PFS was found compared to PALOMA-3 (11.6 vs. 9.5 months; HR 0.70; 95% CI 0.54 - 0.90).CONCLUSION: This study suggests no impact of neutropenia-related treatment modifications on PFS and confirms inferior outcomes outside clinical trial eligibility.

BACKGROUND: Many studies have compared real-world clinical outcomes of immunotherapy in patients with metastatic non-small cell lung cancer (NSCLC) with reported outcomes data from pivotal trials. However, any differences observed could be only limitedly explored further for causation because of the unavailability of individual patient data (IPD) from trial participants. The present study aims to explore the additional benefit of comparison with IPD.METHODS: This study compares progression free survival (PFS) and overall survival (OS) of metastatic NSCLC patients treated with second line nivolumab in real-world clinical practice (n = 141) with IPD from participants in the Checkmate-057 clinical trial (n = 292). Univariate and multivariate Cox proportional hazards models were used to construct HRs for real-world practice versus clinical trial.RESULTS: Real-world patients were older (64 vs. 61 years), had more often ECOG PS ≥ 2 (5 vs. 0%) and were less often treated with subsequent anti-cancer treatment (28.4 vs. 42.5%) compared to trial patients. The median PFS in real-world patients was longer (3.84 (95%CI: 3.19-5.49) vs 2.30 (2.20-3.50) months) and the OS shorter than in trial participants (8.25 (6.93-13.2) vs. 12.2 (9.90-15.1) months). Adjustment with available patient characteristics, led to a shift in the hazard ratio (HR) for OS, but not for PFS (HRs from 1.13 (0.88-1.44) to 1.07 (0.83-1.38), and from 0.82 (0.66-1.03) to 0.79 (0.63-1.00), respectively).CONCLUSIONS: This study is an example how IPD from both real-world and trial patients can be applied to search for factors that could explain an efficacy-effectiveness gap. Making IPD from clinical trials available to the international research community allows this.

In Vietnam, STEM-based teaching approaches have been recommended for schools since 2018 with the integration of multiple related courses in schools. Teachers' perspectives on integrated STEM education, and how to design a STEM lesson that supports students’ learning are critical for ensuring that an integrated STEM curriculum is implemented successfully. This paper aims to describe a study applied successfully to STEM education in teaching Mathematics, in particular “Trigonometry ratio of an acute angle” in Vietnam. This study utilized mixed methods approaches with three phases: the first stage employed a quantitative study to examine the Vietnamese teachers' perspectives on STEM education. The second phase was an experiment on teaching while applying STEM education to design and organize a mathematics lesson, and the final phase was to employ a qualitative study to explore the Vietnamese students' experiences of STEM education connected with real-world problem solving and 21st-century skills development. A total of 47 teachers and 85 students participated in this study and data was collected through multi ways of surveys and semi-structured interviews. The findings show Vietnamese teachers' perspective of the necessity and importance of applying STEM education, however, they reported facing many challenges. A lesson designed as a STEM education application and the student's feedback regards the real-world roles. Learning outcomes connect with 21st-century skills in this study that are expected to provide the success evidence for further discussion and practice to improve the effectiveness of teaching and learning STEM education in Vietnam.

The challenges of sustainable development require a consistent transformation of decision-making practices in society and in the industry. In this regard, Virtual Reality (VR) is an effective tool, providing experiences that are not accessible in the real world. The overview effect is a feeling of interconnectedness and responsibility towards our planet and its inhabitants described by astronauts after seeing the Earth during spaceflights. We present a VR application merging the overview effect with data visualization. We illustrate the design process and perform a pilot test to assess the emotions raised by the VR experience. Furthermore, we report feedback from design engineering and sustainability experts discussing the applications' potential in decision-making contexts, including product development processes. © The Author(s), 2023. Published by Cambridge University Press.

Data quality assessment has become a prominent component in the successful execution of complex data-driven artificial intelligence (AI) software systems. In practice, real-world applications generate huge volumes of data at speeds. These data streams require analysis and preprocessing before being permanently stored or used in a learning task. Therefore, significant attention has been paid to the systematic management and construction of high-quality datasets. Nevertheless, managing voluminous and high-velocity data streams is usually performed manually (i.e. offline), making it an impractical strategy in production environments. To address this challenge, DataOps has emerged to achieve life-cycle automation of data processes using DevOps principles. However, determining the data quality based on a fitness scale constitutes a complex task within the framework of DataOps. This paper presents a novel Data Quality Scoring Operations (DQSOps) framework that yields a quality score for production data in DataOps workflows. The framework incorporates two scoring approaches, an ML prediction-based approach that predicts the data quality score and a standard-based approach that periodically produces the ground-truth scores based on assessing several data quality dimensions. We deploy the DQSOps framework in a real-world industrial use case. The results show that DQSOps achieves significant computational speedup rates compared to the conventional approach of data quality scoring while maintaining high prediction performance.

Autonomous agents embedded in a physical environment need the ability to recognize objects and their properties from sensory data. Such a perceptual ability is often implemented by supervised machine learning models, which are pre-trained using a set of labelled data. In real-world, open-ended deployments, however, it is unrealistic to assume to have a pre-trained model for all possible environments. Therefore, agents need to dynamically learn/adapt/extend their perceptual abilities online, in an autonomous way, by exploring and interacting with the environment where they operate. This paper describes a way to do so, by exploiting symbolic planning. Specifically, we formalize the problem of automatically training a neural network to recognize object properties as a symbolic planning problem (using PDDL). We use planning techniques to produce a strategy for automating the training dataset creation and the learning process. Finally, we provide an experimental evaluation in both a simulated and a real environment, which shows that the proposed approach is able to successfully learn how to recognize new object properties., This work has been partially supported by AI-Plan4EU and TAILOR, two projects funded by the EU Horizon 2020 research and innovation program under GA n. 101016442 and n. 952215, respectively, and by MUR PRIN-2020 project RIPER (n. 20203FFYLK). We acknowledge the support of the PNRR project FAIR - Future AI Research (PE00000013), under the NRRP MUR program funded by the NextGenerationEU. This work has also been partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.

Real-world applications that are safety-critical and resource-constrained necessitate using compact and robust Deep Neural Networks (DNNs) against adversarial data perturbation. MobileNet-tiny has been introduced as a compact DNN to deploy on edge devices to reduce the size of networks. To make DNNs more robust against adversarial data, adversarial training methods have been proposed. However, recent research has investigated the robustness of large-scale DNNs (such as WideResNet), but the robustness of tiny DNNs has not been analysed. In this paper, we analyse how the width of the blocks in MobileNet-tiny affects the robustness of the network against adversarial data perturbation. Specifically, we evaluate natural accuracy, robust accuracy, and perturbation instability metrics on the MobileNet-tiny with various inverted bottleneck blocks with different configurations. We generate configurations for inverted bottleneck blocks using different width-multipliers and expand-ratio hyper-parameters. We discover that expanding the width of the blocks in MobileNet-tiny can improve the natural and robust accuracy but increases perturbation instability. In addition, after a certain threshold, increasing the width of the network does not have significant gains in robust accuracy and increases perturbation instability. We also analyse the relationship between the width-multipliers and expand-ratio hyper-parameters with the Lipchitz constant, both theoretically and empirically. It shows that wider inverted bottleneck blocks tend to have significant perturbation instability. These architectural insights can be useful in developing adversarially robust tiny DNNs for edge devices.

Robot operating system 2 (ROS 2) is increasingly popular both in research and commercial robotic systems. ROS 2 is designed to allow real-time execution and data communication, enabling rapid prototyping and deployment of robotic systems. In order to predict and calculate execution times in ROS 2, one needs to analyze its internal scheduler, called executor. The executor has been updated in various distributions of ROS 2, which is shown to impact significantly the periodic execution invoked by the underlying operating system's timers, potentially causing unexpected latencies. To expose the mentioned impact due to executor differences, in this paper, we present an experimental evaluation of the execution behavior of ROS 2's schedulable entities, namely callbacks, among the existing versions of the executor. We visualize the differences of callback execution order via simulation, and we create design-level scenarios that impact the execution of periodically scheduled callbacks, negatively. Moreover, we show how such negative impact can be mitigated by using multi-threaded executors. Finally, we illustrate the observed behavior on a real-world centralized multi-agent robot system. Our work aims to raise awareness within the ROS 2 developer community, regarding possible problems of timer blocking, and propose a mitigation solution of the latter.

[Background] The combination of trifluridine and tipiracil is indicated in patients with metastatic colorectal cancer previously treated or non-candidates to chemotherapy and biological therapies. This study in routine clinical practice aimed to describe the effectiveness and safety of trifluridine and tipiracil and identify prognostic factors in patients with metastatic colorectal cancer in Spain., [Methods] This analysis was a retrospective, observational, multicenter study that included patients aged ≥18 years who had received treatment with trifluridine/tipiracil for metastatic colorectal cancer in third- or subsequent lines., [Results] Overall, 294 were evaluated. Trifluridine/tipiracilmedian (minimum, maximum) treatment duration was 3.5 (1.0–29.0) months, and 128 (43.5%) patients received subsequent treatments. One hundred (34%) patients showed disease control rate, and the median progression-free survival and overall survival from trifluridine/tipiracil treatment onset were 3.7 and 7.5 months, respectively. The most frequently reported adverse events were asthenia (all grades, 57.9%) and neutropenia (all grades, 51.3%). A 39.1% and 4.4% of the participants had a dose reduction and a treatment interruption due to toxicity. Patients with age ≥65 years, low tumor burden, ≤2 metastasis sites, treatment dose reduction, neutropenia, and ≥6 cycles, had significantly higher overall survival, progression-free survival, and response rate., [Conclusions] This real-life study indicates that trifluridine/tipiracil shows effectiveness and safety in treating patients with metastatic colorectal cancer. The results show a profile of metastatic colorectal cancer patients with previously unknown prognostic factors who have a more significant benefit from treatment with trifluridine/tipiracil in routine clinical practice.

Background: Italy can be viewed as a laboratory to assess the quality of mental healthcare delivered in a community-oriented system, especially for severe mental disorders, such as personality disorders. Although initiatives based on clinical indicators for assessing the quality of mental healthcare have been developed by transnational-organisations, there is still no widespread practice of measuring the quality of care pathways delivered to patients with severe mental disorders in a community-oriented system, especially using administrative healthcare databases. The aim of the study is to evaluate the quality of care delivered to patients with personality disorders taken-in-care by mental health services of four Italian regions (Lombardy, Emilia-Romagna, Lazio, Sicily). Methods: A set of thirty-three clinical indicators, concerning accessibility, appropriateness, continuity, and safety of care, was implemented using regional healthcare utilization databases, containing data on mental health treatments and diagnosis, hospital admissions, outpatient interventions and exams and drug prescriptions. RESULTS: 31,688 prevalent patients with personality disorders treated in 2015 were identified, of whom 2,331 newly taken-in-care. One-in-10 patients received a standardized assessment, the treatment discontinuity affected half of the cases. 12.7% of prevalent patients received at least one hospitalization, 10.6% in the newly taken-in-care cohort. 6-out-of-10 patients had contact with community-services within 14 days from hospital discharge. Access to psychotherapy and psychoeducational treatments was low and delivered with a low intensity. The median of psychosocial interventions per person-year was 19.1 and 9.4, respectively, in prevalent and newly taken-in-care cases. Nearly 50% of patients received pharmacological treatments. Conclusions: Healthcare utilization databases were used to systematically evaluate and assess service delivery across regional mental health system

Artificial Intelligence (AI) in medical applications holds great promise. However, the use of Machine Learning-based (ML) systems in clinical practice is still minimal. It is uniquely difficult to introduce clinician-facing ML-based systems in practice, which has been recognised in HCI and related fields. Recent publications have begun to address the sociotechnical challenges of designing, developing, and successfully deploying clinician-facing ML-based systems. We conducted a qualitative systematic review and provided answers to the question: "How can HCI researchers and practitioners contribute to the successful realisation of ML in medical practice?"We reviewed 25 eligible papers that investigated the real-world clinical implications of concrete clinician-facing ML-based systems. The main contributions of this systematic review are: (1) an overview of the technical aspects of ML innovation and their consequences for HCI researchers and practitioners; (2) a description of the different roles that ML-based systems can take in clinical settings; (3) a conceptualisation of the main activities of medical ML innovation processes; (4) identification of five sociotechnical interdependencies that emerge from medical ML innovation; and (5) implications for HCI researchers and practitioners on how to mitigate the sociotechnical challenges of medical ML innovation.

Background: Comparative data on mortality in COVID-19 patients treated with molnupiravir or with nirmatrelvir plus ritonavir are inconclusive. We therefore compared all-cause mortality in community-dwelling COVID-19 patients treated with these drugs during the Omicron era. Methods: Data collected in the nationwide, population-based, cohort of patients registered in the database of the Italian Medicines Agency (AIFA) were used. To increase completeness of the recorded deaths and date correctness, a cross-check with the National Death Registry provided by the Ministry of the Interior was performed. We included in this study all patients infected by SARS-CoV-2 treated within 5 days after the test date and symptom onset between February 8 and April 30, 2022. All-cause mortalities by day 28 were compared between the two treatment groups after balancing for baseline characteristics using weights obtained from a gradient boosting machine algorithm. Findings: In the considered timeframe, 17,977 patients treated with molnupiravir and 11,576 patients with nirmatrelvir plus ritonavir were included in the analysis. Most patients (25,617/29,553 = 86.7%) received a full vaccine course including the booster dose. A higher crude incidence rate of all-cause mortality was found among molnupiravir users (51.83 per 100,000 person-days), compared to nirmatrelvir plus ritonavir users (22.29 per 100,000 person-days). However, molnupiravir-treated patients were older than those treated with nirmatrelvir plus ritonavir and differences between the two populations were found as far as types of co-morbidities were concerned. For this reason, we compared the weight-adjusted cumulative incidences using the Aalen estimator and found that the adjusted cumulative incidence rates were 1.23% (95% CI 1.07%–1.38%) for molnupiravir-treated and 0.78% (95% CI 0.58%–0.98%) for nirmatrelvir plus ritonavir-treated patients (adjusted log rank p = 0.0002). Moreover, the weight-adjusted mixed-effect Cox model i

At the time of first acute coronary syndrome (ACS) hospital admission, women are generally older and have more comorbidities than men, which may explain differences in their short-term prognosis. However, few studies have focused on differences in the out-of-hospital management of men and women. This study investigated (i) the risk of clinical outcomes, (ii) the use of out-of-hospital healthcare and (iii) the effects of clinical recommendations on outcomes in men vs. women. A total of 90,779 residents of the Lombardy Region (Italy) were hospitalized for ACS from 2011 to 2015. Exposure to prescribed drugs, diagnostic procedures, laboratory tests, and cardiac rehabilitation in the first year after ACS hospitalization were recorded. To evaluate whether sex can modify the relationship between clinical recommendations and outcomes, adjusted Cox models were separately fitted for men and women. Women were exposed to fewer treatments, required fewer outpatient services than men and had a lower risk of long-term clinical events. The stratified analysis showed an association between adherence to clinical recommendations and a lower risk of clinical outcomes in both sexes. Since improved adherence to clinical recommendations seems to be beneficial for both sexes, tight out-of-hospital healthcare control should be recommended to achieve favourable clinical benefits.

Background: The assessment of the quality of care pathways delivered to people with severe mental disorders in a community-based system remains uncommon, especially using healthcare utilization databases. The aim of the study was to evaluate the quality of care provided to people with bipolar disorders taken-in-care by mental health services of four Italian areas (Lombardy, Emilia-Romagna, Lazio, province of Palermo). Methods: Thirty-six quality indicators were implemented to assess quality of mental health care for patients with bipolar disorders, according to three dimensions (accessibility and appropriateness, continuity, and safety). Data were retrieved from healthcare utilization (HCU) databases, which contain data on mental health treatments, hospital admissions, outpatient interventions, laboratory tests and drug prescriptions. Results: 29,242 prevalent and 752 incident cases taken-in-care by regional mental health services with a diagnosis of bipolar disorder in 2015 were identified. Age-standardized treated prevalence rate was 16.2 (per 10,000 adult residents) and treated incidence rate 1.3. In the year of evaluation, 97% of prevalent cases had ≥ 1 outpatient/day-care contacts and 88% had ≥ 1 psychiatric visits. The median of outpatient/day-care contacts was 9.3 interventions per-year. Psychoeducation was provided to 3.5% of patients and psychotherapy to 11.5%, with low intensity. 63% prevalent cases were treated with antipsychotics, 71.5% with mood stabilizers, 46.6% with antidepressants. Appropriate laboratory tests were conducted in less than one-third of prevalent patients with a prescription of antipsychotics; three quarters of those with a prescription of lithium. Lower proportions were observed for incident patients. In prevalent patients, the Standardized Mortality Ratio was 1.35 (95% CI: 1.26–1.44): 1.18 (1.07–1.29) in females, 1.60 (1.45–1.77) in males. Heterogeneity across areas was considerable in both cohorts. Conclusions: We found a meaningful

Objectives: To describe the incorporation of monoclonal antibodies (mAb) in real-world (RW) practice for the treatment of patients with relapsed refractory multiple myeloma (RRMM) in a setting with other treatment alternatives. Methods: This was an observational, multicenter, ambispective study of RRMM treated with or without a mAb. Results: A total of 171 patients were included. For the group treated without mAb, the median (95% CI) progression-free survival (PFS) to relapse was 22.4 (17.8-27.0) months; partial response or better (≥PR) and complete response or better (≥CR) was observed in 74.1% and 24.1% of patients, respectively; and median time to first response in first relapse was 2.0 months and in second relapse was 2.5 months. For the group of patients treated with mAb in first or second relapse, the median PFS was 20.9 (95% CI, could not be evaluated) months; the ≥ PR and ≥ CR rates were 76,2% and 28.6%, respectively; and the median time to first response in first relapse was 1.2 month and in second relapse was 1.0 months. The safety profiles for the combinations were consistent with those expected. Conclusions: The incorporation of mAb in RW practice for the treatment of RRMM has shown good quality and speed of response with a similar safety profile shown in randomized clinical trials.

Introduction: Over the past decade, ALK tyrosine kinase inhibitors have delivered unprecedented survival for individuals with ALK-positive (ALK+) lung cancers. Real-world data enhance the understanding of optimal drug sequencing and expectations for survival. Methods: Multicenter real-world study of individuals with pretreated advanced ALK+ lung cancers managed on a lorlatinib access program between 2016 and 2020. Key outcomes were lorlatinib efficacy, tolerability, and treatment sequencing. Progression-free survival (PFS) and overall survival (OS) were calculated using the Kaplan-Meier method among all individuals (PFSa and OSa), with at least 30 days (one-cycle) lorlatinib exposure (PFSb and OSb), and with good performance status (PFSc and OSc). Subgroups of interest were analyzed to assess signals of potential clinical applicability. Two OS index dates were analyzed, from lorlatinib initiation and advanced ALK+ diagnosis. Results: The population (N = 38, 10 sites) was heavily pretreated (23 had ≥ 2 previous treatment lines) with a high disease burden (26 had 2–4 sites and 11 had > 4 sites of metastatic disease, 19 had brain metastases). The overall response rate was 44% and the disease control rate was 81%. Lorlatinib dose reduction (18%), interruption (16%), and discontinuation (3%) were consistent with the trial experience. From advanced ALK+ diagnosis, the median OS for populations a, b, and c was 45.0 months, 69.9 months and 61.2 months respectively. From lorlatinib initiation, the median PFSa, PFSb and PFSc was 7.3 months, 13.2 months and 27.7 months and the median OSa, OSb and OSc was 19.9 months, 25.1 months and 27.7 months. The median PFSa with versus without brain metastases was 34.6 months versus 5.8 months (p = 0.09). The intracranial median PFS was 14.2 months. Previous good response versus poor response to the first ALK-directed therapy median PFSa was 27.7 months versus 4.7 months with a hazard ratio of 0.3 (p = 0.01). Conclusions: Lorlatinib is a p

Background: Nivolumab, an anti–programmed cell death 1 immuno-oncology therapy, is approved as an adjuvant treatment for patients with completely resected stage III or stage IV melanoma. PRESERV MEL (Prospective and REtrospective Study of nivolumab thERapy in adjuVant MELanoma) is a real-world observational study evaluating the effectiveness and safety of adjuvant nivolumab in patients with completely resected stage III or stage IV melanoma in clinical practice in Belgium and Luxembourg. Methods: Patients were enrolled prospectively and retrospectively during a 2-year period (January 2019–January 2021), and will be followed for 5 years. The results reported here are for the second interim analysis (cutoff date 31 December 2021). The index date was the date of first administration of adjuvant nivolumab. Patients received nivolumab for up to 12 months per label. Outcomes included relapse-free survival (RFS), adverse events (AEs)/treatment-related AEs (TRAEs), and health-related quality of life (HRQoL; assessed in prospectively enrolled patients using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ-C30), Functional Assessment of Cancer Therapy—Melanoma (FACT-M), and EQ-5D-3L instruments). HRQoL was evaluated at group level (mean change in scores from baseline based on minimally important differences) and individual patient level (percentage of patients with clinically important scores based on threshold of clinical importance). Outcomes were analyzed descriptively. Results: The study enrolled 152 patients (125 prospective, 27 retrospective) at 15 hospitals in Belgium and Luxembourg. Minimum potential follow-up at time of analysis was 11.4 months. Median age was 60 years (range 29–85), and 53% of patients were male. At 12 and 18 months, the RFS rates were 74.7% (95% confidence interval (CI): 66.9–80.9) and 68.4% (95% CI: 60.0–75.5), respectively. Median RFS was not reached. Grade 3 or 4 TRAEs were reported in 1, SCOPUS: ar.j, info:eu-repo/semantics/published

Introduction: The current study describes real-world clinical outcomes and factor usage among patients with haemophilia B switching from standard half-life factor IX (SHL FIX) treatment to recombinant factor IX Fc fusion protein (rFIXFc) prophylaxis in European treatment centres. Methods: This non-interventional, retrospective, multicentre chart review evaluated medical records from adult and paediatric patients with haemophilia B in Denmark, Germany and the UK. Patients had documented SHL FIX treatment, on-demand or prophylaxis, for ≥ 6 months before starting rFIXFc prophylaxis, and subsequent data for ≥ 6 months afterwards (up to 24 months). Primary endpoints included annualised bleeding rates (ABRs), prophylactic factor consumption and injection frequency. Results: Data from 30 patients (24/30 [80.0%] with severe disease) showed overall mean (standard deviation, SD) ABRs of 4.7 (6.3) on SHL FIX treatment and 1.7 (2.3) after switching to rFIXFc prophylaxis. The reduction in mean (SD) ABRs was greater when switching from SHL FIX on-demand treatment (n = 6), with a decrease from 10.5 (9.9) to 2.6 (4.5), than when switching from SHL FIX prophylaxis (n = 24), with a decrease from 3.3 (4.3) to 1.5 (1.4). Among prior SHL FIX prophylaxis patients, switching to rFIXFc prophylaxis increased the proportion of those with zero bleeds from 21.7% to 45.8% during the 6 months before and after switching, respectively. In the total population, five of six target joints (83.3%) present when patients started rFIXFc prophylaxis subsequently resolved. In patients switching from SHL FIX prophylaxis to rFIXFc prophylaxis, mean (SD) weekly injection frequency was reduced by 1.0 (0.7) and mean (SD) factor consumption was reduced by 27.7 (49.6) IU/kg/week. Conclusion: This study demonstrates the effectiveness of rFIXFc prophylaxis in real-world clinical practice. Improvements in both clinical effectiveness and factor usage associated with rFIXFc prophylaxis may potentially reduce patien

Background Comparative data on mortality in COVID-19 patients treated with molnupiravir or with nirmatrelvir plus ritonavir are inconclusive. We therefore compared all-cause mortality in community-dwelling COVID-19 patients treated with these drugs during the Omicron era.Methods Data collected in the nationwide, population-based, cohort of patients registered in the database of the Italian Medicines Agency (AIFA) were used. To increase completeness of the recorded deaths and date correctness, a crosscheck with the National Death Registry provided by the Ministry of the Interior was performed. We included in this study all patients infected by SARS-CoV-2 treated within 5 days after the test date and symptom onset between February 8 and April 30, 2022. All-cause mortalities by day 28 were compared between the two treatment groups after balancing for baseline characteristics using weights obtained from a gradient boosting machine algorithm. Findings In the considered timeframe, 17,977 patients treated with molnupiravir and 11,576 patients with nirmatrelvir plus ritonavir were included in the analysis. Most patients (25,617/29,553 = 86.7%) received a full vaccine course including the booster dose. A higher crude incidence rate of all-cause mortality was found among molnupiravir users (51.83 per 100,000 person-days), compared to nirmatrelvir plus ritonavir users (22.29 per 100,000 person-days). However, molnupiravir-treated patients were older than those treated with nirmatrelvir plus ritonavir and differences between the two populations were found as far as types of co-morbidities wereconcerned. For this reason, we compared the weight-adjusted cumulative incidences using the Aalen estimator and found that the adjusted cumulative incidence rates were 1.23% (95% CI 1.07%-1.38%) for molnupiravir-treated and 0.78% (95% CI 0.58%-0.98%) for nirmatrelvir plus ritonavir-treated patients (adjusted log rank p = 0.0002). Moreover, the weight-adjusted mixed-effect Cox model includi

[Abstract] Introduction: COMPACT, a non-interventional study, evaluated the persistence, effectiveness, safety and patient-reported outcomes (PROs) in patients with rheumatoid arthritis (RA), axial-spondyloarthritis (axSpA) or psoriatic arthritis (PsA) treated with SDZ ETN (etanercept [ETN] biosimilar) in Europe and Canada. Methods: Patients (aged ≥ 18 years) who have been treated with SDZ ETN were categorised on the basis of prior treatment status (groups A-D): patients in clinical remission or with low disease activity under treatment with reference ETN or biosimilar ETN and switched to SDZ ETN; patients who received non-ETN targeted therapies and switched to SDZ ETN; biologic-naïve patients who started SDZ ETN after conventional therapy failure; or disease-modifying anti-rheumatic drug (DMARD)-naïve patients with RA considered suitable for treatment initiation with a biologic and started on treatment with SDZ ETN. The primary endpoint was drug persistence, defined as time from study enrolment until discontinuation of SDZ ETN treatment. Results: Of the 1466 patients recruited, 844 (57.6%) had RA, 334 (22.8%) had axSpA and 288 (19.6%) had PsA. Patients had an ongoing SDZ ETN treatment at the time of enrolment for an observed average of 138 days (range 1-841); 22.7% of patients discontinued SDZ ETN through 12 months of study observation. Overall, all the patients receiving SDZ ETN showed good treatment persistence at 12 months with discontinuation rates of 15.2%, 25.7% and 27.8% in groups A, B and C, respectively. Across all patient groups, no major differences were observed in the disease activity and PRO scores between baseline and month 12. Injection-site reactions were low across the treatment groups. Conclusion: These results support the effectiveness and safety of SDZ ETN treatment in patients with RA, axSpA or PsA in real-life conditions. The treatment persistence rates observed were consistent with previously published reports of patients treated with refere

We present a cross-lingual approach for the extraction of Vossian Antonomasia, a stylistic device especially popular in newspaper articles. We evaluate a zero-shot transfer learning approach and two approaches that use machinetranslated training and test data. We show that our proposed models achieve strong results on all test datasets in the target language. As annotated data is sparse, especially in the target language, we generate additional test data to evaluate our models and conclude with a robustness study on real-world data.

Purpose: To measure indicators of timeliness and continuity of treatments on patients with schizophrenic disorder in ‘real-life’ practice, and to validate them through their relationship with relapse occurrences. Methods: The target population was from four Italian regions overall covering 22 million beneficiaries of the NHS (37% of the entire Italian population). The cohort included 12,054 patients newly taken into care for schizophrenic disorder between January 2015 and June 2016. The self-controlled case series (SCCS) design was used to estimate the incidence rate ratio of relapse occurrences according to mental healthcare coverage. Results: Poor timeliness (82% and 33% of cohort members had not yet started treatment with psychosocial interventions and antipsychotic drug therapy within the first year after they were taken into care) and continuity (27% and 23% of patients were persistent with psychosocial interventions, and antipsychotic drug therapy within the first 2 years after starting the specific treatment) were observed. According to SCCS design, 4794 relapses occurred during 9430 PY (with incidence rate of 50.8 every 100 PY). Compared with periods not covered by mental healthcare, those covered by psychosocial intervention alone, antipsychotic drugs alone and by psychosocial intervention and antipsychotic drugs together were, respectively, associated with relapse rate reductions of 28% (95% CI 4–46%), 24% (17–30%) and 44% (32–53%). Conclusion: Healthcare administrative data may contribute to monitor and to assess the effectiveness of a mental health system. Persistent use of both psychosocial intervention and antipsychotic drugs reduces risk of severe relapse.

Eosinophils have a broad range of functions, both homeostatic and pathological, mediated through an array of cell surface receptors and specific secretory granules that promote interactions with their microenvironment. Eosinophil development, differentiation, activation, survival and recruitment are closely regulated by a number of type 2 cytokines, including interleukin (IL)-5, the key driver of eosinophilopoiesis. Evidence shows that type 2 inflammation, driven mainly by interleukin (IL)-4, IL-5 and IL-13, plays an important role in the pathophysiology of eosinophilic airway diseases, including asthma, chronic rhinosinusitis with nasal polyps, eosinophilic granulomatosis with polyangiitis and hypereosinophilic syndrome. Several biologic therapies have been developed to suppress type 2 inflammation, namely mepolizumab, reslizumab, benralizumab, dupilumab, omalizumab and tezepelumab. While these therapies have been associated with clinical benefits in a range of eosinophilic diseases, their development has highlighted several challenges and directions for future research. These include the need for further information on disease progression and identification of treatable traits, including clinical characteristics or biomarkers that will improve the prediction of treatment response. The Nordic countries have a long tradition of collaboration using patient registries and Nordic asthma registries provide unique opportunities to address these research questions. One example of such a registry is the NORdic Dataset for aSThmA Research (NORDSTAR), a longitudinal population-based dataset containing all 3.3 million individuals with asthma from four Nordic countries (Denmark, Finland, Norway and Sweden). Large-scale, real-world registry data such as those from Nordic countries may provide important information regarding the progression of eosinophilic asthma, in addition to clinical characteristics or biomarkers that could allow targeted treatment and ensure optimal patient

Background KRAS mutations, present in over 40% of metastatic colorectal cancer (mCRC), are negative predictive factors for anti-EGFR therapy. Mutations in KRAS-G12C have a cysteine residue for which drugs have been developed. Published data on this specific mutation are conflicting; thus, we studied the frequency and clinical characteristics in a real-world and population-based setting. Methods Patients from three Nordic population-based cohorts and the real-life RAXO-study were combined. RAS and BRAF tests were performed in routine healthcare, except for one cohort. The dataset consisted of 2,559 patients, of which 1,871 could be accurately classified as KRAS, NRAS, and BRAF-V600E. Demographics, treatments, and outcomes were compared using logistic regression. Overall survival (OS) was estimated with Kaplan-Meier, and differences were compared using Cox regression, adjusted for baseline factors. Results The KRAS-G12C frequency was 2%-4% of all tested in the seven cohorts (mean 3%) and 4%-8% of KRAS mutated tumors in the cohorts (mean 7%). Metastasectomies and ablations were performed more often (38% vs. 28%, p = 0.040), and bevacizumab was added more often (any line 74% vs. 59%, p = 0.007) for patients with KRAS-G12C- vs. other KRAS-mutated tumors, whereas chemotherapy was given to similar proportions. OS did not differ according to KRAS mutation, neither overall (adjusted hazard ratio (HR) 1.03; 95% CI 0.74-1.42, reference KRAS-G12C) nor within treatment groups defined as "systemic chemotherapy, alone or with biologics", "metastasectomy and/or ablations", or "best supportive care", RAS and BRAF wild-type tumors (n = 548) differed similarly to KRAS-G12C, as to other KRAS- or NRAS-mutated (n = 66) tumors. Conclusions In these real-life and population-based cohorts, there were no significant differences in patient characteristics and outcomes between patients with KRAS-G12C tumors and those with other KRAS mutations. This contrasts with the results of most previous s

Background and objectivesDiffuse-tenosynovial giant cell tumor (D-TGCT) is a rare, locally aggressive, typically benign neoplasm affecting mainly large joints, representing a wide clinical spectrum. We provide a picture of the treatment journey of D-TGCT patients as a 2-year observational follow-up.MethodsThe TGCT Observational Platform Project registry was a multinational, multicenter, prospective observational study at tertiary sarcoma centers spanning seven European countries and two US sites. Histologically confirmed D-TGCT patients were categorized as either those who remained on initial treatment strategy (determined at baseline visit) or those who changed treatment strategy with specific changes documented (e.g., systemic treatment to surgery) at the 1-year and/or 2-year follow-up visits.ResultsA total of 176 patients were assessed, mean diagnosis age was 38.4 (SD ± 14.6) years; most patients had a knee tumor (120/176, 68.2%). For the 2-year observation period, most patients (75.5%) remained on the baseline treatment strategy throughout, 54/79 patients (68.4%) remained no treatment, 30/45 patients (66.7%) remained systemic treatment, 39/39 patients (100%) remained surgery. Those who changed treatment strategy utilized multimodal treatment options.ConclusionsThis is the first prospectively collected analysis to describe D-TGCT patient treatments over an extended follow-up and demonstrates the need for multidisciplinary teams to determine an optimal treatment strategy.

Introduction'Real-world' data for mold-active triazoles (MATs) in the treatment of invasive fungal infections (IFIs) are lacking. This study evaluated usage of MATs in a disease registry for the management of IFIs.MethodsData were collected for this multicenter, observational, prospective study from 55 US centers, between March 2017 and April 2020. Eligible patients received isavuconazole, posaconazole, or voriconazole as MAT monotherapy (one MAT) or multiple/sequenced MAT therapy (more than one MAT) for prophylaxis or treatment. Patients were enrolled within 60 days of MAT initiation. The primary objective was to characterize patients receiving a MAT and their patterns of therapy. The full analysis set (FAS) included eligible patients for the relevant enrollment protocol, and the safety analysis set (SAF) included patients who received ≥ 1 MAT dose.ResultsOverall, 2009 patients were enrolled in the SAF. The FAS comprised 1993 patients (510 isavuconazole; 540 posaconazole; 491 voriconazole; 452 multiple/sequenced MAT therapies); 816 and 1177 received treatment and prophylaxis at study index/enrollment, respectively. Around half (57.8%) of patients were male, and median age was 59 years. Among patients with IFIs during the study, the most common pathogens were Aspergillus fumigatus in the isavuconazole (18.2% [10/55]) and voriconazole (25.5% [12/47]) groups and Candida glabrata in the posaconazole group (20.9% [9/43]); the lungs were the most common infection site (58.2% [166/285]). Most patients were maintained on MAT monotherapy (77.3% [1541/1993]), and 79.4% (1520/1915) completed their MAT therapies. A complete/partial clinical response was reported in 59.1% (591/1001) of patients with a clinical response assessment. Breakthrough IFIs were reported in 7.1% (73/1030) of prophylaxis patients. Adverse drug reactions (ADRs) were reported in 14.7% (296/2009) of patients (3.9% [20/514] isavuconazole; 11.3% [62/547] posaconazole; 14.2% [70/494] voriconazole).Co

Within the telecommunications industry, a positioning system for estimating user equipment (UE) location using purely information available for the basestation has an enormous number of potential uses. The link between physical position and the network channel state enables potential positioning systems to function by under- standing the network channel state dependency on location, using a model-based, data-based, or a combined approach. A key exploitable phenomenon linked to position is that of multi-path propaga- tion, wherein transmissions can arrive from multiple directions to the UE, with a unique propagation pattern corresponding to a unique environment. In fifth gen- eration wireless technology (5G), multi-path components are already exploited for beamforming with massive multiple-input multiple-output (MIMO) technol- ogy. Basestations therefore have a preexisting pipeline for obtaining beamformed channel matrices from channel state information (CSI) transmitted by the UE. A data-driven approach using multi-path propagation phenomena for positioning is possible through utilizing the already available beamformed channel matrix in the basestation. In this thesis the practical data-driven deep-learning approach for UE position- ing in 5G using beamformed channel matrices is examined. Real-world data is utilized to judge the applicability of the approach, with measurements done on a commercial-grade Ericsson 5G testbench in both non-line-of-sight (nLoS) and line- of-sight (LoS) scenarios. Using a similar approach to other papers in the field, a su- pervised deep-learning approach is used for instantaneous position estimation. For improving positioning accuracy through trajectory estimation, a novel approach of using particle filtering with network ensemble outputs for kernel density estima- tion of an observation probability density function is proposed. The results show that using the outlined methods position is possible to estimate in real-world pedes- trian, In this thesis a novel combined approach for phone positioning in 5G using deep learning and data processing is examined. The proposed method combination results in a mean accuracy of around 2-5 meters, demonstrating a promising path forward to a workable alternative to current navigation systems. The concept underlying the proposed method is that physical position and the state of the 5G radio connection are linked. Deep-learning algorithms can then learn to understand this link and predict possible locations of all devices connected to the 5G system. By simulating realistic pedestrian movement in the background, a series of predictions can then be used to better pinpoint real user position in real-time. In practice, this means that with the methods proposed in this thesis, position can be predicted with existing infrastructure using only 5G connection state. Furthermore, the results were obtained through realistic measurements on Ericsson 5G testbench equipment under non-ideal conditions with the 5G transmitter not directly visible, showing the viability of the system in a real-world scenario.

Guselkumab treatment outcomes and persistence were assessed in a real-world cohort of Finnish patients with difficult-to-treat plaque psoriasis over a median follow-up of 1 year. Data on 181 patients who initiated guselkumab at the 15 study centres were collected retrospectively from the patient charts. Prior exposure to biologic therapies was common, with 56% and 35% having used at least 1 and 2 biologics, respectively. Median guselkumab treatment duration was 11 months with 21 patients (12%) discontinuing treatment during follow-up. Of 85 patients with a follow-up duration of at least 1 year, 73 (86%) were still on guselkumab at 1 year. Significant improvements during follow-up were seen in the absolute Psoriasis Area and Severity Index (PASI) scores with 32 patients (80%) having absolute PASI ≤ 2 after a 9–14-month treatment. Guselkumab treatment was effective and treatment persistence was high in the nationwide Finnish real-life setting.

Background: KRAS mutations, present in over 40% of metastatic colorectal cancer (mCRC), are negative predictive factors for anti-EGFR therapy. Mutations in KRAS-G12C have a cysteine residue for which drugs have been developed. Published data on this specific mutation are conflicting; thus, we studied the frequency and clinical characteristics in a real-world and population-based setting. Methods: Patients from three Nordic population-based cohorts and the real-life RAXO-study were combined. RAS and BRAF tests were performed in routine healthcare, except for one cohort. The dataset consisted of 2,559 patients, of which 1,871 could be accurately classified as KRAS, NRAS, and BRAF-V600E. Demographics, treatments, and outcomes were compared using logistic regression. Overall survival (OS) was estimated with Kaplan–Meier, and differences were compared using Cox regression, adjusted for baseline factors. Results: The KRAS-G12C frequency was 2%–4% of all tested in the seven cohorts (mean 3%) and 4%–8% of KRAS mutated tumors in the cohorts (mean 7%). Metastasectomies and ablations were performed more often (38% vs. 28%, p = 0.040), and bevacizumab was added more often (any line 74% vs. 59%, p = 0.007) for patients with KRAS-G12C- vs. other KRAS-mutated tumors, whereas chemotherapy was given to similar proportions. OS did not differ according to KRAS mutation, neither overall (adjusted hazard ratio (HR) 1.03; 95% CI 0.74–1.42, reference KRAS-G12C) nor within treatment groups defined as “systemic chemotherapy, alone or with biologics”, “metastasectomy and/or ablations”, or “best supportive care”, RAS and BRAF wild-type tumors (n = 548) differed similarly to KRAS-G12C, as to other KRAS- or NRAS-mutated (n = 66) tumors. Conclusions: In these real-life and population-based cohorts, there were no significant differences in patient characteristics and outcomes between patients with KRAS-G12C tumors and those with other KRAS mutations. This contrasts with the results of mo

Objectives: This study aimed to assess the cost-effectiveness profile of adherence to recommendations for the community management of patients discharged with a diagnosis of acute coronary syndrome (ACS). Methods: The cohort of 50 282 residents in the Lombardy Region (Italy) who were discharged with a diagnosis of ACS during 2011 to 2015 was followed up until 2018. Adherence to selected recommendations including drug therapies (DTs), outpatient controls, and rehabilitation, experienced during the first year after index discharge, was considered. Adherent and nonadherent cohort members were matched on high-dimensional propensity scores. Composite clinical outcomes (cardiovascular hospital admissions and all-cause mortality) and healthcare costs were assessed for a time horizon of 5 years. Cost-effectiveness profile of adherence to recommendations was measured through the incremental cost-effectiveness ratio, that is, the incremental cost for 1 day free from the composite clinical outcome. Results: Adherence to DTs, outpatient controls, and rehabilitation, respectively, regarded 39%, 81%, and 3% of cohort members. Compared with nonadherent patients, those adherent to DTs, outpatient controls, and rehabilitation had (1) a delay in the occurrence of the composite clinical outcome of 50, 43, and 73 days, respectively, and (2) lower (on average, €199 per year for DTs) and higher costs (€292 and €1024 for outpatient controls and rehabilitation). Cost-effectiveness profiles were better for patients with myocardial infarction than those with angina and for patients with more severe clinical complexity than those with milder conditions. Conclusions: Health-related and economic benefits are expected from improving adherence to international guidelines recommendations concerning outpatient treatments and monitoring of patients with ACS.

29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021 -- 9 June 2021 through 11 June 2021 -- 170536, 3D shape completion plays a crucial role in transforming the distorted real world data to the digital data which represents the original data accurately. In recent times, there has been several works on 3D shape completion with deep learning models. Due to the input requirements of deep learning models, it is necessary to form the input data into a specific format before feeding into the network. In this work, Multilayer Spherical Depth Parameters used with a specific deep learning model for 3D shape completion and its highly accurate results will be presented. © 2021 IEEE.