Real Sets Research Articles

A Model‐Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in Oncology

ABSTRACTThe primary purpose of an oncology dose‐finding trial for novel anticancer agents has been shifting from determining the maximum tolerated dose to identifying an optimal dose (OD) that is tolerable and therapeutically beneficial for subjects in subsequent clinical trials. In 2022, the FDA Oncology Center of Excellence initiated Project Optimus to reform the paradigm of dose optimization and dose selection in oncology drug development and issued a draft guidance. The guidance suggests that dose‐finding trials include randomized dose–response cohorts of multiple doses and incorporate information on pharmacokinetics (PK) in addition to safety and efficacy data to select the OD. Furthermore, PK information could be a quick alternative to efficacy data to predict the minimum efficacious dose and decide the dose assignment. This article proposes a model‐based trial design for dose optimization with a randomization scheme based on PK outcomes in oncology. A simulation study shows that the proposed design has advantages compared to the other designs in the percentage of correct OD selection and the average number of patients assigned to OD in various realistic settings.

Defective regression models for cure rate data with competing risks

ABSTRACT In this paper, we propose a novel method for the analysis of cure rate data with competing risks using defective distributions. We develop two defective regression models for the analysis of competing risk data subjected to random right censoring. The proposed models enable us to estimate the cure fraction directly from the model. Simultaneously, we also estimate the regression parameters corresponding to each cause of failure using the method of maximum likelihood. We conduct a simulation study to evaluate the finite sample performance of the proposed estimators. The practical usefulness of the procedures is illustrated using two real-life data sets.

Rehabilitation of a quadruple amputee with leukemia: A challenging endeavor

Making a person with quadruple amputation walk again is a challenging task for the rehabilitation team. Quadruple amputation secondary to symmetrical peripheral gangrene is a rare clinical scenario posing challenges in rehabilitation. Literature regarding rehabilitation of persons with multiple amputations is limited. This case describes the rehabilitation of a 57-year-old lady suffering from acute myeloid leukaemia who underwent quadruple amputation. She had undergone bilateral transtibial and bilateral transradial amputation after vasopressor-induced symmetrical peripheral gangrene. In view of expected guarded level of functional independence, ambulatory independence was the primary goal at admission to Department of PMR. The various steps taken in rehabilitation and modifications made to assistive devices are described in this article. Challenges faced during various phases of training, and subsequent ambulation are detailed in this article. Overcoming limitations, the client was made to be an indoor ambulator with appropriate prostheses and mobility aids. She was partially independent for activities of daily life after in-patient rehabilitation. The background of leukaemia and subsequent chemotherapy also affected the rehabilitation of this patient. Although various studies have described cases of quadruple amputation rehabilitation achieving functional independence and ambulation, the absence of specific guidelines and protocols make rehabilitation of persons with multiple amputations inefficient. This case study also shows the need for personalized goal setting for persons with multiple amputations. Realistic goal setting, psychological counselling, and an interdisciplinary approach are imperative in rehabilitation of persons with quadruple amputation. Flexible functional scales specific to persons with multiple amputations are necessary to evaluate such persons objectively. Studies with larger sample size, longer follow-ups, and comprehensive review of existing literature are needed to standardize rehabilitation of quadruple amputation and evaluate the various factors that may affect rehabilitation outcome.

Dicke superradiant heat current enhancement in circuit quantum electrodynamics

Controlling the flow of energy and heat at the microscale is crucial to achieve energy-efficient quantum technologies, for on-chip thermal management, and to realize quantum heat engines and refrigerators. Yet, the efficiency of current quantum technologies is affected by thermal noise, and efficient cooling of quantum devices remains challenging in various solid-state implementations such as superconducting circuits. Collective effects, such as the Dicke superradiant emission, have been exploited to enhance the performance of quantum devices. However, the inherently transient nature of Dicke superradiant emission raises questions about its impact on steady-state properties. Here, we study how to enhance the steady-state heat current flowing between a hot bath and a cold bath through an ensemble of N qubits, that are collectively coupled to the thermal baths. Remarkably, we find a regime where the heat current scales quadratically with N in a finite-size scenario. Conversely, when approaching the thermodynamic limit, we prove that the collective scenario exhibits a parametric enhancement over the noncollective case. We then consider the presence of a third uncontrolled bath, interacting locally with each qubit, that models unavoidable couplings to the external environment. Despite having a nonperturbative effect on the steady-state currents, we show that the collective enhancement is robust to such an addition. Finally, we discuss the feasibility of realizing such a Dicke heat valve with superconducting circuits. Our findings indicate that in a minimal realistic experimental setting with two superconducting qubits, the collective advantage offers an enhancement of approximately 10% compared to the noncollective scenario. Published by the American Physical Society 2024

Visual search for hazardous items: using virtual reality (VR) in laypersons to test wearable displays for firefighters

In virtual reality (VR), we assessed how untrained participants searched for fire sources with the digital twin of a novel augmented reality (AR) device: a firefighter’s helmet equipped with a heat sensor and an integrated display indicating the heat distribution in its field of view. This was compared to the digital twin of a current state-of-the-art device, a handheld thermal imaging camera. The study had three aims: (i) compare the novel device to the current standard, (ii) demonstrate the usefulness of VR for developing AR devices, (iii) investigate visual search in a complex, realistic task free of visual context. Users detected fire sources faster with the thermal camera than with the helmet display. Responses in target-present trials were faster than in target-absent trials for both devices. Fire localization after detection was numerically faster and more accurate, in particular in the horizontal plane, for the helmet display than for the thermal camera. Search was strongly biased to start on the left-hand side of each room, reminiscent of pseudoneglect in scene viewing. Our study exemplifies how VR can be used to study vision in realistic settings, to foster the development of AR devices, and to obtain results relevant to basic science and applications alike.

Enhancing Clinical Education Training with Immersive Reality (XR)

A core element of clinical education is the observed structured clinical examination (OSCE) that simulates real-life clinical practice. These OSCEs can be enhanced through combining the best elements of emerging technologies in the design of enhanced simulation environments to prepare healthcare graduates for changing clinical practice as it integrates new and emerging technologies. New and emerging immersive reality (XR) headsets that allow digital enhancement of practice with real tools and procedures can be combined with haptic feedback such as a high-fidelity manikin within an interactive immersive room that can replicate a wide variety of real-world scenarios at the touch of a button. In this way XR can enhance authentic learning in clinical and first responder practice by enabling exposure to critical elements of clinical simulation in a safe, contextual learning environment that is cost effective and scalable compared to the expense of simulations involving actors and physical real-life sets. In response this concise paper introduces the development of a framework for enhanced simulation practice using the Blended Learning Simulation Suite (BLISS).

Sodium-Glucose Cotransporter 2 Inhibitors Improve Body Composition by Increasing the Skeletal Muscle Mass/Fat Mass Ratio in Patients with Type 2 Diabetes: A 52-Week Prospective Real-Life Study

Background: Sodium-glucose cotransporter 2 inhibitors (SGLT2is) induce body weight loss, but their effect on skeletal muscle mass (SMM) and strength needs to be better elucidated. Objectives: This study aimed to evaluate the effects of SGLT2i on SMM in a real-life population setting of patients with type 2 diabetes (T2D). Secondary outcomes included changes in liver steatosis and in anthropometric and glucometabolic parameters. Methods: Seventy-one patients were treated with SGLT2is as an add-on to metformin for 52 consecutive weeks. Visits were scheduled at baseline (T0) and after 6 (T6) and 12 months of therapy (T12) and included the checking of laboratory tests, measurement of anthropometric parameters, bioimpedance analysis of body composition, and abdominal ultrasound (US). Results: Fat mass (FM) and visceral adipose tissue (VAT) progressively decreased compared to the baseline (FM: −2.9 ± 0.6 kg at T6; −2.8 ± 0.6 kg at T12; VAT: −0.3 ± 0.1 L at T6; −0.4 ± 0.1 L at T12; all p < 0.01). Changes in SMM were less pronounced (−0.4 ± 0.3 kg at T6, ns; −0.7 ± 0.4 kg at T12, p < 0.05), yielding a beneficial increase in the SMM/FM ratio (+0.3 ± 0.05 at T6 and +0.2 ± 0.05 at T12, all p < 0.01). No significant changes in sarcopenia, sarcopenic obesity, fat-free mass, muscle strength, and water compartments were observed at the end of the follow-up period. Anthropometric and glucometabolic parameters, insulin resistance, liver enzymes, and biometric indices and US grading of hepatic steatosis improved throughout this study. Conclusions: In a real-life setting, SGLT2i therapy is associated with weight loss attributable to FM rather than SMM loss without any relevant deterioration in muscle strength. In addition, SGLT2is proved to have beneficial effects on steatotic liver disease.

Benign Evolution of Complex Regional Pain Syndrome (CRPS) Type 1 in Patients Treated with Intravenous Neridronate: A Single-Center Real-Life Experience

Objective: To investigate the long-term effects of intravenous neridronate treatment in patients with complex regional pain syndrome type 1 (CRPS) in a real-life setting. Methods: We conducted a retrospective study on consecutive CRPS patients treated at our hospital from February 2018 to July 2023. All were treated within three months of the onset of CRPS symptoms. The Patient-Reported Outcomes Measurement Information System 29-Item Health Profile (PROMIS-29) version 2.1 was administered. The main outcome of interest was the evolution of the PROMIS-29 scores from baseline to the last follow-up visit. Patients were categorized as “complete responders” or “non-complete responders”. The association of clinical and demographic variables with a complete response was analyzed using chi-square tests and univariate logistic regression. Results: Thirty-six patients were included, with a median follow-up time of 4.8 years. A significant improvement was noted in the mean numerical pain rating scale (from 6.4 ± 1.9 to 3.1 ± 2.4, p < 0.001), as well as across all PROMIS-29 domains. Physical function improved from 34.2 ± 4.9 to 49.2 ± 9.9, p < 0.001; anxiety from 58.0 ± 6.7 to 49.6 ± 6.9, p < 0.001; depression from 55.3 ± 6.3 to 47.7 ± 6.6, p < 0.001; fatigue from 55.7 ± 7.7 to 50.9 ± 8.7, p < 0.001; sleep disturbance from 53.8 ± 6.8 to 51.3 ± 6.6, p = 0.034; social roles and activities from 41.8 ± 5.2 to 51.8 ± 8.9, p < 0.001; and pain interference from 64.1 ± 5.9 to 52.4 ± 9.9, p < 0.001. The likelihood of achieving a complete response was associated with the male sex, foot or ankle injuries (compared to hand and wrist injuries), and a younger age. No association was found with the type of inciting event or with the body mass index. Conclusions: Our real-life data indicate that early treatment with neridronate leads to substantial benefits in patients affected by CRPS type 1. The strongest responses are seen in young patients, males, and those with lower limb involvement.

Predicting arbitrary state properties from single Hamiltonian quench dynamics

Analog quantum simulation is an essential routine for quantum computing and plays a crucial role in studying quantum many-body physics. Typically, the quantum evolution of an analog simulator is largely determined by its physical characteristics, lacking the precise control or versatility of quantum gates. This limitation poses challenges in extracting physical properties on analog quantum simulators, an essential step of quantum simulations. To address this issue, we introduce the protocol, which uses a single quench Hamiltonian for estimating arbitrary state properties, eliminating the need for ancillary systems and random unitaries. Additionally, we derive the sample complexity of this protocol and show that it performs comparably to the classical shadow protocol. The Hamiltonian shadow protocol does not require sophisticated control and can be applied to a wide range of analog quantum simulators. We demonstrate its utility through numerical demonstrations with Rydberg atom arrays under realistic parameter settings. The new protocol significantly broadens the application of randomized measurements for analog quantum simulators without precise control and ancillary systems. Published by the American Physical Society 2024

Safety and Efficacy of Dalbavancin in Real Life: Retrospective Analysis of a Large Monocentric Case Series of Patients Treated for Skin/Soft Tissue and Other Difficult-to-Treat Infections

Background: Dalbavancin is a long-acting lipoglycopeptide, approved for treatment of skin and skin structure infections. Its PK/PD profile and safety allow for short hospital stays even in the case of difficult-to-treat infections requiring long courses of therapy, e.g., osteomyelitis, cardiovascular, and prosthetic infections. Objectives: We aimed to evaluate the safety and efficacy of dalbavancin in real life settings for both in-label and off-label indications. Methods: retrospective evaluation of all consecutive patients treated with dalbavancin at our site between May 2017 and September 2021. Results: A total of 100 patients treated with dalbavancin and followed up for 6 months after treatment (58% male; median age 63.5 years, median Charlson Comorbidity Index CCI = 2.7, 28% inpatients) were included with the following indications: acute bacterial skin and skin structure infections (22%), bone and prosthetic infections (57%), and cardiovascular infections (19%). Infections were caused by MSSA (30%), MRSA (5%), MR-CoNS (20%), and Streptococcus spp. (8%). In 32 cases, no isolate was obtained. The average number of infusions was 5 (s.d. = 3). Neither ensuing alteration of renal function nor neutropenia or thrombocytopenia were observed during treatment and follow-up. Two self-limiting skin rashes occurred. The overall clinical success rate was 84%—91% for registered and 82% for unregistered indications. The prescription of higher loading doses was the only predictor independently associated with better outcomes in multivariate models (OR: 5.2, 95%CI: 1.5–17.9, p < 0.01). Conclusions: Dalbavancin proved to be effective for skin and skin structure infections, as well as for difficult-to-treat infections in highly comorbid patients. Regarding tolerability, our results support the use of dalbavancin for long-lasting treatments of deep-seated infections.

A mixed methods study of student pharmacist perceptions of their confidence and competence in the provision of clinical assessment

Abstract Introduction Pharmacist involvement in clinical assessment or examination has recently come into the focus in the United Kingdom with the transition of the pharmacy workforce to prescribers. Clinical assessment starts with the collection of information on an individual’s past medical history and clinical presentation, and the interpretation of tests, observations, and physical assessments to inform a differential diagnosis.1 The range of clinical skills student pharmacists gain from placements during the MPharm is variable and shaped by local demands for pharmacy services. Therefore, there is a need for additional training on clinical assessment skills in classroom teaching.2-4 Aim To identify student pharmacist perceptions and beliefs on their competence in conducting clinical assessment. Methods Ethics approval for this research study was granted by the Strathclyde Institute of Pharmacy and Biomedical Sciences Ethics Committee and conducted between October-December 2023. A mixed-methods study was conducted using a survey and focus group discussions developed from the literature and validated through discussion to collect student pharmacist perceptions of the role of the pharmacist and current gaps/barriers to pharmacist provision of clinical assessments. Students from all years of the MPharm were invited by email to participate (n=615). Audio recordings captured from focus group discussions were thematically analysed to identify key themes. Results Four focus groups were held with a total of 30 students. There were 89 respondents to the online survey (119 in total). Across both approaches, five key themes were identified from the survey and four from the focus group interviews. These themes centred around student pharmacist perceived role of the pharmacist, time and technical resources available in the pharmacy workplace, and the current curriculum. Most students agreed that such clinics would be beneficial to their training. Discussion and Conclusions Student-led clinics are gaining popularity as a work-based approach to learning. We found varied perceptions of the pharmacist’s role by participant response, suggesting that the clinical nature of pharmacy as a profession must be highlighted to prospective students to ensure those entering the profession are aware of the responsibilities they may be required to undertake. A limitation of this study is that student perceptions reflect the views of a single institution. Careful design of future clinics is required to ensure their seamless integration in the existing MPharm curriculum, in a realistic setting reflecting the workplace, and sufficient support from practitioners to implement them. Future work in this area should focus on how clinical assessment skills should be learned and assessed in student populations.

Beyond Recommendations: From Backward to Forward AI Support of Pilots' Decision-Making Process

AI is anticipated to enhance human decision-making in high-stakes domains like aviation, but adoption is often hindered by challenges such as inappropriate reliance and poor alignment with users' decision-making. Recent research suggests that a core underlying issue is the recommendation-centric design of many AI systems, i.e., they give end-to-end recommendations and ignore the rest of the decision-making process. Alternative support paradigms are rare, and it remains unclear how the few that do exist compare to recommendation-centric support. In this work, we aimed to empirically compare recommendation-centric support to an alternative paradigm, continuous support, in the context of diversions in aviation. We conducted a mixed-methods study with 32 professional pilots in a realistic setting. To ensure the quality of our study scenarios, we conducted a focus group with four additional pilots prior to the study. We found that continuous support can support pilots' decision-making in a forward direction, allowing them to think more beyond the limits of the system and make faster decisions when combined with recommendations, though the forward support can be disrupted. Participants' statements further suggest a shift in design goal away from providing recommendations, to supporting quick information gathering. Our results show ways to design more helpful and effective AI decision support that goes beyond end-to-end recommendations.

Device-independent certification of desirable properties with a confidence interval

In the development of quantum technologies, a reliable means for characterizing quantum devices, be it a measurement device, a state-preparation device, or a transformation device, is crucial. However, the conventional approach based on, for example, quantum state tomography or process tomography relies on assumptions that are often not necessarily justifiable in a realistic experimental setting. Although the device-independent (DI) approach to this problem bypasses the shortcomings above by making only minimal, justifiable assumptions, most of the theoretical proposals to date only work in the idealized setting where independent and identically distributed (i.i.d.) trials are assumed. Here, we provide a versatile solution for rigorous device-independent certification that does not rely on the i.i.d. assumption. Specifically, we describe how the prediction-based ratio (PBR) protocol and martingale-based protocol developed for hypothesis testing can be applied in the present context to achieve a device-independent certification of desirable properties with confidence interval (CI). To illustrate the versatility of these methods, we demonstrate how we can use them to certify—with finite data—the underlying negativity, Hilbert space dimension, entanglement depth, and fidelity to some target pure state. In particular, we provide examples showing how the amount of certifiable negativity and fidelity scales with the number of trials and how many experimental trials one needs to certify a qutrit state space or the presence of genuine tripartite entanglement. Overall, we have found that the PBR protocol and the martingale-based protocol often offer similar performance, even though the latter does have to presuppose any witness (Bell-like inequality). In contrast, our findings also show that the performance of the martingale-based protocol may be severely affected by one’s choice of Bell-like inequality. Intriguingly, a Bell function useful for self-testing does not necessarily give the optimal confidence-gain rate for certifying the fidelity to the corresponding target state.

Attenuation of bulk waves using locally resonant soil-coupled metabarriers

Abstract Low frequency ground-borne vibrations generated by transport infrastructure are one of the most serious causes of disturbance to the general population. One possibility to reduce this problem is to use the wave filtering properties of elastic metamaterials. However, their integration in the soil complicates the prediction of their response, and the influence of soil-structure interaction needs to be correctly evaluated for an efficient design. The aim of this work is to experimentally evaluate the efficiency of metamaterial trench barriers set in soil in attenuating vibrations, using low-frequency local resonance mechanisms. A lab scale model is proposed comprising different resonating structures and a cylindrical encasement is adopted to couple the structure to the soil. The influence of various parameters is evaluated, such as metamaterial structure, geometrical characteristics of the resonator, and constituent materials. Finite Element simulations are used to develop a suitable design, analysing mode shapes and resonance frequencies of structures with and without the surrounding encasement. Experimental modal analysis is then performed on the corresponding fabricated samples, providing both model validation and out-of-soil mechanical characterization. Finally, vibration transmission loss measurements are performed in a setup in which different resonant metamaterial barriers are embedded into the soil sample, allowing the evaluation of barrier performance. Results indicate that the metamaterial structures provide good attenuation of vibrations in selected intervals in the low to high frequency range (1–5 kHz), demonstrating the feasibility of the approach in a scaled sample. Preliminary data regarding the structures providing preferable design characteristics is also obtained. These results can be useful for the design of trench barriers scaled to large dimensions in more realistic applicative settings.

A two-echelon multi-trip vehicle routing problem with synchronization for an integrated water- and land-based transportation system

This study focuses on two-echelon synchronized logistics problems in the context of integrated water- and land-based transportation (IWLT) systems. The aim is to meet the increasing demand in city logistics as a result of the growth in transport activities, including parcel delivery, food delivery, and waste collection. We propose two models, a novel mixed integer linear joint model, and a logic-based Benders’ decomposition (LBBD) model, for a two-echelon problem under realistic settings such as multi-trips, time windows, and synchronization at the satellites with no storage and limited resource capacities. The objective is to optimize transfers and satellite assignments, thereby reducing overall logistics costs for street vehicles and vessels. Computational experiments demonstrate that the LBBD model is more robust in terms of solution quality and solution time on average while the added value of the LBBD is more evident when solving large-scale instances with 100 customers, reducing the overall costs by 10.6% on average and significantly reducing the fleet costs on both networks. Furthermore, we assess the effect of changing cost parameters and satellite locations in the proposed IWLT system–analyzing system behavior and suggesting potential improvements–and evaluate several system alternatives in city logistics–consisting of different transportation network designs (single- and two-echelon), vehicle types, and operational constraints. On average, the proposed two-echelon IWLT system reduces the number of kilometers traveled by vehicles at street level by ranging from 20% to 30% compared to a typical single-echelon service design that relies solely on trucks.

Logistics service sharing in cross-border e-commerce

While the demand for cross-border e-commerce has grown rapidly, challenges have emerged for both retailers and consumers participating in this global market. Retailers have been struggling with high logistics costs to fulfill cross-border demand, while the lack of trust in foreign retailers is a major issue for consumers. In this paper, we study a cross-border collaboration scheme between a domestic and a foreign retailer to mitigate these challenges. This entails a co-opetition framework where the domestic retailer performs the last-mile delivery of the foreign retailer’s orders in exchange for a logistics service fee. We model demand via a Multinomial Logit (MNL) choice model where the consumers are trust- and price-sensitive. We compare the market outcomes of the two retailers in “pre-collaboration” and “post-collaboration” settings. We find that there exist win-win outcomes where both retailers benefit from collaboration under realistic settings. We also show that a cooperative mechanism can lead to higher profits for both retailers compared to the non-cooperative mechanism for setting the logistics service fee, if the contract terms are decided carefully.

HFS-CSR: A hierarchical feature selection method based on correlation and structural redundancy

Feature selection (FS) is a crucial step in data engineering, as it not only saves time and resources for model training but also improves the prediction performance. In many realistic data sets, the feature space is formed by binary features which are related via generalization-specialization relationships (a.k.a., hierarchical feature space). These interdependencies among features, which can be described via a directed acyclic graph, present new challenges for classical FS methods. In this paper, a Hierarchical Feature Selection method based on Correlation and Structural Redundancy (HFS-CSR) is proposed to address it. In HFS-CSR, the correlation between features and the class label is measured based on Fisher Score whereas the structural redundancy among features are assessed quantitatively via hierarchical redundancy and depth penalties. The importance of features are determined by combining them adaptively for feature filtering. Experiments are conducted based on two kinds of typical data sets with hierarchical feature space: aging gene data sets and NLP data sets. The results demonstrate that HFS-CSR can achieve better performance compared with seven existing FS methods.

Beyond breathalyzers: AI-powered speech analysis for alcohol intoxication detection

Detecting potential alcohol inebriation or intoxication status holds paramount significance for social prevention and security. Beyond its association with long-term health effects, alcohol consumption can lead to immediate consequences, including reduced control over one’s actions, with traffic fatalities representing one of the most tragic outcomes.This study leveraged the Alcohol Language corpus, involving 162 subjects recorded both in sober and inebriated states. Participants provided 60 speech samples while sober and 30 when intoxicated, all within a realistic car setting using head-mounted microphones. Our research endeavors encompassed comprehensive stratified statistical tests to examine the impact of alcohol consumption on speech production while uncovering the influence of covariates such as age, gender, and drinking habits.Additionally, we introduced a speaker-neutral machine learning algorithm, based on the Domain-Adversarial Neural Network architecture. This approach aimed to overcome challenges posed by individual differences that often complicate intoxicated speech analysis. Notably, our findings highlighted the effectiveness of features like the RASTA-filtered auditory spectrum. Nevertheless, the results from statistical tests emphasized the need for techniques that minimize inter-subject variability.As for the automatic classification, the proposed architecture exhibited promising results, yielding a classification accuracy slightly exceeding 70% on an independent test set. Although preliminary, our research demonstrates the potential for detecting alcohol-induced speech changes, benefiting societal well-being and security. It also underscores the importance of developing strategies that account for individual differences while harnessing the power of automatic models to effectively distinguish between sober and intoxicated individuals.

Treatment of atopic dermatitis with abrocitinib in real practice in Spain: efficacy and safety results from a 24-week multicenter study.

Abrocitinib, a selective JAK 1 inhibitor, was recently approved in Europe. Despite its approval, real-world data on its efficacy and safety in treating moderate-to-severe atopic dermatitis (AD) remains limited. This study aimed to evaluate the short-term effectiveness and safety of abrocitinib in a real-life setting for patients with moderate-to-severe AD. We conducted a retrospective multicenter study involving adult patients with moderate-to-severe AD who started abrocitinib treatment between May 1, 2023, and September 30, 2023, in 15 Spanish hospitals. Treatment doses were 100 or 200 mg daily, based on clinical assessment. Data collection included patient demographics, AD history, comorbidities, previous treatments, and disease severity indicators such as SCORing atopic dermatitis (SCORAD), Eczema Area and Severity Index (EASI), body surface area, and Peak Pruritus NRS scores at baseline, 4, 12, and 24 weeks. Quality of life was measured using the Dermatology Life Quality Index (DLQI), and safety was assessed by monitoring adverse reactions and various biochemical parameters. The cohort comprised 76 patients with an average age of 33.93 years; 57.89% were male. Before abrocitinib, 36.84% were naïve to advanced therapies. The baseline mean scores were SCORAD 47.04, EASI 21.79, and DLQI 15.01. At Week 24, there were significant improvements: EASI was reduced to 2.81, and 70.58% of the patients achieved EASI 75. However, 18.42% discontinued treatment mainly due to inefficacy or adverse effects. The safety profile was favorable, with 22.37% reporting mild adverse events (AEs) and one serious case of cutaneous lymphoma. This first Spanish series assessing abrocitinib in real-world conditions reveals a significant improvement in AD symptoms and quality of life in a range of severity and prior treatment failures. Abrocitinib was well-tolerated, with few serious AEs, highlighting its potential as an effective treatment option for AD.

A simheuristic for project portfolio optimization combining individual project risk, scheduling effects, interruptions, and project risk correlations

This paper introduces a simheuristic method to the Project Portfolio Selection Problem, designed to maximize the net present value of the portfolio while considering uncertain costs, schedules, interruptions, and inter-project risk correlations. The novel approach combines techniques from Monte Carlo simulation, critical path analysis, queuing theory, and optimization, integrating baseline schedules, project-level uncertainties, budgetary constraints, and risk correlations in a single model. A computational experiment is conducted on a realistic set of ten candidate projects and validated respect to the deterministic version of the problem, demonstrating its ability to select near optimal portfolio proposals with varying combinations of risk and net present value. The findings highlight the significant impact of factors such as contingency reserve allocation policies, operational interruptions, and project risk correlations on portfolio decisions, constituting a helpful framework for the decision-makers at portfolio level.