Update Rate Research Articles

Theoretical study of H-atom abstraction by CH3OȮ radicals from aldehydes and alcohols: Ab initio and comprehensive kinetic modeling

Reaction kinetics of H-atom abstraction from C1C3 alcohols, including CH3OH, C2H5OH, NC3H7OH, IC3H7OH, and C1C2 aldehydes, including CH2O, CH3CHO, by CH3OȮ radicals is investigated in this work through high-level ab initio calculations. Electronic structure optimizations are performed for all the stationary points with M06–2X/6−311++g(d,p) method. Quadratic configuration interaction method QCISD(T)/cc-pVXZ (where X = D and T) and Møller–Plesset perturbation theory MP2/cc-pVXZ (where X = D, T, and Q) are used to calculate single point energies. Subsequently, rate coefficients for all H-atom abstraction channels are determined using conventional transition state theory with unsymmetric tunneling corrections. These calculated results are updated to a recently updated model and then compared against expansive experimental datasets to investigate their influence on the model prediction performance. The updated model shows obvious discrepancies with the original model, where the updated model is less reactive for CH3CHO, C2H5OH, NC3H7OH, and IC3H7OH, while showing negligible differences for CH3OH and CH2O due to the lack of CH3OȮ radical formation. Sensitivity and flux analyses are further conducted, through which the difference between the studied species in their oxidation pathways and the relative importance of H-atom abstraction by CH3OȮ radicals is highlighted. With the updated rate parameters, the branching ratios of H-atom abstractions from CH2O and CH3CHO are significantly altered for CH3CHO, C2H5OH, NC3H7OH and IC3H7OH, with an obvious shift away from the abstraction channel by CH3OȮ. Further analyses highlight the critical roles of CH2O and CH3CHO chemistry as core chemistries for large hydrocarbons (e.g., carbon number > 1), which have been inadequately described in existing chemistry models. Systematic efforts are urgently needed to improve the existing CH2O and CH3CHO chemistries.

Management of Positioning Functions in Cellular Networks for Time-Sensitive Transportation Applications

Device positioning has generally been recognized as an enabling technology for numerous vehicular applications in intelligent transportation systems (ITS). The downlink time difference of arrival (DL-TDOA) technique in cellular networks requires range information of geographically diverse base stations (BSs) to be measured by user equipment (UE) through the positioning reference signal (PRS). However, inter-cell interference from surrounding BSs can be particularly serious under poor network planning or dense deployments. This may lead to a relatively longer measurement time to locate the UE, causing an unacceptable location update rate to time-sensitive applications. In this case, PRS muting of certain wireless resources has been envisioned as a promising solution to increase the detectability of a weak BS. In this paper, to reduce UE measurement latency while ensuring high location accuracy, we propose a muting strategy managed by positioning functions that utilizes a combination of optimized pseudo-random sequences (CO-PRS) for multiple BSs to coordinate the muting of PRS resources. The original sequence is first truncated according to the muting period, and a modified greedy selection is performed to form a set of control sequences as the muting configurations (MC) with balance and concurrency constraints. Moreover, efficient information exchange can be achieved with the seeds used for regenerating the MC. Extensive simulations demonstrate that the proposed scheme outperforms the conventional random and ideal muting benchmarks in terms of measurement latency by about 30%, especially when dealing with severe near-far problems in cellular networks.

Event-Based Security Control for Markov Jump Cyber–Physical Systems under Denial-of-Service Attacks: A Dual-Mode Switching Strategy

This paper studies the design of dual-mode resilient event-triggered control strategy for Markov jump cyber–physical systems (MJCPSs) under denial-of-service (DoS) attacks. Firstly, a novel resilient event-triggering scheme dependent on the DoS signal is developed to select the corresponding control protocol based on the current network quality of services. Particularly, the potential relationship between the triggering signal and system mode under DoS attacks is discussed, aiming to eliminate both Zeno behavior and singular triggering behavior by calculating the minimum and maximum data update rates. Then, we design an event-based dual-mode security controller to ensure that the closed-loop system has stochastic stability and good robust H∞ performance under DoS attacks. By constructing a Lyapunov–Krasovskii functional which depends on the lower and upper bounds of time delay, sufficient conditions for the existence of dual-mode security controller gains and resilient triggering parameters are presented with the LMI form. Finally, simulation results show that the proposed security control strategy has good robustness against DoS attacks.

Analysis of Chinese National Standards on Packaging and the Environment (CNSPE) Based on Standard Literature Bibliometrics

This paper aims to understand the status of the Chinese National Standards on Packaging and the Environment (CNSPE), analyze the existing problems, and discover their possible solutions. Based on the standard bibliometric literature, the metadata information from the CNSPE have been collected and analyzed. The results indicated that the number of CNSPE released showed a wave-like growth with two peaks during 2006–2010 and 2016–2020 driven by both external and internal factors. The basic standard was the main standard sort. The average valid period of a CNSPE was 5.90 years, while the update rate was 23.33%. Public institutions lead the drafting committee of the CNSPE. The percentage of adopting the international or foreign standards was 28.86%, and the average conversion time was 7.61 years. There were four problems deduced from the results, including the unbalanced supply of different sorts of CNSPE, long valid period of standards with low update rates, low engagement of the enterprises, and loose links between national standards and international standards. The corresponding solutions are (1) strengthening market research and combining with policy development to optimize the supply of different sorts of CNSPE; (2) improving the process management ability of standardization organizations to enhance the supervision and feedback of standards development and implementation; (3) providing trainings and broadening dissemination while fulfilling the reward mechanism; and (4) enhancing the compatibility between the national standards system and the international standards system to promote the standard internationalization level.

Global epidemiology of actinic keratosis in the general population: a systematic review and meta-analysis.

Actinic keratosis (AK) is a common dermatological condition, and among the most common dermatological diagnoses in older populations. Although the prevalence of AK depends on demographic and environmental factors, little is known about the global context of AK. To provide a comprehensive and updated analysis of the global prevalence rate and incidence of AK in the general population through a systematic review and meta-analysis, and - through subgroup analyses - to identify high-risk phenotypes, demographic and lifestyle risk factors and regional variations in disease prevalence. A systematic search of Embase, MEDLINE, Web of Science and Google Scholar was performed on 20 May 2022. Two reviewers independently screened and assessed the quality of each study using a validated critical appraisal checklist. Epidemiological measurements (e.g. prevalence) from individual studies performed in the general population were then pooled in a random-effects meta-analysis. Subgroup analyses (i.e. population age, geographical region, occupation, sex and study quality) were conducted. Of the 65 articles that made it through the full-text screening, 60 reported a point prevalence. A meta-analysis of these articles yielded an overall point prevalence of 14% [95% confidence interval (CI) 14-15]. In further analyses, the calculated prevalence rate varied depending on subgroup. The pooled incidence rate from the seven eligible studies analysed was 1928 per 100 000 person-years (PY; 95% CI -439 to 4294). This comprehensive meta-analysis provides an updated global prevalence rate of AK of 14%, indicating a significant worldwide disease burden. The incidence rate of AK was found to be 1928 per 100 000 PY, emphasizing a growing public health concern. However, high heterogeneity among studies suggests that various factors influence the AK prevalence rate, necessitating further research to understand the observed differences.

Joint mixed-timescale optimization of content caching and delivery policy in NOMA-based vehicular networks

Recently, the development of Internet of Vehicles (IoV) and the increasing popularity of video applications have led to the fast-growing in-car video demand causing numerous challenges in wireless networks. Pre-caching and non-orthogonal multiple access (NOMA) have been regarded as two effective techniques to alleviate the mentioned challenge. In this paper, we propose a cache-aided cooperative transmission to maximize the quality of service (QoS) in the NOMA-based vehicular network. A QoS-oriented joint optimization problem is formulated, which incorporates power allocation, content caching, and delivery strategy. Considering, on the one hand, the slow update rate of cache content and, on the other hand, frequent handovers of vehicles between different transmitters, a mixed-timescale optimization is proposed where the serving cache is updated in a long-term phase, while content delivery and power allocation are optimized in a short-term phase. In the proposed approach, content caching is determined based on future user requests, vehicle tracking, and other delivery information. To make this possible, we leverage a substantial number of stochastic samples to approximate content caching in the long-term caching phase. Due to the NOMA-based transmission and integral variables, the setting leads to a Mixed Integer Non-Linear Programming (MINLP) problem, which is NP-hard. To solve this problem, an iterative method based on sample average approximation (SAA) and Successive Convex Approximation (SCA) is applied. Simulations demonstrate that the proposed algorithm can achieve better QoS than other recently proposed transmission schemes.

A dual adaptive robust control for nonlinear systems with parameter and state estimation

Stabilization and learning are imperative to the high-performance feedback control of nonlinear systems. A dual adaptive robust control (DARC) scheme is proposed for nonlinear systems with model uncertainties to achieve a desired level of performance. Only the output of the nonlinear system is accessible in this work, all the states and parameters are learned online. Firstly, the DARC uses the prior physical bounds of systems to design a discontinuous projection with update rate limits which confines the bounds of parameter and state estimation. Then robustness of the nonlinear system can be guaranteed by the deterministic robust control (DRC) method. Secondly, a dual adaptive estimation mechanism (DAEM) is developed to learn the unknown parameters and states of systems. One part of the DAEM is the bounded gain forgetting (BGF) estimator, which is developed to handle inaccurate parameters and parametric variations. The other is the adaptive unscented Kalman filter (AUKF) synthesized for state estimation. The AUKF contains a statistic estimator based on the maximum a posterior (MAP) rule to estimate the unknown covariance matrix. Finally, simulation results illustrate the effectiveness of the suggested method.

Using the LSTM Neural Network and the UWB Positioning System to Predict the Position of Low and High Speed Moving Objects.

Automation of transportation will play a crucial role in the future when people driving vehicles will be replaced by autonomous systems. Currently, the positioning systems are not used alone but are combined in order to create cooperative positioning systems. The ultra-wideband (UWB) system is an excellent alternative to the global positioning system (GPS) in a limited area but has some drawbacks. Despite many advantages of various object positioning systems, none is free from the problem of object displacement during measurement (data acquisition), which affects positioning accuracy. In addition, temporarily missing data from the absolute positioning system can lead to dangerous situations. Moreover, data pre-processing is unavoidable and takes some time, affecting additionally the object's displacement in relation to its previous position and its starting point of the new positioning process. So, the prediction of the position of an object is necessary to minimize the time when the position is unknown or out of date, especially when the object is moving at high speed and the position update rate is low. This article proposes using the long short-term memory (LSTM) artificial neural network to predict objects' positions based on historical data from the UWB system and inertial navigation. The proposed solution creates a reliable positioning system that predicts 10 positions of low and high-speed moving objects with an error below 10 cm. Position prediction allows detection of possible collisions-the intersection of the trajectories of moving objects.

Ultrasonic- and IMU-Based High-Precision UAV Localization for the Low-Cost Autonomous Inspection in Oil and Gas Pressure Vessels

With the increasing demands for unmanned aerial vehicle (UAV) based autonomous inspections in the oil and gas industry, one of the challenging issues for 3D UAV positioning has emerged due to the satellite signal blocking. Considering the existing characteristics of the ultrasonic based technique, such as the low cost, extremely lightweight and high positioning accuracy, it can be promising as the potential solution. Nevertheless, the low position update rate and vulnerable positioning performance to the changing environment still limit its applications on UAV. Therefore, in this article, an ultrasonic and inertial measurement unit (IMU) based localisation algorithm and low cost UAV autonomous inspection system are presented. With the incorporation of the IMU, the position update rate, accuracy and stability of the algorithm can all be significantly improved. This is done by the adaptively estimated noise covariance matrices through the proposed adaptive extended Kalman filter (AEKF) algorithm and the added weighting factors. Followed by, an additional virtual observation process is presented to overcome the unavailability of the observation information for further performance improvement. Finally, extensive numerical results and field tests demonstrate that the proposed algorithm and system can achieve the high update rate, reliable, accurate and precision UAV positioning in oil and gas pressure vessels and are feasible for the UAV autonomous inspection in these environments.

Closed-Loop Magnetic Manipulation for Robotic Transesophageal Echocardiography

This article presents a closed-loop magnetic manipulation framework for robotic transesophageal echocardiography (TEE) acquisitions. Different from previous work on intracorporeal robotic ultrasound acquisitions that focus on continuum robot control, we first investigate the use of magnetic control methods for more direct, intuitive, and accurate manipulation of the distal tip of the probe. We modify a standard TEE probe by attaching a permanent magnet and an inertial measurement unit (IMU) sensor to the probe tip and replacing the flexible gastroscope with a soft tether containing only wires for transmitting ultrasound and IMU data and show that six-degree-of-freedom (DOF) localization and five-DOF closed-loop control of the probe can be achieved with an external permanent magnet based on the fusion of internal inertial measurement and external magnetic field sensing data. The proposed method does not require complex structures or motions of the actuator and the probe compared with existing magnetic manipulation methods. We have conducted extensive experiments to validate the effectiveness of the framework in terms of localization accuracy, update rate, workspace size, and tracking accuracy. In addition, our results obtained on a realistic cardiac tissue-mimicking phantom show that the proposed framework is applicable in real conditions and can generally meet the requirements for teleoperated TEE acquisitions.

A method to improve the update rate of underwater acoustic positioning system

Underwater positioning system obtains relative position between a transponder and a transceiver by measuring round trip time (RTT) and angle of arrival. The position update rate (PUR) cannot be greater than 1/RTT, and when one transceiver locates multiple transponders, the PUR becomes smaller. This paper proposes a method to increase the PUR. The proposed method minimizes “idle time” by allowing the transceiver to send additional pings without packet transmission-reception collisions, rather than waiting for the response to the previous ping sent to the transponder. It is essential that the reception (transmission) of the ping and the transmission (reception) of the response should not be overlapped in the transponder (transceiver). In order to avoid these collisions, the ping transmission time is adaptively determined by considering the bound of packet reception times drawn by ping duration (PD), response signal duration (RD), and the maximum relative speed. In addition, the transceiver assigns a delay before sending the response signal upon receiving each ping. These adaptive features effectively adapt to changes due to mobility. We derive a theoretical upper bound of the PUR and verify this bound by computer simulations. [Work supported by KIMST funded by the Agency of Korea Coast Guard (KIMST-20210547).]

National, regional, and global estimates of preterm birth in 2020, with trends from 2010: a systematic analysis

Preterm birth is the leading cause of neonatal mortality and is associated with long-term physical, neurodevelopmental, and socioeconomic effects. This study updated national preterm birth rates and trends, plus novel estimates by gestational age subgroups, to inform progress towards global health goals and targets, and aimed to update country, regional, and global estimates of preterm birth for 2020 in addition to trends between 2010 and 2020. We systematically searched population-based, nationally representative data on preterm birth from Jan 1, 2010, to Dec 31, 2020 and study data (26 March-14 April, 2021) for countries and areas with no national-level data. The analysis included 679 data points (86% nationally representative administrative data [582 of 679 data points]) from 103 countries and areas (62% of countries and areas having nationally representative administrative data [64 of 103 data points]). A Bayesian hierarchical regression was used for estimating country-level preterm rates, which incoporated country-specific intercepts, low birthweight as a covariate, non-linear time trends, and bias adjustments based on a data quality categorisation, and other indicators such as method of gestational age estimation. An estimated 13·4 million (95% credible interval [CrI] 12·3-15·2 million) newborn babies were born preterm (<37 weeks) in 2020 (9·9% of all births [95% CrI 9·1-11·2]) compared with 13·8 million (12·7-15·5 million) in 2010 (9·8% of all births [9·0-11·0]) worldwide. The global annual rate of reduction was estimated at -0·14% from 2010 to 2020. In total, 55·6% of total livebirths are in southern Asia (26·8% [36 099 000 of 134 767 000]) and sub-Saharan Africa (28·7% [38 819 300 of 134 767 000]), yet these two regions accounted for approximately 65% (8 692 000 of 13 376 200) of all preterm births globally in 2020. Of the 33 countries and areas in the highest data quality category, none were in southern Asia or sub-Saharan Africa compared with 94% (30 of 32 countries) in high-income countries and areas. Worldwide from 2010 to 2020, approximately 15% of all preterm births occurred at less than 32 weeks of gestation, requiring more neonatal care (<28 weeks: 4·2%, 95% CI 3·1-5·0, 567 800 [410 200-663 200 newborn babies]); 28-32 weeks: 10·4% [9·5-10·6], 1 392 500 [1 274 800-1 422 600 newborn babies]). There has been no measurable change in preterm birth rates over the last decade at global level. Despite increasing facility birth rates and substantial focus on routine health data systems, there remain many missed opportunities to improve preterm birth data. Gaps in national routine data for preterm birth are most marked in regions of southern Asia and sub-Saharan Africa, which also have the highest estimated burden of preterm births. Countries need to prioritise programmatic investments to prevent preterm birth and to ensure evidence-based quality care when preterm birth occurs. Investments in improving data quality are crucial so that preterm birth data can be improved and used for action and accountability processes. The Children's Investment Fund Foundation and the UNDP, United Nations Population Fund-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction.

Optimal Broadcast Scheduling Algorithm for a Multi-AUV Acoustic Communication Network

In systems of multiple autonomous underwater vehicles (AUVs), to achieve cooperative operation and cluster intelligence, information is often disseminated via broadcasting. However, due to the long propagation delay and slow transmission rate of underwater acoustic communication, traditional broadcast scheduling algorithms require a long broadcast period to avoid signal collision. To improve the channel utilization rate as much as possible and improve the update rate for broadcast information, we propose an optimal broadcast scheduling algorithm. This algorithm uses the location information of AUVs to adjust the broadcast sequence and broadcast schedule, to achieve the shortest possible collision-free broadcast period in the broadcast network for the current node distribution. Simulation experiments show that this algorithm can achieve a broadcast period much shorter than that of traditional TDMA and higher channel utilization without signal collision. In addition, the simulations prove the feasibility of applying the algorithm in an actual MAC protocol.

Differential Evolution With Domain Transform

Although a significant advancement of differential evolution (DE) for global optimization has been witnessed in the past two decades, the problems of premature convergence and stagnation are still open questions that hinder the performance. Both are likely to occur on complicated multi-modal functions, but the phenomena differ. Premature convergence refers to a rapid loss of population diversity when attracted to a local minimum while stagnation happens even though the population is diverse. To deal with these problems, this paper proposes a domain transform (DT) methodology. Different from existing fitness analysis which mainly utilizes the original fitness landscape information, DT yields a transformed fitness landscape with transform operation to the frequency domain and inverse transform operation back to the solution domain, between which the first few highest frequencies are removed. With the deletion operation, the transformed fitness landscape becomes smoother and facilitates the escape from local minima and stagnation on complicated multi-modal functions. Simulation results show that DT significantly improves the population successful update rate and population convergence. The constructed DTDE algorithm consequently exhibits remarkable improvements on the baseline algorithm and outperforms several state-of-the-art DE variants. DT has also been extended for noisy optimization and it performs better than the baseline, the classic resampling method, state-ofthe-art DE variants as well as several popular noisy evolutionary optimization algorithms.

Target-Network Update Linked with Learning Rate Decay Based on Mutual Information and Reward in Deep Reinforcement Learning

In this study, a target-network update of deep reinforcement learning (DRL) based on mutual information (MI) and rewards is proposed. In DRL, updating the target network from the Q network was used to reduce training diversity and contribute to the stability of learning. If it is not properly updated, the overall update rate is reduced to mitigate this problem. Simply slowing down is not recommended because it reduces the speed of the decaying learning rate. Some studies have been conducted to improve the issues with the t-soft update based on the Student’s-t distribution or a method that does not use the target-network. However, there are certain situations in which using the Student’s-t distribution might fail or force it to use more hyperparameters. A few studies have used MI in deep neural networks to improve the decaying learning rate and directly update the target-network by replaying experiences. Therefore, in this study, the MI and reward provided in the experience replay of DRL are combined to improve both the decaying learning rate and the target-network updating. Utilizing rewards is appropriate for use in environments with intrinsic symmetry. It has been confirmed in various OpenAI gymnasiums that stable learning is possible while maintaining an improvement in the decaying learning rate.

Differing Definitions of First-Ever Stroke Influence Incidence Estimates More than Trends: A Study Using Linked Administrative Data

Introduction: Researchers apply varying definitions when measuring stroke incidence using administrative data. We aimed to investigate the sensitivity of incidence estimates to varying definitions of stroke and lookback periods and to provide updated incidence rates and trends for Western Australia (WA). Methods: We used linked state-wide hospital and death data from 1985 to 2017 to identify incident strokes from 2005 to 2017. A standard definition was applied which included strokes coded as the principal hospital diagnosis or the underlying cause of death, with a 10-year lookback used to clear prevalent cases. Alternative definitions were compared against the standard definition by percentage difference in case numbers. Age-standardised incidence rates were calculated, and age- and sex-adjusted Poisson regression models were used to estimate incidence trends. Results: The standard definition with a 10-year lookback period captured 31,274 incident strokes. Capture increased by 19.3% when including secondary diagnoses, 4.1% when including nontraumatic subdural and extradural haemorrhage, and 8.1% when including associated causes of death. Excluding death records reduced capture by 11.1%. A 20-year lookback reduced over-ascertainment by 2.0%, and a 1-year lookback increased capture by 13.3%. Incidence declined 0.6% annually (95% confidence interval −0.9, −0.3). Annual reductions were similar for most definitions except when death records were excluded (−0.1%, CI: −0.4, 0.2) and with the shortest lookback periods (greatest annual reduction). Conclusion: Stroke incidence has declined in WA. Differing methods of identifying stroke influence estimates of incidence to a greater extent than estimates of trends. Reductions in stroke incidence over time are primarily driven by declines in fatal strokes.

Analysis of UTM Tracking Performance for Conformance Monitoring via Hybrid SITL Monte Carlo Methods

Conformance monitoring supports UTM safety by observing if unmanned aircraft (UA) are adhering to declared operational intent. As a supporting system, robust cooperative tracking is critical. Nevertheless, tracking systems for UAS traffic management (UTM) are in an early stage and under-standardized, and existing literature hardly addresses the problem. To bridge this gap, this study aims to probabilistically evaluate the impact of the change in tracking performances on the effectiveness of conformance monitoring. We propose a Monte Carlo simulation-based method. To ensure a realistic simulation environment, we use a hybrid software-in-the-loop (SITL) scheme. The major uncertainties contributing to the stochastic evaluation are measured separately and are integrated into the final Monte Carlo simulation. Latency tests were conducted to assess the performance of different communication technologies for cooperative tracking. Flight technical error generation via SITL simulations and navigational system error generation based on flight experiments were employed to model UA trajectory uncertainty. Based on these tests, further Monte Carlo simulations were used to study the overall impacts of various tracking key performance indicators in UTM conformance monitoring. Results suggest that the extrapolation of UA position enables quicker non-conformance detection, but introduces greater variability in detection delay, and exacerbates the incidence of nuisance alerts and missed detections, particularly when latencies are high and velocity errors are severe. Recommendations for UA position update rates of ≥1 Hz remain consistent with previous studies, as investments in increasing the update rate do not lead to corresponding improvements in conformance monitoring performance according to simulation results.

A High-Accuracy Star Centroid Extraction Method Based on Kalman Filter for Multi-Exposure Imaging Star Sensors.

A multi-exposure imaging approach proposed in earlier studies is used to increase star sensors' attitude update rate by N times. Unfortunately, serious noises are also introduced in the star image due to multiple exposures. Therefore, a star centroid extraction method based on Kalman Filter is proposed in this paper. Firstly, star point prediction windows are generated based on centroids' kinematic model. Secondly, the classic centroid method is used to calculate the coarse centroids of the star points within the prediction windows. Lastly, the coarse centroids are, respectively, processed by each Kalman Filter to filter image noises, and thus fine centroids are obtained. Simulations are conducted to verify the Kalman-Filter-based estimation model. Under noises with zero mean and ±0.4, ±1.0, and ±2.5 pixel maximum deviations, the coordinate errors after filtering are reduced to about 37.5%, 26.3%, and 20.7% of the original ones, respectively. In addition, experiments are conducted to verify the star point prediction windows. Among 100 star images, the average proportion of the number of effective star point objects obtained by the star point prediction windows in the total object number of each star image is calculated as only 0.95%. Both the simulated and experimental results demonstrate the feasibility and effectiveness of the proposed method.

New progress in an old debate? Applying the DSM-5 criteria to assess traumatic events and stressor-related disorders in cancer survivors.

The rather broad definition of medical trauma within DSM-IV has contributed to long-lasting debates on the applicability of Posttraumatic Stress Disorder (PTSD) in oncological patients and its differentiation from Adjustment Disorder (AjD) which results from non-traumatic critical life events. The DSM-5 criteria have introduced a narrower definition of medical traumatization. However, studies on updated prevalence rates in cancer patients are missing. Within a cross-sectional study, we assessed hematological cancer survivors using the Structured Clinical Interview for DSM-5. We investigated (i) the frequency and type of cancer-related stressors, (ii) the proportion of stressors qualifying as traumatic according to DSM-5 (i.e., an event of sudden and catastrophic character) and (iii) the prevalence of PTSD, AjD and cancer-related PTSD according to DSM-5. 291 patients participated (response rate: 58%). Mean age was 54years, 60% were male. 168 patients (59%) reported cancer-related stressors, with the most frequent being cancer diagnosis disclosure (n=58, 27%). Eight percent of reported stressors qualified as traumatic events according to DSM-5. Five (1.8%), 15 (5.3%) and 20 (7.0%) cancer survivors met DSM-5 criteria for current PTSD, lifetime PTSD and AjD, respectively. Among all PTSD cases, three were cancer-related (1.1%). In addition, seven patients (2.5%) metall symptoms for cancer-related PTSD, but not the DSM-5 criterion for medical trauma. Considering receiving the cancer diagnosis as traumatic event, which is debatable according to DSM-5, 38% of stressors qualified as traumatic and six patients (2.1%) met criteria for cancer-related PTSD. DSM-5 criteria enable a clear identification of traumatic events in the context of cancer. This change may inform discussions on the appropriateness of PTSD in cancer patients and facilitates its differentiation from AjD. Larger studies need to validate our findings.

Addition of daratumumab to lenalidomide, bortezomib, and dexamethasone for transplantation-eligible patients with newly diagnosed multiple myeloma (GRIFFIN): final analysis of an open-label, randomised, phase 2 trial

Addition of daratumumab to lenalidomide, bortezomib, and dexamethasone (D-RVd) in the GRIFFIN study improved the stringent complete response rate by the end of consolidation in transplantation-eligible patients with newly diagnosed multiple myeloma. Here, we report the findings of the predefined final analysis. GRIFFIN was an open-label, randomised, active-controlled, phase 2 trial done in 35 research centres in the USA. Patients had newly diagnosed multiple myeloma with measurable disease by M protein or free light chain, were aged 18-70 years, had an ECOG performance score of 0-2, and were eligible for autologous haematopoietic stem-cell transplantation (HSCT). Patients were randomly assigned (1:1) to four D-RVd or RVd induction cycles, autologous HSCT, two D-RVd or RVd consolidation cycles, and lenalidomide with or without daratumumab maintenance therapy for 2 years. Patients received 21-day cycles of oral lenalidomide (25 mg on days 1-14), subcutaneous bortezomib (1·3 mg/m2 on days 1, 4, 8, and 11), oral dexamethasone (40 mg weekly) with or without intravenous daratumumab (16 mg/kg weekly, cycles 1-4; day 1, cycles 5-6). Maintenance therapy (28-day cycles) was oral lenalidomide (10 mg on days 1-21) with or without daratumumab (16 mg/kg intravenously every 4 or 8 weeks, or 1800 mg subcutaneously monthly). Patients could continue lenalidomide maintenance after study treatment completion. The primary endpoint was stringent complete response rate by the end of consolidation in the response-evaluable population, and has already been reported. Here we report updated stringent complete response rates and secondary outcomes including progression-free survival and overall survival. The trial is registered with ClinicalTrials.gov (NCT02874742) and ended on April 8, 2022. Between Dec 20, 2016, and April 10, 2018, 104 patients were randomly assigned to the D-RVd group and 103 were randomly assigned to the RVd group; most patients were White (85 [82%] in the D-RVd group and 76 [74%] in the RVd group) and male (58 [56%] in the D-RVd group and 60 [58%] in the RVd group). At a median follow-up of 49·6 months (IQR 47·4-52·1), D-RVd improved rates of stringent complete response (67 [67%] of 100] vs 47 [48%] of 98]; odds ratio 2·18 [95% CI 1·22-3·89], p=0·0079), and 4-year progression-free survival was 87·2% (95% CI 77·9-92·8) for D-RVd versus 70·0% (95% CI 55·9-80·3) for RVd, with a hazard ratio (HR) of 0·45 (95% CI 0·21-0·95, p=0·032) for risk of disease progression or death with D-RVd. Median overall survival was not reached for either group (HR 0·90 [95% CI 0·31-2·56], p=0·84). The most common grade 3-4 treatment-emergent adverse events in the D-RVd versus RVd groups were neutropenia (46 [46%] of 99 vs 23 [23%] of 102), lymphopenia (23 [23%] vs 23 [23%]), leukopenia (17 [17%] vs eight [8%]), thrombocytopenia (16 [16%] vs nine [9%]), pneumonia (12 [12%] vs 14 [14%]), and hypophosphataemia (ten [10%] vs 11 [11%]). Serious treatment-emergent adverse events occurred in 46 (46%) of 99 patients in the D-RVd group and in 53 (52%) of 102 patients in the RVd group. One patient in each treatment group reported a treatment-emergent adverse event that resulted in death (bronchopneumonia in the D-RVd group; cause unknown in the RVd group); neither was related to study treatment. No new safety concerns occurred with maintenance therapy. Addition of daratumumab to RVd improved the depth of response and progression-free survival in transplantation-eligible patients with newly diagnosed multiple myeloma. These results justify further evaluation in phase 3 studies. Janssen Oncology.