Off-label use of clomiphene citrate to treat anabolic androgenic steroid induced hypogonadism upon cessation among men (CloTASH) - A pilot study protocol.

Background: Non-prescribed anabolic androgenic steroid (AAS) use is associated with AAS-induced hypogonadism (ASIH), and metabolic, cardiovascular, and mental health risks. Symptoms of ASIH (fatigue, depression, anxiety, sexual dysfunction) are hard to endure following cessation, but there is no consensus on whether endocrine treatment should be used to treat ASIH. This proof-of-concept study aims to explore safety of off-label clomiphene citrate therapy, whether the treatment will reduce the symptoms of androgen deficiency, and to study changes in health risks after cessation. Methods: In this open-labeled non-randomized off-label hormone intervention pilot study, we shall include males with AAS dependence intending to cease use. The 16-week intervention included clomiphene citrate, transdermal testosterone gel for the first four weeks and optional human chorionic gonadotropin (hCG) from week 4 if low treatment response. Measures of physical and mental health will be examined from ongoing AAS use, during the intervention, and at 6- and 12 months post cessation. Change in self-reported symptoms of hypogonadism and other withdrawal symptoms will be compared with data from a group of men who ended AAS use temporarily without the medical intervention. The study may provide valuable clinical insights and may be used to inform the design of future intervention studies.

A novel in vitro cell model of the proteinase/antiproteinase balance observed in alpha-1 antitrypsin deficiency.

Background: Alpha-1 antitrypsin deficiency (AATD) is a genetic condition resulting from mutations in the alpha-1 antitrypsin (AAT) protein, a major systemic antiproteinase, resulting in reduced/no release of AAT, disrupting the proteinase/antiproteinase balance. A sustained imbalance can cause structural changes to the lung parenchyma, leading to emphysema. Predicting and assessing human responses to potential therapeutic candidates from preclinical animal studies have been challenging. Our aims were to develop a more physiologically relevant in vitro model of the proteinase/antiproteinase balance and assess whether the data generated could better predict the efficacy of pharmacological candidates to inform decisions on clinical trials, together with expected biomarker responses. Methods: We developed an in vitro model assessing the proteinase/antiproteinase balance by the changes in the fibrinogen cleavage products of neutrophil elastase (NE) and proteinase 3 (PR3). This allowed the assessment of physiological and pharmaceutical neutrophil serine proteinase (NSP) inhibitors to determine the putative threshold at which the maximal effect is achieved. Results: AAT significantly reduced NE and PR3 activity footprints, with the maximal reduction achieved at concentrations above 10 µM. The inhibitor MPH966 alone also significantly reduced NE footprint generation in a concentration-dependent manner, leveling out above 100 nM but had no effect on the PR3 footprint. At levels of AAT consistent with AATD, MPH966 had an additive effect, reducing the NE activity footprint more than either inhibitor alone. Conclusion: Our results support an inhibitor threshold above which the activity footprint generation appears resistant to increasing dosage. Our model can support the testing of inhibitors, confirming activity biomarkers as indicators of likely pharmaceutical efficacy, the assessment of NSP activity in the pathophysiology of emphysema, and the likely function of biological or pharmacological inhibitors in disease management.

Data-Driven Identification of Potentially Successful Intervention Implementations Using 5 Years of Opioid Prescribing Data: Retrospective Database Study.

BACKGROUND: We have previously demonstrated that opioid prescribing increased by 127% between 1998 and 2016. New policies aimed at tackling this increasing trend have been recommended by public health bodies, and there is some evidence that progress is being made. OBJECTIVE: We sought to extend our previous work and develop a data-driven approach to identify general practices and clinical commissioning groups (CCGs) whose prescribing data suggest that interventions to reduce the prescribing of opioids may have been successfully implemented. METHODS: We analyzed 5 years of prescribing data (December 2014 to November 2019) for 3 opioid prescribing measures-total opioid prescribing as oral morphine equivalent per 1000 registered population, the number of high-dose opioids prescribed per 1000 registered population, and the number of high-dose opioids as a percentage of total opioids prescribed. Using a data-driven approach, we applied a modified version of our change detection Python library to identify reductions in these measures over time, which may be consistent with the successful implementation of an intervention to reduce opioid prescribing. This analysis was carried out for general practices and CCGs, and organizations were ranked according to the change in prescribing rate. RESULTS: We identified a reduction in total opioid prescribing in 94 (49.2%) out of 191 CCGs, with a median reduction of 15.1 (IQR 11.8-18.7; range 9.0-32.8) in total oral morphine equivalence per 1000 patients. We present data for the 3 CCGs and practices demonstrating the biggest reduction in opioid prescribing for each of the 3 opioid prescribing measures. We observed a 40% proportional drop (8.9% absolute reduction) in the regular prescribing of high-dose opioids (measured as a percentage of regular opioids) in the highest-ranked CCG (North Tyneside); a 99% drop in this same measure was found in several practices (44%-95% absolute reduction). Decile plots demonstrate that CCGs exhibiting large reductions in opioid prescribing do so via slow and gradual reductions over a long period of time (typically over a period of 2 years); in contrast, practices exhibiting large reductions do so rapidly over a much shorter period of time. CONCLUSIONS: By applying 1 of our existing analysis tools to a national data set, we were able to identify rapid and maintained changes in opioid prescribing within practices and CCGs and rank organizations by the magnitude of reduction. Highly ranked organizations are candidates for further qualitative research into intervention design and implementation.

Practical QSP application from the preclinical phase to enhance the probability of clinical success: Insights from case studies in oncology.

Quantitative Systems Pharmacology (QSP) has emerged as a promising modeling and simulation (M&S) approach in drug development, with potential to improve clinical success rates. While conventional M&S has significantly contributed to quantitative understanding in late preclinical and clinical phases, it falls short in explaining unexpected phenomena and testing hypotheses in the early research phase. QSP presents a solution to these limitations. To harness the full potential of QSP in early preclinical stages, preclinical modelers who are familiar with conventional M&S need to update their understanding of the differences between conventional M&S and QSP. This review focuses on QSP applications during the preclinical stage, citing case examples and sharing our experiences in oncology. We emphasize the critical role of QSP in increasing the probability of success for clinical proof of concept (PoC) when applied from the early preclinical stage. Enhancing the quality of both hypotheses and QSP models from early preclinical stage is of critical importance. Once a QSP model achieves credibility, it facilitates predictions of clinical responses and potential biomarkers. We propose that sequential QSP applications from preclinical stages can improve success rates of clinical PoC, and emphasize the importance of refining both hypotheses and QSP models throughout the process.

Learning the Meanings of Function Words From Grounded Language Using a Visual Question Answering Model.

Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question answering models apparently can learn to use function words as part of answering questions about complex visual scenes. In this paper, we study what these models learn about function words, in the hope of better understanding how the meanings of these words can be learned by both models and children. We show that recurrent models trained on visually grounded language learn gradient semantics for function words requiring spatial and numerical reasoning. Furthermore, we find that these models can learn the meanings of logical connectives and and or without any prior knowledge of logical reasoning as well as early evidence that they are sensitive to alternative expressions when interpreting language. Finally, we show that word learning difficulty is dependent on the frequency of models' input. Our findings offer proof-of-concept evidence that it is possible to learn the nuanced interpretations of function words in a visually grounded context by using non-symbolic general statistical learning algorithms, without any prior knowledge of linguistic meaning.

Designing, Developing, and Testing a Chatbot for Parents and Caregivers of Children and Young People With Rheumatological Conditions (the IMPACT Study): Protocol for a Co-Designed Proof-of-Concept Study.

BACKGROUND: Pediatric rheumatology is a term that encompasses over 80 conditions affecting different organs and systems. Children and young people with rheumatological chronic conditions are known to have high levels of mental health problems and therefore are at risk of poor health outcomes. Clinical psychologists can help children and young people manage the daily difficulties of living with one of these conditions; however, there are insufficient pediatric psychologists in the United Kingdom. We urgently need to consider other ways of providing early, essential support to improve their current well-being. One way of doing this is to empower parents and caregivers to have more of the answers that their children and young people need to support them further between their hospital appointments. OBJECTIVE: The objective of this co-designed proof-of-concept study is to design, develop, and test a chatbot intervention to support parents and caregivers of children and young people with rheumatological conditions. METHODS: This study will explore the needs and views of children and young people with rheumatological conditions, their siblings, parents, and caregivers, as well as health care professionals working in pediatric rheumatology. We will ask approximately 100 participants in focus groups where they think the gaps are in current clinical care and what ideas they have for improving upon them. Creative experience-based co-design workshops will then decide upon top priorities to develop further while informing the appearance, functionality, and practical delivery of a chatbot intervention. Upon completion of a minimum viable product, approximately 100 parents and caregivers will user-test the chatbot intervention in an iterative sprint methodology to determine its worth as a mechanism for support for parents. RESULTS: A total of 73 children, young people, parents, caregivers, and health care professionals have so far been enrolled in the study, which began in November 2023. The anticipated completion date of the study is April 2026. The data analysis is expected to be completed in January 2026, with the results being published in April 2026. CONCLUSIONS: This study will provide evidence on the accessibility, acceptability, and usability of a chatbot intervention for parents and caregivers of children and young people with rheumatological conditions. If proven useful, it could lead to a future efficacy trial of one of the first chatbot interventions to provide targeted and user-suggested support for parents and caregivers of children with chronic health conditions in health care services. This study is unique in that it will detail the needs and wants of children, young people, siblings, parents, and caregivers to improve the current support given to families living with pediatric rheumatological conditions. It will be conducted across the whole of the United Kingdom for all pediatric rheumatological conditions at all stages of the disease trajectory. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57238.

Coronary bypass surgery guided by computed tomography in a low-risk population.

BACKGROUND AND AIMS: In patients with three-vessel disease and/or left main disease, selecting revascularization strategy based on coronary computed tomography angiography (CCTA) has a high level of virtual agreement with treatment decisions based on invasive coronary angiography (ICA). METHODS: In this study, coronary artery bypass grafting (CABG) procedures were planned based on CCTA without knowledge of ICA. The CABG strategy was recommended by a central core laboratory assessing the anatomy and functionality of the coronary circulation. The primary feasibility endpoint was the percentage of operations performed without access to the ICA. The primary safety endpoint was graft patency on 30-day follow-up CCTA. Secondary endpoints included topographical adequacy of grafting, major adverse cardiac and cerebrovascular (MACCE), and major bleeding events at 30 days. The study was considered positive if the lower boundary of confidence intervals (CI) for feasibility was ≥75% (NCT04142021). RESULTS: The study enrolled 114 patients with a mean (standard deviation) anatomical SYNTAX score and Society of Thoracic Surgery score of 43.6 (15.3) and 0.81 (0.63), respectively. Unblinding ICA was required in one case yielding a feasibility of 99.1% (95% CI 95.2%-100%). The concordance and agreement in revascularization planning between the ICA- and CCTA-Heart Teams was 82.9% with a moderate kappa of 0.58 (95% CI 0.50-0.66) and between the CCTA-Heart Team and actual treatment was 83.7% with a substantial kappa of 0.61 (95% CI 0.53-0.68). The 30-day follow-up CCTA in 102 patients (91.9%) showed an anastomosis patency rate of 92.6%, whilst MACCE was 7.2% and major bleeding 2.7%. CONCLUSIONS: CABG guided by CCTA is feasible and has an acceptable safety profile in a selected population of complex coronary artery disease.

Effects of proof-of-concept training on reducing work stress and anxiety of junior medical staff: a randomized controlled trial proof-of-concept.

BACKGROUND: Psychological stress and anxiety have seriously affected the ability of new clinicians to adapt and coordinate their clinical work. Traditional pre-job training is often not very good at assisting new recruits to regulate their emotional problems. METHODS: This study is a randomized controlled study. A total of 435 newly recruited clinicians participated in the study. 428 clinicians were randomized into a control group (n = 214) and an intervention group (n = 214). The control group conducted regular pre-job training. Doctors of the intervention group attend a themed course every two weeks on the basis of regular induction training. Their physiological status was evaluated by Perceived Stress Scale (PPS-10), Generalized Anxiety Scale (GAD-7) and Psychological Resilience Scale (CD-RISC-10) 3 months later. Participants in the intervention group received a training satisfaction questionnaire. RESULTS: After entering the clinic for 3 months, the PSS-10 and GAD-7 scores of the intervention group were significantly lower than that of the control group. Consistently, the CD-RISC-10 score of new clinicians who received proof-of-concept pre-job training was significantly higher than that of new doctors in the control group. CONCLUSION: New doctors received the proof-of-concept group experienced alleviation in stress and anxiety.

A Novel Ear Impression-Taking Method Using Structured Light Imaging and Machine Learning: A Pilot Proof of Concept Study with Patients' Feedback on Prototype.

INTRODUCTION: Taking an ear impression is a minimally invasive procedure. A review of existing literature suggests that contactless methods of scanning the ear have not been developed. We proposed to establish a correlation between external ear features with the ear canal and with this proof of concept to develop a prototype and an algorithm for capturing and predicting ear canal information. METHODS: We developed a novel prototype using structured light imaging to capture external images of the ear. Using a large database of existing ear impression images obtained by traditional methods, correlation analyses were carried out and established. A deep neural network was devised to build a predictive algorithm. Patients undergoing hearing aid evaluation undertook both methods of ear impression-taking. We evaluated their subjective feedback and determined if there was a close enough objective match between the images obtained from the impression techniques. RESULTS: A prototype was developed and deployed for trial, and most participants were comfortable with this novel method of ear impression-taking. Partial matching of the ear canal could be obtained from the images taken, and the predictive algorithm applied for a few sample images was within good standard of error with proof of concept established. DISCUSSION: Further studies are warranted to strengthen the predictive capabilities of the algorithm and determine optimal prototype imaging positions so that sufficient ear canal information can be obtained for three-dimensional printing. Ear impression-taking may then have the potential to be automated, with the possibility of same-day three-dimensional printing of the earmold to provide timely access.

Data extraction for evidence synthesis using a large language model: A proof-of-concept study.

Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to increase efficiency and accuracy of data extraction for evidence synthesis. The objective of this proof-of-concept study was to assess the performance of an LLM (Claude 2) in extracting data elements from published studies, compared with human data extraction as employed in systematic reviews. Our analysis utilized a convenience sample of 10 English-language, open-access publications of randomized controlled trials included in a single systematic review. We selected 16 distinct types of data, posing varying degrees of difficulty (160 data elements across 10 studies). We used the browser version of Claude 2 to upload the portable document format of each publication and then prompted the model for each data element. Across 160 data elements, Claude 2 demonstrated an overall accuracy of 96.3% with a high test-retest reliability (replication 1: 96.9%; replication 2: 95.0% accuracy). Overall, Claude 2 made 6 errors on 160 data items. The most common errors (n = 4) were missed data items. Importantly, Claude 2's ease of use was high; it required no technical expertise or labeled training data for effective operation (i.e., zero-shot learning). Based on findings of our proof-of-concept study, leveraging LLMs has the potential to substantially enhance the efficiency and accuracy of data extraction for evidence syntheses.

Experimental validation off-line a nonlinear controller for removal of chromium using non-living cells of Yarrowia lipolytica.

The removal of hexavalent chromium [Cr (VI)] using non-living cells of Yarrowia lipolytica was investigated. Batch and continuous studies on removal of Cr (VI) achieved 97% and 99% removal from aqueous phase, respectively. The specific uptake values at pH of 2 in batch process were 40.73 ± 1.3 mg/g and 30.09 ± 0.23 mg/g on non-living cells, when 100 and 200 mg/L of metal Cr (VI) concentrations were used. In order to investigate the regulation of Cr (VI) under continuous operation based on reaction volume numerically a new class of feedback controller from structure polynomial was designed. The proposed methodology was used to an experimentally kinetic model for a removal Cr (VI) from Yarrowia lipolytica biomass was showed satisfactory closed-loop performance the proposed controller. Starting from an off-line optimization performed in simulation, we present the controller implementation, focussing on the methodology required to could be suitable for implementation in real time. In our experimental results, we highlight some discrepancies between simulation and reality despite these differences, the controller managed to perform convergence to removal Cr (VI). Finally, the results validated with off-line samples suggest that the proposed control could be suitable for in application in potential scenarios for wastewater treatment.

Designing mHealth Apps to Incorporate Evidence-Based Techniques for Prolonging User Engagement.

Maintaining user engagement with mobile health (mHealth) apps can be a challenge. Previously, we developed a conceptual model to optimize patient engagement in mHealth apps by incorporating multiple evidence-based methods, including increasing health literacy, enhancing technical competence, and improving feelings about participation in clinical trials. This viewpoint aims to report on a series of exploratory mini-experiments demonstrating the feasibility of testing our previously published engagement conceptual model. We collected data from 6 participants using an app that showed a series of educational videos and obtained additional data via questionnaires to illustrate and pilot the approach. The videos addressed 3 elements shown to relate to engagement in health care app use: increasing health literacy, enhancing technical competence, and improving positive feelings about participation in clinical trials. We measured changes in participants' knowledge and feelings, collected feedback on the videos and content, made revisions based on this feedback, and conducted participant reassessments. The findings support the feasibility of an iterative approach to creating and refining engagement enhancements in mHealth apps. Systematically identifying the key evidence-based elements intended to be included in an app's design and then systematically testing the implantation of each element separately until a satisfactory level of positive impact is achieved is feasible and should be incorporated into standard app design. While mHealth apps have shown promise, participants are more likely to drop out than to be retained. This viewpoint highlights the potential for mHealth researchers to test and refine mHealth apps using approaches to better engage users.

Combination MCP-Mod for two-drug combination dose-ranging studies.

Combination therapies with multiple mechanisms of action can offer improved efficacy and/or safety profiles when compared to a single therapy with one mechanism of action. Consequently, the number of combination therapy studies have increased multi-fold, both in oncology and non-oncology indications. However, identifying the optimal doses of each drug in a combination therapy can require a large sample size and prolong study timelines, especially when full factorial designs are used. In this paper, we extend the MCP-Mod design of Bretz, Pinheiro, and Branson to a three-dimensional space to model the dose-response surface of a two-drug combination under the framework of Combination (Comb) MCP-Mod. The resulting model yields a set of dosages for each drug in the combination that elicits the target response so that an optimal dose for the combination can be selected for pivotal studies. We construct three-dimensional dose-response models for the combination and formulate the contrast test statistic to select the best model, which can then be used to select the optimal dose. Guidance to calculate power and sample size calculations are provided to assist study design. Simulation studies show that Comb MCP-Mod performs as well as the conventional multiple comparisons approach in controlling the family-wise error rate at the desired alpha level. However, Comb MCP-Mod is more powerful than the classical multiple comparisons approach in detecting dose-response relationships when treatment is non-null. The probability of correctly identifying the underlying dose-response relationship is generally higher when using Comb MCP-Mod than when using the multiple comparisons approach.

Urine: A Pitfall for Molecular Detection of Toscana Virus? An Analytical Proof-of-Concept Study.

Toscana virus (TOSV), a sandfly-borne virus, is an important etiological agent in human acute meningitis and meningoencephalitis in the Mediterranean area during the summer. However, the actual number of TOSV infections is underestimated. Laboratory confirmation is necessary because TOSV infection has overlapping clinical features with other neuro-invasive viral infections. Nowadays, the reference test for direct diagnosis in the acute phase of TOSV infection is the PCR based method for detecting TOSV in cerebrospinal fluid and/or plasma, serum, or blood. Although poorly employed, urine is another helpful biological matrix for TOSV detection. Urine is a matrix rich in PCR inhibitors that affect PCR efficiency; consequently, false negatives could be generated. To investigate the potential effect of urine PCR inhibitors on TOSV detection, we compared undiluted and diluted urine using 10-fold series of spiked TOSV. The results showed a significant improvement in TOSV detection performance in diluted urine (1 TCID50 vs. 1 × 104 TCID50 limit of detection and 101.35% vs. 129.62% efficiency, respectively, in diluted and undiluted urine). In conclusion, our data provide preliminary important insights into the use of diluted urine to limit the impact of the inhibitory effects of urine on the detection of TOSV in RT-PCR-based approaches.

Crossover randomized controlled trial of bumetanide to rescue an attack of exercise induced hand weakness in hypokalaemic periodic paralysis.

The aim of this study was to establish whether bumetanide can abort an acute attack of weakness in patients with HypoPP. This was a randomised, double-blind, cross-over, placebo-controlled phase II clinical trial. Focal attack of weakness was induced by isometric exercise of ADM followed by rest (McManis protocol). Participants had two study visits and received either placebo or 2 mg bumetanide at attack onset (defined as 40 % decrement in the abductor digiti minimi CMAP amplitude from peak). CMAP measurements assessed attack severity and duration. Nine participants completed both visits. CMAP percentage of peak amplitudes in the bumetanide (40.6 %) versus placebo (34.9 %) group at 1hr following treatment did not differ significantly (estimated effect difference 5.9 % (95 % CI: (-5.7 %; 17.5 %), p = 0.27, primary outcome). CMAP amplitudes assessed by the area under the curve for early (0-2hr post-treatment) and late (2-4 h post-treatment) efficacy were not statistically different between bumetanide and placebo (early effect estimate 0.043, p = 0.3; late effect estimate 0.085, p = 0.1). Two participants recovered from the attack following bumetanide intake; none recovered following placebo. Bumetanide was well tolerated but not efficacious to rescue a focal attack in an immobilised hand in the majority of patients, although data supports further studies of this agent.

Surgery for internal rotation contracture in infancy may obviate the need for brachial plexus nerve reconstruction: early experience.

BACKGROUND: Shoulder internal rotation contracture and subluxation in the first year of life has long been recognized in some patients with brachial plexus birth injury (BPBI). Surgical management of shoulder pathology has traditionally been undertaken following nerve reconstruction as necessary. In some patients; however, shoulder pathology may impair or obscure functional neuromuscular recovery of the upper extremity. As a proof of concept, we report a highly selected subset of patients with BPBI in whom shoulder surgery undertaken before one year of age obviated the need for neuroma resection and nerve grafting. METHODS: A retrospective review was performed of all patients with upper trunk BPBI who underwent shoulder surgery before one year of age from 2015 to 2018. Upper extremity motor function was evaluated with preoperative and postoperative Active Movement Scale scores, Cookie tests, and the requirement for subsequent neuroma resection and nerve grafting. RESULTS: Fifteen patients with BPBI meeting the inclusion criteria underwent shoulder surgery (including a subscapularis slide and tendon transfers of the teres major and latissimus dorsi muscles) before 1 year of age. Preoperatively, no patients of the appropriate age passed the Cookie test for elbow flexion. Thirteen patients either passed the Cookie test or scored Active Movement Scale score 7 for elbow flexion at or before the last available follow-up undertaken at a median age of 3.4 [1.4, 5.2] years. One of those 13 patients underwent single fascicular distal nerve transfer to improve elbow flexion before subsequently passing the Cookie test. Two patients did not have sufficient follow-up to assess elbow flexion. CONCLUSION: Although the exact role of shoulder surgery in infancy for BPBI remains to be defined, the findings from this study provide proof of concept that early, targeted surgical treatment of the shoulder may obviate the need for brachial plexus nerve reconstruction in a highly selected group of infants with BPBI.

Constructing a clinical radiographic knee osteoarthritis database using artificial intelligence tools with limited human labor: A proof of principle.

OBJECTIVE: To create a scalable and feasible retrospective consecutive knee osteoarthritis (OA) radiographic database with limited human labor using commercial and custom-built artificial intelligence (AI) tools. METHODS: We applied four AI tools, two commercially available and two custom-built tools, to analyze 6 years of clinical consecutive knee radiographs from patients aged 35-79 at the University of Copenhagen Hospital, Bispebjerg-Frederiksberg Hospital, Denmark. The tools provided Kellgren-Lawrence (KL) grades, joint space widths, patella osteophyte detection, radiographic view detection, knee joint implant detection, and radiographic marker detection. RESULTS: In total, 25,778 knee radiographs from 8575 patients were included in the database after excluding inapplicable radiographs, and 92.5% of the knees had a complete OA dataset. Using the four AI tools, we saved about 800 hours of radiologist reading time and only manually reviewed 16.0% of the images in the database. CONCLUSIONS: This study shows that clinical knee OA databases can be built using AI with limited human reading time for uniform grading and measurements. The concept is scalable temporally and across geographic regions and could help diversify further OA research by efficiently including radiographic knee OA data from different populations globally. We can prevent data dredging and overfitting OA theories on existing trite cohorts by including various gene pools and continuous expansion of new clinical cohorts. Furthermore, the suggested tools and applied approaches provide an ability to retest previous hypotheses and test new hypotheses on real-life clinical data with current disease prevalence and trends.

A Bayesian phase II proof-of-concept design for clinical trials with longitudinal endpoints.

Existing phase II clinical trial designs focus on a single scalar endpoint, such as a binary, continuous, or survival endpoint. In some clinical trials, such as pain management studies, the efficacy endpoint of interest is measured longitudinally. We propose a Bayesian phase II design for such clinical trials. We model the longitudinal measurement process using Bayesian hierarchical model, where subject-specific trajectory shrinks toward the population trajectory to borrow information across subjects. The Bayesian penalized spline is used to model subject-specific and population trajectories without making strong parametric assumption on their shapes. We use the area under the curve of the trajectory as the summary of the treatment effect over time. The design takes a group sequential approach and takes into account both statistical significance and clinical relevance. Bayesian criteria is proposed to make interim and final decisions based on the evidence of statistical significance and clinical relevance. The proposed design is highly flexible and can accommodate trials with one or multiple longitudinal endpoints, as well as a longitudinal primary endpoint with a secondary endpoint. Simulation study shows that the proposed design is robust with desirable operating characteristics.

Proof-of-concept for a thin conical X-ray target optimized for intensity and directionality for use in a carbon nanotube-based compact X-ray tube.

BACKGROUND: Carbon nanotube-based cold cathode technology has revolutionized the miniaturization of X-ray tubes. However, current applications of these devices required optimization for large, uniform fields with low intensity. PURPOSE: This work investigated the feasibility and radiological characteristics of a novel conical X-ray target optimized for high intensity and high directionality to be used in a compact X-ray tube. METHODS: The proposed device uses an ultrathin, conical tungsten-diamond target that exhibits significant heat loading while maintaining a small focal spot size and promoting forward-directedness of the X-ray field through preferential attenuation of oblique-angled photons. The electrostatic and thermal properties of the theoretical tube were calculated and analyzed using COMSOL Multiphysics software. The production, transport, and calculation of radiological properties associated with the resultant X-ray field were performed using the Geant4 toolkit via its wrapper, TOPAS. RESULTS: Heat transfer analysis of this X-ray tube demonstrated the feasibility of a 200-kV electron beam bombarding the proposed target at a maximum current of 100 mA using a 1-ms symmetric duty cycle. The cathode of the X-ray tube was designed to be segmented into nine switchable electrical segments for modulation of the focal spot size from 0.4- to 10.8-mm. After importing the COMSOL-derived electron beam into TOPAS for X-ray production simulations, radiological analysis of the resultant field demonstrated high levels of intrinsic beam collimation while maintaining high intensity. A maximum dose rate of 17,887 cGy/min was calculated for 1-mm depth in water at 7-cm distance. CONCLUSIONS: The proposed X-ray tube design can create highly directional X-ray fields with superior fluence compared to that of current commercial X-ray tubes of comparable size.

Interim decision making in seamless trial designs: An application in an adaptive dose-finding study in a rare kidney disease.

Adaptive seamless trial designs, combining the learning and confirming cycles of drug development in a single trial, have gained popularity in recent years. Adaptations may include dose selection, sample size re-estimation and enrichment of the study population. Despite methodological advances and recognition of the potential efficiency gains such designs offer, their implementation, including how to enable efficient decision making on the adaptations in interim analyzes, remains a key challenge in their adoption. This manuscript uses a case study of an adaptive seamless proof-of-concept (Phase 2a)/dose-finding (Phase 2b) to showcase potential adaptive features that can be implemented in trial designs at earlier development stages and the role of simulations in assessing the design operating characteristics and specifying the decision rules for the adaptations. It further outlines the elements needed to support successful interim analysis decision making on the adaptations while safeguarding study integrity, including the role of different stakeholders, interactive simulation-based tools to facilitate decision making and operational aspects requiring preplanning. The benefits of the adaptive Phase 2a/2b design chosen compared to following the traditional two separate studies (2a and 2b) paradigm are discussed. With careful planning and appreciation of their complexity and components needed for their implementation, seamless adaptive designs have the potential to yield significant savings both in terms of time and resources.