An overview of precision oncology basket and umbrella trials for clinicians.

With advancements in biomarkers and momentum in precision medicine, biomarker-guided trials such as basket trials and umbrella trials have been developed under the master protocol framework. A master protocol refers to a single, overarching design developed to evaluate multiple hypotheses with the general goal of improving the efficiency of trial evaluation. One type of master protocol is the basket trial, in which a targeted therapy is evaluated for multiple diseases that share common molecular alterations or risk factors that may help predict whether the patients will respond to the given therapy. Another variant of a master protocol is the umbrella trial, in which multiple targeted therapies are evaluated for a single disease that is stratified into multiple subgroups based on different molecular or other predictive risk factors. Both designs follow the core principle of precision medicine-to tailor intervention strategies based on the patient's risk factor(s) that can help predict whether they will respond to a specific treatment. There have been increasing numbers of basket and umbrella trials, but they are still poorly understood. This article reviews common characteristics of basket and umbrella trials, key trials and recent US Food and Drug Administration approvals for precision oncology, and important considerations for clinical readers when critically evaluating future publications on basket trials and umbrella trials and for researchers when designing these clinical trials.

Adaptive designs in public health: Vaccine and cluster randomized trials go Bayesian.

Clinical trials in public health-particularly those conducted in low- and middle-income countries-often involve communicable and non-communicable diseases with high disease burden and unmet needs. Trials conducted in these regions often are faced with resource limitations, so improving the efficiencies of these trials is critical. Adaptive trial designs have the potential to save trial time and resources and reduce the number of patients receiving ineffective interventions. In this paper, we provide a detailed account of the implementation of vaccine and cluster randomized trials within the framework of Bayesian adaptive trials, with emphasis on computational efficiency and flexibility with regard to stopping rules and allocation ratios. We offer an educated approach to selecting prior distributions and a data-driven empirical Bayes method for plug-in estimates for nuisance parameters.

The role of CXCL1 in crosstalk between endocrine resistant breast cancer and fibroblast.

BACKGROUND: ER positive breast cancer is currently targeted using various endocrine therapies. Despite the proven therapeutic efficacy, resistance to the drug and reoccurrence of tumor appears to be a complication that many patients deal with. Molecular pathways underlying the development of resistance are being widely studied. METHODS AND RESULTS: In this study, using four established endocrine resistant breast cancer (ERBC) cell lines, we characterized CXCL1 as a secreted factor in crosstalk between ERBC cells and fibroblasts. Protein array revealed upregulation of CXCL1 and we confirmed the CXCL1 expression by real-time qRT-PCR and U-Plex assay. Co-culturing ERBC cells with fibroblasts enhanced the cell growth and migration compared to monoculture. The crosstalk of ERBC cells with fibroblasts significantly activates ERK/MAPK signaling pathway while reparixin, CXCR1/2 receptor inhibitor, attenuates the activity. Reparixin displayed the ERBC cell growth inhibition and the combination treatment with reparixin and CDK4/6 inhibitor (palbociclib and ribociclib) increased these inhibitory effect. CONCLUSIONS: Taken together, our study implicates CXCL1 as a critical role in ERBC growth and metastasis via crosstalk with fibroblast and cotargeting CXCR1/2 and CDK4/6 could potentially overcome endocrine resistant breast cancer.

Assessing the performance of group-based trajectory modeling method to discover different patterns of medication adherence.

It is well known that medication adherence is critical to patient outcomes and can decrease patient mortality. The Pharmacy Quality Alliance (PQA) has recognized and identified medication adherence as an important indicator of medication-use quality. Hence, there is a need to use the right methods to assess medication adherence. The PQA has endorsed the proportion of days covered (PDC) as the primary method of measuring adherence. Although easy to calculate, the PDC has however several drawbacks as a method of measuring adherence. PDC is a deterministic approach that cannot capture the complexity of a dynamic phenomenon. Group-based trajectory modeling (GBTM) is increasingly proposed as an alternative to capture heterogeneity in medication adherence. The main goal of this paper is to demonstrate, through a simulation study, the ability of GBTM to capture treatment adherence when compared to its deterministic PDC analogue and to the nonparametric longitudinal K-means. A time-varying treatment was generated as a quadratic function of time, baseline, and time-varying covariates. Three trajectory models are considered combining a cat's cradle effect, and a rainbow effect. The performance of GBTM was compared to the PDC and longitudinal K-means using the absolute bias, the variance, the c-statistics, the relative bias, and the relative variance. For all explored scenarios, we find that GBTM performed better in capturing different patterns of medication adherence with lower relative bias and variance even under model misspecification than PDC and longitudinal K-means.

Improving the efficiency of clinical trials in multiple sclerosis.

BACKGROUND: Phase 3 clinical trials for disease-modifying therapies in relapsing-remitting multiple sclerosis (RRMS) have utilized a limited number of conventional designs with a high degree of success. However, these designs limit the types of questions that can be addressed, and the time and cost required. Moreover, trials involving people with progressive multiple sclerosis (MS) have been less successful. OBJECTIVE: The objective of this paper is to discuss complex innovative trial designs, intermediate and composite outcomes and to improve the efficiency of trial design in MS and broaden questions that can be addressed, particularly as applied to progressive MS. METHODS: We held an international workshop with experts in clinical trial design. RESULTS: Recommendations include increasing the use of complex innovative designs, developing biomarkers to enrich progressive MS trial populations, prioritize intermediate outcomes for further development that target therapeutic mechanisms of action other than peripherally mediated inflammation, investigate acceptability to people with MS of data linkage for studying long-term outcomes of clinical trials, use Bayesian designs to potentially reduce sample sizes required for pediatric trials, and provide sustained funding for platform trials and registries that can support pragmatic trials. CONCLUSION: Novel trial designs and further development of intermediate outcomes may improve clinical trial efficiency in MS and address novel therapeutic questions.

A 5-year outcome of propranolol for the treatment of paediatric intracranial cavernoma: case report and a review of the literature.

We describe a case of a young male patient with KRIT1-driven familial cavernous malformation syndrome who developed multiple brain cavernomas, intracranial bleeding, and persistent seizures. Due to the relentless growth of cavernous malformations and recurrent intracranial bleeds, it was decided to enrol the patient in the "Propranolol for Intracranial Cavernoma" (PICC) pilot trial at our institution. Over the 5-year treatment period with 20 to 40-mg oral propranolol three times daily (TDS), we noted the near-complete arrest of the growth of cavernous malformations with no further evidence of intracranial bleeding or any further seizures. The observed outcome is consistent with the extremely limited published literature on the topic; thus, this case provides important evidence that supports the use of propranolol as a prophylactic treatment for paediatric intracranial cavernomas. We strongly encourage and recommend future prospective randomised controlled trials to definitively assess and characterize the therapeutic utility of propranolol in this patient population.

Treatment of primitive myxoid mesenchymal tumour of infancy: a management paradigm focusing on surgical nuances.

Primitive myxoid mesenchymal tumour of infancy (PMMTI) is a rare mesenchymal tumour that typically appears in those under 6 months of age and preferentially affects the deep soft tissues of the trunk and paravertebral spinal regions. PMMTI has only recently been described, and there is scarce literature reporting cases regarding the management paradigm of the tumour. We report the case of an 11-week-old male who presented with bilaterally reduced movement and brisk reflexes in his lower limbs, and irritability. Despite numerous radiological investigations, including MRI, PMMTI was only diagnosed upon biopsy and histopathology. Although PMMTI is known to be relatively unresponsive to chemotherapy, we observed a notable decrease in tumour size after a series of chemotherapy sessions. After two-staged surgical resection of the tumour, the patient is currently stable and under close follow-up. In this article, we aim to report on the patient's clinical presentation, investigations, diagnosis, and treatment, while also discussing the findings from a review of the literature pertaining to future approaches in managing PMMTI. Overall, this case highlights the importance of considering PMMTI in the differential diagnosis of deep soft tissue tumours in young infants and the potential for a combination of chemotherapy and surgical resection to be effective in treating this rare tumour.

Virtual student-led neuroscience conferencing: a UK multicentre prospective study investigating delegate outcomes and delivery mode.

BACKGROUND: Clinical neuroscience training programmes are becoming increasingly competitive to enter. UK university neuroscience societies act as a local environment for students to develop their career interests and provide portfolio building opportunities through hosting events such as annual conferences. Recently there has been a transition to more of these events being held online yet the impact of this, if any, remains unclear. This prospective study aimed to identify the impact of student-led neuroscience conferences on delegates and examine attitudes towards an online delivery approach. METHODS: Multi-centre prospective survey study using pre-conference, post-conference, and 6-month post-conference online questionnaires distributed at 6 virtual student-led neuroscience conferences in 2021. The questionnaires had five-domains: demographics, career aspirations, academic skillsets, an educational manipulation check (EMC) and mode of delivery preference. RESULTS: Nine hundred twenty-four surveys were completed across 559 conference attendances. 79.9% of delegates were medical students. Interest in a neuroscience career (p < 0.001), preparedness to undertake research (p < 0.001) and presentation (p < 0.001), as well as EMC scores (p < 0.001) increased immediately post conference. Most participants at 6 months post-attendance had completed an academic project (71.9%) or presentation (50.9%), although 88.8% were lost to follow up. Online format was preferred (65%) with reasons including elimination of travel and access to home facilities whilst lack of face-to-face interaction and engagement were recognised limitations. CONCLUSION: UK student-led online neuroscience conferences play a role in developing knowledge and may facilitate career interest, academic skillset and longer term portfolio building. A hybrid virtual and in-person experience would offer an ideal solution to future conferencing, providing options promoting engagement and interactivity whilst advocating sustainability, accessibility and widening participation.

The Neurology and Neurosurgery Interest Group (NANSIG)-ten years of cultivating interest in clinical neurosciences.

Collaboration and successful teamworking are important components of clinical practise, and these skills should be cultivated early in medical school. The breadth of current medical school curricula means that students often have limited exposure to clinical neurosciences. Since its inception in 2009, the Neurology and Neurosurgery Interest Group (NANSIG) has become a national (UK and Republic of Ireland) example of student and junior doctor synergistic collaboration to deliver educational materials, research, conferences, seminars and workshops, as well as advocating for diversity in this field. Recently, it has expanded to incorporate an international audience and cater for a larger group of young medical professionals. The organisation has overcome numerous challenges and is constantly innovating new approaches to harness the necessary knowledge, skills and network to succeed in a career in neurosciences, neurology and neurosurgery. This article summarises the initiatives undertaken by the group over its first 10 years of existence and its organisational structure, as well as its future plans.

Smart E-Textiles: Overview of Components and Outlook.

Smart textiles have gained great interest from academia and industries alike, spanning interdisciplinary efforts from materials science, electrical engineering, art, design, and computer science. While recent innovation has been promising, unmet needs between the commercial and academic sectors are pronounced in this field, especially for electronic-based textiles, or e-textiles. In this review, we aim to address the gap by (i) holistically investigating e-textiles' constituents and their evolution, (ii) identifying the needs and roles of each discipline and sector, and (iii) addressing the gaps between them. The components of e-textiles-base fabrics, interconnects, sensors, actuators, computers, and power storage/generation-can be made at multiscale levels of textile, e.g., fiber, yarn, fabric, coatings, and embellishments. The applications, current state, and sustainable future directions for e-textile fields are discussed, which encompasses health monitoring, soft robotics, education, and fashion applications.

How to Use and Interpret the Results of a Platform Trial: Users' Guide to the Medical Literature.

Platform trials are a type of randomized clinical trial that allow simultaneous comparison of multiple intervention groups against a single control group that serves as a common control based on a prespecified interim analysis plan. The platform trial design enables introduction of new interventions after the trial is initiated to evaluate multiple interventions in an ongoing manner using a single overarching protocol called a master (or core) protocol. When multiple treatment candidates are available, rapid scientific therapeutic discoveries may be made. Platform trials have important potential advantages in creating an efficient trial infrastructure that can help address critical clinical questions as the evidence evolves. Platform trials have recently been used in investigations of evolving therapies for patients with COVID-19. The purpose of this Users' Guide to the Medical Literature is to describe fundamental concepts of platform trials and master protocols and review issues in the conduct and interpretation of these studies. This Users' Guide is intended to help clinicians and readers understand articles reporting on interventions evaluated using platform trial designs.

Clinical Trial Data Sharing for COVID-19-Related Research.

This paper aims to provide a perspective on data sharing practices in the context of the COVID-19 pandemic. The scientific community has made several important inroads in the fight against COVID-19, and there are over 2500 clinical trials registered globally. Within the context of the rapidly changing pandemic, we are seeing a large number of trials conducted without results being made available. It is likely that a plethora of trials have stopped early, not for statistical reasons but due to lack of feasibility. Trials stopped early for feasibility are, by definition, statistically underpowered and thereby prone to inconclusive findings. Statistical power is not necessarily linear with the total sample size, and even small reductions in patient numbers or events can have a substantial impact on the research outcomes. Given the profusion of clinical trials investigating identical or similar treatments across different geographical and clinical contexts, one must also consider that the likelihood of a substantial number of false-positive and false-negative trials, emerging with the increasing overall number of trials, adds to public perceptions of uncertainty. This issue is complicated further by the evolving nature of the pandemic, wherein baseline assumptions on control group risk factors used to develop sample size calculations are far more challenging than those in the case of well-documented diseases. The standard answer to these challenges during nonpandemic settings is to assess each trial for statistical power and risk-of-bias and then pool the reported aggregated results using meta-analytic approaches. This solution simply will not suffice for COVID-19. Even with random-effects meta-analysis models, it will be difficult to adjust for the heterogeneity of different trials with aggregated reported data alone, especially given the absence of common data standards and outcome measures. To date, several groups have proposed structures and partnerships for data sharing. As COVID-19 has forced reconsideration of policies, processes, and interests, this is the time to advance scientific cooperation and shift the clinical research enterprise toward a data-sharing culture to maximize our response in the service of public health.

Utilizing Bayesian predictive power in clinical trial design.

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.

Identification of Naegleria fowleri proteins linked to primary amoebic meningoencephalitis.

Naegleria fowleri (N. fowleri) causes primary amoebic meningoencephalitis, a rapidly fatal disease of the central nervous system. N. fowleri can exist in cyst, flagellate or amoebic forms, depending on environmental conditions. The amoebic form can invade the brain following introduction into the nasal passages. When applied intranasally to a mouse model, cultured N. fowleri amoebae exhibit low virulence. However, upon serial passage in mouse brain, the amoebae acquire a highly virulent state. In the present study, a proteomics approach was applied to the identification of N. fowleri amoeba proteins whose expression was associated with the highly virulent state in mice. Mice were inoculated intranasally with axenically cultured amoebae or with mouse-passaged amoebae. Examination by light and electron microscopy revealed no morphological differences. However, mouse-passaged amoebae were more virulent in mice as indicated by exhibiting a two log10 titre decrease in median infective dose 50 (ID50). Scatter plot analysis of amoebic lysates revealed a subset of proteins, the expression of which was associated with highly virulent amoebae. MS-MS indicated that this subset contained proteins that shared homology with those linked to cytoskeletal rearrangement and the invasion process. Invasion assays were performed in the presence of a select inhibitor to expand on the findings. The collective results suggest that N. fowleri gene products linked to cytoskeletal rearrangement and invasion may be candidate targets in the management of primary amoebic meningoencephalitis.

Treatment modifying factors of biologics for psoriatic arthritis: a systematic review and Bayesian meta-regression.

OBJECTIVES: The aim of this study was to explore factors that modify treatment effects of non-conventional biologics versus placebo in patients with psoriatic arthritis. METHODS: A systematic literature review and meta-regression was conducted. The biologics included etanercept, infliximab, adalimumab, golimumab, certolizumab, ustekinumab, tocilizumab, anakinra, abatacept, rituximab, and secukinumab. Outcomes included American College of Rheumatology (ACR) 20 and 50, Psoriasis Area Severity Index (PASI) 75, and 36-Item Short Form Health Survey (SF-36) Physical and Mental Component Summaries (PCS and MCS). RESULTS: Twelve RCTs were eligible for meta-regression. Treatment effects for ACR-20 at 12 weeks were higher in trials with longer disease durations (OR=2.94), and lower in trials enrolling older patients (OR=0.48), and those recently published (OR=0.49). Treatment effects for ACR-50 at 12 weeks were higher in trials with more males (OR=2.27), but lower in trials with high prior anti-TNF use (OR=0.28) and recently published trials (OR=0.37). For PASI-75, trials with more male patients (24 weeks: OR=2.56), and with higher swollen and tender joint counts (12 weeks: OR=8.33; 24 weeks: OR=14.44) showed higher treatment effects, and trials with high prior anti-TNF use had lower effects (OR=0.41). Treatment effects for SF-36 PCS at 24 weeks were higher in trials with longer psoriasis disease durations (OR=2.95) and PsA disease durations (OR=4.76), and those published earlier (OR=4.19). CONCLUSIONS: Our analyses show that differences in baseline characteristics may explain some of the differences in response to biologics versus placebo across different trials. Accounting for these factors in future studies will likely be important.

The medical students' perspective of faculty and informal mentors: a questionnaire study.

BACKGROUND: Student mentoring is an important aspect of undergraduate medical education. While medical schools often assign faculty advisors to medical students as mentors to support their educational experience, it is possible for the students to pursue mentors informally. The possible role of these informal mentors and their interactions with the students in a faculty mentorship program has not been reported. This study builds upon previous work that suggested many students have informal mentors, and that there might be interplay between these two types of mentors. This study was conducted to report the experience of undergraduate medical students in a faculty mentorship program of their faculty mentors and if applicable, of their informal mentors. METHODS: One month before residency (post-graduate training for Canadians) ranking, the survey was administered to the graduating class of 2014 at the University of Calgary's Cumming School of Medicine. The survey was created from focus groups of the previous graduating class of 2013. The survey investigated meeting characteristics and the students' perceptions of faculty advisors and informal mentors, and the students' intended choice for residency. RESULTS: The study response rate was 86% (95 of 111); 58% (54 of 93) of the students reported having an informal mentor. There was no reported difference in satisfaction ratings of the Faculty mentorship program between students with only faculty mentors and those with also informal mentors. Students' reporting of their satisfaction with the Faculty mentorship program and the faculty mentors did not differ between the students with informal mentors and those with faculty mentors only. The students' meeting frequency, discussed topics, and perceived characteristics of faculty mentors were not associated with having an informal mentor. The students generally perceived their informal mentors more positively than their faculty mentors. The reported student career intention was associated with the discipline of informal mentors and not with the discipline of faculty mentors. CONCLUSIONS: Informal mentorship was common for medical students. The presence of an informal mentor was not associated with dissatisfaction with the Faculty advisor or with the mentorship program. It is likely students may pursue informal mentorship for career-related reasons.

Tailoring nanorod alignment in a polymer matrix by elongational flow under confinement: simulation, experiments, and surface enhanced Raman scattering application.

Mesoscale simulation, electrospinning and Raman scattering experiments have been carried out to demonstrate that examination and control of nanorod configuration in a polymer matrix under elongational flow and confinement can lead to enhanced sensing. First, coarse-grained molecular dynamics (CGMD) was employed to probe the diffusivity, orientation, and dispersion of nanorods in a model polymer melt under planar elongational flow. Compared to shear flow, elongational flow gives rise to enhanced dispersion and orientation of nanorods, which are predicted to be improved with increasing the aspect ratio of nanorods and polymer chain length. As comparative experiments, we have electrospun gold (Au) nanorods with polyvinyl alcohol (PVA), and the resulting Au nanorod configuration in PVA nanofibers is in good agreement with the predicted simulation. Furthermore, coaxial electrospinning of Au nanorod/PVA-PVA (shell-core) was applied to selectively place Au nanorods in the cylindrical sheath layer, and the alignment of Au nanorods near the fiber surface was confirmed by TEM analysis and CGMD simulation under uniaxial elongation. Finally, the Au nanorod-PVA fibers were tested for surface-enhanced Raman spectroscopy for sensing applications. The coaxially electrospun fibers have demonstrated much greater signal peak strength when compared with monoaxially electrospun fibers with the same Au nanorod loading. This comprehensive study demonstrates how extensional flow and multi-layered fluids can direct the orientation and dispersion of nanorod in a polymer matrix, leading to enhanced sensing performance.

Formation of interconnected morphologies via nanorod inclusion in the confined assembly of symmetric block copolymers.

We have investigated the effect of nanorods on the symmetry breaking of a model diblock copolymer under cylindrical confinement using coarse-grained molecular dynamics. Unlike nanoparticles, nanorods can readily be interconnected with each other and also induce connection across self-assembly domains at much lower loading than nanoparticles. Such interconnecting nanorods, when incorporated within the nanofiber confined assembled block copolymer, have great potential for providing highly conductive pathways for energy applications, such as battery electrodes and separators. Symmetric block copolymers (BCP) under cylindrical confinement with a nanorod aspect ratio (N) of 1, 5, and 10 are examined with three different types of nanorod-BCP attractions: (a) neutral nanorods, (b) A (wall-attractive phase)-attractive nanorods, and (c) B (wall-repulsive phase)-attractive nanorods. The system was studied with both selective and neutral walls, which affect the orientation of the interconnected nanorod network. Upon close examination of the BCP-nanorod self-assembly, we discovered that the ratio of the interphase distance to the nanorod aspect ratio (I/N) can be correlated to the onset of nanorod interconnectivity and formation of asymmetrical interconnected BCP morphology. By developing a phase diagram with respect to I/N, one can predict the formation of desired BCP morphology and the critical loading of nanorods for connected morphologies in cylindrical confinement.