Multi-site Collaboration Research Articles

Federated learning enables big data for rare cancer boundary detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Can the UK AQ-10 be applicable to Chinese samples with autism spectrum disorder in Hong Kong? Cross-cultural similarities and differences.

The current study aimed at testing and developing alternative short versions of autism spectrum quotient (AQ-10) (adult [self-report], adult [parent-report], adolescent, and child versions) for use in Hong Kong. First, the various versions of AQ-10 developed in the United Kingdom (the AQ-10-UK) were applied to Hong Kong Chinese samples and demonstrated satisfactory discriminative power (AUCs 0.77-0.94). Second, the Hong Kong Chinese versions of AQ-10 (AQ-10-HK) were developed, using the same methodology as in the original UK study. There were some changes in the choice of items and cut-offs. The AQ-10-HK demonstrated slightly greater discriminative power (AUCs 0.88-0.97) to that of the AQ-10-UK, but the differences in AUCs were not statistically significant. Compared to the corresponding full-length versions, both the UK and HK short forms did not seem to lose any significant discriminative power. Yet, the various versions of AQ, be they the full-length or AQ-10, appeared to consistently exhibit slightly smaller AUCs with the Hong Kong Chinese samples than with the UK samples. So, this study found both cross-cultural similarities and differences. The AQ-10-HK was recommended for local practice to maximize the advantage gained. Yet, for international multi-site research collaboration, involving the UK and HK, the original AQ-10-UK can be used for direct comparison of data.

O25 - Contemporary Maternity Research Priorities for the Nation’s Biggest Health Service: Results of a Delphi Study

Western Australian Country Health Service (WACHS) is one of the world’s largest health service by area. The diversity of resourcing, population density and remote locations results in distinctive challenges and opportunities in the provision of maternity care. The aim of this Delphi study was to establish a collaborative, interdisciplinary evidence-based consensus regarding maternity research priorities across the service. A three-round Delphi survey method was used. Maternity professionals employed by WACHS (including midwives, obstetricians, GP obstetricians, Aboriginal maternity workers, remote area nurses and midwifery managers / leaders) were invited to participate. The first round collected demographic data and had free text fields, encouraging participants to create a list of ideas, problems and opportunities that could be addressed through research. Responses from the first questionnaire were grouped and summarised. A total of 52 key concepts were identified which were classified across five domains: Clinical Care; Aboriginal Health; Workforce and Education, Logistics and Health Systems; and, Health Equity. The second-round survey sought ranking of the importance and perceived priority of each research topic proposed. The top 15 ranked research topics from round two were then circulated to all WACHS maternity professionals in a round three survey and a final priority ranking to guide the focus of future research activities at WACHS was obtained. The final results will be available in May 2022 and will report the first-ever systematic and scientific consensus of maternity research priorities identified by the maternity professionals working in the unique settings presented in rural and remote Western Australia. The Delphi will offer an evidence-informed list of research priorities as identified by WACHS maternity professionals. It is anticipated that the study will enhance engagement, collaboration and enthusiasm within the interdisciplinary maternity team to undertake research locally, potentially, with multi-site collaborations within WA or nationally.

'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studies.

Multi-site collaboration, which gathers together samples from multiple sites, is a powerful way to overcome the small-sample problem in the neuroimaging field and has the potential to discover more robust and reproducible biomarkers. However, confounds among the datasets caused by various site-specific factors may dramatically reduce the cross-site reproducibility performance. To properly remove confounds while improving cross-site task performances, we propose a maximum classifier discrepancy generative adversarial network (MCD-GAN) that combines the advantages of generative models and maximum discrepancy theory. The mechanisms of MCD-GAN and how it harmonizes the dataset are visualized using simulated data. The performance of MCD-GAN was also compared with state-of-the-art methods (e.g., ComBat, cycle-GAN) within Adolescent Brain Cognitive Development (ABCD) dataset. Result demonstrates that the proposed MCD-GAN can effectively improve the cross-site gender classification performance by harmonizing site effects. Our proposed framework is also suitable for various classification/prediction tasks and is promising to facilitate the cross-site reproducibility of neuroimaging studies. Clinical Relevance- This work provides an efficient method for removing sites effects and improving reproducibility in large-cohort neuroimaging studies.

Bitbox: A Cloud-based data sharing solution for medical images.

With the modernization and digitisation of the healthcare system, the need for exchanging medical data has become increasingly compelling. Biomedical imaging has been no exception, where the gathering of medical imaging acquisitions from multi-site collaborations have enabled to reach data sizes never imaginable until few years ago. Usually, medical imaging data have very large volume and diverse complexity, requiring bespoken transfer systems that protect personal information as well as data integrity. Despite many digital innovations, there are still technical and regulatory bottlenecks that make biomedical imaging data exchange challenging. Here we present Bitbox, a web-based application which provides a reliable yet straightforward service to securely exchange medical imaging data. With Bitbox, both imaging and non-imaging data of any type can be transferred from any external and independent site into a centralized server. A showcase of the system will be illustrated for the COVID-19 Clinical Neuroscience Study (COVID-CNS) project, a UK-wide experimental medicine study to investigate the neurological and neuropsychiatric effects of COVID-19 infections in hundreds of patients.

New strategies for standardised and appropriate access to a complete acute lymphocytic leukaemia diagnostic panel for children in Mexico: an observational study

Approximately 50% of all childhood cancer cases in Mexico are acute lymphocytic leukaemia. Survival rates are suboptimal when compared with those in high-income countries, and poor access to standardised testing and treatment has been identified as a contributing factor. Mexico in Alliance with St Jude (MAS) is a multisite intersectoral collaboration created in 2016 to improve childhood cancer outcomes. MAS conducted a retrospective analysis of childhood acute lymphocytic leukaemia where diagnostic disparities and risk-group classification emerged as a challenge; 419 (72%) of 578 of patients with confirmed acute lymphocytic leukaemia did not have access supporting fluorescent in-situ hybridisation (FISH) testing and 226 (39%) of 578 patients did not have minimal residual disease evaluation. FISH results were reported in a median of 15 days (SD 17) and cytogenetic results were reported after a median of 22 days (SD 27). In response, MAS launched The Bridge Project, in 2019, to improve access, accuracy, and timeliness of diagnostic information for children with acute lymphocytic leukaemia in Mexico. A consensus-derived standardised diagnostic panel for children aged 0-18 years with suspected acute lymphocytic leukaemia was developed, including morphology, immunophenotype, karyotype, FISH, DNA index, and minimal residual disease evaluation at two timepoints: day 15 and after consolidation. Participating centres shipped diagnostic samples to a single central laboratory. Paediatric oncologists, nurses, clinical research coordinators, and laboratory technicians held weekly meetings for quality improvement. The Bridge Project has benefited 255 children by providing consistent access to a comprehensive diagnostic panel. 556 (94%) of 591 samples arrived within the target timeframe (≤48 h). Immunophenotype, karyotype, DNA index, FISH, and minimal residual disease access increased from 97%, 76%, 77%, 28%, and 61%, respectively, to 100%. The single central laboratory produced flow cytometry results (immunophenotype and minimal residual disease) and FISH results within 5 days and karyotype results within 13 days of sample arrival. Many structural and logistical challenges were successfully addressed through multidisciplinary and intersectoral collaboration. Eleven additional institutions joined the project in 2022, up from five in 2021. Timely access to standard specialised diagnostic testing for children with suspected acute lymphocytic leukaemia following a centralised approach is possible in lower-resource settings through multisite intersectoral collaboration. This synergistic action is benefiting children by providing timely access to a comprehensive diagnostic panel and serves as an example of health system resilience. Fundación Gonzalo Río Arronte (Mexico City, Mexico); Casa de la Amistad para niños con Cáncer (Mexico City, Mexico); St Jude Children's Research Hospital (Memphis, TN, USA).

Abstract 248: IMPLEMENT-HF: An Initiative To Improve Guideline Adherence Across The Continuum

Background & Objectives: Nearly 1 in 4 heart failure (HF) patients are readmitted within 30 days of discharge and nearly half readmitted in 6 months. HF prevalence is projected to continue increasing resulting in over 8 million adults with HF by 2030. Rising prevalence and poor outcomes provide significant improvement opportunities. Health system participation in a quality improvement (QI) initiative promoting adherence to evidence-based scientific clinical practice guidelines informs high quality care and improves patient outcomes. IMPLEMENT-HF, an American Heart Association (AHA) multi-site QI collaborative across inpatient and outpatient settings, uses implementation science and data analysis to improve guideline adherence across the HF care continuum. Methods: The IMPLEMENT-HF program targets the transformation of HF care in seven national regions. Organizations across the care continuum collect baseline and 30-day follow-up HF data and contribute to learning collaboratives. Data sources include HF measures in the AHA Outpatient Pilot Registry and Get With The Guidelines®-Heart Failure (GWTG-HF) inpatient and post-acute data. In addition to quantitative data, qualitative data including needs assessments, model sharing queries, and evaluation surveys are assessed. After establishing benchmark data, performance is evaluated continuously to identify care gaps. Opportunities for HF QI from this analysis emanate from 1:1 site meetings, regional, and initiative-wide learning collaboratives. AHA staff monitor data to recommend improvements, provide consultation, and deliver targeted training and resources to address common guideline adherence barriers. Intended Analyses: Demonstrate improved guideline adherence across the currently participating 60 sites; benchmark clinical outcomes, esp., mortality, against prevailing community norms with a goal absolute reduction in cardiovascular mortality of 5%; and use multi-site collaboration to develop and promulgate implementation strategies. Conclusions: This three-year multi-region QI initiative connects sites to share challenges and strategies, develop resources, and analyze data to foster continuous guideline adherence improvement across the HF care continuum.

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network.

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures.

Electrophysiological and Behavioral Evidence for Hyper- and Hyposensitivity in Rare Genetic Syndromes Associated with Autism.

Our study reviewed abnormalities in spontaneous, as well as event-related, brain activity in syndromes with a known genetic underpinning that are associated with autistic symptomatology. Based on behavioral and neurophysiological evidence, we tentatively subdivided the syndromes on primarily hyper-sensitive (Fragile X, Angelman) and hypo-sensitive (Phelan–McDermid, Rett, Tuberous Sclerosis, Neurofibromatosis 1), pointing to the way of segregation of heterogeneous idiopathic ASD, that includes both hyper-sensitive and hypo-sensitive individuals. This segmentation links abnormalities in different genes, such as FMR1, UBE3A, GABRB3, GABRA5, GABRG3, SHANK3, MECP2, TSC1, TSC2, and NF1, that are causative to the above-mentioned syndromes and associated with synaptic transmission and cell growth, as well as with translational and transcriptional regulation and with sensory sensitivity. Excitation/inhibition imbalance related to GABAergic signaling, and the interplay of tonic and phasic inhibition in different brain regions might underlie this relationship. However, more research is needed. As most genetic syndromes are very rare, future investigations in this field will benefit from multi-site collaboration with a common protocol for electrophysiological and event-related potential (EEG/ERP) research that should include an investigation into all modalities and stages of sensory processing, as well as potential biomarkers of GABAergic signaling (such as 40-Hz ASSR).

Innovations in Undergraduate Research Training Through Multisite Collaborative Programming: American Heart Association Summer Undergraduate Research Experience Syndicate.

BackgroundTo support diversity in biomedical science, the American Heart Association launched the Supporting Undergraduate Research Experiences for undergraduate students from underrepresented backgrounds to provide mentorship and high‐level exposure at 5 leading medical institutions. Here we describe the initial formation of the partnership and the alteration made in response to the program to accommodate COVID‐19 safety precautions.Methods and ResultsWe outline how programming shifted from local, in‐person programming in the summer of 2019 to a collaborative, mainly virtual curriculum in 2020 using students’ self‐reported before and after surveys from both 2019 (n=33) and 2020 (n=42). Students from both in‐person (2019) and virtual programs (2020) self‐reported significant gains in scientific proficiency. A qualitative‐directed content analysis of student open‐response questions was performed. Students reported extensive benefits from the 2020 virtual training, including Personal Gains, Research Skills, Thinking and Working Like a Scientist, and Attitudes and Behaviors. Notedly, we observed increases in the Attitudes and Behaviors category. We outline the pros and cons of in‐person and virtual programming and make recommendations moving forward in a postpandemic world with hybrid work and learning systems.ConclusionsOur effort informs the development of future undergraduate research training programs, significantly maximizing a hybrid training modality. The American Heart Association Supporting Undergraduate Research Experiences serves as a model for building multi‐institutional partnerships and providing research experiences that overcome institutional barriers and support students' interests, commitment, and ability to persist in science, technology, engineering, and math fields.

The Sickle Cell Disease Ontology: recent development and expansion of the universal sickle cell knowledge representation.

The Sickle Cell Disease (SCD) Ontology (SCDO, https://scdontology.h3abionet.org/) provides a comprehensive knowledge base of SCD management, systems and standardized human and machine-readable resources that unambiguously describe terminology and concepts about SCD for researchers, patients and clinicians. The SCDO was launched in 2016 and is continuously updated in quantity, as well as in quality, to effectively support the curation of SCD research, patient databasing and clinical informatics applications. SCD knowledge from the scientific literature is used to update existing SCDO terms and create new terms where necessary. Here, we report major updates to the SCDO, from December 2019 until April 2021, for promoting interoperability and facilitating SCD data harmonization, sharing and integration across different studies and for retrospective multi-site research collaborations. SCDO developers continue to collaborate with the SCD community, clinicians and researchers to improve specific ontology areas and expand standardized descriptions to conditions influencing SCD phenotypic expressions and clinical manifestations of the sickling process, e.g. thalassemias. Database URL: https://scdontology.h3abionet.org/

Behavioral Activation as a Principle-Based Treatment: Developments from a Multi-Site Collaboration to Advance Adolescent Depression Treatment

ABSTRACT Adolescent depression is a serious and debilitating disorder associated with lifelong negative outcomes, including heightened risk for recurrence into adulthood, psychiatric comorbidities, and suicide. Among evidence-based treatments for adolescents, psychotherapies for depression have the smallest effect sizes of all psychiatric conditions studied. Advancing care for depression in adolescents is complex due to the heterogeneity in etiology and co-occurring difficulties among youth presenting with depression symptoms. This and a companion paper (Lewandowski et al., 2022) draw on a recent multisite collaboration that focused on implementing depression treatment for adolescents within clinical and research contexts. Specifically, this paper will review our work adapting behavioral activation (BA) as a principle-based framework to improve effectiveness and efficiency of depression treatment used within clinical and research settings in academic medical centers. Piloted adaptations include the use of BA principles to address idiographic drivers of depression and in-session BA “exposures” to illustrate BA principles. Case vignettes illustrate these adaptations of BA to address adolescent depression in the context of co-occurring difficulties.

Increasing animal cognition research in zoos

Animal cognition covers various mental processes including perception, learning, decision-making and memory, and animal behavior is often used as a proxy for measuring cognition. Animal cognition/behavior research has multiple benefits; it provides fundamental knowledge of animal biology and evolution but can also have applied conservation and welfare applications. Zoos provide an excellent yet relatively untapped resource for animal cognition research, because they house a wide variety of species-many of which are under threat-and allow close observation and relatively high experimental control compared to the wild. Multi-zoo collaboration leads to increased sample size and species representation, which in turn leads to more robust science. However, there are salient challenges associated with zoo-based cognitive research, which are animal-based (e.g., small sample sizes at single zoos, untrained/unhabituated subjects, side effects) and human-based (e.g., time restrictions, safety concerns, and perceptions of animals interacting with unnatural technology or apparatus). We aim to increase the understanding and subsequent uptake of animal cognition research in zoos, by transparently outlining the main benefits and challenges. Importantly, we use our own research (1) a study on novelty responses in hornbills, and (2) a multi-site collaboration called the "ManyBirds" Project to demonstrate how challenges may be overcome. These potential options include using "drop and go" apparatuses that require no training, close human contact or animal separation. This study is aimed at zoo animal care and research staff, as well as external researchers interested in zoo-based studies.

Sleep and circadian informatics data harmonization: a workshop report from the Sleep Research Society and Sleep Research Network.

The increasing availability and complexity of sleep and circadian data are equally exciting and challenging. The field is in constant technological development, generating better high-resolution physiological and molecular data than ever before. Yet, the promise of large-scale studies leveraging millions of patients is limited by suboptimal approaches for data sharing and interoperability. As a result, integration of valuable clinical and basic resources is problematic, preventing knowledge discovery and rapid translation of findings into clinical care. To understand the current data landscape in the sleep and circadian domains, the Sleep Research Society (SRS) and the Sleep Research Network (now a task force of the SRS) organized a workshop on informatics and data harmonization, presented at the World Sleep Congress 2019, in Vancouver, Canada. Experts in translational informatics gathered with sleep research experts to discuss opportunities and challenges in defining strategies for data harmonization. The goal of this workshop was to fuel discussion and foster innovative approaches for data integration and development of informatics infrastructure supporting multi-site collaboration. Key recommendations included collecting and storing findable, accessible, interoperable, and reusable data; identifying existing international cohorts and resources supporting research in sleep and circadian biology; and defining the most relevant sleep data elements and associated metadata that could be supported by early integration initiatives. This report introduces foundational concepts with the goal of facilitating engagement between the sleep/circadian and informatics communities and is a call to action for the implementation and adoption of data harmonization strategies in this domain.

Translating Evidence to Practice: A Multisite Collaboration to Implement Guidelines and Improve Constipation Management in Patients With Cancer.

Despite the high incidence of constipation in people with cancer, there is little research on management strategies for opioid-induced constipation (OIC). This project used the Plan-Do-Study-Act model to examine implementation of the Oncology Nursing Society GuidelinesTM to improve constipation management in patients with cancer. Nurse champions at four sites identified practice gaps, including providing education on OIC for patients who are new to opioids and increasing follow-up assessment. This project demonstrates that multisite, collaborative projects are feasible and may enhance patient quality of life and decrease anticipated complications.

Molecular and MRD-Based Characterization of Acute Lymphoblastic Leukemia in Mexico: Experience from the Mexico in Alliance with St. Jude “Bridge Project”

▪Background: Cancer is the second leading cause of death in Mexico among children 5-14 years. In 2017, Mexico in Alliance with St. Jude (MAS), a multi-site intersectoral collaboration, explored reasons for suboptimal outcomes for children with acute lymphoblastic leukemia (ALL). Results showed 82% of patients to be classified as high-risk and 30% of patients be missing standard molecular or minimal residual disease (MRD) studies needed to inform risk- group stratification. Making sense of the molecular characteristics was challenging in the context of variable access and lack of common denominators. These findings led to the development of the “Bridge Project”; a prospective quality improvement demonstration project aiming to bridge this access and quality gap through multi-site collaboration, centralization, and standardization.Methods: Six MAS collaborating hospitals, located in six different states (Mérida, Guadalajara, Sinaloa, Baja California, Chiapas, and Veracruz), have sent diagnostic samples for children 0-18 years old with suspected ALL to Hospital Infantil Teletón de Oncología (HITO), in Queretaro, which serves as the centralized laboratory for the MAS cooperative group. Access to the diagnostic panel is secured upfront through dedicated funding obtained from a local foundation. The first sample was shipped in July 2019. The consensus-derived diagnostic panel includes morphology, immunophenotype, karyotype, fluorescent in situ hybridization (FISH), molecular biology (RT-PCR) and flow cytometry (FC) MRD at two time points. Protocols vary by institution and MRD evaluation is only done if the institutional protocol incorporates MRD-evaluation into the risk-group stratification. Hospitals send several empty boxes prior to shipping patient samples to assess their regional shipping vendors and timelines. The also standardize data collection processes and use PDSA cycles to monitor sample quality and address issues with sample quality. HITO produces FC results (for diagnosis or MRD evaluation) and FISH/cytogenetic results within 3 to 21 days of sample arrival.Results: As of July 2021, the centralized lab has received samples from 217 patients with suspected ALL through this project and 93% of these samples have arrived within the 48hr target. Of these, 176 (81.1%) had confirmed ALL and 14 (6.4%) had acute myeloid leukemia (AML), 2 (0.9%) cases had other malignant conditions, and in 25 (11.5%) of the cases leukemia was ruled out. Among the 176 cases of confirmed ALL, 162 (92%) had B-cell lineage and 14 (8%) had T-cell lineage. FISH was reported for 172 (97.7%) patients and positive in 126 (73.2%) cases; 46 (26.7%) cases had reported gains, 34 (19.7%) detected t(12;21), 18 (10.4%) detected iAMP cr21, 8 (4.7%) detected breaks of the MLL gene t(4;11), 7 (4%) detected t(1;19), and 6 (3.4%) detected t(9;22). Four T-cell ALL cases had breaks CDKN2A del(9)(p21) and three cases had TRA/D rearrangement (14) (q11.2). Karyotype alterations were detected in 90 (52.3%) of the samples, of which 41 (23.8%) showed hyperdiploidy and 13 (7%) showed complex karyotype. One case of hypodiploid was identified. Day 15 MRD was assessed in 131 (80%) patients with B-cell lineage, Day 84 MRD was assessed in 99 (61.1%) patients with B-cell lineage, and Day 29 MRD in 8 (57.1%) patients with T-cell lineage whose treatment schema utilizes MRD-based stratification. Among B-lineage patients, 84% had MRD <1% at Day 15 and 94.9% MRD <0.01% at Day 84. Among T-cell lineage patients, 75% had MRD <0.01% at Day 29 and 80% MRD <0.01% at Day 84, but numbers for T-cell lineage were small.Conclusions: Given proper structural and financial supports, patients with suspected childhood ALL in Mexico can access a comprehensive diagnostic panel following a centralized laboratory approach. Preliminary results from the Bridge Project allow characterizing childhood ALL to a degree that has not been previously possible in Mexico. In this cohort, favorable characteristics such a t(12;21), gains, and hyperdiploidy are observed in frequencies similar to those reported in Hispanic cohorts in high-income countries. MRD results are for B-cell lineage are also consistent with the literature. Continued engagement in this project from hospitals in diverse geographic settings and with diverse patient populations will allow the MAS cooperative group to continue to improve the characterization of childhood ALL in Mexico. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

PONT: A Protocol for Online Neuropsychological Testing.

A major challenge for neuropsychological research arises from the fact that we are dealing with a limited resource: the patients. Not only is it difficult to identify and recruit these individuals, but their ability to participate in research projects can be limited by their medical condition. As such, sample sizes are small, and considerable time (e.g., 2 years) is required to complete a study. To address limitations inherent to laboratory-based neuropsychological research, we developed a protocol for online neuropsychological testing (PONT). We describe the implementation of PONT and provide the required information and materials for recruiting participants, conducting remote neurological evaluations, and testing patients in an automated, self-administered manner. The protocol can be easily tailored to target a broad range of patient groups, especially those who can be contacted via support groups or multisite collaborations. To highlight the operation of PONT and describe some of the unique challenges that arise in online neuropsychological research, we summarize our experience using PONT in a research program involving individuals with Parkinson disease and spinocerebellar ataxia. In a 10-month period, by contacting 646 support group coordinators, we were able to assemble a participant pool with over 100 patients in each group from across the United States. Moreover, we completed six experiments (n > 300) exploring their performance on a range of tasks examining motor and cognitive abilities. The efficiency of PONT in terms of data collection, combined with the convenience it offers the participants, promises a new approach that can increase the impact of neuropsychological research.

COVID-19 and maternity care in South East London: shared working and learning initiative

The SARS-CoV-2 COVID-19 pandemic has had an immediate and profound impact on how healthcare systems organise and deliver services and specifically, there is a disproportionate negative impact on Black, Asian...

Collaborative Risk-Adapted Treatment for Pediatric Acute Lymphoblastic Leukemia in Mexico

Introduction:Outcomes for acute lymphoblastic leukemia (ALL) reported by high-income countries have historically not been reproducible in low- and middle-income countries (LMIC). In Mexico, 5-year event-free survival rate (EFS) for ALL is close to 50% and reasons for the inability to reproduce HIC results include excess of treatment-related mortality (TRM) and high relapse rates (RR). Although higher intensity is bound to lead to lower RR, the increased TRM seen in LMIC abrogates this benefit, leading to poor outcomes.Methods:In April 2016, the group Mexico in Alliance with St. Jude (MAS) was created with the aim to increase survival of children with cancer in Mexico via multi-site collaboration. Work began with ALL, considering its high incidence (89.5 cases per million per year). A retrospective review, including 207 patients diagnosed in 2015 at the 8 member centers was initially performed. Analysis of early therapy results in November 2016 (done to document baseline clinical characteristics and major contributors to early treatment failure) showed, 82% of patients classified as high-risk for reasons including: Leukocytosis >50,000 (27%), age >10 years (36%), T-cell immunophenotype (8%), CNS3 (4%), hypodiploidy (3%); mediastinal mass (4%), testicular infiltration (3%), poor response to prednisone (14%), prior treatment (8%), MLL (1%); iAmp21 (1%), and BCR-ABL (1%). Molecular studies and MRD were not send in up to a third of patients. Among MRD samples sent, 28% were interpreted as high, suggesting difficulty with distinction between leukemic blasts and hematogones. Excess of high-risk patients was noted, but accounted for from use of DNA index as independent predictor for high-risk disease, prior treatment, continuation of therapy after treatment abandonment, lack of MRD validation, and missing of a prognostic factor (due to lack of access to molecular studies, among others). TRM during induction was 12%, primarily as a result from infection, induction failure 2%, and a treatment abandonment rate 4%. At time of analysis, 75% were alive and under treatment, with RR of 8%. Documented survival was therefore already considerably lower than expected for the early follow-up. Unexpectedly high prevalence of classic adverse risk factors was not identified. Early survival was most again affected by high TRM rate during induction and early treatment.Results: Considering these data, three main lines of action were identified: a) Modernization of risk assignment across the 8 sites through collaborative regionalization of specialized diagnostic techniques, which allows homogeneous access to a pre-determined molecular biology panel and two MRD time points, and classification in 3 rather than 2 risk-groups; b) Reduction of TRM via implementation of a supportive therapies portfolio inclusive of 4 validated strategies and application of treatment de-intensification when feasible; and c) Establishment of a data management system to facilitate documentation of outcomes.Proposal:The developed protocol standardizes the introduction of three risk groups: Favorable-risk (FR), Intermediate-risk (IR) and High-risk (HR) based on clinical, genetic and biologic criteria. All patients share a de-intensified 4-drug remission induction therapy, undergo early response evaluation using MRD by flow cytometry, proceed to intensification unless induction failure is documented and receive final risk assignment after a second MRD check at the end of intensification. Intensification occurs with intermediate (FR) or high-dose (IR and HR) methotrexate in association with E. coli Asparaginase (ASP), considering the protective effect from methotrexate toxicity of such association described by Capizzi, a lower rate of allergic reactions to ASP when the time without ASP is reduced, and lack of access to Erwinia ASP or PEG. CNS prophylaxis with radiation therapy is completely omitted and replaced by lumbar punctures. FR patients receive one reinduction without anthracyclines, IR patients one reinduction with anthracyclines, and HR patients two reinductions. Continuation therapy continues for a total of two years, with three intensity levels defined based on risk group.Conclusion:Early adoption of new diagnostic technologies and of opportunities for de-intensification are crucial in LMIC in order to identify patients with favorable risk disease and reduce the burden of early mortality. DisclosuresNo relevant conflicts of interest to declare.

Pooling resources to enhance rigour in psychophysiological research: Insights from open science approaches to meta-analysis

Recent years have witnessed calls for increased rigour and credibility in the cognitive and behavioural sciences, including psychophysiology. Many procedures exist to increase rigour, and among the most important is the need to increase statistical power. Achieving sufficient statistical power, however, is a considerable challenge for resource intensive methodologies, particularly for between-subjects designs. Meta-analysis is one potential solution; yet, the validity of such quantitative review is limited by potential bias in both the primary literature and in meta-analysis itself. Here, we provide a non-technical overview and evaluation of open science methods that could be adopted to increase the transparency of novel meta-analyses. We also contrast post hoc statistical procedures that can be used to correct for publication bias in the primary literature. We suggest that traditional meta-analyses, as applied in ERP research, are exploratory in nature, providing a range of plausible effect sizes without necessarily having the ability to confirm (or disconfirm) existing hypotheses. To complement traditional approaches, we detail how prospective meta-analyses, combined with multisite collaboration, could be used to conduct statistically powerful, confirmatory ERP research.