Sharing sensitive data in life sciences: an overview of centralized and federated approaches.

Biomedical data are generated and collected from various sources, including medical imaging, laboratory tests and genome sequencing. Sharing these data for research can help address unmet health needs, contribute to scientific breakthroughs, accelerate the development of more effective treatments and inform public health policy. Due to the potential sensitivity of such data, however, privacy concerns have led to policies that restrict data sharing. In addition, sharing sensitive data requires a secure and robust infrastructure with appropriate storage solutions. Here, we examine and compare the centralized and federated data sharing models through the prism of five large-scale and real-world use cases of strategic significance within the European data sharing landscape: the French Health Data Hub, the BBMRI-ERIC Colorectal Cancer Cohort, the federated European Genome-phenome Archive, the Observational Medical Outcomes Partnership/OHDSI network and the EBRAINS Medical Informatics Platform. Our analysis indicates that centralized models facilitate data linkage, harmonization and interoperability, while federated models facilitate scaling up and legal compliance, as the data typically reside on the data generator's premises, allowing for better control of how data are shared. This comparative study thus offers guidance on the selection of the most appropriate sharing strategy for sensitive datasets and provides key insights for informed decision-making in data sharing efforts.

An assessment of the informative value of data sharing statements in clinical trial registries.

BACKGROUND: The provision of data sharing statements (DSS) for clinical trials has been made mandatory by different stakeholders. DSS are a device to clarify whether there is intention to share individual participant data (IPD). What is missing is a detailed assessment of whether DSS are providing clear and understandable information about the conditions for data sharing of IPD for secondary use. METHODS: A random sample of 200 COVID-19 clinical trials with explicit DSS was drawn from the ECRIN clinical research metadata repository. The DSS were assessed and classified, by two experienced experts and one assessor with less experience in data sharing (DS), into different categories (unclear, no sharing, no plans, yes but vague, yes on request, yes with specified storage location, yes but with complex conditions). RESULTS: Between the two experts the agreement was moderate to substantial (kappa=0.62, 95% CI [0.55, 0.70]). Agreement considerably decreased when these experts were compared with a third person who was less experienced and trained in data sharing ("assessor") (kappa=0.33, 95% CI [0.25, 0.41]; 0.35, 95% CI [0.27, 0.43]). Between the two experts and under supervision of an independent moderator, a consensus was achieved for those cases, where both experts had disagreed, and the result was used as "gold standard" for further analysis. At least some degree of willingness of DS (data sharing) was expressed in 63.5% (127/200) cases. Of these cases, around one quarter (31/127) were vague statements of support for data sharing but without useful detail. In around half of the cases (60/127) it was stated that IPD could be obtained by request. Only in in slightly more than 10% of the cases (15/127) it was stated that the IPD would be transferred to a specific data repository. In the remaining cases (21/127), a more complex regime was described or referenced, which could not be allocated to one of the three previous groups. As a result of the consensus meetings, the classification system was updated. CONCLUSION: The study showed that the current DSS that imply possible data sharing are often not easy to interpret, even by relatively experienced staff. Machine based interpretation, which would be necessary for any practical application, is currently not possible. Machine learning and / or natural language processing techniques might improve machine actionability, but would represent a very substantial investment of research effort. The cheaper and easier option would be for data providers, data requestors, funders and platforms to adopt a clearer, more structured and more standardised approach to specifying, providing and collecting DSS. TRIAL REGISTRATION: The protocol for the study was pre-registered on ZENODO ( https://zenodo.org/record/7064624#.Y4DIAHbMJD8 ).

Assessing the impact of sex on high-frequency repetitive transcranial magnetic stimulation´s clinical response in schizophrenia - results from a secondary analysis.

BACKGROUND: The evidence for repetitive transcranial magnetic stimulation (rTMS) to treat negative symptoms in schizophrenia (SCZ) is increasing, although variable response rates remain a challenge. Subject´s sex critically influences rTMS´ treatment outcomes. Females with major depressive disorder are more likely to respond to rTMS, while SCZ data is scarce. METHODS: Using data from the 'rTMS for the Treatment of Negative Symptoms in Schizophrenia' (RESIS) trial we assessed the impact of sex on rTMS´ clinical response rate from screening up to 105 days after intervention among SCZ patients. The impact of resting motor threshold (RMT) on response rates was also assessed. RESULTS: 157 patients received either active or sham rTMS treatment. No significant group differences were observed. Linear mixed model showed no effects on response rates (all p > 0.519). Apart from a significant sex*time interaction for the positive subscale of the positive and negative syndrome scale (PANSS) scores (p = 0.032), no other significant effects of sex on continuous PANSS scores were observed. RMT had no effect on response rate. CONCLUSION: In the largest rTMS trial on the treatment of SCZ negative symptoms we did not observe any significant effect of sex on treatment outcomes. Better assessments of sex-related differences could improve treatment individualisation.

"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences.

ECRIN - CESSDA strategies for cross metadata mappings in selected areas between life sciences and social sciences and humanities.

Background: The recent COVID-19 (Corona Virus Disease 2019) pandemic dramatically underlined the multi-faceted nature of health research, requiring input from basic biological sciences, pharmaceutical technologies, clinical research), social sciences and public health and social engineering. Systems that could work across different disciplines would therefore seem to be a useful idea to explore. In this study we investigated whether metadata schemas and vocabularies used for discovering scientific studies and resources in the social sciences and in clinical research are similar enough to allow information from different source disciplines to be easily retrieved and presented together. Methods: As a first step a literature search was performed, exemplarily identifying studies and resources, in which data from social sciences have been usefully employed or integrated with that from clinical research and clinical trials. In a second step a comparison of metadata schemas and related resource catalogues in ECRIN (European Clinical Research Infrastructure Network) and CESSDA (Consortium of European Social Science Data Archives) was performed. The focus was on discovery metadata, here defined as the metadata elements used to identify and locate scientific resources. Results: A close view at the metadata schemas of CESSDA and ECRIN and the basic discovery metadata as well as a crosswalk between ECRIN and CESSDA metadata schemas have shown that there is considerable resemblance between them. Conclusions: The resemblance could serve as a promising starting point to implement a common search mechanism for ECRIN and CESSDA metadata. In the paper four different options for how to proceed with implementation issues are presented.

An iterative and interdisciplinary categorisation process towards FAIRer digital resources for sensitive life-sciences data.

For life science infrastructures, sensitive data generate an additional layer of complexity. Cross-domain categorisation and discovery of digital resources related to sensitive data presents major interoperability challenges. To support this FAIRification process, a toolbox demonstrator aiming at support for discovery of digital objects related to sensitive data (e.g., regulations, guidelines, best practice, tools) has been developed. The toolbox is based upon a categorisation system developed and harmonised across a cluster of 6 life science research infrastructures. Three different versions were built, tested by subsequent pilot studies, finally leading to a system with 7 main categories (sensitive data type, resource type, research field, data type, stage in data sharing life cycle, geographical scope, specific topics). 109 resources attached with the tags in pilot study 3 were used as the initial content for the toolbox demonstrator, a software tool allowing searching of digital objects linked to sensitive data with filtering based upon the categorisation system. Important next steps are a broad evaluation of the usability and user-friendliness of the toolbox, extension to more resources, broader adoption by different life-science communities, and a long-term vision for maintenance and sustainability.

Medical journal requirements for clinical trial data sharing: Ripe for improvement.

Florian Naudet and co-authors discuss strengthening requirements for sharing clinical trial data.

Status, use and impact of sharing individual participant data from clinical trials: a scoping review.

OBJECTIVES: To explore the impact of data-sharing initiatives on the intent to share data, on actual data sharing, on the use of shared data and on research output and impact of shared data. ELIGIBILITY CRITERIA: All studies investigating data-sharing practices for individual participant data (IPD) from clinical trials. SOURCES OF EVIDENCE: We searched the Medline database, the Cochrane Library, the Science Citation Index Expanded and the Social Sciences Citation Index via Web of Science, and preprints and proceedings of the International Congress on Peer Review and Scientific Publication. In addition, we inspected major clinical trial data-sharing platforms, contacted major journals/publishers, editorial groups and some funders. CHARTING METHODS: Two reviewers independently extracted information on methods and results from resources identified using a standardised questionnaire. A map of the extracted data was constructed and accompanied by a narrative summary for each outcome domain. RESULTS: 93 studies identified in the literature search (published between 2001 and 2020, median: 2018) and 5 from additional information sources were included in the scoping review. Most studies were descriptive and focused on early phases of the data-sharing process. While the willingness to share IPD from clinical trials is extremely high, actual data-sharing rates are suboptimal. A survey of journal data suggests poor to moderate enforcement of the policies by publishers. Metrics provided by platforms suggest that a large majority of data remains unrequested. When requested, the purpose of the reuse is more often secondary analyses and meta-analyses, rarely re-analyses. Finally, studies focused on the real impact of data-sharing were rare and used surrogates such as citation metrics. CONCLUSIONS: There is currently a gap in the evidence base for the impact of IPD sharing, which entails uncertainties in the implementation of current data-sharing policies. High level evidence is needed to assess whether the value of medical research increases with data-sharing practices.

Effects of high-frequency prefrontal rTMS on heart frequency rates and blood pressure in schizophrenia.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a safe non-invasive neuromodulation technique used for the treatment of various neuropsychiatric disorders. The effect of rTMS applied to the cortex on autonomic functions has not been studied in detail in patient cohorts, yet patients who receive rTMS may have disease-associated impairments in the autonomic system and may receive medication that may pronounce autonomic dysfunctions. METHODS: Using data from the 'rTMS for the Treatment of Negative Symptoms in Schizophrenia' (RESIS) trial we evaluated the effect of rTMS applied to the left dorsolateral prefrontal cortex (DLPFC) on autonomic nervous system-related parameters such as blood pressure (BP) and heart rate (HR) in both reclining and standing postures from screening up to 105 days after intervention among patients with schizophrenia. RESULTS: 157 patients received either active (n = 76) or sham (n = 81) rTMS treatment. Apart from gender no significant group differences were observed. During intervention, Linear Mixed Model (LMM) analyses showed no significant time × group interactions nor time effects for any of the variables (all p > 0.055). During the whole trial beside a significant time × group interaction for diastolic BP (p = 0.017) in the standing posture, no significant time × group interactions for other variables (all p > 0.140) were found. CONCLUSION: These secondary analyses of the largest available rTMS trial on the treatment of negative symptoms in schizophrenia did not show a significant effect of active rTMS compared to sham rTMS on heart rate or blood pressure, neither during the intervention period nor during the follow-up period.

Reconvalescent plasma/camostat mesylate in early SARS-CoV-2 Q-PCR positive high-risk individuals (RES-Q-HR): a structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: Currently, there are no approved treatments for early disease stages of COVID-19 and few strategies to prevent disease progression after infection with SARS-CoV-2. The objective of this study is to evaluate the safety and efficacy of convalescent plasma (CP) or camostat mesylate administered within 72 h of diagnosis of SARS-CoV-2 infection in adult individuals with pre-existing risk factors at higher risk of getting seriously ill with COVID-19. Camostat mesylate acts as an inhibitor of the host cell serine protease TMPRSS2 and prevents the virus from entering the cell. CP represents another antiviral strategy in terms of passive immunization. The working hypothesis to be tested in the RES-Q-HR study is that the early use of CP or camostat mesylate reduces the likelihood of disease progression to (modified) WHO stages 4b-8 in SARS-CoV-2-positive adult patients at high risk of moderate or severe COVID-19 progression. TRIAL DESIGN: This study is a 4-arm (parallel group), multicenter, randomized (2:2:1:1 ratio), partly double-blind, controlled trial to evaluate the safety and efficacy of convalescent plasma (CP) or camostat mesylate with control or placebo in adult patients diagnosed with SARS-CoV-2 infection and high risk for progression to moderate/severe COVID-19. Superiority of the intervention arms will be tested. PARTICIPANTS: The trial is conducted at 10-15 tertiary care centers in Germany. Individuals aged 18 years or above with ability to provide written informed consent with SARS-CoV-2 infection, confirmed by PCR within 3 days or less before enrolment and the presence of at least one SARS-CoV-2 symptom (such as fever, cough, shortness of breath, sore throat, headache, fatigue, smell/and or taste disorder, diarrhea, abdominal symptoms, exanthema) and symptom duration of not more than 3 days. Further inclusion criteria comprise: Presence of at least one of the following criteria indicating increased risk for severe COVID-19: Age > 75 years Chronic obstructive pulmonary disease (COPD) and/or pulmonary fibrosis BMI > 40 kg/m2 Age > 65 years with at least one other risk factor (BMI > 35 kg/m2, coronary artery disease (CAD), chronic kidney disease (CKD) with GFR < 60 ml/min but ≥ 30 ml/min, diabetes mellitus, active tumor disease) BMI > 35 kg/m2 with at least one other risk factor (CAD, CKD with GFR < 60 ml/min but ≥ 30 ml/min, diabetes mellitus, active tumor disease) Exclusion criteria: 1. Age < 18 years 2. Unable to give informed consent 3. Pregnant women or breastfeeding mothers 4. Previous transfusion reaction or other contraindication to a plasma transfusion 5. Known hypersensitivity to camostat mesylate and/or severe pancreatitis 6. Volume stress due to CP administration would be intolerable 7. Known IgA deficiency 8. Life expectancy < 6 months 9. Duration SARS-CoV-2 typical symptoms > 3 days 10. SARS-CoV-2 PCR detection older than 3 days 11. SARS-CoV-2 associated clinical condition ≥ WHO stage 3 (patients hospitalized for other reasons than COVID-19 may be included if they fulfill all inclusion and none of the exclusion criteria) 12. Previously or currently hospitalized due to SARS-CoV-2 13. Previous antiviral therapy for SARS-CoV-2 14. ALT or AST > 5 x ULN at screening 15. Liver cirrhosis > Child A (patients with Child B/C cirrhosis are excluded from the trial) 16. Chronic kidney disease with GFR < 30 ml/min 17. Concurrent or planned anticancer treatment during trial period 18. Accommodation in an institution due to legal orders (§40(4) AMG). 19. Any psycho-social condition hampering compliance with the study protocol. 20. Evidence of current drug or alcohol abuse 21. Use of other investigational treatment within 5 half-lives of enrolment is prohibited 22. Previous use of convalescent plasma for COVID-19 23. Concomitant proven influenza A infection 24. Patients with organ or bone marrow transplant in the three months prior to screening visit INTERVENTION AND COMPARATOR: Participants will be randomized to the following 4 groups: 1) Convalescent plasma (CP), 2 units at screening/baseline visit (day 0) or day 1; CP is defined by the presence of neutralizing anti-SARS-CoV-2 antibodies with titers ≥ 1:160; individuals with body weight ≥ 150 kg will receive a third unit of plasma on day 3 2) Camostat mesylate (200 mg per capsule, one capsule taken each in the morning, afternoon and evening on days 1-7) 3) Standard of care (SOC, control for CP) 4) Placebo (identical in appearance to camostat mesylate capsules, one capsule taken each morning, afternoon and evening on days 1-7; for camostat mesylate control group) Participants will be monitored after screening/baseline on day 3, day 5, day 8, and day 14. On day 28 and day 56, telephone visits and on day 90, another outpatient visit are scheduled. Adverse events and serious adverse events will be monitored and reported until the end of the study. An independent data safety monitoring committee will review trial progression and safety. MAIN OUTCOMES: The primary endpoint of the study is the cumulative number of individuals who progress to or beyond category 4b on the modified WHO COVID-19 ordinal scale (defined as hospitalization with COVID-19 pneumonia and additional oxygen demand via nasal cannula or mask) within 28 days after randomization. RANDOMIZATION: Participants will be randomized using the Alea-Tool ( aleaclinical.com ) in a 2:2:1:1 ratio to the treatment arms (1) CP, (2) camostat mesylate, (3) standard of care (SoC), and (4) placebo matching camostat mesylate. Randomization will be stratified by study center. BLINDING (MASKING): The camostat mesylate treatment arm and the respective placebo will be blinded for participants, caregivers, and those assessing outcomes. The treatment arms convalescent plasma and standard of care will not be blinded and thus are open-labeled, unblinded. NUMBERS TO BE RANDOMIZED (SAMPLE SIZE): Overall, n = 994 participants will be randomized to the following groups: n = 331 to convalescent plasma (CP), n = 331 to camostat mesylate, n = 166 to standard of care (SoC), and n = 166 to placebo matching camostat mesylate. TRIAL STATUS: The RES-Q-HR protocol (V04F) was approved on the 18 December 2020 by the local ethics committee and by the regulatory institutions PEI/BfARM on the 2 December 2020. The trial was opened for recruitment on 26 December 2020; the first patient was enrolled on 7 January 2021 and randomized on 8 January 2021. Recruitment shall be completed by June 2021. The current protocol version RES-Q HR V05F is from 4 January 2021, which was approved on the 18 January 2021. TRIAL REGISTRATION: EudraCT Number 2020-004695-18 . Registered on September 29, 2020. ClinicalTrial.gov NCT04681430 . Registered on December 23, 2020, prior to the start of the enrollment (which was opened on December 26, 2020). FULL PROTOCOL: The full protocol (V05F) is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this letter serves as a summary of the key elements of the full protocol. The study protocol has been reported in accordance with the Standard Protocol Items: Recommendations for Clinical Interventional Trials (SPIRIT) guidelines (Additional file 2).

European survey on national harmonization in clinical research.

BACKGROUND: Clinical trials remain key to the development of evidence-based medical practice. However, they are becoming increasingly complex, mainly in a multinational setting. To address these challenges, the European Union (EU) adopted the Clinical Trial Regulation EU No. 536/2014 (CTR). Once in force, the CTR will lead to more consistent rules and simplification of procedures for conducting clinical trials throughout the EU. Existing harmonization initiatives and "research infrastructures" for clinical trials may facilitate this process. This publication offers a snapshot of the current level of harmonization activities in academic clinical research in Europe. METHODS: A survey was performed among the member and observer countries of the European Clinical Research Infrastructure Network (ECRIN), using a standardized questionnaire. Three rounds of data collection were performed to maximize completeness and comparability of the received answers. The survey aimed to describe the harmonization of academic clinical research processes at national level, to facilitate the exchange of expertise and experience among countries, and to identify new fields of action. RESULTS: Most scientific partners already have in place various working groups and harmonization activities at national level. Furthermore, they are involved in and open to sharing their know-how and documents. Since harmonization was mainly a bottom-up approach up until now, the extent and topics dealt with are diverse and there is only little cross-networking and cross-country exchange so far. CONCLUSIONS: Currently, the ECRIN member countries offer a very solid base and collaborative spirit for further aligning processes and exchanging best practices for clinical research in Europe. They can support a smooth implementation of the EU CTR and may act as single contact with consolidated expertise in a country.

Assessment of a demonstrator repository for individual clinical trial data built upon DSpace.

Background: Given the increasing number and heterogeneity of data repositories, an improvement and harmonisation of practice within repositories for clinical trial data is urgently needed. The objective of the study was to develop and evaluate a demonstrator repository, using a widely used repository system (DSpace), and then explore its suitability for providing access to individual participant data (IPD) from clinical research. Methods: After a study of the available options, DSpace (version 6.3) was selected as the software for developing a demonstrator implementation of a repository for clinical trial data. In total, 19 quality criteria were defined, using previous work assessing clinical data repositories as a guide, and the demonstrator implementation was then assessed with respect to those criteria. Results: Generally, the performance of the DSpace demonstrator repository in supporting sensitive personal data such as that from clinical trials was strong, with 14 requirements demonstrated (74%), including the necessary support for metadata and identifiers. Two requirements could not be demonstrated (the ability to include de-identification tools and the availabiltiy of a self-attestation system) and three requirements were only partially demonstrated (ability to provide links to de-identification tools and requirements, incorporation of a data transfer agreement in system workflow, and capability to offer managed access through application on a case by case basis). Conclusions: Technically, the system was able to support most of the pre-defined requirements, though there are areas where support could be improved. Of course, in a productive repository, appropriate policies and procedures would be needed to direct the use of the available technical features. A technical evaluation should therefore be seen as indicating a system's potential, rather than being a definite assessment of its suitability. DSpace clearly has considerable potential in this context and appears a suitable base for further exploration of the issues around storing sensitive data.

Promoting stigma coping and empowerment in patients with schizophrenia and depression: results of a cluster-RCT.

There is a need for interventions supporting patients with mental health conditions in coping with stigma and discrimination. A psycho-educational group therapy module to promote stigma coping and empowerment (STEM) was developed and tested for efficacy in patients with schizophrenia or depression. 30 clinical centers participated in a cluster-randomized clinical trial, representing a broad spectrum of mental health care settings: in-patient (acute treatment, rehabilitation), out-patient, and day-hospitals. As randomized, patients in the intervention group clusters/centers received an illness-specific eight sessions standard psychoeducational group therapy plus three specific sessions on stigma coping and empowerment ('STEM'). In the control group clusters the same standard psychoeducational group therapy was extended to 11 sessions followed by one booster session in both conditions. In total, N = 462 patients were included in the analysis (N = 117 with schizophrenia spectrum disorders, ICD-10 F2x; N = 345 with depression, ICD-10 F31.3-F31.5, F32-F34, and F43.2). Clinical and stigma-related measures were assessed before and directly after treatment, as well as after 6 weeks, 6 months, and 12 months (M12). Primary outcome was improvement in quality of life (QoL) assessed with the WHO-QOL-BREF between pre-assessment and M12 analyzed by mixed models and adjusted for pre-treatment differences. Overall, QoL and secondary outcome measures (symptoms, functioning, compliance, internalized stigma, self-esteem, empowerment) improved significantly, but there was no significant difference between intervention and control group. The short STEM module has proven its practicability as an add-on in different settings in routine mental health care. The overall increase in empowerment in both, schizophrenia and depression, indicates patients' treatment benefit. However, factors contributing to improvement need to be explored.The study has been registered in the following trial registers. ClinicalTrials.gov: https://register.clinicaltrials.gov/ Registration number: NCT01655368. DRKS: https://www.drks.de/drks_web/ Registration number: DRKS00004217.

Evaluation of repositories for sharing individual-participant data from clinical studies.

BACKGROUND: Data repositories have the potential to play an important role in the effective and safe sharing of individual-participant data (IPD) from clinical studies. We analysed the current landscape of data repositories to create a detailed description of available repositories and assess their suitability for hosting data from clinical studies, from the perspective of the clinical researcher. METHODS: We assessed repositories that enable storage, sharing, discoverability, re-use of the IPD and associated documents from clinical studies using a pre-defined set of 34 items and publicly available information from April to June 2018. For this purpose, we developed an indicator set to capture the maturity of the repositories' procedures and their suitability for the hosting of IPD. The indicators cover guidelines for data upload and data de-identification, data quality controls, contracts for upload and storage, flexibility of access, application of identifiers, availability of metadata, and long-term preservation. RESULTS: We analysed 25 repositories, from an initial set of 55 identified as possibly relevant. Half of the included repositories were generic, i.e. not limited to a specific disease or clinical area and 13 were launched in the last 8 years. The sample was extremely heterogeneous and included repositories developed by research funders, infrastructures, universities, and editors. All but three repositories do not apply a fee for uploading, storage or access to data. None of the repositories completely demonstrated all the items included in the indicator set, but three repositories (Dryad, Drum, EASY) met - fully or partially - all items. Flexibility of data-access modalities appears to be limited, being lacking in half of the repositories. CONCLUSIONS: Our evaluation, though often hampered by the lack of sufficient information, can help researchers to find a suitable repository for their datasets. Some repositories are more mature because of their support for clinical dataset preparation, contractual agreements, metadata and identifiers, different modalities of access, and long-term preservation of data. Further work is now required to achieve a more robust and accurate system for evaluation, which in turn may encourage the sharing of clinical study data. TRIAL REGISTRATION: Study protocol available at https://zenodo.org/record/1438261#.W64kW9Egrcs .

Efficacy of high-frequency repetitive transcranial magnetic stimulation in schizophrenia patients with treatment-resistant negative symptoms treated with clozapine.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a promising augmentation treatment for schizophrenia, however there are few controlled studies of rTMS augmentation of clozapine. METHODS: Using data from the 'rTMS for the Treatment of Negative Symptoms in Schizophrenia' (RESIS) trial we examined the impact of rTMS on PANSS total, general, positive and negative symptoms among participants on clozapine. rTMS was applied to the left dorsolateral prefrontal cortex (DLPFC) for five treatment sessions/week for 3-weeks as augmentation for patients with a predominant negative syndrome of schizophrenia, as rated on PANSS. RESULTS: 26 participants from the RESIS trial were on clozapine, receiving active (N=12) or sham (N=14) rTMS treatment. In our Linear Mixed Model (LMM) analysis, time×group interactions were significant in the PANSS positive subscale (p=0.003) (not being the corresponding behavioral output for DLPFC stimulation), the PANSS general subscale (p<0.001), the PANSS total scale (p=0.015), but not the PANSS negative subscale (p=0.301) (primary endpoint of the RESIS trial), when all PANSS measurements from screening to day 105 were included. Descriptive data suggests that in the active group the improvement was more pronounced compared to the sham rTMS group. CONCLUSIONS: In this largest available clozapine cohort, active rTMS may be more effective than sham rTMS when added to clozapine for positive and total psychotic symptoms. These findings should be interpreted with caution given this is a secondary analysis with a limited number of participants.

Classification of processes involved in sharing individual participant data from clinical trials.

Background: In recent years, a cultural change in the handling of research data has resulted in the promotion of a culture of openness and an increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of many actors and actions. Individual services and tools to support data sharing are becoming available, but what is missing is a detailed, structured and comprehensive list of processes and subprocesses involved and the tools and services needed. Methods: Principles and recommendations from a published consensus document on data sharing were analysed in detail by a small expert group. Processes and subprocesses involved in data sharing were identified and linked to actors and possible supporting services and tools. Definitions adapted from the business process model and notation (BPMN) were applied in the analysis. Results: A detailed and comprehensive tabulation of individual processes and subprocesses involved in data sharing, structured according to 9 main processes, is provided. Possible tools and services to support these processes are identified and grouped according to the major type of support. Conclusions: The identification of the individual processes and subprocesses and supporting tools and services, is a first step towards development of a generic framework or architecture for the sharing of data from clinical trials. Such a framework is needed to provide an overview of how the various actors, research processes and services could interact to form a sustainable system for data sharing.

Efficacy of high-frequency repetitive transcranial magnetic stimulation on PANSS factors in schizophrenia with predominant negative symptoms - Results from an exploratory re-analysis.

Repetitive transcranial magnetic stimulation (rTMS) applied to the left frontal lobe is discussed to be a promising add-on treatment for negative symptoms in schizophrenia. The Positive and Negative Syndrome Scale (PANSS) has been used as outcome parameter in several previous rTMS trials, but studies focusing on PANSS factor analyses are lacking. For this purpose, we used the available PANSS data of the 'rTMS for the Treatment of Negative Symptoms in Schizophrenia' (RESIS) trial to calculate different literature-based PANSS factors and to re-evaluate the impact of rTMS on negative symptoms in this trial. In an exploratory re-analysis of published data from the RESIS study (Wobrock et al. 2015), we tested the impact of rTMS applied to the left dorsolateral prefrontal cortex on two PANSS factors for negative symptoms in psychotic disorders as well as on a PANSS five-factor consensus model intending to show that active rTMS treatment improves PANSS negative symptom subscores. In accordance to the original analysis, all PANSS factors showed an improvement over time in the active and, to a considerable extent, also in the sham rTMS group. However, comparing the data before and directly after the rTMS intervention, the PANSS excitement factor improved in the active rTMS group significantly more than in the sham group, but this finding did not persist if follow-up data were taken into account. These additional analyses extend the previously reported RESIS trial results showing unspecific improvements in the PANSS positive subscale in the active rTMS group. Our PANSS factor-based approach to investigate the impact of prefrontal rTMS on different negative symptom domains confirmed no overall beneficial effect of the active compared to sham rTMS.

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis.

Background: The variability of responses to plasticity-inducing repetitive transcranial magnetic stimulation (rTMS) challenges its successful application in psychiatric care. No objective means currently exists to individually predict the patients' response to rTMS. Methods: We used machine learning to develop and validate such tools using the pre-treatment structural Magnetic Resonance Images (sMRI) of 92 patients with schizophrenia enrolled in the multisite RESIS trial (http://clinicaltrials.gov, NCT00783120): patients were randomized to either active (N = 45) or sham (N = 47) 10-Hz rTMS applied to the left dorsolateral prefrontal cortex 5 days per week for 21 days. The prediction target was nonresponse vs response defined by a ≥20% pre-post Positive and Negative Syndrome Scale (PANSS) negative score reduction. Results: Our models predicted this endpoint with a cross-validated balanced accuracy (BAC) of 85% (nonresponse/response: 79%/90%) in patients receiving active rTMS, but only with 51% (48%/55%) in the sham-treated sample. Leave-site-out cross-validation demonstrated cross-site generalizability of the active rTMS predictor despite smaller training samples (BAC: 71%). The predictive pre-treatment pattern involved gray matter density reductions in prefrontal, insular, medio-temporal, and cerebellar cortices, and increments in parietal and thalamic structures. The low BAC of 58% produced by the active rTMS predictor in sham-treated patients, as well as its poor performance in predicting positive symptom courses supported the therapeutic specificity of this brain pattern. Conclusions: Individual responses to active rTMS in patients with predominant negative schizophrenia may be accurately predicted using structural neuromarkers. Further multisite studies are needed to externally validate the proposed treatment stratifier and develop more personalized and biologically informed rTMS interventions.