1 | Page Schistosomiasis Data Platform Stakeholder Meeting World Health Organization, Geneva 3 – 4 September 2015 Meeting Report This report summarizes the discussion and agreements of a stakeholder meeting to discuss needs and requirements for sharing schistosomiasis treatment efficacy trials data. The meeting took place in Geneva on 3-4 September 2015. It was convened by The Special Programme for Research and Training in Tropical Diseases (TDR) and the WHO Neglected Tropical Diseases department (WHO/NTD). Participants. Stakeholders represented a community of clinical researchers, country control programmes managers, one platform developer and funding agencies. The List of Participants and Agenda are in Annex 2. All participants filled the declaration of interest form; all but one declared no conflicts. The one case was discussed with WHO legal counsel and resolved. Content of the meeting. The meeting was organised around three broad areas: (1) contemporary issues around data-sharing and evidence-generation; (2) examples of an initial pilot project of praziquantel clinical trial data based upon an existing malaria platform; (3) stakeholders’ input into the needs, scope, benefits and issues, and design of a data-sharing platform of schistosomiasis treatment study data. Scope of the meeting. The meeting was organised following the recommendations of the Committee on Strategies for Responsible Sharing of Clinical Data of the Institute of Medicine of the National Academies (2014) to engage the community in discussions around: (1) stakeholders’ responsibilities in fostering a culture in which sharing is the norm; (2) what data should be shared when; (3) with whom should data be shared and under what conditions; (4) how stakeholders should work together on key challenges towards a vision for data sharing.
Transcript
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Schistosomiasis Data Platform Stakeholder Meeting
World Health Organization, Geneva 3 – 4 September 2015
Meeting Report
This report summarizes the discussion and agreements of a stakeholder meeting to discuss needs
and requirements for sharing schistosomiasis treatment efficacy trials data. The meeting took place
in Geneva on 3-4 September 2015. It was convened by The Special Programme for Research and
Training in Tropical Diseases (TDR) and the WHO Neglected Tropical Diseases department
(WHO/NTD).
Participants. Stakeholders represented a community of clinical researchers, country control
programmes managers, one platform developer and funding agencies. The List of Participants and
Agenda are in Annex 2. All participants filled the declaration of interest form; all but one declared
no conflicts. The one case was discussed with WHO legal counsel and resolved.
Content of the meeting. The meeting was organised around three broad areas: (1) contemporary
issues around data-sharing and evidence-generation; (2) examples of an initial pilot project of
praziquantel clinical trial data based upon an existing malaria platform; (3) stakeholders’ input into
the needs, scope, benefits and issues, and design of a data-sharing platform of schistosomiasis
treatment study data.
Scope of the meeting. The meeting was organised following the recommendations of the
Committee on Strategies for Responsible Sharing of Clinical Data of the Institute of Medicine of the
National Academies (2014) to engage the community in discussions around: (1) stakeholders’
responsibilities in fostering a culture in which sharing is the norm; (2) what data should be shared
when; (3) with whom should data be shared and under what conditions; (4) how stakeholders
should work together on key challenges towards a vision for data sharing.
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A. BACKGROUND
1. Introduction: Rationale for data-sharing
1.1. Evidence for policy. Treatment recommendations and policies rely and depend on the
quality of the evidence-base. Systematic reviews and meta-analyses are an essential
element in the generation of such evidence, but are contingent upon research results being
made publicly available, as well as the quality of studies. Oftentimes, the lack of generally
adopted standards makes it difficult to derive definite conclusions using published
aggregated results. Collating and analysing individual-participant level data partly corrects
this problem and allows one to utilise more fully the potential for generating evidence
from the total range of the studies conducted.
1.2. Data sharing
1.2.1. Obligations and efficiencies. Sharing primary research data is advocated by the
World Health Organization (WHO) and other bodies (Moorthy et al, PLoS Medicine
2015; IOM report, 2014) and is now required by research sponsors and funders (to
maximise the impact of the research they fund), as well as publishers (concerned
about the reliability and reproducibility of the results they publish); researchers
will increasingly be compelled to commit to share results and data sets in order to
get funded, as well as having their results published in principled scientific
journals.
1.2.2. Moral imperatives and social mission. Data and knowledge are increasingly
seen as ‘public goods’ which are no longer to be ‘owned’ by the individuals or
institutions that generate them. Consequently, it is an ethical obligation for all data
generators and holders to facilitate and participate in this activity of ‘caretaking’ by
not shutting the data away. This ethical obligation is all the more important in the
case of neglected tropical diseases, for which the amount of generated data is
limited compared to the extent of the problem and disease burden, and for which
resources are scarce. Avoiding duplication of research by making what already
exists sustainably available and accessible to others is therefore required.
1.2.3. Data generators. Some participants expressed concerns about data generators
conducting challenging clinical trials in the field being at a disadvantage with
respect to data users in more privileged environments. There was a general
agreement that clinical field research should be encouraged and protected, and
investments should be made into funding studies and strengthening local
capacities.
1.2.4. Stakeholders’ responsibilities. Meeting these principles requires that
stakeholders jointly work together to design the physical platform and governance
structure where data can be collated and accessed. Stakeholders present at the
meeting represented researchers, country control programmes and funding
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agencies. As concerns and fears regarding data sharing and misuse still abound,
trusted organisations are required to lead the way and limit barriers. In particular,
WHO must promote equal access and ethics. It should negotiate with governments
and research organisations as needed to drive a ‘buy-in’ from all countries and the
community at large in the important initiative of data sharing, and to spread the
newly emerging concepts of ‘caretaking’ or ‘guardianship’ rather than ‘ownership’
of data. A consensual WHO endorsement is very important to advocate for sharing
of data and transparency on how data are handled. Such a universal agreement will
promote trust, and spread the idea that the shared data is placed in a ‘safe
harbour’.
1.2.5. Data ‘caretakers’. Considering the information and technology (IT) tools
currently available, it was noted that the data repository does not need to
physically hold all the data in a specific place: the option of cloud storage enables
actors worldwide to securely access data via a server, wherever it may be based,
and is cost-effective. Such IT infrastructure strongly facilitates the process of
‘sharing’, as the data are not locked in a specific space, are not given away at a loss
of the initial provider, and remain a sustainable resource that can be used and re-
used at will without depriving future users from access.
1.3. In this evolving context, participants of the workshop considered and discussed the
benefits and challenges of sharing data for the schistosomiasis research and disease
control community.
2. Benefits to participation
2.1. Scientific benefits: Aggregated data bring benefits because the goal of research is to
produce generalizable results and a robust evidence-base, upon which decision-makers
can make rational choices for case management, disease control, and research. Merging
data provides advantages of numbers and enables the study of varied ranges of patient
populations, doses, age groups, and treatment performance in different settings.
2.2. Practical benefits:
2.2.1. Standardized data capture, datasets, and analytical tools allow consistent analyses
and interpretation of results in the context of other studies. A standardised
collation of available data will aid the design of future studies that can generate
comparable datasets.
2.2.2. A data platform will provide a safe environment in which to store data in order to
meet the requirements for data disclosure of funding agencies and publishers. It
will also make similar data more easily discoverable and retrievable and will
provide greater visibility to individual groups.
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2.3. Capacity strengthening opportunities in disease-endemic countries:
2.3.1. Establishing a data-sharing initiative will help in creating opportunities for
strengthening the in-country capacity for data management and analysis, in
particular for individual-participant level data meta-analyses. Generally speaking,
elements of capacity building should be an integral part of every clinical research
study. Furthermore, more structured curriculum and training programmes should
be explored (for instance by TDR, but also other funders and development
agencies) to address this systemic need.
3. Risks and challenges
3.1. Data ‘ownership’: While acknowledging that the situation is evolving and that data-
sharing is becoming an opt-out rather than opt-in activity for researchers and data
generators, there is still a widespread feeling of ‘proprietary information’, and that the
investigator ‘own’ the data.
3.2. Recognition: There is a fear that data users will not acknowledge or credit those who are
generating the data, which may be mitigated if access to and use of data were to be
regulated. The reason for this is that those generating data in the disease-endemic
countries generally suffer from limited data management and analysis capacity, and
believe that they will not be able to compete with researchers from resource-rich
countries. This creates an artificial dichotomy between data-providers and data-users. The
above-mentioned capacity building initiatives aim at correcting this situation. In addition,
when data are re-analysed, it is important to fully acknowledge data contributions.
3.3. Restrictions: Some countries might have regulations that could restrict sharing and use of
data generated by country control programmes or local research groups; there might be
study-specific requirements which would limit data sharing and re-analysis.
B. DISCUSSION
4. Governance
4.1. The participants stressed that trust in the process is key, and that proper governance of a
“responsible data sharing platform” is essential to address the abovementioned concerns.
4.2. While WHO and TDR cannot host the repository and provide the financial support for
long-term sustainability of the platform, they were seen as the required guarantor. The
participants asked that WHO and TDR:
4.2.1. Continue to lead this initiative, and further promote and steer the platform.
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4.2.2. Work with the stakeholders to define the terms and conditions and terms of
reference for the platform, terms of submission for data-providers, and obligations
for data-users.
4.2.3. Help find an appropriate host for the platform, which will meet the
abovementioned terms and conditions. The repository will be run by a third party,
academic institute, or another institution and must have the bioinformatics
experience and technical capacity to upload, curate, and manage such data, as well
as provide prospects for sustainability. Potential means of selecting the data
reference centre were discussed, including e.g. (i) through a call to which all
potential institutions apply and are selected in a transparent manner; (ii) through
a consortium formed that would consist of key players who would work together
to apply to funding bodies together; or (iii) by building upon existing facilities to
minimise costs and shorten timelines.
4.2.4. Facilitate search for funders and long-term sustainability.
5. Access to data
5.1. General data access rules: Various models were considered: Model 1 – closed, only open
to contributors; Model 2 – gated via a Data Access Committee (DAC); Model 3 – completely
open. The majority of the meeting participants agreed on a gated model with a DAC (Model
2) (see 5.2 below) whereby: (i) data-providers will always have access to the data they
have contributed themselves; (ii) curators will have access to all of the data, which is
essential for its standardisation; (iii) prospective data-users requesting access to the
whole or part of the dataset (including other parties and individual study data-
contributors) will have access to relevant data only upon permission of the DAC. It was
also generally agreed that summary aggregated (not individual-participant level) data,
with related dataset descriptors (metadata), will be made available on a website page with
unrestricted access, so as to make it possible for all to browse, by category, for potentially
useful datasets.
5.2. Regulation body: A core Data Access Committee (DAC) should be formed to assess
requests and grant access to data for analyses according to an agreed set of criteria and
obligations (see 4.2.2). The design of a “responsible data sharing platform” will ensure
data security. Based on previous experience of existing datacentres, a small committee and
the use of simple access rules will provide the most effective and cost-efficient solution.
5.3. General data security and quality rules: The repository must ensure security of the data
from upload to storage and transfer, and have appropriate backup systems in place. Data
providers must ensure full data anonymity and provide protocols on how the study was
conducted and the data were collected, which will accompany the database; data
providers are also responsible for data quality.
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6. Technical aspects (Annex 1)
7. Next steps
7.1. Meeting report: draft prepared by secretariat and shared; final summary report will be
posted on the WHO/TDR and NTD websites (including a French version); possible
publication in PLoS NTD for greater visibility.
7.2. Options for shorter and longer term plans will be discussed and developed with the group.
The creation of a steering committee will be considered if the more inclusive process
involving the entire group should prove too cumbersome.
7.3. TDR will submit the project for review to the Intervention and Implementation Research
(IIR) Scientific Working Group (SWG) at their meeting in December.
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Annex 1: Technical aspects
Data gathered
No need to have STH during the drug efficacy trial targeting Schistosoma, suggested to have a similar repository for STH given a similar analysis and study design.
o Minimal requirements
o Study design: randomized controlled trials; non-randomized trials; multiple arms; WHO guidelines recommend; registration number at clinical trials
Info on
Brand of drug
Active compound
Dose
Age
Gender
Egg count before and after
Amount of stool/urine examined
Follow-up time (history data based on thresholds for follow-up of M-A; in future recommended WHO guidelines)
Diagnostic method
Date of treatment(s)
Date of each pre-intervention analysis
Date of each follow-up analysis
Note1: labelling of the variables/legend; link dates to analysis results
Note 2: inclusion of untreated subjects (refusing/contra-indication/pregnancy).
Note 3: inclusion of STH when KK is applied.
Note 4: original individual egg counts no means of eggs slide
Note 5: adding data of M&E data for an operational evaluation
Note 6: number of tablets taken
Note 7: follow-up according to pre-patent period
o No year limit. Surveys not meeting the minimal requirements will automatically be
omitted.
o Optional data
Viability of the eggs
Weight
Species of snails
Mixed infections (STH/Schistosoma spp)
Adverse events (requirement for new drugs/drug combination)
Treatment history at population level (historical data: desirable; future data: recommend).
Treatment history at individual level (difficult to collect).
No need for having information on the snails.
Note 1: definition of location for GPS.
Other information on the study
Inclusion and exclusion criteria
Protocol
Ways of sorting/displaying data
o Step-wise display: (i) map providing sample size, CR and ERR (different maps/colour code for each drug, species); (ii) details on sample size, drug, dose, CR, ERR, follow-up period; country/district, reference per strata in a Table (country, drug, Schistosma spp., dose, etc.).
Analysis envisioned on shared data
o Automated and standardized re-analysis
Standard analysis for drug efficacy estimates: CR and ERR (both formulae) and confidence intervals;
Comparing with efficacy results with other trials already present in the database;
Some summary of individual analysis.
o Non-automated analysis
Research questions
Efficacy in pre-SAC
Impact MDA on drug efficacy
Geographical hot spots where drugs are failing
Mixed infections
How to organize the working groups to answer them?
Anyone should be able to do them
Specification of the question/identification of the group to avoid overlap/repetition; put on the website
Organization should be discussed on a large base
Sustainability of the chosen structure
Management of website
Place hosting website, all countries are eligible
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Annex 1: Agenda and List of Participants
DRAFT AGENDA
Schistosomiasis Data Platform Stakeholders Meeting
3 – 4 September 2015, Geneva
When What Who
Day 1, 3 September 2015. 9.00-17.30
9.00-10.30 Welcome Director TDR Introductions All Election of Chairperson and Rapporteur Scope of the meeting: why are we here, what we want to
achieve. Needs and rationale for sharing anti-schistosoma treatment data
P. Olliaro, A. Garba Followed by initial discussion
Treatment data landscape: systematic assessment of available trials which could contribute to the database.
A. Julé Followed by general discussion
10.30-11.00 Coffee break Prototype database – demo. P. Guérin
Followed by general discussion
Data Management. Data curation: issues with constructing a common dataset
M. Vaillant
Examples of analyses possible with individual-level participant data:
Results of pooled analyses from data shared in the pilot database
Modelling responses
P. Olliaro, M. Vaillant M. Walker
13.00-14.00 Lunch break 14.00-15.30 Stakeholders views on the requirements and scope of a
data-sharing platform All
15.30-16.00 Coffee break 16.00-17.30 General discussion on principles of contributions, access
and use of a shared database All
Definition and objectives of working works 17.30 Adjourn
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When What Who
Day 2, 4 September 2015. 9.00-17.30
9.00 Breakdown groups All 10.30-11.00 Coffee break 11.00-12.30 Breakdown groups All 12.30-14.00 Lunch break 14.00-17.30 Report of working groups WG Rapporteurs General discussion. Definition of follow-up actions and next
steps All
Summary 17.30 Close of the meeting P. Olliaro, A. Garba
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Schistosomiasis Treatment efficacy - Data Sharing Platform Stakeholders Meeting
3- 4 September 2015
Starling Geneva Hotel & Conference Center
Geneva, Switzerland
List of participants
Professor Abdoulaye Dabo Department of Epidemiology of Infectious Diseases Faculty of Medicine, Pharmacy and Dentistry UMI 3189, University of Sciences, Techniques and Technologies of Bamako Box 1805 Bamako Mali
Ms Amélie Julé Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive Oxford, OX3 7FZ United Kingdom
Dr Anna Phillips Schistosomiasis Control Initiative Imperial College London VB11 Medical School Norfolk Place, St Mary's Campus London W2 1PG United Kingdom
Dr Annette Olsen Department of Veterinary Disease Biology Faculty of Health and Medical Sciences Dyrlægevej 100 DK-1870 Frederiksberg C Denmark
Dr Bruno Levecke Department of Virology, Parasitology and Immunology Ghent University Faculty of Veterinary Medicine Salisburylaan 133 Merelbeke 9820 Belgium
Professor Charles King Professoressor of International Health Center for Global Health and Diseases Case Western Reserve University School of Medicine Cleveland, Ohio 44106 United States of America
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Professor Eliezer N'goran Unité de Formation et de Recherche Biosciences Université Félix Houphouët-Boigny Abidjan 02 BP 770 Côte d'Ivoire
Dr Garba Amina A. Hamidou Riseal Niger 1448, Avenue de l’Independence BP.13724, Niamey, Niger
Dr Idrissa Talla Direction de la Lutte contre la Maladie Ministère de la Santé Dakar Senegal
Professor Jutta Reinhard-Rupp Head of Translational Innovation Platform Global Health Research & Development Merck Serono S.A. 7 Route de la Verrerie 1267 Coinsins Switzerland
Professor Juerg Utzinger Director, Swiss Tropical and Public Health Institute Socinstr. 57 Basel 4051 Switzerland
Dr Mark Booth Senior Lecturer School of Medicine, Pharmacy and Health Durham University Thornaby United Kingdom
Dr Michel Vaillant Researcher Competence Center in Methodology and Statistics Luxembourg Institute of Health 1A-B, rue Thomas Edison, L-1445 Strassen Luxembourg
Dr Mohamed Ouldabdallahi Moukah Initiative mauritanienne pour la lutte contre les maladies endémiques « MEDCINGO » ilôt 358, Riyad Pk8 Nouakchott Mauritania
Dr Moussa Sacko Laboratory of Parasitology Institut National de Recherche en Santé Publique Bamako 1771 Mali
Dr Monique Dorkenoo Lecturer Parasitology Faculté Mixte de Médecine et de Pharmacie Université de Lomé 373 rue Atakora Sito-Aeroport BP 7941 Lomé Togo
Dr Martin Walker Department of Infectious Disease Epidemiology Faculty of Medicine (St Mary’s campus) Imperial College London Norfolk Place Paddington London United Kingdom
Dr Narcis Kabatareine Vector Control Division Ministry of Health P.O. Box 1661 Kampala Uganda
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Professor Nicholas Midzi Department of Medical Microbiology College of Health Sciences University of Zimbabwe Causeway Harare Zimbabwe
Dr Olusola Ojurongbe Department of Medical Microbiology and Parasitology, Ladoke Akintola University of Technology, Osogbo, Nigeria
Dr Otavio Pieri Laboratorio de Eco-Epidemiologia e Controle da Esquistossomose e Geohelmintoses Instituto Oswaldo Cruz, FIOCRUZ Rio de Janeiro Brazil
Dr Pauline Mwinzi Centre for Global Health Research Kenya Medical Research Institute (KEMRI) Central Kisumu Kisumu Kenya
Professor Philippe Guérin WorldWide Antimalarial Resistance Network (WWARN) University of Oxford Oxford United Kingdom
Professor Rashika El Ridi Zoology Department, Faculty of Science Cairo University Cairo 12613 Egypt
Professor Steven E. Kern Deputy Director, Quantitative Sciences Global Health – Integrated Development Bill & Melinda Gates Foundation P.O. Box 23350 Seattle WA 98102 United States of America
Dr Safari Methusela Kinung’hi National Institute for Medical Research (NIMR) Mwanza centre Mwanza Tanzania
Dr Shaali Ame Laboratory Division Public Health Laboratory Ivo de Carneri P.O. Box 122, Wawi Chake Chake Pemba Tanzania
Dr Victor Mwanakasale Copperbelt University School of Medicine Ndola Zambia
Dr Yaobi Zhang Helen Keller International Regional Office for Africa BP 29.898 Dakar-Yoff Senegal
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WHO SECRETARIAT
Dr John REEDER, Director, Special Programme for Research & Training in Tropical Diseases
Dr Piero OLLIARO, Team leader IIR, Special Programme for Research & Training in Tropical
Diseases
Dr Corinne MERLE, IIR, Special Programme for Research & Training in Tropical Diseases
Dr Dirk ENGELS, Director, Control of Neglected Tropical Diseases, NTD
Dr Amadou GARBA DJIRMAY, Preventive Chemotherapy and Transmission control, NTD
Dr Guo JIAGANG, Preventive Chemotherapy and Transmission control, NTD
Dr Antonio MONTRESOR, Preventive Chemotherapy and Transmission control, NTD
Dr Pamela Sabina MBABAZI, Preventive Chemotherapy and Transmission control
Dr Louis-Albert TCHUEM TCHUENTÉ, Mapping Officer, Neglected Tropical Diseases, WHO IST/WA
