1. Overview of NCI Epidemiology and Genomics Research Program (EGRP) Cohort Data Sharing Practices
Sharon R. Williams
Sally S. Tinkle
Brian L. Zuckerman
Sarah R. Collins
Dorit T. Stein
Tram Lam
29 October 2016

2. Epidemiology and Genomics Research Program (EGRP)
National Cancer Institute’s (NCI) Division of Cancer Control and Population Sciences (DCCPS) EGRP “provides opportunities for scientists to increase understanding of cancer causes and prevention in human populations”
Largest funder of etiologic cancer epidemiology grants nationally and worldwide
NCI DCCPS, “About the Epidemiology and Genomics Research Program”, accessed September 2016

3. Data Sharing in EGRP Cohorts
Long-term Outcomes
Increased efficiency of research
Increased quality of research
Increased collabortiveness
Expansion of population of cancer researchers

4. Evaluation
NCI asked the IDA Science and Technology Policy Institute (STPI) to evaluate the epidemiology data sharing practices developed by principal investigators (PIs) in the NCI EGRP

5. Methods Three stages of the evaluation:
1) Preliminary data collection from 23 EGRP cohort websites
2) Pilot analysis of 2 EGRP funded cohorts
3) Interviews with 9 EGRP cohorts

6. Interview Methods Purpose of the cohort interviews: Interview topics:
Understand EGRP cohorts’ current data sharing policies and practices and
Gather their perspectives and concerns about a centralized data repository and data sharing embargo period
Interview topics:
Data sharing definition
Advertising data sharing
Number of requests and profiles of requestors
Data sharing process
Collaborator requirements
Costs and cost-sharing
Centralized Database concerns
Embargo period comments

7. Cohorts Selected Nine cohorts:
New York University Women’s Health Study (NYUWHS)
Southern Community Cohort Study (SCCS)
St. Jude LIFE Cohort (SJL)
California Teacher’s Study (CTS)
Multi-ethnic Cohort Study of Diet and Cancer (MEC)
Pathways Study (Pathways)
Adventist Health-Study II (AHS2)
Iowa Women’s Health Study (IWHS)
Singapore Chinese Health Study and Shanghai Cohort Study (SCHS/SCS)

8. Key Findings

9. Advertising Data Sharing Opportunities and Initial Contact
Most cohorts do not have a formal mechanism for advertising data sharing opportunities and rely on networks of colleagues, academic presentations, and the NCI Cohort Consortia to share information about their data
Personal communication, specifically , is the common method of first contact by a data requestor

10. Number of Data Sharing Requests and Decision Timeline
Most cohorts have between 1-20 requests per year
1 cohort receives requests per year
Almost all cohorts reported notifying data requestors of a decision less than 4 weeks after submission

11. Approval and Rejection Rates
All cohorts reported approving the majority and rejecting few, if any, data sharing requests
Requests were denied for the following reasons:
Cohort data are not appropriate for the proposed project
Project is already underway or planned within the cohort
Request would deplete biospecimen samples
Project is deemed not scientifically valid or strong

12. Data Sharing Process
Sharing within and outside cohort institutions and networks varied
Most cohorts have a formal review committee for data sharing requests
Most cohorts reported requiring or requesting inclusion of a cohort investigator in the data analysis or manuscript preparation process

13. Cost-Sharing Estimates
3 cohorts reported requiring reimbursement under certain circumstances, including if the request is effort-intensive or if the requesting PI receives grant funding for the project
2 cohorts reported charging a fee
Ranges from 3-15% time for programmers and data managers
Between $2,000-3,000 per dataset
1 cohort reported building in 5-10% time for data managers in grant-funded projects
2 cohorts reported spending pro bono time on data sharing efforts
4 cohorts reported difficulty in recovering costs for programmer, database manager, and statistician time

14. Depositing Data into a Centralized Public Database
4 cohorts reported that their informed consent would allow for data deposition into a centralized repository
3 cohorts reported that they would need IRB approval before depositing data
2 cohorts did not think data deposition would be approved by their IRB or allowed by state law

15. Centralized Data Depot Support and Concerns
5 cohorts expressed support for a centralized data depot
4 cohorts reported not supporting a centralized data depot
Whether expressing support or not, the majority of cohorts had concerns about a central repository including:
Mischaracterization and misinterpretation of data, especially clinical, demographic, and nutritional data
Aggregation and harmonization of disparate sources of data
Risk to participant privacy due to re-identification
Sharing data jeopardizing future grant funding
Concern over the influx of resources necessary to prepare and deposit data into a central repository
Explain bullets

16. Length of an Embargo Period
6 cohorts reported supporting an embargo period between 1-5 years after data collection is complete
3 cohorts had difficulty quantifying the length of an embargo period, but agreed it is important
Cohorts noted that determining when data collection is complete can be difficult with cohorts that are continuously re-contacting and surveying their population
Explain

17. Biospecimen Sharing Procedures and Costs
3 cohorts had different biospecimen sharing procedures, such as a separate review process
Others noted that biospecimen requests may be subject to more critical review since biospecimens, unlike data, are a finite resource

18. Discussion Data sharing norms vs. execution?
Do these data sharing attitudes promote long-term desired outcomes?
Increased efficiency of research
Increased quality of research
Increased collaborativeness/interdisciplinary of research
Expansion of population of cancer investigators
STPI appreciates the opportunity to provide these data and welcomes NCI comment and discussion

19. Additional Slides

20. Interview Questions What is your definition for sharing data?
How do you advertise/share information about data sharing opportunities?
How do people first contact you if they are interested in data sharing?
How do you track data sharing requests?
How many requests do you get for data sharing per year? What is the timeline from time of formal data request submission to decision? How many are approved? How many are rejected? What are the reasons for rejections?
In the past 5 years, whom have you shared your data with?
How many are from inside your network?
How many are from former graduate or post-doc students affiliated with the lab/grant?
How many are from outside your lab/grant but within the university?
How many are from outside your lab/grant and outside your university, but within one of the other NCI consortia?
Do you know how many were Early Stage Investigators or students when they requested data?
How many are outside your network?
What is your process for sharing data?
If you have mentoring [i.e. analyses would be overseen by the PI] or collaborator requirements [i.e., authorship] to share data, do you assist data requesters with finding a mentor or collaborator?
How do you release data? Format? How do you actually provide data to requesters?
What are the costs involved? Administrative, technical, analytic? Is there a different price structure for government vs. academia vs. industry?
Where do you currently deposit data? How would you describe your experience?
Would your current informed consent allow you to deposit de-identified data into a publicly available dataset?
What are your thoughts about a centralized data depot for individual-level epidemiologic data?
How long do you think an embargo period should be? In other words, when can people begin to request access to the data (e.g., the length of the grant, 2 years from cleaning)?
What are your procedures for sharing specimens, if different from the procedures for sharing data? Is there a different procedure for sharing specimens outside of your network of co-Investigators vs. inside your network?

21. Q5 Data: Number of Requests, Decision Timeline, and Approval and Rejection Rates
Cohort
Requests per Year
Decision Timeline
Approval Rate
Rejection Rate
NYUWHS
2–5
2–4 weeks
Most
None in 2015
SCCS
40–50
1 week after committee meeting
>90%
About 10%
SJL
New cohort
1–2 weeks
Most pooling requests approved
1 rejection in memory
CTS
10–12
Majority
Declined 2 requests ever
MEC 20
4 weeks
91% 9%
Pathways 10
Nearly all
<1 request per year
AHS2
2–3
About 3 months
A few
IWHS
8–10 average (5–6 last year)
2–3 days after form submitted
1–2 requests rejected each year
SCHS/SCS
10–15
3–4 weeks
>95%
About 5%

22. Q6 Data: Rates of Sharing
Within Network
Outside Network
Cohort
Former Students
Within University
Within NCI Consortia
ESIs
General
NYUWHS
1 every other year
Half of requests
Yes
Half of requests outside NCI Consortia and NYU network NA
SCCS 3
>50
SJL
Mainly shared internally within St. Jude
Not aware
Shared with K-award investigators
CTS
Most requests from NCI Cohort Consortia
Large proportion of non-NCI Consortia requests
2–4 per year
MEC
10 requests
20% of requests
Large proportion
Good proportion
40% of requests
Pathways 4 5 1
AHS2
Majority of requests
Majority of requests
IWHS
Not recently
10% of requests
90% of requests 2
SCHS/SCS 23 14 18 6

23. Q9 Data: Format and Type of Data Release
Cohort
Data Format
Type of Transfer
NYUWHS
Cleaned, de-identified
NYU secure data transmission system; or upload and send to requestor, depends on what requestor wants
SCCS
Cleaned
Zip file download through SCCS online request system; biospecimens FedExed in batches
SJL
Only cleaned, annotated
Secure FTP
CTS
Open hole in CTS network and give requestor a password to go in and grab data; or password protected, encrypted disk
MEC
Raw (MEC investigators), cleaned (outside investigators)
Secure FTP (if major participant), or university file drop service
Pathways
Secure Kaiser file transfer site; or encrypted , depends on what requestor wants
AHS2
Cleaned, de-identified (do not release raw data)
Access through visiting scholar position; remote access (future)
IWHS
Raw or cleaned, de-identified (only)
SCHS/SCS