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Vivli Researcher Spotlight: Dr. Yizhe Xu on analyzing clinical trial data to inform development of machine learning tools

October 2, 2023

Yizhe Xu is a Postdoctoral Researcher at Stanford Center for Biomedical Informatics Research, Stanford University. Dr. Xu’s team submitted a research proposal to access Vivli to conduct analysis relevant to their topic, “Applying machine learning tools to personalize dabigatran treatment decisions”. The team’s completed research has been presented to the research community at conferences and in publications including the Journal of Biomedical Informatics. She sat down with Vivli to tell us more about accessing individual participant data to advance her research, and the potential for machine learning tools to support more accurate estimation and evaluation of heterogeneous treatment effects.

Tell us more about your research. What is the current state of management in your public disclosure topic?
Our final paper has been published in the Journal of Biomedical Informatics as of July 2023.

What led you to want to research this topic?
First of all, treatment effect heterogeneity is an important question that informs clinical decision making given the fact that treatment effects often vary across patients. Thus, accurate estimation of individual treatment effects helps to tailor treatment to patient characteristics and maximizes their benefits. However, it has been realized by a wide group of researchers that estimating treatment heterogeneity is challenging, so we summarized the best practices and advanced methodologies and showed a case study on how to carefully estimate heterogeneous treatment effects using the RE-LY and RELY-ABLE trials.

What difference do you hope your research might make, either in the field or for patients? How has it moved forward the treatment of patients?
We hope our case study provides clear instructions and serves as a concrete example for clinical researchers, and that by following our suggestions, they will be able to avoid possible false discoveries of treatment heterogeneity and prevent misleading findings. The improvement of research quality will directly benefit everyday clinical care in the sense that patients will truly benefit from personalized treatment selection if there is treatment heterogeneity and can be estimated reasonably well. On the other hand, we can save the clinicians’ time and efforts on considering personalized treatment when the treatment effect is essentially uniform across patients.

How could your findings be used in future clinical trials in your disease area?
The statistical methods we have summarized and the guidance we provide on how to select a method and evaluate the model performance can be applied to clinical trials in any disease area. However, for observational studies, practitioners need to consider adjusting for confounding, for instance, using methods such as propensity score matching or weighting.

How did the data you accessed through Vivli help you in answering your research question?
Very well. The RE-LY trial enables a case study for us to demonstrate the principled approach we proposed for estimating heterogeneous treatment effect in a real study. The RE-LY study has a large data size, and the fact that it is an RCT helps to simplify the task of treatment effect estimation.

What was your experience like in the process of requesting data using the Vivli platform?
It was an okay experience – we had some difficulties in resolving issues related to the DUA, which made us wait for quite a while, but we were able to get the access eventually.

Would you use the Vivli platform again? Would you recommend Vivli to others? What improvements would you recommend?
Yes, especially if I think some of the unique data sources on the Vivli platform will help to answer particular research questions of my interest. I will also recommend Vivli to others for the same reason. I would recommend simplifying the data requesting process to shorten the waiting time, as well as expanding user autonomy – particularly that users do not need to make a request every time they want to export results.

What advice would you give to other researchers about doing this kind of analysis?
We encourage researchers to understand their data first, then select the most suitable statistical approaches based on that knowledge. After that, we suggest interpreting findings based on the results from multiple estimators that are weighted by their performance, which is evaluated using several different metrics. Please also see our paper for our detailed recommendations.

Interested in finding out more about how access to Vivli’s data repository can help advance your research? Find out more about how to search and request data.

There’s more on Vivli than just clinical trial data

September 25, 2023

Did you know there’s more on Vivli than just clinical trial data? The majority of our repository of data comes from clinical trial data, but also includes significant numbers of platform trials, observational studies, and real-world evidence resources.

Vivli’s repository of data from nearly 7,000 research studies is available to search freely. Enter any relevant keyword and you’ll get a listing of pertinent studies of different kinds. Here are some recent search results using common keywords for studies that are not clinical trials:

Observational: 198

Natural history: 26

Platform trial: 420

Explore our How To Guides to learn more about accessing and searching for data with Vivli. If you’d like to take your research further, you can get in touch with us for more information about specific studies or requesting access to data.

Vivli launches Portals to support more effective data sharing and data reuse

September 19, 2023

Vivli is delighted to announce the launch of our new Portals feature, designed to highlight therapeutic areas of interest to the research community. One of our first portals focuses on available data relevant to HIV/AIDS, a priority area of research focus for NIH.

We’ve designed Portals to make data from HIV/AIDS clinical trials more visible and discoverable. Vivli’s repository of data is built on nearly 7,000 research studies across a wide range of research areas, and includes a growing number being shared by individual researchers. This data repository provides a valuable resource for researchers to both share and access data that can be used to accelerate the progress of scientific research.

Are you an HIV/AIDS researcher? We’d love to hear from you, whether you’ve got data to share or are interested in exploring our data resources to request. Explore our new HIV/AIDS Portal and find out more about how Vivli can support your research.

This is funded in whole or in part with Federal funds from the Office of AIDS Research, National Institutes of Health, 1OT2DB000003-01, awarded to Vivli.

Vivli CEO Rebecca Li to speak at the NIDDK Central Repository 20th Anniversary Workshop

September 18, 2023

Vivli’s CEO, Rebecca Li, will speak at the NIDDK Central Repository 20th Anniversary Workshop: Promoting Secondary Research to Accelerate Medical Breakthroughs and Innovation. This online event, hosted by the National Institute of Diabetes and Digestive and Kidney Diseases, will take place on September 19-20, 2023.

Li will participate as a panelist in a discussion session on ‘Supporting NIDDK-Funded Research and Expanding NIDDK’s Data Ecosystem’. This session will focus on real-world examples in which NIDDK-funded research is strengthening the data ecosystem and accelerating medical breakthroughs through secondary research, and is scheduled to run on Wednesday, September 20. NIDDK has been making data available to researchers in the Vivli repository since 2022.

The 20th Anniversary Workshop will review the NIDDK Central Repository program from its early beginnings to its current state, and engage a diverse range of experts from the research community to share experiences and explore future possibilities. Registration is open until Tuesday, September 19 – find out more and register on the event website.

Vivli to host workshop at 2023 Cochrane Colloquium

August 31, 2023

Vivli will host a workshop at the 2023 Cochrane Colloquium in London on September 4. The Cochrane Colloquium is an annual event for Cochrane in support of its mission to promote evidence-informed health decision-making.

Vivli’s workshop will focus on “Practical advice for accessing patient-level data from a data sharing platform for evidence synthesis.” This session will provide:

an introduction to the Vivli platform, including an overview of data available and hands-on group work on how to submit a request for data
an overview of first-hand experience of using patient level data using Vivli’s data sharing platform as a case study
a discussion session focusing on some of the opportunities and challenges associated with using patient level data (for example: what to do when data needed to answer the hypothesis is not available via a single data sharing platform?)

This session will be a mixture of hands-on practice and opportunities to hear from researchers who have used the platform, patient advocates, and data providers. There will also be time for participants to ask questions about the data access process.

Vivli Senior Director Julie Wood will be joined by Alan Chant, the patient representative on the Independent Review Panel; Catrin Tudur Smith from the University of Liverpool; and Rebecca Sudlow from Roche to facilitate this workshop.

For more information on the 2023 Cochrane Colloquium and to register for this session, please see the event schedule. Please note that participation in this session is open only to registered Colloquium attendees.

Vivli Senior Advisor speaks at CDISC 2023 Japan Interchange Program

July 10, 2023

Vivli Data Request Process

Vivli Senior Advisor Azusa Tsukida spoke at Clinical Data Interchange Standards Consortium (CDISC) 2023 Japan Interchange Program on July 10.

Tsukida presented during the session on ‘Real World Data & Regulatory Presentations/Perspectives’. Her talk focused on the benefits of data sharing, using case studies from data contributors who are sharing high-quality data via the Vivli platform to enable access to researchers worldwide and contribute to scientific discovery.

CDISC works to develop and advance data standards to support transforming incompatible formats, inconsistent methodologies, and diverse perspectives into a coherent framework for generating clinical research data that is accessible, interoperable, and reusable. More than 80% of the data available in Vivli is formatted in the CDISC-SDTM standard.

Find out more about how you can request data from Vivli’s repository and help accelerate the progress of health research.

Vivli Researcher Spotlight: Dr. Fasihul Khan on the potential for biomarkers to predict outcomes for people with pulmonary fibrosis

May 23, 2023

Fasihul Khan, M.D., Ph.D., is a consultant at Glenfield Hospital, University Hospitals of Leicester NHS UK. Dr. Khan’s team submitted a research proposal to access Vivli to conduct analysis relevant to their topic, “A systematic review and individual patient data meta-analysis of physiological biomarkers in idiopathic pulmonary fibrosis”. The team’s completed research has been presented to the research community at conferences and in publications including American Journal of Respiratory and Critical Care Medicine. He sat down with Vivli to tell us more about accessing individual participant data to advance his research, and the potential for biomarkers to predict outcomes for people with pulmonary fibrosis.

Please tell us more about your research – what led you to want to research this particular topic?

So my area of interest is pulmonary fibrosis, which is a condition causing scarring of the lungs. Pulmonary fibrosis is a relatively rare condition, and therefore the number of studies in this area are limited, although expanding rapidly. I was keen to synthesize some of the existing information that was already available. I wanted to perform a systematic review, specifically looking to see whether there are blood biomarkers that can predict outcomes in patients with diagnosed pulmonary fibrosis. When I started searching the literature, it very quickly became apparent that there were several published studies, but actually the data and the way the studies were reported were very heterogeneous. Individually the studies yielded inconsistent results, utilized data-dependent thresholds, and frequently did not adjust for confounders. Therefore, I sought individual participant data which helped overcome these limitations and enabled robust data analyses to be performed leading to reliable conclusions.

Could you talk about what it was like to work across multiple data-sharing platforms; how did you handle that?

This was not straightforward! I created summary estimates from each study separately on the different platforms in Vivli and in CSDR, then imported them manually onto my own database. I then used additional software to pool the summary estimates. Having the data all in one place would have saved me a lot of time and stress!

Not a lot of researchers have the perseverance to do what you did. What advice would you give to researchers before they start off? Things you wish you’d known before you started?

I think it’s important to consider the project as a whole. It is highly likely the process will take much longer than you think, and that’s not necessarily any individual or organization’s fault. You need to have a clear understanding with contingency plans for each stage, and give yourself plenty of time! Be clear about your research question, and whether individual participant data are likely to improve your research, before committing to the additional effort. Speak to others who have been through the process of acquiring individual participant data, and your institution to understand timescales for data sharing agreements as these are likely to be time consuming and potential limiting factors.

Once you were able to access the individual patient data, were you able to get past the reporting limitations and find what you needed?

Absolutely; once we had the raw data, we were able to perform our analysis and produce some very meaningful results, which we have subsequently published in two journals. The first was a blood biomarker paper in the European Respiratory Journal which was the first blood biomarker study in pulmonary fibrosis to utilize this approach, and provides robust estimates of the association between matrix-metalloproteinase 7 and disease progression.

The second paper was published in the American Journal of Respiratory Critical Care Medicine. In this paper, we looked at change in FVC which is a lung function measurement used to assess progression in pulmonary fibrosis. All interventional clinical trials measure FVC as an endpoint – typically at 12 months, but patients have additional FVC measurements at baseline, 3, and 6 months. The purpose of our research was to evaluate whether short term changes in FVC i.e. over three-months, are associated with overall mortality. In other words, can we shorten clinical trials by finding an earlier signal than the 12 months FVC change that is currently accepted by regulators. Since the association between short term FVC change and mortality was not reported in any clinical study, we needed the individual participant data to model this association. Indeed, we were able to find that three-month FVC change is associated with mortality, and perhaps more importantly a treatment effect could be observed between treatment and placebo arms at three-months. The findings of this study have been well received by the research community, and have already been adopted into the design of an adaptive trial in IPF. Lots of hard work, but worth it as the results are likely to generate further research which ultimately will hopefully impact patients in a positive manner!

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