B18a. Secondary use of clinical trials data in health research: A Practical Guide
Tracks
Data, Technology and Informatics
| Wednesday, June 4, 2025 |
| 2:45 PM - 3:45 PM |
| C2.5+C2.6 |
Chair & Speakers
Dr Kylie Hunter
Research Fellow
NHMRC Clinical Trials Centre, University of Sydney
B18a. Secondary use of clinical trials data in health research: A Practical Guide
Abstract
Background: Data sharing can add tremendous value to existing clinical trials data. The Health Studies Australian National Data Asset (HeSANDA) program by the ARDC built a national infrastructure platform to allow researchers to access and share data from health studies. Yet, guidance around how these data may be used for secondary research was lacking.
Objective: To address this, ARDC sought to develop a theoretical framework for the use of clinical trials data for secondary research.
Methods: The framework was derived from research papers, consultation with key stakeholders, and a discussion group among the meta-research community at AIMOS 2023 to identify secondary research scenarios.
Results: The resulting framework for secondary data use comprises four different scenarios:
1) Evidence synthesis (including aggregate and individual participant data meta-analysis);
2) Secondary analyses (e.g. descriptive, economic, prognostic, predictive, exploratory analysis);
3) Reproducibility, replication and validation (to verify the accuracy, validity, and trustworthiness of the scientific findings of original studies); and
4) Education and Methods Development (e.g. teaching/learning data analysis methods, demonstrating new statistical methods).
Full details, including step-by-step user guides and illustrative case studies are available in a published report (Hunter et al. 2024 http://doi.org/10.5281/zenodo.12768050).
We anticipate this framework and report will maximise the scientific value of the HeSANDA platform and inform secondary research in general.
Objective: To address this, ARDC sought to develop a theoretical framework for the use of clinical trials data for secondary research.
Methods: The framework was derived from research papers, consultation with key stakeholders, and a discussion group among the meta-research community at AIMOS 2023 to identify secondary research scenarios.
Results: The resulting framework for secondary data use comprises four different scenarios:
1) Evidence synthesis (including aggregate and individual participant data meta-analysis);
2) Secondary analyses (e.g. descriptive, economic, prognostic, predictive, exploratory analysis);
3) Reproducibility, replication and validation (to verify the accuracy, validity, and trustworthiness of the scientific findings of original studies); and
4) Education and Methods Development (e.g. teaching/learning data analysis methods, demonstrating new statistical methods).
Full details, including step-by-step user guides and illustrative case studies are available in a published report (Hunter et al. 2024 http://doi.org/10.5281/zenodo.12768050).
We anticipate this framework and report will maximise the scientific value of the HeSANDA platform and inform secondary research in general.
Biography
Kylie Hunter is a Research Fellow and co-lead of the NextGen Evidence Synthesis Team at the NHMRC Clinical Trials Centre, University of Sydney. Her research centres on advancing evidence synthesis methods to address high-priority health research questions, with a particular focus on individual participant data, prospective meta-analysis, research integrity, and child health.
Dr Kristy Robledo
Senior Research Fellow in Biostatistics
NHMRC Clinical Trials Centre, University of Sydney
B18a. Secondary use of clinical trials data in health research: A Practical Guide
Abstract
Background: Data sharing can add tremendous value to existing clinical trials data. The Health Studies Australian National Data Asset (HeSANDA) program by the ARDC built a national infrastructure platform to allow researchers to access and share data from health studies. Yet, guidance around how these data may be used for secondary research was lacking.
Objective: To address this, ARDC sought to develop a theoretical framework for the use of clinical trials data for secondary research.
Methods: The framework was derived from research papers, consultation with key stakeholders, and a discussion group among the meta-research community at AIMOS 2023 to identify secondary research scenarios.
Results: The resulting framework for secondary data use comprises four different scenarios:
1) Evidence synthesis (including aggregate and individual participant data meta-analysis);
2) Secondary analyses (e.g. descriptive, economic, prognostic, predictive, exploratory analysis);
3) Reproducibility, replication and validation (to verify the accuracy, validity, and trustworthiness of the scientific findings of original studies); and
4) Education and Methods Development (e.g. teaching/learning data analysis methods, demonstrating new statistical methods).
Full details, including step-by-step user guides and illustrative case studies are available in a published report (Hunter et al. 2024 http://doi.org/10.5281/zenodo.12768050).
We anticipate this framework and report will maximise the scientific value of the HeSANDA platform and inform secondary research in general.
Objective: To address this, ARDC sought to develop a theoretical framework for the use of clinical trials data for secondary research.
Methods: The framework was derived from research papers, consultation with key stakeholders, and a discussion group among the meta-research community at AIMOS 2023 to identify secondary research scenarios.
Results: The resulting framework for secondary data use comprises four different scenarios:
1) Evidence synthesis (including aggregate and individual participant data meta-analysis);
2) Secondary analyses (e.g. descriptive, economic, prognostic, predictive, exploratory analysis);
3) Reproducibility, replication and validation (to verify the accuracy, validity, and trustworthiness of the scientific findings of original studies); and
4) Education and Methods Development (e.g. teaching/learning data analysis methods, demonstrating new statistical methods).
Full details, including step-by-step user guides and illustrative case studies are available in a published report (Hunter et al. 2024 http://doi.org/10.5281/zenodo.12768050).
We anticipate this framework and report will maximise the scientific value of the HeSANDA platform and inform secondary research in general.
Biography
