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Improving Clinical Registry Data Quality via Linkage With Survival Data From State-Based Population Registries
Samuel Smith1,2, Kate Drummond3,4, Anthony Dowling2,3
1Systems Biology and Personalised Medicine Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.
JCO Clinical Cancer Informatics
|June 26, 2024
Summary
Linking brain cancer registry data with death records significantly improved survival outcome accuracy. This data linkage (DL) is crucial for reliable real-world data (RWD) research and understanding patient survival.
Area of Science:
- Oncology
- Biostatistics
- Data Science
Background:
- Real-world data (RWD) from cancer clinical registries are vital for research.
- Accurate capture of death data is challenging, potentially compromising survival outcome integrity.
- Inaccurate survival data can lead to misinterpretation of RWD in clinical research.
Purpose of the Study:
- To explore the utility of data linkage (DL) to state-based registries.
- To enhance the capture of survival outcomes in brain cancer patients.
- To assess the impact of DL on the accuracy of overall survival (OS) calculations.
Main Methods:
- Identified adult brain tumor patients from the Brain Tumour Registry Australia: Innovation and Translation (BRAIN) database.
- Matched patients lacking recorded death dates with the Victorian Births, Deaths and Marriages (BDM) registry using full name and date of birth.
- Compared overall survival (OS) outcomes pre- and post-data linkage (DL).
Main Results:
- 74% of 7,346 patients had no recorded death date or recent follow-up.
- 29% of these patients were successfully matched with a death date via DL.
- Overall survival was significantly overestimated pre-DL (median 29.9 months) compared to post-DL (median 16.7 months).
Conclusions:
- A high proportion of brain cancer patients in clinical registries have missing death data.
- Missing death data, due to informative censoring, inflates overall survival calculations.
- Ongoing DL to pertinent registries is recommended for accurate survival data and RWD interpretation.
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