Use Cases Requiring Privacy-Preserving Record Linkage in Paediatric Oncology.
Dieter HaynKarl KreinerEmanuel SandnerMartin BaumgartnerBernhard JammerbundMarkus FalgenhauerVanessa DüsterPriyanka Devi-MarulkarGudrun SchleiermacherRuth LadensteinSchreier GünterPublished in: Cancers (2024)
Large datasets in paediatric oncology are inherently rare. Therefore, it is paramount to fully exploit all available data, which are distributed over several resources, including biomaterials, images, clinical trials, and registries. With privacy-preserving record linkage (PPRL), personalised or pseudonymised datasets can be merged, without disclosing the patients' identities. Although PPRL is implemented in various settings, use case descriptions are currently fragmented and incomplete. The present paper provides a comprehensive overview of current and future use cases for PPRL in paediatric oncology. We analysed the literature, projects, and trial protocols, identified use cases along a hypothetical patient journey, and discussed use cases with paediatric oncology experts. To structure PPRL use cases, we defined six key dimensions: distributed personalised records, pseudonymisation, distributed pseudonymised records, record linkage, linked data, and data analysis. Selected use cases were described (a) per dimension and (b) on a multi-dimensional level. While focusing on paediatric oncology, most aspects are also applicable to other (particularly rare) diseases. We conclude that PPRL is a key concept in paediatric oncology. Therefore, PPRL strategies should already be considered when starting research projects, to avoid distributed data silos, to maximise the knowledge derived from collected data, and, ultimately, to improve outcomes for children with cancer.
Keyphrases
- palliative care
- intensive care unit
- data analysis
- big data
- emergency department
- clinical trial
- electronic health record
- genome wide
- machine learning
- ejection fraction
- newly diagnosed
- young adults
- squamous cell carcinoma
- dna methylation
- gene expression
- artificial intelligence
- chronic kidney disease
- adipose tissue
- neural network
- prognostic factors
- hiv infected
- hiv testing
- weight loss
- single cell
- papillary thyroid
- high density
- glycemic control
- squamous cell
- current status
- tissue engineering