Real-world data on diffuse large B-cell lymphoma in 2010-2019: usability of large data sets of Finnish hospital data lakes.
Samuli T TuominenKristiina Uusi-RauvaTea BlomSirkku JyrkkiöKaisa TuppurainenErika AlannePublished in: Future oncology (London, England) (2022)
Background: Real-world data on diffuse large B-cell lymphoma (DLBCL) has remained incomplete. In Finland, health record data originally recorded in different hospital data record systems are collectively available via data lake technology, enabling efficient extraction and analysis of large data sets. The usability of Finnish data lake data in the assessment of DLBCL was evaluated. Methods: Adult DLBCL patients diagnosed between 2010 and 2019, home municipality in the Hospital District of Southwest Finland and data available in respective data lake were included. Results: The algorithmic determination of treatment lines and respective survival was successful. Patient characterization was feasible, albeit partly incomplete because of limited data content/availability and coverage. Stage, International Prognostic Index and cell of origin were available for 63.0, 68.3 and 28.4% of patients, respectively. Genetic aberrations were not structurally available or feasible to extract without a manual chart review. Conclusion: Finnish data lakes represent an efficient way to analyze large DLBCL data sets. The current study provides a tool for developing recording practices in routine care.
Keyphrases
- electronic health record
- diffuse large b cell lymphoma
- healthcare
- big data
- end stage renal disease
- public health
- emergency department
- chronic kidney disease
- newly diagnosed
- epstein barr virus
- gene expression
- ejection fraction
- bone marrow
- palliative care
- chronic pain
- social media
- case report
- pain management
- high resolution
- clinical practice
- genome wide
- molecularly imprinted
- cell therapy
- simultaneous determination
- solid phase extraction
- anti inflammatory
- health insurance
- combination therapy