In oncology, determining lines of therapy (LoT) has long been a methodological challenge not only in clinical practice, but also in clinical research, health technology assessment, and regulatory-grade real-world evidence (RWE).
A paper by Saini et al. proposes a systematic framework for deriving LoT in patients with solid tumors, addressing one of the most persistent issues in oncology RWE methodology –
LoT is often inferred from imperfect treatment data.
This becomes especially challenging in register-based and administrative datasets, where researchers frequently face:
- Incomplete treatment capture
- Limited regimen granularity
- Unclear treatment intent
- Lack of disease progression data
- Inconsistent recording of regimen modification
As oncology RWE increasingly informs regulatory and payer decisions, the methodological rigor behind LoT derivation deserves far more attention.
One of the most important takeaways from this paper is that transparency may matter more than “perfect” definitions. Explicit algorithms, prespecified rules, and sensitivity analyses are critical for reproducibility and interpretability.
The paper also reinforces an important point for modern RWE strategy – Many real-world datasets were not originally designed for regulatory-grade oncology research.
This is where hybrid data approaches become increasingly valuable. Combining registers with medical chart data, clinician input, or other complementary data sources can improve treatment context and reduce false precision in LoT assignment.
Writer: Kelvin Kwok
A highly relevant read for anyone who is working in:
#OncologyRWE
#Pharmacoepidemiology
#CancerResearch
#CancerCare
#RealWorldEvidence
#RealWorldData
