Why do we need blended survival analysis?
Blended survival analysis represents a significant advancement in health technology assessment (HTA) by combining clinical trial data with real-world evidence (RWE) to improve the accuracy of long-term survival estimates. Traditional survival analysis often falls short, as it relies heavily on extrapolating clinical trial data, which typically covers only 40% of the model time horizon, potentially leading to unrealistic survival projections. Blended survival analysis addresses this limitation by incorporating RWE, which provides a more comprehensive view of patient outcomes beyond the controlled environment of clinical trials.
Benefits and Challenges of Blended Survival Analysis
Benefits:
- Enhanced Accuracy: By integrating RWE, blended survival analysis produces more realistic survival estimates that align better with clinical expectations. This is crucial for making informed decisions in HTA, especially when clinical trial follow-up is limited.
- Longer Follow-Up: RWE offers extended follow-up periods compared to clinical trials, capturing patient outcomes over a longer duration and providing insights into the long-term effectiveness of treatments.
- Real-World Applicability: Data from real-world settings reflect patient experiences outside the controlled conditions of clinical trials, offering a more accurate representation of how treatments perform in everyday clinical practice.
- Reduced Uncertainty: Incorporating RWE reduces the uncertainty inherent in relying solely on clinical trial data, leading to more robust cost-effectiveness analyses and better-informed healthcare decisions.
Challenges:
- Data Quality and Availability: The reliability of blended survival analysis heavily depends on the quality and comparability of the RWE. Discrepancies between clinical trial populations and real-world cohorts can skew results, necessitating careful selection and validation of RWE sources.
- Methodological Variability: The lack of standardized guidelines for incorporating RWE into survival analysis poses a challenge. Currently, methodologies are evolving, and HTA bodies like NICE have yet to establish specific protocols, leading to variability in application and acceptance.
- Reliance on Clinical Opinion: In the absence of comprehensive patient-level data, clinical expert opinions are often used to construct RWE curves. This approach, while valuable, introduces subjectivity and potential bias into the analysis.
- Complexity in Justification: HTA submissions utilizing blended survival analysis require detailed methodological justifications. This includes explaining the choice of data sources, blending techniques, and the assumptions made, which can be labor-intensive and complex.
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