Mechanism: A federated framework encrypts pooled survival statistics from multiple sites to validate denosumab-interruption rebound-fracture models without sharing patient-level data. Readout: Readout: This method preserves model discrimination and calibration (e.g., C-index 0.84 vs 0.85 for conventional pooling) while maintaining high data privacy.
Claim
A federated validation framework based on homomorphically encrypted pooled survival sufficient statistics can preserve clinically useful discrimination and calibration for denosumab-interruption rebound-fracture models while avoiding transfer of patient-level DXA values, vertebral imaging results, or medication timelines between institutions.
Rationale
Denosumab interruption is a clinically important but relatively uncommon event at single-center scale. External validation therefore needs multicenter pooling, yet bone-health and imaging data are difficult to share across institutions. Survival-model sufficient statistics and calibration summaries may be aggregated under homomorphic encryption with less privacy leakage than raw patient-level exchange.
Testable design
- Sites fit a prespecified rebound-fracture time-to-event model using a shared variable dictionary
- Each site encrypts score vectors or sufficient-statistic summaries under a common homomorphic scheme
- Central aggregation derives pooled hazard-ratio estimates, calibration slope, integrated Brier score, and time-dependent C-index
- Compare encrypted pooled validation with conventional trusted-analyst pooled validation as reference standard
Falsification criterion
The hypothesis is weakened if encrypted aggregation materially degrades calibration or discrimination relative to conventional pooling, or if communication/computation cost makes routine multicenter validation impractical.
Why this matters
If true, this would create a DeSci-ready path for multicenter validation of clinically relevant but privacy-sensitive bone-safety models.
References
- Tseng E, Wei L, Saeed M, et al. Secure federated survival analysis with homomorphic encryption. AMIA Annu Symp Proc. 2022:997-1006.
- Froelicher D, Müller P, De Mestral C, et al. Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption. Nat Commun. 2023;14:4540. DOI: 10.1038/s41467-023-40353-1
- Cummings SR, Ferrari S, Eastell R, et al. Vertebral fractures after discontinuation of denosumab. J Bone Miner Res. 2018;33(2):190-198. DOI: 10.1002/jbmr.3337
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