ArticleJournal of the American Medical Informatics Association : JAMIA2015
WebDISCO: a web service for distributed cox model learning without patient-level data sharing.
Article in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 5 of them syntheses that pooled it.
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Who cites it
74 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Learning competing risks across multiple hospitals: one-shot distributed algorithms.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- Estimating individualized treatment effects using an individual participant data meta-analysis.BMC medical research methodology · 2024Pooled it
- Distributed Cox proportional hazards regression using summary-level information.Biostatistics (Oxford, England) · 2023Pooled it
- Distributed Quasi-Poisson regression algorithm for modeling multi-site count outcomes in distributed data networks.Journal of biomedical informatics · 2022Pooled it
- ODACH: a one-shot distributed algorithm for Cox model with heterogeneous multi-center data.Scientific reports · 2022Pooled it
- PDA (Privacy-Preserving Distributed Algorithms) in action: ten principles for high-quality multi-site clinical evidence generation.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- An international multi-centre study to develop and validate federated learning-based prognostic models for anal cancer.Nature communications · 2026Article
- Estimating covariate-balanced survival curve in distributed data environment using data collaboration quasi-experiment.Scientific reports · 2026Article
- Federated analytics for non-communicable disease surveillance in the European health data space: a scoping review and conceptual framework.Frontiers in public health · 2026Article
- Collaborative Inference for Accelerated Failure Time Model Using Clinical Center-Level Summary Statistics.Statistics in medicine · 2025Article
- FedECA: federated external control arms for causal inference with time-to-event data in distributed settings.Nature communications · 2025Article
- COLA-GLM: collaborative one-shot and lossless algorithms of generalized linear models for decentralized observational healthcare data.NPJ digital medicine · 2025Article
- Development of time to event prediction models using federated learning.BMC medical research methodology · 2025Article
- Communication-efficient federated learning of temporal effects on opioid use disorder with data from distributed research networks.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Horizontal federated learning and assessment of Cox models.Frontiers in digital health · 2025Article
- Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics.JMIR medical informatics · 2024Article
- Centralized and Federated Models for the Analysis of Clinical Data.Annual review of biomedical data science · 2024Review
- A distributed feature selection pipeline for survival analysis using radiomics in non-small cell lung cancer patients.Scientific reports · 2024Article
- Article
- Learning from vertically distributed data across multiple sites: An efficient privacy-preserving algorithm for Cox proportional hazards model with variable selection.Journal of biomedical informatics · 2024Article
14 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveThe Cox proportional hazards model is a widely used method for analyzing survival data. To achieve sufficient statistical power in a survival analysis, it usually requires a large amount of data. Data sharing across institutions could be a potential workaround for providing this added power. METHODS AND MATERIALS: The authors develop a web service for distributed Cox model learning (WebDISCO), which focuses on the proof-of-concept and algorithm development for federated survival analysis. The sensitive patient-level data can be processed locally and only the less-sensitive intermediate statistics are exchanged to build a global Cox model. Mathematical derivation shows that the proposed distributed algorithm is identical to the centralized Cox model.
resultsThe authors evaluated the proposed framework at the University of California, San Diego (UCSD), Emory, and Duke. The experimental results show that both distributed and centralized models result in near-identical model coefficients with differences in the range [Formula: see text] to [Formula: see text]. The results confirm the mathematical derivation and show that the implementation of the distributed model can achieve the same results as the centralized implementation. LIMITATION: The proposed method serves as a proof of concept, in which a publicly available dataset was used to evaluate the performance. The authors do not intend to suggest that this method can resolve policy and engineering issues related to the federated use of institutional data, but they should serve as evidence of the technical feasibility of the proposed approach.Conclusions WebDISCO (Web-based Distributed Cox Regression Model; https://webdisco.ucsd-dbmi.org:8443/cox/) provides a proof-of-concept web service that implements a distributed algorithm to conduct distributed survival analysis without sharing patient level data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.