title: WebDISCO: a web service for distributed cox model learning without patient-level data sharing.
abstract: OBJECTIVE
  The 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
  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.
  
  
  RESULTS
  The 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA Email: challen@ucsd.edu, shw070@ucsd.edu, z1ji@ucsd.edu, x1jiang@ucsd.edu, machado@ucsd.edu.
authors.forename: Chia-Lun
authors.initials: CL
authors.lastname: Lu
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA Email: challen@ucsd.edu, shw070@ucsd.edu, z1ji@ucsd.edu, x1jiang@ucsd.edu, machado@ucsd.edu shw070@ucsd.edu x1jiang@ucsd.edu.
authors.forename: Shuang
authors.initials: S
authors.lastname: Wang
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA Email: challen@ucsd.edu, shw070@ucsd.edu, z1ji@ucsd.edu, x1jiang@ucsd.edu, machado@ucsd.edu.
authors.forename: Zhanglong
authors.initials: Z
authors.lastname: Ji
authors.affiliation: Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, 27708, USA Email: yuan.wu@duke.edu.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Wu
authors.affiliation: Department of Mathematics & Computer Science, Emory University, Atlanta, GA 30322, USA. Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA Email: challen@ucsd.edu, shw070@ucsd.edu, z1ji@ucsd.edu, x1jiang@ucsd.edu, machado@ucsd.edu.
authors.forename: Li
authors.initials: L
authors.lastname: Xiong
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA Email: challen@ucsd.edu, shw070@ucsd.edu, z1ji@ucsd.edu, x1jiang@ucsd.edu, machado@ucsd.edu Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA Email: challen@ucsd.edu, shw070@ucsd.edu, z1ji@ucsd.edu, x1jiang@ucsd.edu, machado@ucsd.edu.
authors.forename: Xiaoqian
authors.initials: X
authors.lastname: Jiang
authors.affiliation: Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA Email: challen@ucsd.edu, shw070@ucsd.edu, z1ji@ucsd.edu, x1jiang@ucsd.edu, machado@ucsd.edu.
authors.forename: Lucila
authors.initials: L
authors.lastname: Ohno-Machado
mesh_terms: D000465:Algorithms; D003195:Computer Communication Networks; D066264:Datasets as Topic; D020000:Decision Support Systems, Clinical; D006801:Humans; D033181:Information Dissemination / Q000379:methods; D020407:Internet; D016016:Proportional Hazards Models; D016019:Survival Analysis
keywords: clinical information systems; cox model; decision support systems; distributed modeling