Evidence map›Paper›PMID 32477635›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2020

Toward a More Accurate Accrual to Clinical Trials: Joint Cohort Discovery Using Bloom Filters and Homomorphic Encryption.

Xiao Dong, David A Randolph

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Xiao DongCenter for Clinical and Translational Science, University of Illinois at Chicago, Chicago, Illinois, USA.
David A RandolphCenter for Clinical and Translational Science, University of Illinois at Chicago, Chicago, Illinois, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable cohort discovery is an essential early part of clinical study design. Indeed, it is the defining feature of many clinical research networks, including the recently launched Accrual to Clinical Trials (ACT) network. As currently deployed, however, the ACT network only allows cohort queries in isolated silos, rendering cohort discovery across sites unreliable. Here we demonstrate a novel protocol to provide network participants access to more accurate combined cohort estimates (union cardinality) with other sites. A two-party Elgamal protocol is implemented to ensure privacy and security imperatives, and a special attribute of Bloom filters is exploited for accurate and fast cardinality estimates. To emulate mandatory privacy protecting obfuscation factors (like those applied to the counts reported for individual sites by ACT), we configure the Bloom filter based on the individual site cohort sizes, striking an appropriate balance between accuracy and privacy. Finally, we discuss additional approval and data governance steps required to incorporate our protocol in the current ACT infrastructure.

Identifiers

PMID32477635
PMCPMC7233071

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.