Evidence map›Paper›PMID 37039671›Full record

Trial reportMicrobiology spectrum2023

MiSurv: an Integrative Web Cloud Platform for User-Friendly Microbiome Data Analysis with Survival Responses.

Won Gu, Hyunwook Koh, Hyojung Jang, Byungho Lee, Byungkon Kang

Abstract readClinical Trial
In one paragraph

Trial report in Microbiology spectrum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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

5 authors.

Won Gu *Department of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.
Hyunwook Koh *Department of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.ORCID 0000-0001-6893-7164
Hyojung JangDepartment of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.
Byungho LeeDepartment of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.
Byungkon KangDepartment of Computer Science, The State University of New York, Korea, Incheon, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Investigators have studied the treatment effects on human health or disease, the treatment effects on human microbiome, and the roles of the microbiome on human health or disease. Especially, in a clinical trial, investigators commonly trace disease status over a lengthy period to survey the sequential disease progression for different treatment groups (e.g., treatment versus placebo, new treatment versus old treatment). Hence, disease responses are often available in the form of survival (i.e., time-to-event) responses stratified by treatment groups. While the recent web cloud platforms have enabled user-friendly microbiome data processing and analytics, there is currently no web cloud platform to analyze microbiome data with survival responses. Therefore, we introduce here an integrative web cloud platform, called MiSurv, for comprehensive microbiome data analysis with survival responses.

Indexed as

Diabetes Mellitus, Type 1Gastrointestinal MicrobiomeMicrobiotaCloud ComputingHumansassociation analysismicrobiome data analysisprediction modelingsurvival analysisweb cloud platform

Identifiers

PMID37039671
PMCPMC10269532

What OpenQuestion holds

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LicenceCC BY
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.