Artificial Intelligence in Diagnosis of DFNA9 (DFNA9)

April 2, 2020 updated by: Jessa Hospital

Positive Predictive Value of Machine Learning Tools (Audiogene v4.0) for Diagnosing DFNA9 in a Large Series of p.Pro51Ser Variant Carriers in COCH.

To study the positive predictive value of Audiogene v.4.0 open source online machine learning tool in accurately predicting DFNA9 (DeaFNess autosomal dominant ninth) as top 3 gene loci in a large series of genetically confirmed c.151C>T,p.Pro51Ser (p.P51S) variant carriers in COCH (coagulation factor C Homology).

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

DFNA9 is an autosomal dominant hereditary adult-onset and progressive sensorineural hearing loss which is associated wit vestibular deterioration.

Today, artificial intelligence plays an increasing role in diagnosis of Mendelian hearing losses and in fitting of cochlear implants. An application of this kind is the open source program, Audiogene v4.0, which was elaborated by the Center for Bioinformatics and Computational Biology, University of Iowa City, Iowa, USA. The shape of the audiogram (audioprofile) is easily recognizable in many autosomal dominantly inherited hearing losses. Machine learning based software tools, such as Audiogene v4.0, which was originally developed for prioritizing loci for the Sanger sequencing, could help the clinicians in early diagnosis of DFNA9. This tool only need subjects' age and hearing thresholds (decibel hearing loss (dB HL)) at frequency range of 0.125 - 8 kHz (kiloHerz), left, right or binaural average in order to predict top 3 gene loci according to the data entered in the program.

Goal: to use auditory data of a large series of genetically confirmed p.P51S variant carriers causing DFNA9, which were previously collected for the genotype-phenotype correlation study which terminated recently.

All individual left and right sided hearing thresholds (ranging from 0.125 to 8kHz, with the exception of 1.5 kHz) as well as binaural averaged thresholds were run through Audiogene v4.0.

Descriptive statistics were assessed and statistical analysis was carried out to check for possible differences between age or hearing thresholds between the carrier group with accurate prediction against the carrier group with inaccurate prediction.

Study Type

Observational

Enrollment (Actual)

111

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Belgium
      • Antwerpen, Belgium, 2650
        • University of Antwerp
    • Limburg
      • Hasselt, Limburg, Belgium, 3500
        • Jessa Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

14 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

A large cohort of 111 genetically confirmed p.P51S variant carriers, of whom audiometric data was collected from

Description

Inclusion Criteria:

  • at least 18 years
  • genetically confirmed c.151 C>T, p.Pro51Ser variant carrier in COCH gene
  • not contra-indication for audiometric testing

Exclusion Criteria:

  • <18 years
  • no carrier status for c.151C>T, p.Pro51Ser
  • no auditory data available

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
hearing threshold
Time Frame: 1 hour
audiometry (pure tone) decibel hearing level (dB HL) left, right ear , binaural average
1 hour
age
Time Frame: 1 hour
years, age at time of audiometry
1 hour
prediction gene locus
Time Frame: 1 hour
top 3 gene loci as predicted by Audiogene v4.0 machine learning tool
1 hour

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Jessa Hospital

Investigators

  • Study Director: Vincent Van Rompaey, MD,PhD, University Hospital, Antwerp

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 1, 2020

Primary Completion (Actual)

March 28, 2020

Study Completion (Actual)

March 28, 2020

Study Registration Dates

First Submitted

March 31, 2020

First Submitted That Met QC Criteria

March 31, 2020

First Posted (Actual)

April 2, 2020

Study Record Updates

Last Update Posted (Actual)

April 3, 2020

Last Update Submitted That Met QC Criteria

April 2, 2020

Last Verified

April 1, 2020

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • JessaH-5-ORL

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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