Clinical trial NCT04331015: Artificial Intelligence in Diagnosis of DFNA9
Official title: Positive Predictive Value of Machine Learning Tools (Audiogene v4.0) for Diagnosing DFNA9 in a Large Series of p.Pro51Ser Variant Carriers in COCH.
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: DFNA9
Sensorineural Hearing Loss
Keywords: COCH
DFNA9
sensorineural hearing loss
Lead sponsor: Jessa Hospital
Sponsor class: OTHER
First posted: 2020-04-02
Enrollment: 111
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
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

Brief summary: 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).

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.

Eligibility criteria: 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

Primary outcomes:
measure: hearing threshold
timeFrame: 1 hour
measure: age
timeFrame: 1 hour
measure: prediction gene locus
timeFrame: 1 hour
Secondary outcomes:
Other outcomes:
Locations:
city: Hasselt
country: Belgium
facility: Jessa Hospital
state: Limburg
city: Antwerpen
country: Belgium
facility: University of Antwerp
Study officials:
affiliation: University Hospital, Antwerp
name: Vincent Van Rompaey, MD,PhD
role: STUDY_DIRECTOR
References:
citation: Taylor KR, Deluca AP, Shearer AE, Hildebrand MS, Black-Ziegelbein EA, Anand VN, Sloan CM, Eppsteiner RW, Scheetz TE, Huygen PL, Smith RJ, Braun TA, Casavant TL. AudioGene: predicting hearing loss genotypes from phenotypes to guide genetic screening. Hum Mutat. 2013 Apr;34(4):539-45. doi: 10.1002/humu.22268. Epub 2013 Feb 19.