GlaucomaBEGASNCT06353542
Barcelona Esquerra Glaucoma Artificial Intelligence-based Screening Program (BEGAS)
A study testing Software analysis and Ophthalmologist examination in people with Glaucoma, run by Hospital Clinic of Barcelona at 1 site in Spain.
Trial summary
Two primary care-based screening systems will be tested to identify subjects with referrable glaucoma to hospital care. Subjects between 45 to 64 years old living in the metropolitan area of Barcelona will be invited to participate in a one-time visit, with an optic disc examination and intraocular pressure (IOP). Read more about this study
- Who is it for?
- Ages 40 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Glaucoma
- What is being tested?
- Software analysis and Ophthalmologist examination
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 500 participants
- Where
- 1 siteSpain
- Study dates
- 2 May 2024to Sep 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Patients aged 40 to 80 years old from our reference population
- Family history of glaucoma
- Willingness to participate
- Signed written informed consent
Who cannot join
- Not signing the informed consent
- Patients that had a previous diagnosis of glaucoma or any ophthalmic disease that required a regular ophthalmic examination and/or treatment
- Congenital or childhood glaucoma
- History of strabismus or amblyopia
- Known ophthalmic diseases which imply media opacity (cataract, cornea opacities) that might preclude from taking fundus retinographies
Trial locations and contacts
1 site in 1 country.
Spain1 site, 1 recruiting
- Recruiting
Hospital Clínic - ICOF
Barcelona, Barcelona, 08028
Nestor Ventura Abreu, MD, PhD, +34932275400 ext. 9336, neventura@clinic.cat
Marta Pazos, MD, PhD
About this study
Official title: Barcelona Esquerra Glaucoma Artificial Intelligence-based Screening Program (BEGAS): Artificial Intelligence Applied to Optic Nerve Retinographies for a Glaucoma Screening Program in a Primary-care Setting
Two primary care-based screening systems will be tested to identify subjects with referrable glaucoma to hospital care.
Subjects between 45 to 64 years old living in the metropolitan area of Barcelona will be invited to participate in a one-time visit, with an optic disc examination and intraocular pressure (IOP).
Read more
The criteria for referring a patient will be the detection of glaucoma but with two different approaches depending on which Integrated Practice Unit (IPU) the patients will be allocated to: one arm using an Artificial Intelligence (AI) reading software of the optic disc picture; and the other one will base their referral after an ophthalmic examination performed by an ophthalmologist.
In both circuits, an optic nerve head photography will be obtained, and a masked reading center will be established to determine the ground truth for diagnosis.
This screening trial will explore the level of agreement between both systems and the cost-effectiveness of each of them.
Secondary analyses will include potential diagnostic composite scores (including other ancillary tests, such as optical coherence tomography images, that could maximize the screening process); the identification of population and disease characteristics (type of glaucoma, intraocular pressure) that could increase the effectivity and adherence to the screening process.
Read the detailed description
The purpose of this study is twofold: to validate in our population an Artificial Intelligence (AI) reading software of the optic disc picture, after comparing the estimated result (glaucoma/suspect/normal) to the ground truth; and to conduct a clinical trial where the level of agreement between both systems and the cost-effectiveness of each of them will be tested
In the first phase, a set of patients from our reference population will be selected. A standard-of-care ophthalmic examination with the usual ancillary tests to confirm or rule out the presence of glaucoma (including an optic disc retinography), will be performed. The patient (and the test) will be examined by a glaucoma specialist who will determine the status of the patient.
Then, the retinography will be analyzed by the AI software, providing the estimated result (glaucoma/suspect/normal). The level of agreement between the ground truth and the casted result will confirm the diagnostic accuracy.
In the second phase, a second set of patients will be recruited. In this case, the patients will be randomly allocated to either of the two arms of the study: In arm A the ancillary tests (including the retinography) will be performed, and the software will analyze the retinography, therefore providing the glaucoma status result. In arm B, the patients (and the test) will be examined by a glaucoma specialist who will then determine the status of the patient.
All the patients, irrespective of the diagnosis and the arm of the study will be then explored by another glaucoma specialist (reading center), who will be blinded to where the diagnosis comes from (AI software or glaucoma specialist), to the determine the level of agreement between the two screening systems
- Conditions
- Glaucoma
- Being tested
- Software analysis, Ophthalmologist examination
- Keywords
- Artificial Intelligence, Diagnostic Test: Glaucoma Screening
- Medical subject headings
- Glaucoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Software analysisDiagnostic test
The tested AI software analyzes the optic disc retinography to determine if the patient is healthy, a glaucoma suspect, or a glaucoma case
Ophthalmologist examinationDiagnostic test
The ophthalmologist (a glaucoma specialist) will analyze the tests and will examine the patient to determine if the patient is healthy, a glaucoma suspect or a glaucoma case
| Study group | Role | What they receive |
|---|---|---|
| AI software examination (A) | Experimental | In arm A, the visual acuity, refraction status and the ancillary tests will be performed. The obtained optic disc retinography will be analyzed by the AI software to determine whether the patient was a glaucomatous, suspect or healthy patient. Receives: Diagnostic Test: Software analysis |
| Ophthalmic examination (B) | Active comparator | In arm B, the visual acuity, refraction status and the ancillary tests will be performed, and then the patients (and the test) will be examined by a glaucoma specialist who will determine the status of the patient (glaucomatous, suspect or healthy). Receives: Diagnostic Test: Ophthalmologist examination |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic agreement between the AI software and the ophthalmic examination
Level of agreement between the casted result by the AI software and the ophthalmic examination. This will be determined by the reading person (study chair)
Measured: 18 months
Health-Related Quality of Life (HRQoL)
Health-Related Quality of Life (HRQoL) assessed by Euro Quality of Life -5 Dimensions (EQ-5D), for each arm of the clinical trial. It consists of a visual analog scale, ranging from 0 to 100 (0 being the worst imaginable health and 100 the best health the patient can imagine)
Measured: 18 months
Demographics
Quantitative analysis of age, gender, ethnicity, and family history of glaucoma differences between the two arms
Measured: 18 months
Secondary outcomes (5)
Intraocular pressure
Intraocular pressure values of glaucoma, suspects, and healthy patients of each arm of the study (in mmHg)
Measured: 18 months
Optical coherence tomography (OCT)
OCT values of glaucoma, suspects, and healthy patients of each arm of the study (thickness reported in micrometers)
Measured: 18 months
Visual field
Visual field defects (mean deviation, in decibels) of glaucoma, suspects, and healthy patients of each arm of the study
Measured: 18 months
Cost-effective analysis of both screening methods
Cost-effective analysis will be conducted on each arm of the study comparing direct costs, and degree of visual impairment and comparing it to other screening programs (case-finding scenario)
Mean costs and effects to estimate the Incremental Cost-Effectiveness Ratio (ICER, in euros, €) for artificial intelligence software screening versus ophthalmic examination will be compared
Measured: 18 months
Risk score with parameters associated with positive screening of glaucoma
Analysis of the demographics (present or absent), ocular characteristics (present or absent), OCT values (in micrometers), and visual field values (in decibels) that could be associated with an increased likeliness of glaucoma diagnosis
The degree of contribution of each parameter will be analyzed in a multivariate logistic regression, and then a risk score will be created using a scale from 1 to 100 (with being 1 the lowest value and 100 being the highest) to show how each parameter contributes to a "positive glaucoma diagnosis"
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Apr 2024
- Study start2 May 2024
- Primary completionMar 2026 (estimated)
- Study completionSep 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for GlaucomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Care provider, Investigator
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Hospital Clinic of Barcelona
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Marta Pazos, MD, PhD, Study chair, Glaucoma Consultant - Head of Ophthalmic Surgery Department
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06353542
- Sponsor's protocol ID
- HCB/2023/1206
- Other IDs
- PI23/01856
- Acronym
- BEGAS
- Status last verified
- Mar 2024
- First submitted
- 21 Mar 2024
- Last updated
- 9 Oct 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual Participant Data that could identify any patient will not be shared with other researchers. Patients will only be de-identified if a major health risk is detected, or under legal requirement by the competing authorities.
Publications
Hemelings R, Elen B, Barbosa-Breda J, Lemmens S, Meire M, Pourjavan S, Vandewalle E, Van de Veire S, Blaschko MB, De Boever P, Stalmans I. Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning. Acta Ophthalmol. 2020 Feb;98(1):e94-e100. doi: 10.1111/aos.14193. Epub 2019 Jul 25.
PubMed 31344328US Preventive Services Task Force; Davidson KW, Barry MJ, Mangione CM, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Krist AH, Kubik M, Li L, Ogedegbe G, Owens DK, Pbert L, Silverstein M, Stevermer J, Tseng CW, Wong JB. Screening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021 May 18;325(19):1965-1977. doi: 10.1001/jama.2021.6238.
PubMed 34003218Tan NYQ, Friedman DS, Stalmans I, Ahmed IIK, Sng CCA. Glaucoma screening: where are we and where do we need to go? Curr Opin Ophthalmol. 2020 Mar;31(2):91-100. doi: 10.1097/ICU.0000000000000649.
PubMed 31904596
Study at a glance
From the registry record, last updated by the sponsor on 9 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Barcelona Esquerra Glaucoma Artificial Intelligence-based Screening Program (BEGAS): Artificial Intelligence Applied to Optic Nerve Retinographies for a Glaucoma Screening Program in a Primary-care Setting
- ClinicalTrials.gov ID
- NCT06353542
- Acronym / sponsor ID
- BEGAS / HCB/2023/1206
- Conditions
- Glaucoma
- Keywords
- Artificial Intelligence, Diagnostic Test: Glaucoma Screening
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Hospital Clinic of BarcelonaUniversity, hospital or other
- Study start
- 2 May 2024 (actual)
- Primary completion
- Mar 2026 (estimated)
- Study completion
- Sep 2026 (estimated)
- First posted
- 9 Apr 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Two primary care-based screening systems will be tested to identify subjects with referrable glaucoma to hospital care.
Subjects between 45 to 64 years old living in the metropolitan area of Barcelona will be invited to participate in a one-time visit, with an optic disc examination and intraocular pressure (IOP).
The criteria for referring a patient will be the detection of glaucoma but with two different approaches depending on which Integrated Practice Unit (IPU) the patients will be allocated to: one arm using an Artificial Intelligence (AI) reading software of the optic disc picture; and the other one will base their referral after an ophthalmic examination performed by an ophthalmologist.
In both circuits, an optic nerve head photography will be obtained, and a masked reading center will be established to determine the ground truth for diagnosis.
This screening trial will explore the level of agreement between both systems and the cost-effectiveness of each of them.
Secondary analyses will include potential diagnostic composite scores (including other ancillary tests, such as optical coherence tomography images, that could maximize the screening process); the identification of population and disease characteristics (type of glaucoma, intraocular pressure) that could increase the effectivity and adherence to the screening process.
Detailed description
The purpose of this study is twofold: to validate in our population an Artificial Intelligence (AI) reading software of the optic disc picture, after comparing the estimated result (glaucoma/suspect/normal) to the ground truth; and to conduct a clinical trial where the level of agreement between both systems and the cost-effectiveness of each of them will be tested
In the first phase, a set of patients from our reference population will be selected. A standard-of-care ophthalmic examination with the usual ancillary tests to confirm or rule out the presence of glaucoma (including an optic disc retinography), will be performed. The patient (and the test) will be examined by a glaucoma specialist who will determine the status of the patient.
Then, the retinography will be analyzed by the AI software, providing the estimated result (glaucoma/suspect/normal). The level of agreement between the ground truth and the casted result will confirm the diagnostic accuracy.
In the second phase, a second set of patients will be recruited. In this case, the patients will be randomly allocated to either of the two arms of the study: In arm A the ancillary tests (including the retinography) will be performed, and the software will analyze the retinography, therefore providing the glaucoma status result. In arm B, the patients (and the test) will be examined by a glaucoma specialist who will then determine the status of the patient.
All the patients, irrespective of the diagnosis and the arm of the study will be then explored by another glaucoma specialist (reading center), who will be blinded to where the diagnosis comes from (AI software or glaucoma specialist), to the determine the level of agreement between the two screening systems
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (care provider, investigator)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI software examination (A) | Experimental | Diagnostic Test: Software analysisIn arm A, the visual acuity, refraction status and the ancillary tests will be performed. The obtained optic disc retinography will be analyzed by the AI software to determine whether the patient was a glaucomatous, suspect or healthy patient. |
| Ophthalmic examination (B) | Active comparator | Diagnostic Test: Ophthalmologist examinationIn arm B, the visual acuity, refraction status and the ancillary tests will be performed, and then the patients (and the test) will be examined by a glaucoma specialist who will determine the status of the patient (glaucomatous, suspect or healthy). |
Who may qualify
- Ages
- 40 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Patients aged 40 to 80 years old from our reference population
- Family history of glaucoma
- Willingness to participate
- Signed written informed consent
Key exclusion criteria (5 listed)
- Not signing the informed consent
- Patients that had a previous diagnosis of glaucoma or any ophthalmic disease that required a regular ophthalmic examination and/or treatment
- Congenital or childhood glaucoma
- History of strabismus or amblyopia
- Known ophthalmic diseases which imply media opacity (cataract, cornea opacities) that might preclude from taking fundus retinographies
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Software analysisThe tested AI software analyzes the optic disc retinography to determine if the patient is healthy, a glaucoma suspect, or a glaucoma case | Diagnostic test | AI software examination (A) |
| Ophthalmologist examinationThe ophthalmologist (a glaucoma specialist) will analyze the tests and will examine the patient to determine if the patient is healthy, a glaucoma suspect or a glaucoma case | Diagnostic test | Ophthalmic examination (B) |
Primary outcome
Diagnostic agreement between the AI software and the ophthalmic examination
Time frame: 18 months
Level of agreement between the casted result by the AI software and the ophthalmic examination. This will be determined by the reading person (study chair)
Health-Related Quality of Life (HRQoL)
Time frame: 18 months
Health-Related Quality of Life (HRQoL) assessed by Euro Quality of Life -5 Dimensions (EQ-5D), for each arm of the clinical trial. It consists of a visual analog scale, ranging from 0 to 100 (0 being the worst imaginable health and 100 the best health the patient can imagine)
Demographics
Time frame: 18 months
Quantitative analysis of age, gender, ethnicity, and family history of glaucoma differences between the two arms
5 secondary outcomes
Intraocular pressure
Time frame: 18 months
Optical coherence tomography (OCT)
Time frame: 18 months
Visual field
Time frame: 18 months
Cost-effective analysis of both screening methods
Time frame: 18 months
Risk score with parameters associated with positive screening of glaucoma
Time frame: 6 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Oct 2024.
- Background: PubMed 31344328Hemelings R, Elen B, Barbosa-Breda J, Lemmens S, Meire M, Pourjavan S, Vandewalle E, Van de Veire S, Blaschko MB, De Boever P, Stalmans I. Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning. Acta Ophthalmol. 2020 Feb;98(1):e94-e100. doi: 10.1111/aos.14193. Epub 2019 Jul 25.
- Background: PubMed 34003218US Preventive Services Task Force; Davidson KW, Barry MJ, Mangione CM, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Krist AH, Kubik M, Li L, Ogedegbe G, Owens DK, Pbert L, Silverstein M, Stevermer J, Tseng CW, Wong JB. Screening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021 May 18;325(19):1965-1977. doi: 10.1001/jama.2021.6238.
- Background: PubMed 31904596Tan NYQ, Friedman DS, Stalmans I, Ahmed IIK, Sng CCA. Glaucoma screening: where are we and where do we need to go? Curr Opin Ophthalmol. 2020 Mar;31(2):91-100. doi: 10.1097/ICU.0000000000000649.
- Individual participant dataSharing planned: No. Individual Participant Data that could identify any patient will not be shared with other researchers. Patients will only be de-identified if a major health risk is detected, or under legal requirement by the competing authorities.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Marta Pazos, MD, PhD study chair
Glaucoma Consultant - Head of Ophthalmic Surgery Department
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Software analysis and Ophthalmologist examination in people with Glaucoma, run by Hospital Clinic of Barcelona at 1 site in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 9 Oct 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Nestor Ventura Abreu, MD, PhD (+34932275400 ext. 9336, neventura@clinic.cat), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic agreement between the AI software and the ophthalmic examination (time frame: 18 months). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06353542, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 9 Oct 2024.