Osteoporosis RiskOPTIMALNCT05678569
OsteoPorosis Treatment Identification Using Machine Learning
An observational study of Osteoporosis Risk and Osteoporosis, run by NHS Greater Glasgow and Clyde at 1 site in United Kingdom.
Trial summary
OPTIMAL is a pilot feasibility study for a machine learning (ML) based enhanced screening software for osteoporosis. This tool has been created using machine learning, based on data from NHS Greater Glasgow and Clyde. Read more about this study
- Who is it for?
- Ages 50 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Osteoporosis Risk, Osteoporosis
- What is being tested?
- Dual Energy Xray Absorptiometry
- How many people
- 250 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- Feb 2023to Jun 2023
- Phase
- Observational
- 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 50 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients between the ages of 50 and 80 identified as high risk by the initial model, without a diagnosis of osteoporosis, hyperparathyroidism, or other metabolic bone disease
Who may be able to join
- Age >=50y
- Age <=80y
- Identified as high risk by initial model
Who cannot join
- Age <50y
- Age >80y
- BMI <=18 \& >=30
- Recorded diagnosis of osteoporosis
- Prior prescription of bone protective agents such as:
- bisphosphonate (alendronic acid, risedronate, ibandronate, zoledronic acid) / denosumab / raloxifene / strontium ranelate / teriparatide / romosozumab
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- History of prior DXA imaging (prior quantification of BMD)
- History of metabolic bone disease
- History of primary hyperparathyroidism
Trial locations and contacts
1 site in 1 country.
United Kingdom1 site
West of Scotland Innovation Hub
Glasgow, G51 4TF
Ruairidh Davison, 01415416869, Ruairidh.Davison@ggc.scot.nhs.uk
About this study
Official title: OPTIMAL - OsteoPorosis Treatment Identification Using Machine Learning
OPTIMAL is a pilot feasibility study for a machine learning (ML) based enhanced screening software for osteoporosis.
This tool has been created using machine learning, based on data from NHS Greater Glasgow and Clyde. The study will contact individuals deemed at high risk by the study (750 patients will be re-identified, and these will be contacted starting from the highest risk until 250 patients are recruited) and perform DXA scans, clinical review, and bloods tests that are relevant to osteoporosis. This data will then be compared to the predictions made by the OPTIMAL enhanced screening tool, in order to test how effective it is.
Read the detailed description
The OPTIMAL trial is a feasibility pilot study for an enhanced screening method using a tool developed using machine learning. This tool has been created by Lenus Health Ltd using anonymised health data from NHS GG\&C of patients between the age of 50 and 80 as of 1st of January 2010.
The validation cohort will include all patients in GG\&C between the ages of 50 and 80 as of 1st January 2022 who are not known to have a diagnosis of osteoporosis.
Nanox (Israeli AI company) will use their existing platform to analyse de-identified CT scans of the 5000 patients identified as highest risk in this population to asses for vertebral fracture, which will be used as a parameter in risk assessment for osteoporosis. Because of technical limitations, only a selection of patients can have their imaging assessed by the Nanox platform. The 5000 highest risk patients will be reidentified so that their images can be extracted and de-identified for analysis. We expect approximately 30% of these patients will have available imaging. Identifiable data will remain within the GG\&C cloud.
The trial will use the software to screen for patients at high risk within a cohort of patients aged 50-80 without a diagnosis of osteoporosis. DXA scanning will be used as a ground truth. Patients will have DXA scanning as part of the trial.
There will be a clinical review to remove patients that are felt to be inappropriate for the trial, such as people approaching the end of life, or unable to give consent. The reason for exclusion will be recorded to allow auditing and assessing for bias in selection.
Patients, starting with those at highest risk, will then be contacted by the Fracture Liaison Service until 250 have been recruited. This number has been reached based on power calculations to ensure this trial can effectively compare the OPTIMAL tool with FRAX. This contact will be in the form of a letter from the fracture liaison team, and will come with a patient information sheet and consent form. These forms have been created with the input of a patient experience group.
The participant, should they agree to partake, will then be invited for a single clinic visit at the Queen Elizabeth University Hospital.
At this visit, a doctor will review the patient, and ask questions about their health. They will have blood tests which are relevant to osteoporosis, as well as general health. They will also have a DXA scan to confirm if they do or do not have osteoporosis. A FRAX score will be generated for the purposes of comparison.
Upon completion of data cleaning, at the end of the trial, all data will be transferred The University of Strathclyde secure servers for analysis by Dr Conor McKeag, with oversight from Dr David Young to assess the efficacy and accuracy of the OPTIMAL tool. This will be compared to FRAX, the current standard for risk prediction in osteoporosis.
- Conditions
- Osteoporosis Risk, Osteoporosis
- Being tested
- Dual Energy Xray Absorptiometry
- Keywords
- Machine Learning, Artificial Intelligence, ML, AI, Enhance Screening, Osteoporosis, Routinely Collected Data
- Medical subject headings
- Osteoporosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Dual Energy Xray AbsorptiometryDiagnostic test
Also called DXA, DEXA
DXA for diagnosis of osteoporosis
| Study group | Role | What they receive |
|---|---|---|
| High Risk Group | Group identified by machine learning model as being at high risk of developing osteoporosis. Receives: Diagnostic Test: Dual Energy Xray Absorptiometry |
What is being measured
The primary outcome is the main question the study is designed to answer.
Osteoporosis Diagnosis
Diagnosis of Osteoporosis based on DXA assessment of bone mineral density at Clinical Visit. This will be done at the single clinical visit as part of the trial and will not be repeated.
Measured: At first visit, within 6 months of patient identification.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Jan 2023
- Study startFeb 2023 (estimated)
- Primary completionJun 2023 (estimated)
- Study completionJun 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Osteoporosis RiskStudies 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 250 participants (estimated)
Sponsor and investigators
- Lead sponsor
- NHS Greater Glasgow and Clyde
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05678569
- Sponsor's protocol ID
- OPTIMAL
- Acronym
- OPTIMAL
- Status last verified
- Jan 2023
- First submitted
- 1 Jan 2023
- Last updated
- 10 Jan 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 10 Jan 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- OPTIMAL - OsteoPorosis Treatment Identification Using Machine Learning
- ClinicalTrials.gov ID
- NCT05678569
- Acronym / sponsor ID
- OPTIMAL / OPTIMAL
- Conditions
- Osteoporosis Risk, Osteoporosis
- Keywords
- Machine Learning, Artificial Intelligence, ML, AI, Enhance Screening, Osteoporosis, Routinely Collected Data
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 250 participants (estimated)
- Lead sponsor
- NHS Greater Glasgow and ClydeUniversity, hospital or other
- Study start
- Feb 2023 (estimated)
- Primary completion
- Jun 2023 (estimated)
- Study completion
- Jun 2023 (estimated)
- First posted
- 10 Jan 2023 (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.
OPTIMAL is a pilot feasibility study for a machine learning (ML) based enhanced screening software for osteoporosis.
This tool has been created using machine learning, based on data from NHS Greater Glasgow and Clyde. The study will contact individuals deemed at high risk by the study (750 patients will be re-identified, and these will be contacted starting from the highest risk until 250 patients are recruited) and perform DXA scans, clinical review, and bloods tests that are relevant to osteoporosis. This data will then be compared to the predictions made by the OPTIMAL enhanced screening tool, in order to test how effective it is.
Detailed description
The OPTIMAL trial is a feasibility pilot study for an enhanced screening method using a tool developed using machine learning. This tool has been created by Lenus Health Ltd using anonymised health data from NHS GG\&C of patients between the age of 50 and 80 as of 1st of January 2010.
The validation cohort will include all patients in GG\&C between the ages of 50 and 80 as of 1st January 2022 who are not known to have a diagnosis of osteoporosis.
Nanox (Israeli AI company) will use their existing platform to analyse de-identified CT scans of the 5000 patients identified as highest risk in this population to asses for vertebral fracture, which will be used as a parameter in risk assessment for osteoporosis. Because of technical limitations, only a selection of patients can have their imaging assessed by the Nanox platform. The 5000 highest risk patients will be reidentified so that their images can be extracted and de-identified for analysis. We expect approximately 30% of these patients will have available imaging. Identifiable data will remain within the GG\&C cloud.
The trial will use the software to screen for patients at high risk within a cohort of patients aged 50-80 without a diagnosis of osteoporosis. DXA scanning will be used as a ground truth. Patients will have DXA scanning as part of the trial.
There will be a clinical review to remove patients that are felt to be inappropriate for the trial, such as people approaching the end of life, or unable to give consent. The reason for exclusion will be recorded to allow auditing and assessing for bias in selection.
Patients, starting with those at highest risk, will then be contacted by the Fracture Liaison Service until 250 have been recruited. This number has been reached based on power calculations to ensure this trial can effectively compare the OPTIMAL tool with FRAX. This contact will be in the form of a letter from the fracture liaison team, and will come with a patient information sheet and consent form. These forms have been created with the input of a patient experience group.
The participant, should they agree to partake, will then be invited for a single clinic visit at the Queen Elizabeth University Hospital.
At this visit, a doctor will review the patient, and ask questions about their health. They will have blood tests which are relevant to osteoporosis, as well as general health. They will also have a DXA scan to confirm if they do or do not have osteoporosis. A FRAX score will be generated for the purposes of comparison.
Upon completion of data cleaning, at the end of the trial, all data will be transferred The University of Strathclyde secure servers for analysis by Dr Conor McKeag, with oversight from Dr David Young to assess the efficacy and accuracy of the OPTIMAL tool. This will be compared to FRAX, the current standard for risk prediction in osteoporosis.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| High Risk Group | – | Diagnostic Test: Dual Energy Xray AbsorptiometryGroup identified by machine learning model as being at high risk of developing osteoporosis. |
Who may qualify
- Ages
- 50 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients between the ages of 50 and 80 identified as high risk by the initial model, without a diagnosis of osteoporosis, hyperparathyroidism, or other metabolic bone disease
Key inclusion criteria (3 listed)
- Age >=50y
- Age <=80y
- Identified as high risk by initial model
Key exclusion criteria (9 listed)
- Age <50y
- Age >80y
- BMI <=18 \& >=30
- Recorded diagnosis of osteoporosis
- Prior prescription of bone protective agents such as:
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 |
|---|---|---|
| Dual Energy Xray AbsorptiometryAlso: DXA, DEXADXA for diagnosis of osteoporosis | Diagnostic test | High Risk Group |
Primary outcome
Osteoporosis Diagnosis
Time frame: At first visit, within 6 months of patient identification.
Diagnosis of Osteoporosis based on DXA assessment of bone mineral density at Clinical Visit. This will be done at the single clinical visit as part of the trial and will not be repeated.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Jan 2023.
- Individual participant dataSharing planned: No
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Osteoporosis Risk and Osteoporosis, run by NHS Greater Glasgow and Clyde at 1 site in United Kingdom.
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 3 inclusion and 9 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 10 Jan 2023. 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 United Kingdom. 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 Ruairidh Davison (01414516869, Ruairidh.Davison@ggc.scot.nhs.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Osteoporosis Diagnosis (time frame: At first visit, within 6 months of patient identification.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 10 Jan 2023; AzTrials last refreshed its copy on 28 Oct 2026.