OsteoPorosis Treatment Identification Using Machine Learning

NCT05678569 | Unknown

• 1 other identifier: OPTIMAL
• Study Type: observational
• Target: 250
• Locations: 1 country
• Sites: 1

Brief 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. 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.

Conditions

Osteoporosis Risk; Osteoporosis

Keywords

Machine Learning; Artificial Intelligence; ML; AI; Enhance Screening; Osteoporosis; Routinely Collected Data

Outcome Measures

Primary Outcomes (1)

• 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.

  At first visit, within 6 months of patient identification.

Study Arms (1)

High Risk Group

Group identified by machine learning model as being at high risk of developing osteoporosis.

Diagnostic Test: Dual Energy Xray Absorptiometry

Interventions

Dual Energy Xray Absorptiometry DIAGNOSTIC_TEST

DXA for diagnosis of osteoporosis

Also known as: DXA, DEXA

High Risk Group

Eligibility Criteria

• Age: 50 Years - 80 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

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

You may qualify if:

• Age \>=50y
• Age \<=80y
• Identified as high risk by initial model

You may not qualify if:

• 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
• History of prior DXA imaging (prior quantification of BMD)
• History of metabolic bone disease
• History of primary hyperparathyroidism

Sponsors & Collaborators

• NHS Greater Glasgow and Clyde: lead

Study Sites (1)

West of Scotland Innovation Hub

Glasgow, G51 4TF, United Kingdom

Location

MeSH Terms

Conditions

Osteoporosis

Interventions

Absorptiometry, Photon

Condition Hierarchy (Ancestors)

Bone Diseases, Metabolic; Bone Diseases; Musculoskeletal Diseases; Metabolic Diseases; Nutritional and Metabolic Diseases

Intervention Hierarchy (Ancestors)

Radiography; Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis; Densitometry; Photometry; Chemistry Techniques, Analytical; Investigative Techniques

Central Study Contacts

Ruairidh Davison

CONTACT

01414516869; Ruairidh.Davison@ggc.scot.nhs.uk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 1, 2023
• First Posted: January 10, 2023
• Study Start: February 1, 2023
• Primary Completion: June 1, 2023
• Study Completion: June 1, 2023
• Last Updated: January 10, 2023

Record last verified: 2023-01

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)