Coronary Artery DiseaseGPS-CADNCT05722145
Global Pretest Probability Study of Coronary Artery Disease
An observational study of Coronary Artery Disease, run by National Heart Centre Singapore at 1 site in Singapore.
Trial summary
The use of pre-test probability (PTP) and coronary artery calcium (CAC) scores is guideline-recommended in the evaluation of coronary artery disease (CAD) and stable chest pain. The utility of these scores is population dependent. Read more about this study
- Who is it for?
- Ages 21 to 99 years
- Conditions the study is for
- Coronary Artery Disease
- How many people
- 100,000 participants
- Where
- 1 siteSingapore
- Study dates
- 25 Nov 2022to Aug 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 21 to 99 years
- All sexes
- Adult, Older adult
Study population: Across hospitals and research centres across multiple countries
Who may be able to join
- Age of participants are more than or equals to 21 years old
- The subjects need to have underwent computed tomography angiography (CTA) or non-contrast computer tomography (NCCT) for assessment of coronary artery disease.
Who cannot join
- Age less than 21 years old
- Subjects who are unable to undergo cardiac CT
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Singapore1 site
National Heart Centre Singapore
Singapore, Singapore, 169609
About this study
The use of pre-test probability (PTP) and coronary artery calcium (CAC) scores is guideline-recommended in the evaluation of coronary artery disease (CAD) and stable chest pain. The utility of these scores is population dependent. Previous studies have predominantly been limited to Western populations, despite Asia forming 60% of the global population. However, Asian populations have differing coronary artery phenotypes and may therefore have different PTPs with varying implications for risk stratification. Known difference in CAC implications support a global approach. Hence, this study aims to evaluate a contemporary PTP in diverse real-world Asian, Western and other cohorts and to evaluate the incremental value of CAC in predicting CAD and events. Primarily, the study will compare population specific PTPs and CAC for prediction of coronary computed tomography angiography (CTA) CAD. This could be compared with existing guideline-recommended PTPs alone or with consideration of risk factors or CAC. The study will also evaluate the accuracy of the prediction of major adverse cardiovascular events (MACE) using PTP models, risk factors and/or CAC. Lastly, the study will investigate the accuracy of zero CAC and other minimal risk tools to de-risk cardiovascular disease (CVD) in various populations.
The study will investigate multiple international cohorts of patients referred for noninvasive testing using coronary CTA or other non-invasive imaging modalities. Locally-calibrated PTP models in consideration of risk factors or CAC will be separately tailored to each different cohort, and will be evaluated.
Read the detailed description
This study is an aggregated registry comprising of a retrospective medical record review of individuals from multiple sites. The general approach is to create a large, consolidated, global registry of existing cohorts of patients referred for noninvasive testing using computed tomography (CT). Anonymized images and structured data, including demographics, risk factors, outcomes and CT results will be obtained from multiple sites. The types of images to be analyzed and quantified are non-contrast CT (NCCT) scans and coronary CT angiography (CCTA). CAC score will use Agatston's method while CAD will be assessed using registry data of CCTA reads.
The data collected will include risk factors and demographics such as age, sex, ethnicity, hypertension, smoking, diabetes, dyslipidemia and family history of CAD. Outcomes such as death and myocardial infarctions will be included in the dataset if available. All data received will be anonymized and de-identified. Study team members will check through the study data to ensure that all study data is accurately collected and complete.
The data elements of different cohorts may not harmonize or match with each other. There could be missing data elements or different data inputs. As such, omission or imputation may be used to perform analyses. To minimize data heterogeneity in format, sites will be provided with a standard template and data dictionary. This will complete the initial data harmonization and expected data elements. The collected dataset would then be harmonized by the biostatistics team prior to analysis.
The approximate total study size n = 100,000. Assuming an area under the receiver operating curve (AUC) of 0.70 for existing PTP and CAC methods, this proposal is adequately powered to detect an increase of 0.05 in AUC using a two-sided z-test at a significance level of 0.05. Continuous variables will be expressed as mean and standard deviation. Categorical variables will be expressed as absolute numbers and percentages. Distributions will be tested for normality using Shapiro-Wilk statistics. Non-normally distributed variables will be represented as median with 25th to 75th interquartile range. Comparison of normally distributed continuous variables will be performed using Student's t test for paired and unpaired data. Non-normally distributed variables will be compared using Mann-Whitney Rank Sum tests and Kruskal-Wallis tests. Comparison of categorical data will be performed using Chi-square and Fisher's Exact Tests where appropriate.
Differences in outcomes over time will be analyzed by the Kaplan-Meier analysis with log-rank test for each outcome. Using Cox regressions analysis univariate and multivariate regression analyses will be performed. Univariate analysis will include pre-event variables with p values <0.10. Variables that showed a significant (p<0.05) correlation with the endpoints, after univariate analysis, will be considered in the multivariate models. Odds ratios and 95% confidence interval will be calculated. Statistical significance was established as p<0.05. Advanced machine learning techniques (e.g. neural networks) may be applied.
- Conditions
- Coronary Artery Disease
- Medical subject headings
- Coronary Artery Disease
What is being measured
The primary outcome is the main question the study is designed to answer.
To evaluate and optimize contemporary risk and PTP tools for use in diverse real-world global cohorts by pooling data from multiple large CTA/CAC studies worldwide
Measured: Throughout study, expected to be 5 years
Secondary outcomes (4)
To evaluate and compare existing PTPs and CAC for prediction of CTA-defined CAD using PTP alone, with risk factors (RF) and/or CAC
Measured: Throughout study, expected to be 5 years
To compare the accuracy of prediction of major adverse cardiovascular events (MACE) using PTP alone, with RF and/or CAC
Measured: Throughout study, expected to be 5 years
Determine population-specific optimizations for risk prediction of CAD and MACE and evaluate these newly-modified PTP
Measured: Throughout study, expected to be 5 years
To compare accuracy of zero CAC and minimal risk tools to exclude CAD in various populations (de-risk)
Measured: Throughout study, expected to be 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Feb 2023
- Study start25 Nov 2022
- Primary completionAug 2027 (estimated)
- Study completionAug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Coronary Artery DiseaseStudies 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
- Retrospective
- Enrolment
- 100,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Heart Centre Singapore
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Lohendran Baskaran, Principal investigator, National Heart Centre SingaporePamela Douglas, Study chair, Duke University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05722145
- Sponsor's protocol ID
- 2022-2521
- Acronym
- GPS-CAD
- Status last verified
- May 2025
- First submitted
- 9 Jan 2023
- Last updated
- 4 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Baskaran L, Selva JJ, Mantri AVI, Douglas PS; GPS-CAD Investigators. Design and Rationale of GPS-CAD: Global Pretest Probability Study of Coronary Artery Disease. JACC Asia. 2025 Dec 30:S2772-3747(25)00695-7. doi: 10.1016/j.jacasi.2025.11.016. Online ahead of print.
PubMed 41904715
Study at a glance
From the registry record, last updated by the sponsor on 4 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Global Pretest Probability Study of Coronary Artery Disease
- ClinicalTrials.gov ID
- NCT05722145
- Acronym / sponsor ID
- GPS-CAD / 2022-2521
- Conditions
- Coronary Artery Disease
- Study type
- Observational
- Recruitment status
- Enrolling by invitation
- Enrolment
- 100,000 participants (estimated)
- Lead sponsor
- National Heart Centre SingaporeUniversity, hospital or other
- Study start
- 25 Nov 2022 (actual)
- Primary completion
- Aug 2027 (estimated)
- Study completion
- Aug 2027 (estimated)
- First posted
- 10 Feb 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.
The use of pre-test probability (PTP) and coronary artery calcium (CAC) scores is guideline-recommended in the evaluation of coronary artery disease (CAD) and stable chest pain. The utility of these scores is population dependent. Previous studies have predominantly been limited to Western populations, despite Asia forming 60% of the global population. However, Asian populations have differing coronary artery phenotypes and may therefore have different PTPs with varying implications for risk stratification. Known difference in CAC implications support a global approach. Hence, this study aims to evaluate a contemporary PTP in diverse real-world Asian, Western and other cohorts and to evaluate the incremental value of CAC in predicting CAD and events. Primarily, the study will compare population specific PTPs and CAC for prediction of coronary computed tomography angiography (CTA) CAD. This could be compared with existing guideline-recommended PTPs alone or with consideration of risk factors or CAC. The study will also evaluate the accuracy of the prediction of major adverse cardiovascular events (MACE) using PTP models, risk factors and/or CAC. Lastly, the study will investigate the accuracy of zero CAC and other minimal risk tools to de-risk cardiovascular disease (CVD) in various populations.
The study will investigate multiple international cohorts of patients referred for noninvasive testing using coronary CTA or other non-invasive imaging modalities. Locally-calibrated PTP models in consideration of risk factors or CAC will be separately tailored to each different cohort, and will be evaluated.
Detailed description
This study is an aggregated registry comprising of a retrospective medical record review of individuals from multiple sites. The general approach is to create a large, consolidated, global registry of existing cohorts of patients referred for noninvasive testing using computed tomography (CT). Anonymized images and structured data, including demographics, risk factors, outcomes and CT results will be obtained from multiple sites. The types of images to be analyzed and quantified are non-contrast CT (NCCT) scans and coronary CT angiography (CCTA). CAC score will use Agatston's method while CAD will be assessed using registry data of CCTA reads.
The data collected will include risk factors and demographics such as age, sex, ethnicity, hypertension, smoking, diabetes, dyslipidemia and family history of CAD. Outcomes such as death and myocardial infarctions will be included in the dataset if available. All data received will be anonymized and de-identified. Study team members will check through the study data to ensure that all study data is accurately collected and complete.
The data elements of different cohorts may not harmonize or match with each other. There could be missing data elements or different data inputs. As such, omission or imputation may be used to perform analyses. To minimize data heterogeneity in format, sites will be provided with a standard template and data dictionary. This will complete the initial data harmonization and expected data elements. The collected dataset would then be harmonized by the biostatistics team prior to analysis.
The approximate total study size n = 100,000. Assuming an area under the receiver operating curve (AUC) of 0.70 for existing PTP and CAC methods, this proposal is adequately powered to detect an increase of 0.05 in AUC using a two-sided z-test at a significance level of 0.05. Continuous variables will be expressed as mean and standard deviation. Categorical variables will be expressed as absolute numbers and percentages. Distributions will be tested for normality using Shapiro-Wilk statistics. Non-normally distributed variables will be represented as median with 25th to 75th interquartile range. Comparison of normally distributed continuous variables will be performed using Student's t test for paired and unpaired data. Non-normally distributed variables will be compared using Mann-Whitney Rank Sum tests and Kruskal-Wallis tests. Comparison of categorical data will be performed using Chi-square and Fisher's Exact Tests where appropriate.
Differences in outcomes over time will be analyzed by the Kaplan-Meier analysis with log-rank test for each outcome. Using Cox regressions analysis univariate and multivariate regression analyses will be performed. Univariate analysis will include pre-event variables with p values <0.10. Variables that showed a significant (p<0.05) correlation with the endpoints, after univariate analysis, will be considered in the multivariate models. Odds ratios and 95% confidence interval will be calculated. Statistical significance was established as p<0.05. Advanced machine learning techniques (e.g. neural networks) may be applied.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 21 to 99 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Across hospitals and research centres across multiple countries
Key inclusion criteria (2 listed)
- Age of participants are more than or equals to 21 years old
- The subjects need to have underwent computed tomography angiography (CTA) or non-contrast computer tomography (NCCT) for assessment of coronary artery disease.
Key exclusion criteria (2 listed)
- Age less than 21 years old
- Subjects who are unable to undergo cardiac CT
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
To evaluate and optimize contemporary risk and PTP tools for use in diverse real-world global cohorts by pooling data from multiple large CTA/CAC studies worldwide
Time frame: Throughout study, expected to be 5 years
4 secondary outcomes
To evaluate and compare existing PTPs and CAC for prediction of CTA-defined CAD using PTP alone, with risk factors (RF) and/or CAC
Time frame: Throughout study, expected to be 5 years
To compare the accuracy of prediction of major adverse cardiovascular events (MACE) using PTP alone, with RF and/or CAC
Time frame: Throughout study, expected to be 5 years
Determine population-specific optimizations for risk prediction of CAD and MACE and evaluate these newly-modified PTP
Time frame: Throughout study, expected to be 5 years
To compare accuracy of zero CAC and minimal risk tools to exclude CAD in various populations (de-risk)
Time frame: Throughout study, expected to be 5 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Dec 2025.
- Derived from this study: PubMed 41904715Baskaran L, Selva JJ, Mantri AVI, Douglas PS; GPS-CAD Investigators. Design and Rationale of GPS-CAD: Global Pretest Probability Study of Coronary Artery Disease. JACC Asia. 2025 Dec 30:S2772-3747(25)00695-7. doi: 10.1016/j.jacasi.2025.11.016. Online ahead of print.
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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.
Lohendran Baskaran principal investigator
National Heart Centre Singapore
Pamela Douglas study chair
Duke University
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 Coronary Artery Disease, run by National Heart Centre Singapore at 1 site in Singapore.
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 2 inclusion and 2 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: enrolling by invitation, as of the sponsor's last update on 4 Dec 2025. 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 Singapore. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To evaluate and optimize contemporary risk and PTP tools for use in diverse real-world global cohorts by pooling data from multiple large CTA/CAC studies worldwide (time frame: Throughout study, expected to be 5 years). 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 NCT05722145, which also lists 1 linked publication.
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 4 Dec 2025.