Fabry DiseaseNCT05106764
Early Detection of Fabry Disease
An observational study of Fabry Disease, run by Takeda at 3 sites in Germany.
Trial summary
The main aim of this study is early detection of FD using real-world data for the development of advanced natural language processing methods and to develop a predictive algorithm and to measure the performance of the algorithm in identifying participants with FD. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Fabry Disease
- How many people
- 50 participants
- Where
- 3 sitesGermany
- Study dates
- 30 Nov 2023to 16 Dec 2025
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Data from all in-patient or out- patient datasets of the participating hospital in the last 10 years will be used to test the forecasting power of the algorithm.
Who may be able to join
- In-patient or out-patient datasets of the participating hospital in the last 10 years
- Participants at any age Positive controls: a subset of all participant hospital records that includes the participants with confirmed FD.
Who cannot join
None listed.
Trial locations and contacts
3 sites in 1 country.
Germany3 sites
Universitätsklinikum Erlangen Kinder- und Jugendklinik
Erlangen, 91054
Universitätsklinikum Erlangen Neurologische Klinik
Erlangen, 91054
Universitätsklinikum Giessen
Giessen, 35389
About this study
Official title: Early Detection of Fabry Disease (FD): Using Real-World Data for the Development of Advanced Natural Language Processing Methods: Retrospective Database Analysis
The main aim of this study is early detection of FD using real-world data for the development of advanced natural language processing methods and to develop a predictive algorithm and to measure the performance of the algorithm in identifying participants with FD.
This study is about using data from hospital Electronic Health Record database from the last 10 years to describe the ranking of participants with FD using multilevel likelihood ratios and to validate the algorithm using positive controls. No investigational medicinal product or device will be tested in this study. Hospital electronic health record data will be analyzed for a period of up to 6 months.
- Conditions
- Fabry Disease
- Being tested
- No intervention
- Medical subject headings
- Fabry Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
This is non-interventional study.
| Study group | Role | What they receive |
|---|---|---|
| Retrospective Database Analysis | Data from patient's hospital records of the last 10 years will be collected/extracted retrospectively using epidemiological methods to test the forecasting power of the algorithm. Receives: Other: No intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
Percentage of Participants With Positive Predictive Value (PPV) at Different Cut-off Values (top 10, 20, 50, 100 and 200)
PPV is a clinically relevant statistical measure that indicates how likely participants that screen positive are to be affected by the condition assessed. Thus, the PPV can be considered as the percentage of participants which are identified as FD candidates by the ranking algorithm who are indeed FD participants. As FD predictive algorithm, we will use (multilevel) likelihood ratios (LRs) as this method permits a good use of clinical test results to establish diagnoses for the individual participant. LR is calculated, defined as the probability of a patient who has FD to present with this feature divided by the probability of a participant who not has FD to present with the feature: Likelihood ratio= features the participant/Fabry divided by features the participant/not Fabry. Positive predictive value of the algorithm at several cutoffs (top 10, top 20, top 50, top 100, top 200) will be reported.
Measured: Up to End of the study (approximately 6 months)
Secondary outcomes (1)
Percentage of Participants Based on Ranking With Known FD Using Multilevel Likelihood Ratios For Algorithm Validation Purposes
To validate the algorithm, records of participants with a high predictive value are reexamined by medical experts who assess the likelihood of FD based on the participant records. Percentage of participants based on ranking with known FD using multilevel likelihood ratios for algorithm validation purpose will be reported. Likelihood ratio= features the participant/Fabry divided by features the participant/not Fabry.
Measured: Up to End of the study (approximately 6 months)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Nov 2021
- Study start30 Nov 2023
- Primary completion16 Dec 2025
- Study completion16 Dec 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Fabry DiseaseStudies of the same condition, open and under way.
- More trials run by TakedaThe sponsor's other registered studies.
- 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 50 participants (actual)
Sponsor and investigators
- Lead sponsor
- Takeda
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Study Director, Study director, Takeda
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05106764
- Sponsor's protocol ID
- TAK-675-4011-1
- Other IDs
- FLAGGING FD-1
- Status last verified
- Mar 2026
- First submitted
- 25 Oct 2021
- Last updated
- 16 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Takeda provides access to the de-identified individual participant data (IPD) for eligible studies to aid qualified researchers in addressing legitimate scientific objectives (Takeda's data sharing commitment is available on https://clinicaltrials.takeda.com/takedas-commitment?commitment=5). These IPDs will be provided in a secure research environment following approval of a data sharing request, and under the terms of a data sharing agreement.
Study at a glance
From the registry record, last updated by the sponsor on 16 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Early Detection of Fabry Disease (FD): Using Real-World Data for the Development of Advanced Natural Language Processing Methods: Retrospective Database Analysis
- ClinicalTrials.gov ID
- NCT05106764
- Acronym / sponsor ID
- TAK-675-4011-1
- Conditions
- Fabry Disease
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 50 participants (actual)
- Lead sponsor
- TakedaIndustry (pharma, biotech, devices)
- Study start
- 30 Nov 2023 (actual)
- Primary completion
- 16 Dec 2025 (actual)
- Study completion
- 16 Dec 2025 (actual)
- First posted
- 4 Nov 2021 (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 main aim of this study is early detection of FD using real-world data for the development of advanced natural language processing methods and to develop a predictive algorithm and to measure the performance of the algorithm in identifying participants with FD.
This study is about using data from hospital Electronic Health Record database from the last 10 years to describe the ranking of participants with FD using multilevel likelihood ratios and to validate the algorithm using positive controls. No investigational medicinal product or device will be tested in this study. Hospital electronic health record data will be analyzed for a period of up to 6 months.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Retrospective Database Analysis | – | Other: No interventionData from patient's hospital records of the last 10 years will be collected/extracted retrospectively using epidemiological methods to test the forecasting power of the algorithm. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Data from all in-patient or out- patient datasets of the participating hospital in the last 10 years will be used to test the forecasting power of the algorithm.
Key inclusion criteria (2 listed)
- In-patient or out-patient datasets of the participating hospital in the last 10 years
- Participants at any age Positive controls: a subset of all participant hospital records that includes the participants with confirmed FD.
Key exclusion criteria (0 listed)
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 |
|---|---|---|
| No interventionThis is non-interventional study. | Other | Retrospective Database Analysis |
Primary outcome
Percentage of Participants With Positive Predictive Value (PPV) at Different Cut-off Values (top 10, 20, 50, 100 and 200)
Time frame: Up to End of the study (approximately 6 months)
PPV is a clinically relevant statistical measure that indicates how likely participants that screen positive are to be affected by the condition assessed. Thus, the PPV can be considered as the percentage of participants which are identified as FD candidates by the ranking algorithm who are indeed FD participants. As FD predictive algorithm, we will use (multilevel) likelihood ratios (LRs) as this method permits a good use of clinical test results to establish diagnoses for the individual participant. LR is calculated, defined as the probability of a patient who has FD to present with this feature divided by the probability of a participant who not has FD to present with the feature: Likelihood ratio= features the participant/Fabry divided by features the participant/not Fabry. Positive predictive value of the algorithm at several cutoffs (top 10, top 20, top 50, top 100, top 200) will be reported.
1 secondary outcome
Percentage of Participants Based on Ranking With Known FD Using Multilevel Likelihood Ratios For Algorithm Validation Purposes
Time frame: Up to End of the study (approximately 6 months)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Mar 2026.
- To obtain more information on the study, click here/on this linkLink provided by the sponsor.
- Individual participant dataSharing planned: Yes. Takeda provides access to the de-identified individual participant data (IPD) for eligible studies to aid qualified researchers in addressing legitimate scientific objectives (Takeda's data sharing commitment is available on https://clinicaltrials.takeda.com/takedas-commitment?commitment=5). These IPDs will be provided in a secure research environment following approval of a data sharing request, and under the terms of a data sharing agreement.
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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.
Study Director study director
Takeda
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Fabry Disease, run by Takeda at 3 sites in Germany.
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 0 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: finished, as of the sponsor's last update on 16 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Germany. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Percentage of Participants With Positive Predictive Value (PPV) at Different Cut-off Values (top 10, 20, 50, 100 and 200) (time frame: Up to End of the study (approximately 6 months)). 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 16 Mar 2026.