ATTR-CMNCT06029452
A Retrospective Validation Study To Identify Chart-Based Clinical Diagnosis Of Wild-Type Transthyretin Amyloid Cardiomyopathy (Attrwt-CM) And Non-Amyloid Heart Failure Among Patients With Heart Failure (HF).
An observational study of ATTR-CM, run by Pfizer at 1 site in United States.
Trial summary
This is an observational, retrospective non-inferiority study with a study sample from a large national database. A machine learning (ML) model will use a national database to predict the clinical diagnosis of ATTRwt-CM among HF patients. This study will include HF patients ≥50 years old. Read more about this study
- Who is it for?
- Ages 50 years and older
- Conditions the study is for
- ATTR-CM
- What is being tested?
- Machine learning algorithm
- How many people
- 558 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Sep 2023to 14 Nov 2023
- Phase
- Observational
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Heart failure patients with clinical diagnosis of ATTRwt-CM or non-amyloid HF
Who may be able to join
- HF patients (defined as having ≥1 claim for HF or HF treatment) ≥50 years old with clinical diagnosis of ATTRwt-CM or non-amyloid HF ascertained by charts. Patients will be required to have ≥12 months of continuous activity in the EHR or claims prior to the Index Date.
Who cannot join
- Patients with any of the following diagnoses:
- Light chain (AL) amyloidosis
- Intracranial hemorrhage
- Cerebral amyloid angiopathy
- End stage renal disease
- Blood cancer
Trial locations and contacts
1 site in 1 country.
About this study
Official title: A Retrospective Chart Validation Study Evaluating the Performance of Machine Learning Algorithm (ML) to Predict the Clinical Diagnosis of Wild-type Transthyretin Amyloid Cardiomyopathy (ATTRwt-CM) and Non-amyloid Heart Failure Among Patients With Heart Failure (HF)
This is an observational, retrospective non-inferiority study with a study sample from a large national database.
A machine learning (ML) model will use a national database to predict the clinical diagnosis of ATTRwt-CM among HF patients. This study will include HF patients ≥50 years old.
- Conditions
- ATTR-CM
- Being tested
- Machine learning algorithm
- Keywords
- Chronic Heart Failure
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Machine learning algorithmOther
Software to calculate the predicted probability of ATTRwt-CM for these heart failure patients based on the presence and absence of certain features
| Study group | Role | What they receive |
|---|---|---|
| ATTRwt-CM and non-amyloid heart failure patients | Not described Receives: Other: Machine learning algorithm |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of Participants According to Clinical Diagnosis Predicted Using the Machine Learning (ML) Algorithm
In this outcome measure number of participants were reported according to clinical diagnosis predicted by ML algorithm. True positive (TP) = participants with actual and predicted diagnosis of ATTRwt-CM; False positive (FP) = participants with actual diagnosis of non-amyloid HF and predicted diagnosis of ATTRwt-CM; False negative (FN) = participants with actual diagnosis of ATTRwt-CM and predicted diagnosis of non-amyloid HF; True negative (TN) = participants with actual and predicted diagnosis of non-amyloid HF.
Measured: At diagnosis, anytime during retrospective data identification period of approximately 5.4 years; retrospective data observed in this study for approximately 2.5 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Sep 2023
- Study start1 Sep 2023
- Primary completion14 Nov 2023
- Study completion14 Nov 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Other trials for ATTR-CMStudies of the same condition, open and under way.
- More trials run by PfizerThe 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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 558 participants (actual)
Sponsor and investigators
- Lead sponsor
- Pfizer
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Pfizer CT.gov Call Center, Study director, Pfizer
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06029452
- Sponsor's protocol ID
- B3461111
- Status last verified
- Nov 2024
- First submitted
- 1 Sep 2023
- Last updated
- 3 Jan 2025
- Results posted
- Yes, on ClinicalTrials.gov
- Individual data sharing
- No: Pfizer will provide access to individual de-identified participant data and related study documents (e.g. protocol, Statistical Analysis Plan (SAP), Clinical Study Report (CSR)) upon request from qualified researchers, and subject to certain criteria, conditions, and exceptions. Further details on Pfizer's data sharing criteria and process for requesting access can be found at: https://www.pfizer.com/science/clinical\_trials/trial\_data\_and\_results/data\_requests.
Study at a glance
From the registry record, last updated by the sponsor on 3 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Retrospective Chart Validation Study Evaluating the Performance of Machine Learning Algorithm (ML) to Predict the Clinical Diagnosis of Wild-type Transthyretin Amyloid Cardiomyopathy (ATTRwt-CM) and Non-amyloid Heart Failure Among Patients With Heart Failure (HF)
- ClinicalTrials.gov ID
- NCT06029452
- Acronym / sponsor ID
- B3461111
- Conditions
- ATTR-CM
- Keywords
- Chronic Heart Failure
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 558 participants (actual)
- Lead sponsor
- PfizerIndustry (pharma, biotech, devices)
- Study start
- 1 Sep 2023 (actual)
- Primary completion
- 14 Nov 2023 (actual)
- Study completion
- 14 Nov 2023 (actual)
- First posted
- 8 Sep 2023 (actual)
- Results
- Posted 3 Jan 2025
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is an observational, retrospective non-inferiority study with a study sample from a large national database.
A machine learning (ML) model will use a national database to predict the clinical diagnosis of ATTRwt-CM among HF patients. This study will include HF patients ≥50 years old.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| ATTRwt-CM and non-amyloid heart failure patients | – | Other: Machine learning algorithm |
Who may qualify
- Ages
- 50 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Heart failure patients with clinical diagnosis of ATTRwt-CM or non-amyloid HF
Key inclusion criteria (1 listed)
- HF patients (defined as having ≥1 claim for HF or HF treatment) ≥50 years old with clinical diagnosis of ATTRwt-CM or non-amyloid HF ascertained by charts. Patients will be required to have ≥12 months of continuous activity in the EHR or claims prior to the Index Date.
Key exclusion criteria (6 listed)
- Patients with any of the following diagnoses:
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 |
|---|---|---|
| Machine learning algorithmSoftware to calculate the predicted probability of ATTRwt-CM for these heart failure patients based on the presence and absence of certain features | Other | ATTRwt-CM and non-amyloid heart failure patients |
Primary outcome
Number of Participants According to Clinical Diagnosis Predicted Using the Machine Learning (ML) Algorithm
Time frame: At diagnosis, anytime during retrospective data identification period of approximately 5.4 years; retrospective data observed in this study for approximately 2.5 months
In this outcome measure number of participants were reported according to clinical diagnosis predicted by ML algorithm. True positive (TP) = participants with actual and predicted diagnosis of ATTRwt-CM; False positive (FP) = participants with actual diagnosis of non-amyloid HF and predicted diagnosis of ATTRwt-CM; False negative (FN) = participants with actual diagnosis of ATTRwt-CM and predicted diagnosis of non-amyloid HF; True negative (TN) = participants with actual and predicted diagnosis of non-amyloid HF.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Jan 2025.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- To obtain contact information for a study center near you, click here.Link provided by the sponsor.
- Individual participant dataSharing planned: No. Pfizer will provide access to individual de-identified participant data and related study documents (e.g. protocol, Statistical Analysis Plan (SAP), Clinical Study Report (CSR)) upon request from qualified researchers, and subject to certain criteria, conditions, and exceptions. Further details on Pfizer's data sharing criteria and process for requesting access can be found at: https://www.pfizer.com/science/clinical_trials/trial_data_and_results/data_requests.
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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.
Pfizer CT.gov Call Center study director
Pfizer
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 ATTR-CM, run by Pfizer at 1 site in United States.
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 1 inclusion and 6 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 3 Jan 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 United States. 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?
Yes. Results are posted in the registry (first posted 3 Jan 2025). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
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?
Number of Participants According to Clinical Diagnosis Predicted Using the Machine Learning (ML) Algorithm (time frame: At diagnosis, anytime during retrospective data identification period of approximately 5.4 years; retrospective data observed in this study for approximately 2.5 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 3 Jan 2025.