Heart FailureBIOPHFNCT07332520
Predicting Heart Failure Outcomes With Biomarkers and Imaging
An observational study of Heart Failure and Heart Failure, Systolic, run by Xinjiang Medical University.
Trial summary
This study aims to develop a better model to predict one-year risk of death in patients with heart failure. We will test whether combining information from routine blood tests (like NT-proBNP) and heart scans (measuring features like epicardial fat density) improves risk prediction compared to using either type of… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Heart Failure, Heart Failure, Systolic, Heart Failure, Diastolic
- How many people
- 4,000 participants
- Where
- No sites listed yet
- Study dates
- 1 Jan 2012to 31 Jan 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adults diagnosed with chronic heart failure at the study center between 2012 and 2024.
Who may be able to join
- Age ≥ 18 years.
- Confirmed diagnosis of chronic heart failure.
- Treated at the study center between January 1, 2012, and December 31, 2024.
- Availability of both qualifying blood biomarker test results (NT-proBNP and/or high-sensitivity cardiac troponin) and cardiac imaging (echocardiography and/or cardiac CT) performed within a ±3-month window around the index encounter.
Who cannot join
- Heart failure primarily due to severe primary valvular disease, acute myocardial infarction, myocarditis, or pulmonary embolism.
- End-stage renal disease requiring dialysis.
- Clinical records or follow-up data are severely incomplete, precluding outcome assessment.
About this study
Official title: Blood Biomarkers Combined With Imaging Parameters for Prognostic Assessment in Patients With Different Types of Heart Failure: A Retrospective Single-Center Cohort Study
This study aims to develop a better model to predict one-year risk of death in patients with heart failure. We will test whether combining information from routine blood tests (like NT-proBNP) and heart scans (measuring features like epicardial fat density) improves risk prediction compared to using either type of data alone.
This is a retrospective study using existing medical records of patients treated for chronic heart failure at Xinjiang Medical University First Affiliated Hospital between 2012 and 2024. No new patient contact or interventions are involved.
The goal is to enable more accurate, personalized risk assessment across different types of heart failure (HFrEF, HFmrEF, HFpEF).
Read the detailed description
Background and Rationale:
Accurate prognosis in heart failure (HF) remains challenging due to phenotypic heterogeneity across the spectrum of left ventricular ejection fraction (LVEF). While biomarkers like N-terminal pro-B-type natriuretic peptide (NT-proBNP) and imaging parameters like LVEF are standard prognostic tools, each has limitations. Emerging imaging parameters, such as epicardial adipose tissue (EAT) density (reflecting fat inflammation/fibrosis) and left ventricular global longitudinal strain (LVGLS), offer potential incremental prognostic value but are not yet integrated into routine clinical models. This study aims to systematically evaluate whether a multi-parameter model combining established blood biomarkers and advanced imaging metrics improves the prognostic stratification of patients with HFrEF, HFmrEF, and HFpEF compared to traditional approaches.
Detailed Methodology:
This is a single-center, retrospective cohort study. The study population consists of consecutive adult patients (≥18 years) with a confirmed diagnosis of chronic HF who had both qualifying blood biomarker assessment (NT-proBNP and/or high-sensitivity cardiac troponin) and cardiac imaging (transthoracic echocardiography and/or cardiac computed tomography) performed within a ±3-month window around an index encounter between January 1, 2012, and December 31, 2024, at Xinjiang Medical University First Affiliated Hospital.
Key data to be extracted from electronic health records include: 1) Clinical variables: demographics, comorbidities (e.g., ischemic etiology, diabetes, hypertension), medications, and NYHA class; 2) Blood biomarkers: NT-proBNP, hs-cTnT/I, hs-CRP, and renal function (eGFR); 3) Imaging parameters: LVEF, LVGLS, left atrial volume index (LAVI), E/e' ratio, and EAT volume/density (from CT, if available).
The primary endpoint is all-cause mortality at one year from the index date. Follow-up data will be obtained from hospital records.
Statistical Analysis Plan:
The incremental prognostic value will be assessed by constructing and comparing nested Cox proportional hazards models:
Model 1 (Base Clinical): Includes age, sex, BMI, ischemic etiology, diabetes, and hypertension.
Model 2 (Biomarker-Enhanced): Model 1 + NT-proBNP + eGFR. Model 3 (Imaging-Enhanced): Model 2 + key imaging parameters (e.g., EAT density or LVGLS).
Model performance will be compared using Harrell's C-statistic, the Akaike Information Criterion (AIC), Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). Pre-specified subgroup analyses will be conducted for HFrEF, HFmrEF, and HFpEF phenotypes. Multiple imputation will be used for variables with low rates of missing data (<10%).
- Conditions
- Heart Failure, Heart Failure, Systolic, Heart Failure, Diastolic, Heart Failure With Reduced Ejection Fraction (HFrEF), Heart Failure With Preserved Ejection Fraction (HFPEF), Heart Failure With Mid-Range Ejection Fraction (HFmrEF)
- Keywords
- Heart failure prognosis, Biomarkers, NT-proBNP, Medical imaging, Echocardiography, Computed tomography, Epicardial adipose tissue, Global longitudinal strain, Risk prediction model, Retrospective cohort study, HFpEF, HFrEF, Phenotype, All-cause mortality
- Medical subject headings
- Heart Failure, Heart Failure, Systolic, Heart Failure, Diastolic
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Heart Failure Cohort | Adult patients (≥18 years) with a confirmed diagnosis of chronic heart failure who had both qualifying blood biomarker assessment and cardiac imaging performed within a specified window at the study center between 2012 and 2024. This is an observational cohort. No specific intervention is administered or withheld as part of the research protocol. |
What is being measured
The primary outcome is the main question the study is designed to answer.
All-cause mortality
Occurrence of death from any cause within one year (365 days) from the index date. The index date is defined as the date of the first qualifying encounter that meets all inclusion criteria.
Measured: 1 year
Secondary outcomes (5)
Phenotype-specific prognostic performance
Difference in the predictive performance (measured by Harrell's C-statistic) of the combined biomarker-imaging model across heart failure phenotypes (HFrEF, HFmrEF, HFpEF).
Measured: 1 year
Independent prognostic value of EAT density in HFpEF
Hazard ratio of epicardial adipose tissue (EAT) density for all-cause mortality in HFpEF patients, after adjustment for body mass index (BMI) and high-sensitivity C-reactive protein (hs-CRP).
Measured: 1 year
Occurrence of HFimpEF
The proportion of patients with baseline HFrEF or HFmrEF who achieve HFimpEF, defined as a follow-up LVEF increase by ≥10 percentage points to a value of >40%, assessed by follow-up echocardiography.
Measured: Through study completion,up to 13 years.
Association between baseline NT-proBNP level and HFimpEF
The association quantified by the Odds Ratio (OR) per unit increase in log-transformed baseline NT-proBNP level with the occurrence of HFimpEF, derived from a multivariable logistic regression model.
Measured: Through study completion, up to 13 years.
Association between baseline EAT density and HFimpEF
The association quantified by the Odds Ratio (OR) per unit increase in baseline epicardial adipose tissue (EAT) density (in Hounsfield Units) with the occurrence of HFimpEF, derived from a multivariable logistic regression model.
Measured: Through study completion, up to 13 years.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Jan 2026
- Study start1 Jan 2012
- Primary completion31 Dec 2024
- Study completion31 Jan 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Heart FailureStudies 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
- 4,000 participants (actual)
Sponsor and investigators
- Lead sponsor
- Xinjiang Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xiang Xie, Xinjiang Medical University
- Investigators
- Xiang Xie, PhD, Study chair, First Affiliated Hospital of Xinjiang Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07332520
- Sponsor's protocol ID
- HF_Prognosis_2025
- Other IDs
- K202511-03
- Acronym
- BIOPHF
- Status last verified
- Jan 2026
- First submitted
- 28 Dec 2025
- Last updated
- 27 Jan 2026
- Results posted
- No
- Data monitoring committee
- Yes
- 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 27 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Blood Biomarkers Combined With Imaging Parameters for Prognostic Assessment in Patients With Different Types of Heart Failure: A Retrospective Single-Center Cohort Study
- ClinicalTrials.gov ID
- NCT07332520
- Acronym / sponsor ID
- BIOPHF / HF_Prognosis_2025
- Conditions
- Heart Failure, Heart Failure, Systolic, Heart Failure, Diastolic, Heart Failure With Reduced Ejection Fraction (HFrEF), Heart Failure With Preserved Ejection Fraction (HFPEF), Heart Failure With Mid-Range Ejection Fraction (HFmrEF)
- Keywords
- Heart failure prognosis, Biomarkers, NT-proBNP, Medical imaging, Echocardiography, Computed tomography, Epicardial adipose tissue, Global longitudinal strain
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 4,000 participants (actual)
- Lead sponsor
- Xinjiang Medical UniversityUniversity, hospital or other
- Study start
- 1 Jan 2012 (actual)
- Primary completion
- 31 Dec 2024 (actual)
- Study completion
- 31 Jan 2025 (actual)
- First posted
- 12 Jan 2026 (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.
This study aims to develop a better model to predict one-year risk of death in patients with heart failure. We will test whether combining information from routine blood tests (like NT-proBNP) and heart scans (measuring features like epicardial fat density) improves risk prediction compared to using either type of data alone.
This is a retrospective study using existing medical records of patients treated for chronic heart failure at Xinjiang Medical University First Affiliated Hospital between 2012 and 2024. No new patient contact or interventions are involved.
The goal is to enable more accurate, personalized risk assessment across different types of heart failure (HFrEF, HFmrEF, HFpEF).
Detailed description
Background and Rationale:
Accurate prognosis in heart failure (HF) remains challenging due to phenotypic heterogeneity across the spectrum of left ventricular ejection fraction (LVEF). While biomarkers like N-terminal pro-B-type natriuretic peptide (NT-proBNP) and imaging parameters like LVEF are standard prognostic tools, each has limitations. Emerging imaging parameters, such as epicardial adipose tissue (EAT) density (reflecting fat inflammation/fibrosis) and left ventricular global longitudinal strain (LVGLS), offer potential incremental prognostic value but are not yet integrated into routine clinical models. This study aims to systematically evaluate whether a multi-parameter model combining established blood biomarkers and advanced imaging metrics improves the prognostic stratification of patients with HFrEF, HFmrEF, and HFpEF compared to traditional approaches.
Detailed Methodology:
This is a single-center, retrospective cohort study. The study population consists of consecutive adult patients (≥18 years) with a confirmed diagnosis of chronic HF who had both qualifying blood biomarker assessment (NT-proBNP and/or high-sensitivity cardiac troponin) and cardiac imaging (transthoracic echocardiography and/or cardiac computed tomography) performed within a ±3-month window around an index encounter between January 1, 2012, and December 31, 2024, at Xinjiang Medical University First Affiliated Hospital.
Key data to be extracted from electronic health records include: 1) Clinical variables: demographics, comorbidities (e.g., ischemic etiology, diabetes, hypertension), medications, and NYHA class; 2) Blood biomarkers: NT-proBNP, hs-cTnT/I, hs-CRP, and renal function (eGFR); 3) Imaging parameters: LVEF, LVGLS, left atrial volume index (LAVI), E/e' ratio, and EAT volume/density (from CT, if available).
The primary endpoint is all-cause mortality at one year from the index date. Follow-up data will be obtained from hospital records.
Statistical Analysis Plan:
The incremental prognostic value will be assessed by constructing and comparing nested Cox proportional hazards models:
Model 1 (Base Clinical): Includes age, sex, BMI, ischemic etiology, diabetes, and hypertension.
Model 2 (Biomarker-Enhanced): Model 1 + NT-proBNP + eGFR. Model 3 (Imaging-Enhanced): Model 2 + key imaging parameters (e.g., EAT density or LVGLS).
Model performance will be compared using Harrell's C-statistic, the Akaike Information Criterion (AIC), Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). Pre-specified subgroup analyses will be conducted for HFrEF, HFmrEF, and HFpEF phenotypes. Multiple imputation will be used for variables with low rates of missing data (<10%).
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Heart Failure Cohort | – | –Adult patients (≥18 years) with a confirmed diagnosis of chronic heart failure who had both qualifying blood biomarker assessment and cardiac imaging performed within a specified window at the study center between 2012 and 2024. This is an observational cohort. No specific intervention is administered or withheld as part of the research protocol. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adults diagnosed with chronic heart failure at the study center between 2012 and 2024.
Key inclusion criteria (4 listed)
- Age ≥ 18 years.
- Confirmed diagnosis of chronic heart failure.
- Treated at the study center between January 1, 2012, and December 31, 2024.
- Availability of both qualifying blood biomarker test results (NT-proBNP and/or high-sensitivity cardiac troponin) and cardiac imaging (echocardiography and/or cardiac CT) performed within a ±3-month window around the index encounter.
Key exclusion criteria (3 listed)
- Heart failure primarily due to severe primary valvular disease, acute myocardial infarction, myocarditis, or pulmonary embolism.
- End-stage renal disease requiring dialysis.
- Clinical records or follow-up data are severely incomplete, precluding outcome assessment.
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
All-cause mortality
Time frame: 1 year
Occurrence of death from any cause within one year (365 days) from the index date. The index date is defined as the date of the first qualifying encounter that meets all inclusion criteria.
5 secondary outcomes
Phenotype-specific prognostic performance
Time frame: 1 year
Independent prognostic value of EAT density in HFpEF
Time frame: 1 year
Occurrence of HFimpEF
Time frame: Through study completion,up to 13 years.
Association between baseline NT-proBNP level and HFimpEF
Time frame: Through study completion, up to 13 years.
Association between baseline EAT density and HFimpEF
Time frame: Through study completion, up to 13 years.
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 27 Jan 2026.
- 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.
Xiang Xie, PhD study chair
First Affiliated Hospital of Xinjiang Medical University
Questions about this trial
What is this clinical trial studying?
An observational study of Heart Failure and Heart Failure, Systolic, run by Xinjiang Medical University.
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 4 inclusion and 3 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 27 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
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?
All-cause mortality (time frame: 1 year). 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 27 Jan 2026; AzTrials last refreshed its copy on 6 Nov 2026.