Growth differentiation factor-15 combined with N-terminal prohormone of brain natriuretic peptide increase 1-year prognosis prediction value for patients with acute heart failure: a prospective cohort study

Heart failure (HF) is a life-threatening condition that affects millions worldwide, with acute heart failure (AHF)—a sudden worsening of symptoms like shortness of breath or swelling—carrying a high risk of death and hospital readmission. For doctors, predicting which AHF patients are most at risk is critical to delivering timely, life-saving care. But no single blood test (biomarker) is perfect at identifying these high-risk patients. Two biomarkers—one well-known, one newer—have shown promise, but how they work together wasn’t clear—until now.

The Biomarkers: NT-proBNP and GDF-15

NT-proBNP is a household name in cardiology. It’s released by the heart’s ventricles when they’re stretched from fluid or pressure overload (a hallmark of HF). Doctors use it daily to diagnose AHF and predict who will die or need to be readmitted.

GDF-15 is a newer player. It’s a “stress protein” released by cells during inflammation, injury, or low oxygen (hypoxia). It’s linked to cardiac remodeling—the structural changes in the heart (like thickening or enlargement) that make HF worse. While GDF-15 has been studied in chronic HF, researchers wanted to know: How does it compare to NT-proBNP in predicting 1-year death in AHF? And does combining the two markers make predictions better?

The Study: Following AHF Patients for 1 Year

To answer these questions, a team from the First Affiliated Hospital of Nanjing Medical University in China conducted a prospective cohort study—meaning they enrolled patients and followed them forward in time. Between 2012 and 2016, they recruited 260 adults hospitalized for AHF (either new-onset or a sudden flare-up of chronic HF).

Within 24 hours of admission, doctors collected blood samples to measure NT-proBNP (using a standard test) and GDF-15 (stored at -40°C until analysis). They also recorded patients’ medical histories, symptoms (using the New York Heart Association [NYHA] class to rate fatigue/breathlessness), and test results (like sodium levels, which drop in severe AHF).

The primary goal was to see which patients died from any cause within 1 year. Patients were tracked via clinic visits and phone calls every 3 months.

The Results: Both Markers Work—But Together They’re Better

By the end of the 1-year follow-up, 46 patients (17.7%) had died. The team compared survivors and non-survivors and found two clear trends:

Higher biomarker levels mean higher risk: Non-survivors had significantly higher NT-proBNP (3550 ng/L vs. 1883 ng/L in survivors) and GDF-15 (5055 ng/L vs. 2272 ng/L) levels at admission.
GDF-15 is just as good as NT-proBNP: To measure how well each biomarker predicts death, the team used receiver-operator characteristic (ROC) curves—a tool that assigns an “area under the curve (AUC)” score (0 to 1, where 1 is perfect prediction). GDF-15 had an AUC of 0.707 (meaning it correctly identified risk in 71% of cases), while NT-proBNP scored 0.682 (68% accuracy). The difference between the two was not statistically significant—so GDF-15 was just as good as the “gold standard” NT-proBNP.

But the real breakthrough came when the team combined both markers. Using optimal cut-off values (NT-proBNP >1978 ng/L and GDF-15 >4526 ng/L), the combined score had an AUC of 0.743—meaning it correctly predicted death in 74% of cases. That’s better than either marker alone.

Who Is at Highest Risk?

The team split patients into groups based on whether their biomarker levels were above or below the cut-offs. The results were stark:

Patients with high GDF-15 (above 4526 ng/L) had a 38.2% chance of dying within 1 year—more than three times higher than those with normal GDF-15 (10.4%).
Patients with high NT-proBNP (above 1978 ng/L) had a 25.5% death risk—nearly three times higher than those with normal NT-proBNP (8.9%).
Patients with both markers high had the worst outcomes: 46% died within a year, compared to just 11% of patients with normal or only one high marker.

Even after adjusting for other risk factors (like diabetes, low sodium, or kidney function), having both markers high remained a strong, independent predictor of death—these patients were 5.6 times more likely to die than those with normal levels.

Why Combining Markers Matters

NT-proBNP and GDF-15 reflect different aspects of AHF:

NT-proBNP signals fluid or pressure overload in the heart.
GDF-15 signals inflammation, cell stress, or remodeling—changes in the heart’s structure that make HF worse.

By combining them, doctors get a fuller picture of a patient’s risk. For example, a patient with high NT-proBNP (fluid overload) but normal GDF-15 (no severe inflammation) might be less at risk than someone with both markers high. This “double check” helps doctors spot high-risk patients earlier—so they can provide more aggressive care, like closer monitoring or adjusted medications.

Limitations to Consider

The study has a few caveats:

Small, single-center cohort: The results come from 260 patients at one hospital. Larger, multi-center studies are needed to confirm the findings in more diverse groups.
No long-term follow-up: The study only tracked patients for 1 year—we don’t know how the markers perform over longer periods.
Unknown mechanisms: The team didn’t explore why combining markers works at the molecular level (e.g., how GDF-15 and NT-proBNP interact in the body).

What This Means for Patients and Doctors

For doctors, the takeaway is simple: using both GDF-15 and NT-proBNP can improve risk prediction in AHF. The study provides clear cut-off values (1978 ng/L for NT-proBNP, 4526 ng/L for GDF-15) to help identify high-risk patients—those who need urgent, personalized care.

For patients, this research is a step toward more precise medicine. By better predicting who is most at risk, doctors can intervene earlier to prevent death and improve quality of life.

This study was published in the Chinese Medical Journal in 2019 by researchers from the First Affiliated Hospital of Nanjing Medical University (Nanjing, China) and the Second Affiliated Hospital of Xuzhou Medical College (Xuzhou, China).

doi.org/10.1097/CM9.0000000000000449

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