A comprehensive study of the incremental prognostic value of novel biomarkers in PARADIGM-HF (Bio-PREDICT-HF)
Bibliographic record
Abstract
Abstract Background Although multiple novel biomarkers have individually been shown to predict outcomes in patients with HFrEF, the value of these over and above conventional clinical and laboratory variables, plus natriuretic peptides, is uncertain. Purpose To test the incremental predictive value of 11 novel biomarkers added to a recent prognostic model 1 (PREDICT-HF) derived in PARADIGM-HF and validated in ATMOSPHERE and the Swedish heart failure registry. The PREDICT-HF model includes clinical variables, standard laboratory variables, and BNP or NT-proBNP. Methods 1559 participants enrolled in PARADIGM-HF had all 11 biomarkers of interest measured. These reflected different pathophysiological pathways: (i) myocyte injury (high sensitivity cardiac troponin T), (ii) cardiac remodelling and inflammation (growth stimulation expressed gene 2, growth differentiation factor-15 and galectin-3), (iii) extracellular matrix remodelling (matrix metalloproteinase-2, matrix metalloproteinase-9, tissue inhibitor of metalloproteinase-1), (iv) neurohormonal pathways (aldosterone) and (v) renal dysfunction and injury (cystatin C, kidney injury molecule-1 and urinary albumin to creatinine ratio). The incremental prognostic value of these biomarkers was evaluated using Harrell's C statistic. Results The mean age of participants studied was 67.3 (SD 9.9) years, 1254 (80%) were men and 1103 (71%) were in NYHA class II. During a median follow-up of 31 months, 197 patients died and 300 experienced the primary composite outcome (cardiovascular death or heart failure hospitalization). When each candidate biomarker (log unit) was added individually to the PREDICT-HF base model, GDF-15, ST2, TIMP1, cystatin C, hsTnT and UACR were independent predictors of all-cause mortality (Table 1). GDF-15, TIMP1, hs-TnT and cystatin C consistently increased the risk of both all-cause mortality and the primary outcome. Individuals who had all 4 biomarkers elevated (compared to none elevated) had the highest risk: HR for all-cause mortality 3.65 (2.01–6.64), p<0.0001. Adding these 4 biomarkers to the baseline PREDICT HF model improved the C statistic for all-cause mortality from 0.726 to 0.745. Conclusion Several novel biomarkers provide meaningful additional prognostic information in patients with HFrEF. A multimarker approach incorporating biomarkers reflecting different pathophysiological pathways added most information. This approach may be useful in refining risk and targeting treatment. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): The PARADIGM-HF trial was funded by Novartis.J.J.V.M is supported by a British Heart Foundation Centre of Excellence Grant
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".