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Be part of the knowledge.™New accurate prediction models for heart failure hospitalization and mortality
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Background
The accurate risk prediction of mortality and hospitalizations in heart failure (HF) patients is important for the management of these patients [1,2]. However, existing risk prediction models perform moderately and only one third of them have been validated in a separate cohort [3-5].
In this large European BIOSTAT-CHF study, new risk prediction models of all-cause mortality and hospitalizations in HF patients were developed and validated. The index cohort consisted of 2516 HF patients from 69 centers in 11 European countries; 26% died, 24% was hospitalized at least once for worsening HF and 41% died or had a first event of HF hospitalization. The external validation cohort consisted of 1738 comparable patients from 6 centers in Scotland; 34% died, 35% were hospitalized for worsening HF and 51% died or had a first event of HF hospitalization. Both cohorts had a median follow-up of 21 months.
Main results
Final full prediction models:
- The all-cause mortality model consisted of 16 variables with a raw c-statistic of 0.73 (0.73 after correction for optimism).
- The HF hospitalization model incorporated 10 variables with a raw c-statistic of 0.69 (0.68 after correction for optimism).
- The composite model for all-cause mortality and HF hospitalization consisted of 15 variables with a raw c-statistic of 0.71 (0.70 corrected for optimism).
Final compact prediction models (strongest variables):
- All-cause mortality: more advanced age, higher blood urea nitrogen (BUN) and NT-proBNP, lower hemoglobin and failure to prescribe a beta-blocker predicted a higher all-cause mortality with a raw c-statistic of 0.69 (0.69 after correction for optimism).
- HF hospitalization: more advanced age, HF hospitalization in the year before inclusion, presence of edema, lower systolic blood pressure (SBP) and lower eGFR predicted an increased risk of HF hospitalization with a raw c-statistic of 0.67 and 0.66 after correcting for optimism.
- Combined endpoint: more advanced age, HF hospitalization in the year before inclusion, presence of edema, higher NT-proBNP, lower SBP, hemoglobin, HDL-C and serum sodium concentration, as well as failure to prescribe a beta-blocker, predicted the composite outcome with a raw and optimism corrected c-statistic value of 0.69.
Risk score
The risk score included the following cut-off points for optimal classification: NT-proBNP >4000 pg/mL, BUN >11 mmol/L, HDL<1.05 mmol/L, age >70 years, sodium <140 mmol/L, hemoglobin <12 g/dL, eGFR (CKD-EPI formula) <40 mL/min and SBP <140 mmHg.
Validation
In the validation cohort, the c-statistic for the full models were 0.73, 0.64 and 0.68 for mortality, HF hospitalization and their composite, respectively, and 0.72, 0.61 and 0.67 for the compact models.
Conclusion
In a large European study, new prediction models for all-cause mortality and HF hospitalization were developed and validated, which perform better compared with existing prediction scores and use information that is usually readily available in routine clinical setting. Variables in the all-cause mortality prediction models were different from those in the HF hospitalization models. Based on these findings, a simplified risk score for use in clinical practice was also developed (see link below).
References
1. Dickstein K, Cohen-Solal A, Filippatos G, et al, ESC Committee for Practice Guidelines (CPG). ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: The Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure 2008 of the European Society of Cardiology. Developed in collaboration with the Heart. Failure Association of the ESC (HFA) and endorsed by the European Society of Intensive Care Medicine (ESICM). Eur Heart J 2008;29:2388–2442.
2. McMurray JJ, Adamopoulos S, Anker SD, et al, ESC Committee for Practice Guidelines. ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure 2012: the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure 2012 of the European Society of Cardiology. Developed in collaboration with the Heart. Failure Association (AHA) of the ESC. Eur J Heart Fail 2012;14:803–869.
3. Ouwerkerk W, Voors AA, Zwinderman AH. Factors Influencing the predictive power of models for predicting mortality and/or heart failure hospitalization in patients with heart failure. JACC Heart Fail 2014;2:429–436.
4. Ross JS, Mulvey GK, Stauffer B, et al. Statistical models and patient predictors of readmission for heart failure. Arch Intern Med 2008;168:1371–1386.
5. Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306:1688–1698.
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