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European Heart Journal Advance Access originally published online on May 31, 2007
European Heart Journal 2007 28(15):1827-1834; doi:10.1093/eurheartj/ehm192
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© The European Society of Cardiology 2007. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Predictors and treatment response with cardiac resynchronization therapy in patients with heart failure characterized by dyssynchrony: a pre-defined analysis from the CARE-HF trial

Matthew Richardson1, Nick Freemantle1,*, Melanie J. Calvert1, John G.F. Cleland2, Luigi Tavazzi on behalf of the CARE-HF Study Steering Committee and Investigators3

1 Health Care Evaluation Group, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
2 Department of Cardiology, Castle Hill Hospital, Kingston-upon-Hull, UK
3 Istituto di Ricovero e Cura a Carattere Scientifico, Policlinico San Matteo, Pavia, Italy

Received 9 May 2006; revised 20 February 2007; accepted 13 April 2007; online publish-ahead-of-print 31 May 2007.

* Corresponding author. Tel: +44 121 414 7943; fax: +44 121 414 3353. E-mail address: n.freemantle{at}bham.ac.uk

See page 1790 for the editorial comment on this article (doi:10.1093/eurheartj/ehm254)


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix: calculation of risk...
 Acknowledgements
 References
 
Aims: The cardiac resynchronization therapy in heart failure trial (CARE-HF) demonstrated that cardiac resynchronization therapy (CRT) reduces morbidity and mortality in patients with heart failure and cardiac dyssynchrony. The aim of this study was to develop a prognostic model to evaluate the relationship between prospectively defined patient characteristics and treatment on the trial primary outcome of death from any cause or unplanned hospitalization for a major cardiovascular event.

Methods and results: A total of 813 patients were enrolled in the CARE-HF study and were followed for a mean of 29.4 months. A Cox Proportional Hazards Model was fitted to identify predictors of the primary outcome and any predictors that modified the effect of CRT. Ischaemic aetiology, more severe mitral regurgitation and increased N-terminal pro-brain natriuretic peptide, were associated with an increased risk of death or unplanned cardiovascular hospitalization irrespective of cardiac resynchronization [Hazard ratio (HR) 1.89, 95% CI 1.45–2.46, HR 1.71, 95% CI 1.38–2.12 and HR 1.31, 95% CI 1.17–1.47, respectively] and increasing systolic blood pressure with a decreasing risk of an event (HR 0.99, 95% CI 0.98–1.00). The benefits of cardiac resynchronization were modified by systolic blood pressure and interventricular mechanical delay (IVMD). Patients with increasing systolic blood pressure appear to receive reduced benefit from CRT (HR 1.02, 95% CI 1.00–1.03), whereas those patients with more severe IVMD appear to benefit more from treatment (HR 0.99, 95% CI 0.98–1.00).

Conclusion: Patients with echocardiographic evidence of more severe cardiac dyssynchrony and low systolic blood pressure obtain greater benefit from CRT, although benefits were substantial across the range of subjects included in the trial.

Key Words: Cardiac resynchronization therapy • Prognostic model


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Conclusion
 Appendix: calculation of risk...
 Acknowledgements
 References
 
Heart failure is a common and serious condition with a complex and varied pathophysiology.1 A substantial minority of patients with heart failure due to left ventricular (LV) systolic dysfunction have prolonged QRS and amongst these patients there is a high prevalence of cardiac dyssynchrony, which leads to a decline in cardiac efficiency through diverse mechanisms.2–4 For patients with heart failure due to cardiac dyssynchrony who have persistent moderate or severe symptoms despite standard pharmacological therapy, cardiac resynchronization therapy (CRT) improves cardiac function leading to an improvement in well-being and a reduction in morbidity and mortality.5–8

The cardiac resynchronization therapy in heart failure trial (CARE-HF) is one of the largest randomized studies of CRT, has a longer duration of follow-up than any other, and has a robust primary clinical endpoint.7 These attributes make it a valuable resource for the investigation of those factors that predict the likelihood that a patient will or will not respond to CRT. The aim of this analysis was to evaluate the relationship between prospectively defined clinical, echocardiographic and neurohormonal variables, collected at baseline during the CARE-HF trial, on overall outcome in all patients and on the response to CRT.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Conclusion
 Appendix: calculation of risk...
 Acknowledgements
 References
 
Data source
We used individual patient data collected during the CARE-HF trial. The design and results of the CARE-HF study have been reported previously.7,9 In brief, the CARE-HF trial enrolled 813 patients recruited from 82 centres across Europe. Eligible patients were at least 18 years of age, had evidence of heart failure for at least 6 weeks, and were in New York Heart Association class III or IV despite receipt of standard pharmacologic therapy, with a LV ejection fraction (EF) of < 35%, a LV end-diastolic dimension of ≥ 30 mm (indexed to height), and a QRS interval of > 120 ms on the electrocardiogram. Patients with a QRS interval of 120–149 ms were required to meet two of three additional criteria for dyssynchrony: an aortic pre-ejection delay of more than 140 ms, an interventricular mechanical delay (IVMD) of > 40 ms, or delayed activation of the posterolateral LV wall. The IVMD was calculated as the time difference between the onset of forward flow in the LV (APET) and RV (PPET) outflow tracts: IVMD = APET – PPET.10 A total of 409 patients were randomized to CRT and medical therapy, whereas 404 received medical therapy alone. The primary outcome was the time to death from any cause or an unplanned hospitalization for a major cardiovascular event. Patients were followed up for a mean of 29.4 months.

Statistical analysis
Model specification and validity
A number of potentially important clinical, echocardiographic, and neurohormonal variables collected at baseline were specified a priori for evaluation in a prognostic model. These were mitral regurgitation (MR), end-systolic volume index, aetiology (ischaemic and non-ischaemic disease), EF, use of beta-blockers, age, QRS width (QRS), supine systolic blood pressure (SBP), glomerular filtration rate, N-terminal pro-brain natriuretic peptide, as determined by Roche Assay (NT-pro-BNP), and IVMD.11–13 MR was defined as area of colour flow Doppler regurgitant jet divided by area of left atrium in systole, both in square centimetre.

We fitted Cox Proportional Hazards models to identify predictors of risk of death from any cause or an unplanned hospitalization for a major cardiovascular event (main effects) and to identify any predictors modified by cardiac resynchronization.14,15

Our modelling strategy was based upon the approach suggested by Harrell that attempts to avoid the problem of over-fitting the model.16–19 Over-fitting may occur when P, the total number of predictor degrees of freedom used to fit the model, is large in comparison to N, where N is the number of uncensored event times, or for a binary outcome the number of patients in the smaller (less frequent) primary outcome category. In this study, there where 383 patients with uncensored event times. P can be interpreted as the number of regression coefficients estimated in fitting a model, for this study P = 9. If N/P < 10, this may indicate over fitting, we have 383/9 > 10, this does not indicate over fitting is present. In order to evaluate whether any of the variables had a non-linear relationship with outcome, we assessed transformations of each variable using the natural logarithm and cubic spline.20–24 The Akaike Information Criteria were used to determine the most appropriate transformation.25 The validity of any transformations was further assessed by examining plots of the cumulative Martingale residuals vs. the transformed variable.26,27 The proportional hazards assumption was also assessed. Statistically significant variables identified from univariate analyses were combined in a single Cox Proportional Hazard model using a forward stepwise selection to obtain the final model, the entry criteria for the forward selection procedure was 0.05, meaning a variable has to be significant at the 0.05 level before it can enter the model. All analyses were performed in SAS v 9.1 using the PHREG procedure and the RCS macro.28 The RCS macro28 was used to fit cubic splines with four knots for the continuous variables, with the knot positions specified PHREG, was then used tp genearate a model from which it was possible to determine whether the cubic spline was an appropriate transformation for the particular variable concerned. All analyses were undertaken according to the intention to treat principle.29

To validate the final model two further steps were taken. First, a bootstrap revalidation process was used to estimate the degree of over-fitting from the model fitting process.17 The design library in the statistical package R was used to undertake this validation.30 Second, we used multiple imputation using the SAS procedures MI, and MIANALYSE, to examine the effect of missing data on the final model.31

Estimation of absolute risk
Estimates of the survival function S(t) and the absolute risk (1–S(t)) were produced using the SAS procedure PHREG. Estimation of absolute risk using real patient data provides clinically relevant estimates of risk. Risk estimates were derived on the basis of the maximum follow-up in the CARE-HF, which was 44.7 months, although including censorship patients were only followed for 29.4 months. Thus predicted event rates are considerably higher than those actually observed in the trial.

This work is the first prognostic model derived from a morbidity/mortality trial of CRT, and so the principal aim of the analysis was to identify potential treatment modifiers using robust methods and not to develop a definitive prognostic tool that will require further validation using new data from an appropriate large randomized trial or epidemiological study.

Calculation of risk scores
The coefficients of the final model can be used to generate a risk score for an individual patient.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Conclusion
 Appendix: calculation of risk...
 Acknowledgements
 References
 
The baseline characteristics of patients from the CARE-HF trial are shown in Table 1.


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  		Table 1 Baseline characteristics of the patients

 
These data are consistent with the patients having, on average, moderate to severe LV systolic dysfunction, dilatation and dyssynchrony with a low arterial pressure, and renal dysfunction. About 40% of patients had ischaemic heart disease.

Univariate analyses were used to identify those variables that were significant predictors of outcome (irrespective of treatment allocation) and those variables shown to predict response to CRT (indicated by the CRT * variable interaction term) (Table 2). The most appropriate transformation of each variable is indicated (for example a logarithmic transformation led to the best model fit for MR). The remaining variables (beta-blocker use and QRS width) were not significantly associated with outcome and did not predict response to CRT.


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  		Table 2 Potential predictors of risk: results of univariate analyses

 
Those variables identified to be significantly (P < 0.05) associated with the primary composite outcome, time to death from any cause, or an unplanned hospitalization for a major cardiovascular event were entered in a multivariate Cox Proportional Hazards model (Table 3). Ischeamic aetiology, more severe MR, and increased NT-pro-BNP were all independent predictors of an increased risk of death or unplanned cardiovascular hospitalization irrespective of cardiac resynchronization [Hazard ratio (HR) 1.89, 95% CI 1.45–2.46, HR 1.71, 95% CI 1.38–2.12 and HR 1.31, 95% CI 1.17–1.47, respectively] and increasing SBP with a decreasing risk of an event (HR 0.99, 95% CI 0.98–1.00) (Figure 1A–E). Note, in Figure 1A, 117 mmHg is the median value of SBP for the combined data, i.e. the median for the treatment and control groups combined.


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  		Table 3 Predictors of outcome and response to CRT (Cox Proportional Hazards analysis)

 

Figure 1
Figure 1
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  		Figure 1 (A) Time to first primary event by systolic blood pressure. (B) Time to first primary event by interventricular mechanical delay. (C) Time to first primary event by aetiology (ischaemia). (D) Time to first primary event by mitral regurgitation. (E) Time to first primary event by N-terminal pro-brain natriuretic peptide (pg/ml).

 
Only two variables, IVMD and SBP predicted response to CRT, with modest statistical precision (Figures 2 and 3). Patients with increasing SBP appear to receive reduced benefit from CRT (HR 1.02, 95% CI 1.00–1.03), whereas those patients with more severe IVMD appear to benefit more from treatment (HR 0.99, 95% CI 0.98–1.00).


Figure 2
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  		Figure 2 Time to first primary event by systolic blood pressure (mmHg) and cardiac resynchronization therapy.

 

Figure 3
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  		Figure 3 Time to first primary event by interventricular mechanical delay (ms) and cardiac resynchronization therapy.

 
Absolute risk estimation
The effect of SBP and IVMD on the absolute risk of a patient experiencing death from any cause or an unplanned hospitalization for a major cardiovascular event in the presence and absence of CRT or ischaemic heart disease are shown in Tables 4 and 5, respectively. In both examples, mitral regurgitation, NT-pro-BNP, and IVMD were held constant at the median values (see Table 1).


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  		Table 4 Estimated absolute risk of an event for patients with different systolic blood pressures (117–130 mmHg) with and without cardiac resynchronisation therapy and in the presence and absence of ischaemic heart disease

 

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  		Table 5 Estimated absolute risk of an event for patients with varying interventricular mechanical delay (49–66 ms) with and without cardiac resynchronisation therapy and in the presence and absence of ischaemia

 
The estimated absolute risk of experiencing death or an unplanned hospitalization for cardiovascular cause for a non-ischaemic patient with a SBP of 117 mmHg (the median for the whole dataset) on medical therapy (but not CRT) was 0.97 over the entire trial duration (Table 4). Treatment of such a patient with CRT reduces the estimated absolute risk to 0.41. The presence of ischaemia led to an increase in absolute risk to 0.63 and 0.99 in the presence and absence of CRT, respectively. The absolute risk of experiencing event increased with increasing SBP, this is due to the fact that although SBP alone is associated with a decrease in risk, the statistical interaction between SBP and CRT is associated with a small increase in risk.

The absolute risk for a patient with IVMD of 49 ms vs. a patient with IVMD of 66 ms in the presence and absence of ischaemia and CRT is shown in Table 5. Increasing the IVMD from 49 to 66 ms leads to reductions in the absolute risk of experiencing an event.

Risk score
A quick and convenient way of estimating risk for an individual patient is to substitute patient characteristics in the Cox model. An example showing how the risk score is calculated is given in the appendix (Figures 4 and 5).


Figure 4
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  		Figure 4 Risk score vs. probability of primary event at end of follow-up period.

 

Figure 5
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  		Figure 5 Histogram of risk score for patients at end of follow-up period.

 
Model validation and multiple imputation
The bootstrap validation of the final fitted model indicated only modest over-fitting, around 3.4%. However the model was somewhat sensitive to multiple imputation, where when fitting the final model, the interaction between CRT and SBP was no longer statistically significantly predictive. All other variables remained in the model.


   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Conclusion
 Appendix: calculation of risk...
 Acknowledgements
 References
 
The CARE-HF trial demonstrated that CRT exerts a substantial reduction in morbidity and mortality with little evidence of heterogeneity in pre-defined subgroups.7 This more detailed analysis provides evidence that IVMD and to a lesser extent SBP predict patients' response to CRT. These finding must be treated with a degree of caution as the model is exploratory and the interactions between CRT and either IVMD or SBP were not particularly strong. However, the observed interaction between IVMD and the effects of CRT are consistent with the view that IVMD is a more precise physiological marker of cardiac dyssynchrony, the problem that CRT is designed to treat, than any other variable analysed. IVMD could therefore potentially be used as an inclusion criterion in future randomized controlled trials examining the effects of CRT in patient populations not included in CARE-HF, such as patients with less severe symptoms or with shorter QRS intervals. Whether IVMD should now be used in preference or in addition to QRS duration to identify whether a patient should receive CRT is a matter for the individual clinician to decide and for future research. It is of great importance to note that IVMD is the best predictor of response to CRT in a population having large volumes, low EF, and broad QRS. We cannot state that IVMD is a better predictor of response to CRT in other populations.32

The estimated absolute risk of experiencing a primary outcome event may seem surprisingly high in some cases (absolute risk of 0.99 as shown in Tables 4 and 5). However, patients recruited to the study had severe heart failure (NYHA class III–IV) and therefore had an inherently high risk of experiencing the primary outcome during the study follow-up (which ranged from 18 to 44.7 months). The hazard functions from the model are based upon prediction of event rates across the maximum follow-up from the study, which had reached 55% in the control group in mean 29.4 months of follow-up. In order to estimate the absolute risk of an event with changing SBP and IVMD, the remaining clinical predictors were held constant. It is important to note that since these are also strong clinical predictors of outcome changing these values from the median has a large impact on the estimates of absolute risk. For example, in a non-ischaemic patient not receiving CRT with a SBP of 117 mmHg, use of lower interquartile range values for mitral regurgitation and NT-pro-BNP results in an estimate of absolute risk of approximately 0.84, an absolute reduction of around 13%.

The plasma concentration of NT-pro-BNP was a strong predictor of clinical outcome. Other competing measures of ventricular dysfunction were eliminated from the multivariate model. CRT reduces the severity of mitral regurgitation and plasma concentrations of NT-pro-BNP, and the two phenomena may be related. Any interaction between mitral regurgitation and NT-pro-BNP may be weak due to the occurrence of mitral regurgitation being related to the mechanical consequences of pacing, whereas release of NT-pro-BNP is associated with regional ventricular load and its later biological consequences (ventricular remodelling). It is perhaps not surprising that what they indicate differs on outcome. Despite this interaction between mitral regurgitation and NT-pro-BNP, which might be expected to eliminate one or other from the prognostic model, each provided independent prognostic information. The only other factor that provided important prognostic information was the aetiology of LV dysfunction. Patients with IHD did worse. This may be due to coronary events having an important additional effect on outcome, superimposed on the background severity of ventricular dysfunction as measured by NT-pro-BNP. Therapy, apart from CRT, did not predict outcome but this could reflect the high uptake of treatment with beta-blockers at baseline and changes during the course of the study.

There are a number of limitations to this analysis. In about 25% of patients, the core laboratory did not obtain a valid measure of mitral regurgitation. However, there were few missing data for other variables. Multiple imputations did indicate that the model was somewhat sensitive to missing data, with the interaction between CRT and SBP no longer featuring in the final model when the imputed datasets were used.

We analysed data according to the intention to treat principle.29 Over 95% of patients assigned to CRT received a device before they reached a primary endpoint but resynchronization will have been sub-optimal either due to poor lead placement or failure to obtain adequate capture in some patients. Only 5% of patients received a CRT device before they reached a primary outcome event in the control group. These factors would be expected to reduce the strength of the interaction between baseline IVMD and the effect of CRT. Validation of the model using an independent data set would be valuable. The fact that the primary outcome is a composite measure may also be considered a limitation, but the rate of mortality in the trial was insufficient for us to examine the potential influence of the variables under investigation.


   Conclusion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
Appendix: calculation of risk...
 Acknowledgements
 References
 
CRT has substantial clinical benefits in a broad range of patients with evidence of cardiac dyssynchrony, poor LV systolic function, and persistent symptoms despite pharmacological therapy. This analysis provides further evidence that a measure of cardiac dyssynchrony rather than the QRS interval on the ECG is currently the best marker of dyssynchrony. However, the predicted benefits from the model indicate that CRT appears worthwhile across the range of patients included in the CARE-HF trial.


   Appendix: calculation of risk score for patients within the CARE-HF trial
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix: calculation of risk...
Acknowledgements
 References
 
Methods
Risk score for patient with mitral regurgitation of 38.1, NT-pro-BNP of 2858 pg/ml, systolic blood pressure of 100 mmHg, IVMD of 13.8 ms, ischaemia, and in receipt of CRT would be calculated as follows:

Risk score = 0.5379 loge(MR) + 0.2717 loge(NT-pro-BNP) – 0.0087(SBP) + 0.0010(IVMD) + 0.6340(ischaemic) + 0.0172 (CRT * SBP) – 0.0131(CRT * IVMD) – 1.8740(CRT).

Result
Risk score = 0.5379 loge(38.1) + 0.2717 loge(2858) – 0.0087 (100) + 0.0010(13.8) + 0.6340(ischaemic) + 0.0172 (1 * 100) – 0.0131(1 * 13.8) – 1.8740(1) = 2.93.


   Acknowledgements
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix: calculation of risk...
 Acknowledgements
References
 
The authors would like to thank the CARE-HF Study team for their work on the CARE-HF trial.

Conflict of interest: N.F. has received funding for research, travel, and consulting from a number of companies manufacturing treatments for heart failure, including Medtronic Inc. M.C. has received funding for research and travel from companies which manufacture devices and drugs for the treatment of heart failure, including Medtronic Inc. J.C. has received research grant support and speakers honoraria from Medtronic. J.C. has also received speakers honoraria from Biotronik and Guidant (now Boston Scientific). L.T. has received research grant support and speakers honoraria from Medtronic.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix: calculation of risk...
 Acknowledgements
 References
 

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Predicting the Long-Term Effects of Cardiac Resynchronization Therapy on Mortality From Baseline Variables and the Early Response: A Report From the CARE-HF (Cardiac Resynchronization in Heart Failure) Trial
J. Am. Coll. Cardiol., August 5, 2008; 52(6): 438 - 445.
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J. G F Cleland, A. Tageldien, N. Maarouf, and N. Hobson
Patients with heart failure who require an implantable defibrillator should have cardiac resynchronisation routinely
Heart, August 1, 2008; 94(8): 963 - 966.
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S. Buck, M. Rienstra, A. H. Maass, W. Nieuwland, D. J. Van Veldhuisen, and I. C. Van Gelder
Cardiac resynchronization therapy in patients with heart failure and atrial fibrillation: importance of new-onset atrial fibrillation and total atrial conduction time
Europace, May 1, 2008; 10(5): 558 - 565.
[Abstract] [Full Text] [PDF]

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L. J. Anderson, C. Miyazaki, G. R. Sutherland, and J. K. Oh
Patient Selection and Echocardiographic Assessment of Dyssynchrony in Cardiac Resynchronization Therapy
Circulation, April 15, 2008; 117(15): 2009 - 2023.
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M. Stockburger, S. Fateh-Moghadam, A. Nitardy, O. Celebi, A. Krebs, D. Habedank, and R. Dietz
Baseline Doppler parameters are useful predictors of chronic left ventricular reduction in size by cardiac resynchronization therapy
Europace, January 1, 2008; 10(1): 69 - 74.
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R. N. Doughty, K. Poppe, and J. Stewart
Predicting outcome in severe heart failure. Who will benefit from device therapy (CRT)?
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