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European Journal of Heart Failure 2001 3(3):365-371; doi:10.1016/S1388-9842(01)00132-5
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© 2001 European Society of Cardiology

A cost-effectiveness analysis of bisoprolol for heart failure

Susan Varney*

Imperial College School of Medicine, NHLI-Royal Brompton Campus Dovehouse Street, SW3 6LY, UK


   Abstract
Top
 Notes
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 
Aims: This study considers the cost-effectiveness of bisoprolol in heart failure patients as an adjunctive therapy to usual treatment.

Methods and results: A cost-effectiveness model was constructed using data available from the CIBIS I & II trials and other secondary sources. Differences in patient survival rates were calculated for bisoprolol (n = 1327) and placebo groups (n = 1320) extrapolating data over a 5-year period, under limited and extended benefits scenarios to calculate life years gained (LYG). Hospitalisation rates were calculated using data from both CIBIS trials. Costs were considered under two different patient management protocols for treatment initiation — shared care by outpatient clinics and GPs and initiation by a nurse working in the community. Discounted LYG were calculated to be 0.228 under the limited benefits scenario and 0.368 under the extended benefits scenario. Under the extended benefits scenario shared care resulted in a cost of £268 per LYG or £412 per LYG for community initiation. Under the limited benefits scenario the costs were a £135 saving and £69, respectively.

Conclusion: This analysis has shown bisoprolol to be an economically attractive therapy in comparison with other treatments. It is hoped that its adoption by clinicians will be rapid, despite the labour intensive and time consuming up-titration process involved in its initiation.

Key Words: Cost-effective • Beta-blockers • Heart failure • Bisoprolol

Received August 14, 2000; Revised December 28, 2000; Accepted January 17, 2001


   1. Introduction
Top
 Notes
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 
The incidence and prevalence of chronic heart failure is increasing despite advances in treatment and therefore its cost to the NHS is considerable. Cost of illness studies have in general suggested that approximately 1–2% of the total health care budget in developed countries is expended on heart failure [1]. A UK study found that 66% of this total was accounted for by hospitalisations, therefore it would seem that any treatment which can be shown to reduce hospital admissions may potentially provide large financial savings [2].

Beta-blockers are a relatively new treatment for heart failure and their efficacy in terms of mortality and morbidity has recently been proven in a number of large randomised trials, notably CIBIS II and MERIT-HF [3,4]. In CIBIS II, there were fewer all-cause hospital admissions in the bisoprolol group (33 vs. 39%), and admissions for worsening heart failure were significantly less.

The addition of large trials such as these to the previous evidence seems to have definitively proven the benefit of beta-blockers in heart failure (approx. 15 000 patients have now been enrolled in randomised trials) and several economic evaluations have been conducted using the data available from published clinical trials. These evaluations have been completed in Germany [5], France [6] and the US [7] as well as the UK [8] all with slightly varying results. Short-term studies based on the actual duration of the clinical trials seem to have either shown savings or been cost neutral. The one longer term US study that modelled data over a 10-year period has found what appears to be an acceptable incremental cost-effectiveness ratio in comparison with other interventions. A preliminary economic analysis based on CIBIS II has also been previously reported, however, this did not include the cost of drug initiation and only considered hospitalisations due to worsening heart failure, not other causes [9]. Therefore, there has not as yet been any full analyses based on the newer trials.

We aimed to conduct a cost-effectiveness analysis on beta-blocker therapy in heart failure for the UK, identifying how sensitive the resultant ratio was to changes in the major components of the analysis and additionally, to consider how these cost-effectiveness results compare with those of other interventions.


   2. Methods
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 5. Conclusions
 References
 
The CIBIS II trial was selected as a suitable trial for considering the cost-effectiveness of beta-blockers for a number of reasons. Firstly, it is one of the most recent beta-blocker trials to be reported, secondly it reports both survival and morbidity data and thirdly it is a European study with longer follow-up than the US Carvedilol studies [10] (only a mean of 6.5 months follow-up). In CIBIS II, treatment effects did not differ between participating countries.

The CIBIS II results did not report any quality of life data or even improvements in NYHA classification, so it was not possible to undertake a cost-utility analysis by calculating cost per quality adjusted life year gained (QALY). The cost-effectiveness of bisoprolol was therefore defined as the ratio of the sum of changes in the cost profile associated with bisoprolol, to the additional years of life gained due to the adjunctive treatment. A model was developed to calculate the average discounted costs and the additional life years gained (LYG). The incremental cost-effectiveness ratio (ICER) was thus calculated as:


Formula

where:

  • {Delta}H is the savings from reduced hospitalisations;
  • {Delta}A is the additional ongoing costs associated with bisoprolol (this will decrease over time due to reduced survival probabilities, i.e. drug costs);
  • {Delta}C any difference in common costs between standard and bisoprolol therapy (i.e. drug initiation costs).

Costs were limited to the perspective of the NHS as it is difficult to use a broader viewpoint when basing a cost-effectiveness analysis on the results of a clinical trial that did not report any costing data.

2.1. Effects-survival probabilities and LYG
In the CIBIS II trial, patients were only followed up for a mean of 1.3 years and therefore it was thought that for any cost-effectiveness analysis to be meaningful, the survival data should be extrapolated. It seemed somewhat precarious to extrapolate 1.3 years worth of survival data for more than 5 years so an arbitrary decision was made to cut off at that point.

Presentation of mortality data in the CIBIS II report was highly aggregated and therefore cumulative survival probabilities were estimated for the two groups using the actuarial method. The probabilities were estimated at every 100 day interval and then the data were extrapolated under each of two assumptions.

2.1.1. The extended benefits scenario
Data were extrapolated on the basis of the last interval hazard rate (HR) for both the standard therapy and the bisoprolol group. This assumed benefits would extend on after the trial period (see Fig. 1a).


Figure 1
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  		Fig. 1 (a) Cumulative survival probabilities over 5 years under the extended benefits scenario. (b) Cumulative survival probabilities over 5 years under the limited benefits scenario.

 
2.1.2. The limited benefits scenario
Data were extrapolated on the basis of the average interval HR for the standard therapy group. This assumed no additional benefits from bisoprolol after the end of the trial (see Fig. 1b).

It was thus possible to obtain estimates of cumulative survival probabilities at yearly intervals under both assumptions. LYG were calculated using the standard result that the mean of a non-negative random variable is equal to the area under the corresponding survival function. LYG attributable to bisoprolol were estimated by summing the differences of area under each curve over the five time periods and discounting for all periods except 0–1 years.

2.2. Costs
It should be noted that for the purposes of this analysis there is an interest in the additional costs/savings which may be attributable to bisoprolol, not absolute costs. All costs were updated to 2000 prices using inflationary factors available from NHS Dept. of Health, Hospital and Community Services Costs published by the Dept. of Health.

2.2.1. Drug costs
In the CIBIS II treatment group, 564 patients reached the maximum maintenance phase dose of 10.0 mg once daily, 152 reached 7.5 mg, 176 reached 5 mg, 241<5 mg and 194 were permanently withdrawn from treatment. Using the costs quoted in the British National Formulary for September 2000 this calculates to be an average annual cost of £101.55 per patient.

2.2.2. Hospital admissions and cost
Data referring to hospital admission during the CIBIS II trial are again highly aggregated. The figures reported are for all-cause hospitalisations and hospitalisations for worsening heart failure. Unfortunately these numbers refer to patients admitted at least once with any cause, providing no information on the total number of actual admissions. For this reason, it was conservatively assumed that each patient was admitted only once. It is then possible to calculate the rate of hospitalisations per year by dividing by the mean length of time in the study (1.3 years) and then dividing by the corresponding number of patients within the groups.

As only all-cause hospital admissions and those for worsening heart failure were reported, it was not possible to consider cardiovascular admissions only. These were reported merely as a combined end-point with cardiovascular mortality. It seemed justified, therefore, to base cost calculations on all-cause admissions rather than just admissions for heart failure, as data available on the breakdown of hospital admission causes from the CIBIS, revealed that worsening heart failure accounted for only 50% of all admissions. Other causes included cardiac arrthymias (11%), myocardial infarctions (2%) and a number of other cardiovascular causes, which could feasibly be related to bisoprolol, so using all-cause admissions seemed to be appropriate. It can be argued that all-cause admissions should be used in analysis as any treatment that reduces mortality, exposes the patient to a longer period during which they are at risk of requiring hospitalisation. This could have a substantial impact on the result of costings. Mean costs for cardiology admissions were estimated from the National Schedule of Reference Costs produced by the Department of Health and calculated with reference to the cause of admissions breakdown available for CIBIS.

Having established the rate of hospitalisation for each group, this was multiplied by survival probabilities and costs, discounted and summed over time to give the hospitalisation cost in each treatment group. The cost of admissions associated with bisoprolol could then be subtracted from the cost of admissions for standard therapy to give the savings resulting from reduced admissions due to bisoprolol.

2.2.3. Initiation of therapy costs
The initiation of beta-blocker therapy is currently a highly subjective area. The difficulty lies in the fact that a patient cannot be immediately started on the recommended long-term dose but must be slowly up-titrated to avoid adverse reactions. In the CIBIS II trial the up-titration regime was as shown in Table 1 and it can be seen that this therefore involves six visits over 11 weeks. Guidelines/protocols are currently being prepared to establish how this is actually going to happen in practice as bisoprolol has recently received its UK heart failure license. It is a community licence so that bisoprolol can be initiated in primary care settings. In compliance with the recommendations for bisoprolol in the BNF, clinical status should be monitored after initiation and after each dose increase. It is expected that standard blood tests would also be completed at every visit.


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  		Table 1 Bisoprolol initiation and up-titration regimen

 
Due to the volume of heart failure patients thought to be suitable for beta-blocker therapy and the number and length of visits involved in the up-titration procedure, it does appear that much of the workload may be undertaken by specialist nurses in the future, working in the community. The cost of initiating bisoprolol has thus been considered under two scenarios. The first of these assumes that a nurse working in the community undertakes the initiation (based on practice nurse costs) and the second scenario considers initiation costs based on shared care between GP and hospital outpatient clinics. The latter scenario is based on the experience of some primary care physicians who have already begun initiating heart failure patients onto bisoprolol [11]. Their regimen for initiation is set out in Table 1 and it can be seen that patients are seen once a month in an outpatient clinic for 3 months and three times by their GP in the first month.

Practice nurse, GP and outpatients costs were obtained from the Unit Costs of Health and Social Care 1998 — a series of reports funded by the Department of Health based at the Personal Social Services Research Unit at the University of Kent. Blood test costs were obtained from the Southern Regional Trusts from 1996/1997 and were updated using inflationary factors available from NHS Dept of Health Hospital and Community Services Costs, published by the Department of Health.

2.3. Discounting
As is common in economic analyses, future costs and benefits were discounted to allow for differential timings. The rate currently advised by the UK treasury (6%) was used.

2.4. Sensitivity analysis
In any economic evaluation such as this there are a number of key variables that are subject to uncertainty. Sensitivity analysis allows exploration of the impact of change in one or more of these variables on the result of the analysis. In this analysis uncertainty is already accounted for by considering two scenarios in terms of effectiveness (limited and extended benefits), however, changes in other uncertain variables are also considered. These variables are changes in discount rate, changes in the setting of therapy initiation (community based or GP and hospital combined) changes in the hospitalisation rate and cost of an inpatient episode and changes in the cost of the drug.


   3. Results
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 5. Conclusions
 References
 
3.1. Life years gained
The discounted LYG by the adjunctive use of bisoprolol were estimated to be 0.228 under the limited benefits scenario and 0.368 under the extended benefits scenario over 5 years.

3.2. CEA results
Table 2 shows the incremental costs per LYG for bisoprolol compared with standard therapy for heart failure in both extended and limited benefits scenarios.


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  		Table 2 Cost-effectiveness ratios for extended and limited benefit scenariosa

 
Scenarios 1–4 differ in the hospital rates (HRs) used (calculated for CIBIS and CIBIS II) and how drug initiation takes place. The rest of the scenarios all use hospitalisation rates calculated from CIBIS. Scenarios 5 and 6 consider the effects of not discounting. Scenarios 7–10 look at the effects of 20% increases and decreases in inpatient costs. Finally scenarios 11 and 12 consider a 50% increase in the cost of bisoprolol (in the light of the fact that carvedilol is 2.7 times more expensive)


   4. Discussion
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
5. Conclusions
 References
 
The rate of hospitalisation in the bisoprolol group was calculated to be 0.26 hospitalisations per patient per year and 0.3 in the standard therapy group. This implies a 13.3% reduction in hospitalisations in the bisoprolol group. This however, conservatively assumes only one hospitalisation per patient and is therefore likely to be a gross underestimate.

It is possible to calculate these rates from data available from the first CIBIS trial [12] as the number of actual admissions have been reported. In this trial there were 194 admissions over a mean follow-up of 1.9 years in 320 patients on bisoprolol and 282 admissions over the same mean period in 321 patients on standard therapy. This is a rate of 0.32 hospitalisations per patient per year for bisoprolol and 0.46 for standard therapy. The implied reduction in hospitalisations here is 30.4%.

As the denominator for the cost-effectiveness ratios was found to be small, great variability in results was expected and indeed that is exactly what was found. It can clearly be seen that the cost of a LYG for adjunctive bisoprolol therapy differs markedly depending on the annual hospitalisation rate of patients, as hospitalisations are the main cost drivers in the ratio. The annual rates calculated for CIBIS are likely to be the most realistic as they are calculated from total admissions rather than assuming just one admission per person. The analysis therefore concentrates on ratios calculated using the CIBIS rates.

In general, the extended benefit scenarios are more costly. Obviously in the extended benefits scenario there are more patients surviving and thus at risk of hospitalisation, but this is not traded off sufficiently against the benefits (LYG) to produce a lower cost.

Initiation of beta-blockers by nurses in the community is slightly more costly than shared care, as it is assumed that nurses will actually spend longer with the patient during initiation/up-titration. It is unlikely under the current arrangements for outpatient clinics and GP services that this will happen in practice in the shared care scenario, so standard costs for outpatient appointments and GP clinic appointments have been used. In some scenarios it can be seen that the different costs of these types of therapy initiation can have a marked effect on the resultant ratio (see scenarios 3 and 4 of Table 2).

The wide variation in the tables demonstrates the sensitivity of the results to changes in the cost of inpatient episodes, the discount rate, changes in drug costs and how treatment is initiated. It is interesting to note that the higher the inpatient event cost, the more ‘cost-effective’ the therapy becomes due to the increased savings made.

To judge whether the treatment of heart failure patients with bisoprolol is economically attractive and therefore an appropriate use of NHS resources, it is necessary to make comparisons with other analyses. This must of course be approached with caution, as many studies may not be directly comparable (see Drummond et al. [13] for a full discussion on this area). To make comparisons with our own analysis perhaps the most important feature of comparator studies is the time period over which cost-effectiveness ratios are calculated. Two other studies have been identified which consider costs and benefits for cardiovascular therapies over 5 year periods.

Firstly, treatment with simvastatin after myocardial infarction was found to cost £5502 per life year saved (after discounting) and considered ‘to be well within the range normally considered cost-effective’ [14].

Another study considered the economic efficiency of using pravastatin to prevent the transition from health to cardiovascular disease in men with hypercholesterolaemia. If pravastatin was given to men in high risk groups this resulted in a cost of £13 995 per life year gained (discounted). This increased to £20 375 if high risk groups were not targeted [15].

The results obtained in this analysis are well below the ratios calculated in these other studies and are much more in line with the results found previously for ACE inhibitors [16]. It does appear that bisoprolol for heart failure patients is very economically attractive.

4.1. Study limitations
This analysis clearly has a number of limitations. Firstly by the very nature of the fact that the analysis is a cost effectiveness analysis rather than a cost-utility analysis, implies there has not been any consideration of quality of life improvements for the patient. CIBIS, however, demonstrated that more patients in the bisoprolol group improved by at least one NYHA functional class (48 on placebo vs. 68 on bisoprolol, P=0.04) by the end of the follow-up period.

Secondly, due to the short follow-up in CIBIS II, it was necessary to extrapolate data and therefore attempt to model the likely costs and benefits occurring over a 5-year period. Due to the way the survival data were highly aggregated, even the values used for calculations during the period of the trial are approximate. The non-reporting of total hospital admissions for CIBIS II, also limits the accuracy of results. Although it was possible to additionally use information from CIBIS for annual hospitalisation rate calculations, CIBIS differed from CIBIS II in that the doses of bisoprolol were not the same (maximum dose in CIBIS was 5 mg vs. 10 mg in CIBIS II). This could mean that even using the CIBIS data, the annual hospitalisation rates may be underestimated.

Finally, even though the data have been extrapolated, the cost-effectiveness ratio is calculated on the basis of costs and benefits estimated over a 5-year period, rather than a lifetime. It should be noted that treatment might defer costs rather than reduce them.

Other limitations are a direct result of the non-collection or non-reporting of actual costs from the trial. Costs were estimated from other sources and may be unreliable, as they do not take into account the clinical course of individual patients, for example in terms of cause specific admissions or length of stay.

4.2. NHS expenditure implications
It is difficult to say how many heart failure patients may benefit from bisoprolol as prevalence estimates vary greatly [17]. If we assume there are a million heart failure patients in the UK then approximately 850 000 may tolerate the treatment. Under the extended benefits scenario, using CIBIS II hospitalisation rates this is only a cost of £105 per patient over 5 years (discounted) equating to a total cost to the NHS of £8.9 million.

It will be interesting to consider how bisoprolol will compete with carvedilol once it is formally established in the market place. Carvedilol is currently more costly than bisoprolol (£327 vs. £125 a year per patient — BNF September 2000) but it is questionable whether the extra cost actually confers any increased benefit. Obviously a further economic analysis would be required to consider this but directly comparable data is not yet available from ongoing trials.


   5. Conclusions
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
References
 
Beta-blockers are now clearly indicated as a beneficial treatment for heart failure patients and have been proven in clinical trials to confer both mortality and morbidity benefits. Reducing expensive and often frequent inpatient episodes for these patients makes them very economically attractive in comparison with other treatments for heart conditions, as this analysis has indicated. It is likely that procedures for commencing beta-blockers will be simplified in the future thus increasing the cost-effectiveness of this beneficial treatment.


   Notes
Top
 Notes
Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 
* Tel.: +44-20-7351-8700; fax: +44-20-7351-8733. E-mail address: s.varney{at}rbh.nthames.nhs.uk (S. Varney). Back


   References
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 

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  4. MERIT-HF Study Group. Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure (MERIT-HF). Lancet (1999) 353(9169):2001–2007. Jun 12.[CrossRef][Web of Science][Medline]
  5. Schadlich P.K, Paschen B, Brecht J.G. Economic evaluation of the cardiac insufficiency bisoprolol study for the Federal Republic of Germany. Pharmacoeconomics (1998) 13(1 Pt 2):147–155. Jan.
  6. Levy P, Lechat P, Leizorovicz A, Levy E. A cost-minimization of heart failure therapy with bisoprolol in the French setting: an analysis from CIBIS trial data. Cardiac Insufficiency Bisoprolol Study. Cardiovasc Drugs Ther (1998) 12(3):301–305. Jul.[CrossRef][Web of Science][Medline]
  7. Delea T.E, Vera-Llonch M, Richner R.E, Fowler M.B, Oster G. Cost effectiveness of carvedilol for heart failure. Am J Cardiol (1999) 83(6):890–896. Mar 15.[CrossRef][Web of Science][Medline]
  8. Malek M, Cunningham-Davis J, Malek L, et al. A cost minimisation analysis of cardiac failure treatment in the UK using CIBIS trial data. Cardiac Insufficiency Bisoprolol Study. Int J Clin Pract (1999) 53(1):19–23. Jan–Feb.[Web of Science][Medline]
  9. Malek M. Health economics of heart failure. Heart Dec IV (1999) 82(Suppl: 4):11–13.
  10. Packer M, Bristow M.R, Cohn J.N, et al. The effect of carvedilol on morbidity and mortality in patients with chronic heart failure. US Carvedilol Heart Failure Study Group. N Engl J Med. (1996) 334(21):1349–1355. May 23.[Abstract/Free Full Text]
  11. Ray K.K, Clarkson P.B.M, Watson R.D.S. Beta-blockers in heart failure: no need for trepidation in primary care. Br J Cardiol (1999) 6(9):519–520. Sept.
  12. CIBIS Investigators and Committees. A randomised trial of B-blockade in heart failure. The Cardiac Insufficiency Bisoprolol Study (CIBIS). Circulation (1994) 90:1765–1773.[Abstract/Free Full Text]
  13. Drummond M.F, O'Brien B, Stoddart G.L, Torrence G.W. Methods for the economic evaluation of health care programmes (1997) 2nd Edition. Oxford University Press.
  14. Jonsson B, Johannesson M, Kjekshus J, Olsson A.G, Pedersen T.R, Wedel H. Cost-effectiveness of cholesterol lowering. Results from the Scandinavian Simvastatin Survival Study (4S). Eur Heart J (1996) 17(7):1001–1007. Jul.[Abstract/Free Full Text]
  15. Caro J, Klittich W, McGuire A, et al. The west of Scotland coronary prevention study: economic benefit analysis of primary prevention with pravastatin. Br Med J (1997) 315(7122):1577–1582. Dec 13.[Abstract/Free Full Text]
  16. Hart W, Rhodes G, McMurray J. The cost-effectiveness of enalapril in the treatment of chronic heart failure. Br J Med Econ (1993) 6:91–98.
  17. Dargie H.J, McMurray J.J, McDonagh T.A. Heart failure: implications of the true size of the problem. J Intern Med (1996) 239(4):309–315. Apr Review.[CrossRef][Web of Science][Medline]

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