Long-acting inhaled therapy (beta-agonists, anticholinergics and steroids) for COPD: an overview and network meta-analysis

  • Major change
  • Protocol
  • Overview

Authors

  • Kayleigh M Kew,

    Corresponding author
    1. St George's University of London, Population Health Sciences and Education, London, UK
    • Kayleigh M Kew, Population Health Sciences and Education, St George's University of London, Cranmer Terrace, London, SW17 0RE, UK. kkew@sgul.ac.uk.

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  • Tianjing Li

    1. Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology, Baltimore, Maryland, USA
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Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the efficacy and safety of treatment options for patients whose chronic obstructive pulmonary disease cannot be controlled by short-acting therapies alone. The review will not look at combination therapies usually considered later in the course of the disease.

As part of this overview, we will address the following issues:

  1. How does the long-term efficacy compare between different pharmacological treatments for COPD?

  2. How does combining different pharmacological treatments affect the long-term efficacy?

  3. Are there limitations in the current evidence base which may compromise the conclusions drawn by this overview? If so, what are the implications for future research?

Background

Description of the condition

Chronic Obstructive Pulmonary Disease (COPD) is a respiratory disease characterised by chronic and progressive breathlessness, cough, sputum production, and airflow obstruction, which leads to restricted activity and poor quality of life (GOLD). The World Health Organisation (WHO) has estimated that COPD is the fourth or fifth most common single cause of death worldwide and the treatment and management costs present a significant burden to public health. In the UK the annual cost of COPD to the National Health Service (NHS) is estimated to be £1.3 million per 100,000 people (NICE 2011). Furthermore, because of the slow onset and the under-recognition of the disease, it is heavily under-diagnosed (GOLD). COPD comprises a combination of bronchitis and emphysema and involves chronic inflammation and structural changes in the lung. Cigarette smoking is the most important risk factor, however air pollution and occupational dust and chemicals can also increase the risk of developing the disease. COPD is a progressive disease leading to decreased lung function over time, even with the best available care. There is currently no cure for COPD, though it is both a preventable and treatable disease. As yet, apart from smoking cessation and non-pharmacological treatments such as long term oxygen therapy in hypoxic patients and pulmonary rehabilitation, no intervention has been shown to reduce mortality (GOLD; Puhan 2011). Management of the disease is multi-facetted and includes interventions for smoking cessation (van der Meer 2001), pharmacological treatments (GOLD), education (Effing 2007) and pulmonary rehabilitation (Lacasse 2006; Puhan 2011). Pharmacological therapy is aimed at relieving symptoms, improving exercise tolerance and quality of life, slowing decline and even improving lung function and preventing and treating exacerbations. COPD exacerbations impair patients' quality of life (GOLD) and a large part of the economic burden of COPD is attributed to the cost of managing exacerbations, particularly those resulting in use of acute care services or hospitalisations (Hutchinson 2010). In the UK, one in eight emergency admissions to hospital is for COPD, which makes it the second largest cause of emergency admissions, and one of the most costly conditions treated by the NHS (NICE 2011). Appropriate pharmacological management of the disease is therefore important, particularly to reduce and prevent exacerbations.

Description of the interventions

Pharmacological management for COPD tends to begin with one treatment and additional therapies are introduced as necessary to control symptoms and reduce the frequency and severity of exacerbations (GOLD). The first step is often a short-acting bronchodilator for control of breathlessness when needed: either a short-acting beta2-agonist (SABA) e.g. salbutamol, or the short-acting muscarinic antagonist (SAMA) ipratropium. Both bronchodilators have a duration of action of four to six hours (Beeh 2010) and they improve lung function and breathlessness (Sestini 2009; Appleton 2006). For persistent or worsening breathlessness associated with lung function decline, long-acting bronchodilators may be introduced (GOLD). These comprise long-acting beta2-agonists such as salmeterol or formoterol (LABA, duration of action 12 hours) and indacaterol (duration of action 24 hours); and long-acting anticholinergic agents, such as tiotropium (duration of action 24 hours) and more recently aclidinium bromide and glycopyrronium bromide. Regular treatment with long-acting bronchodilators is preferred over treatment with regular short-acting bronchodilators based on efficacy and side effects (Beeh 2010; GOLD). An alternative if bronchodilators are not available or affordable is theophylline, an oral phosphodiesterase (PDE) inhibitor. However, theophylline is less effective and less well tolerated than inhaled long-acting bronchodilators. For patients with severe or very severe COPD (FEV1 < 50% predicted) and with repeated exacerbations, GOLD recommends the addition of inhaled corticosteroids (ICS) to bronchodilator treatment. ICS are anti-inflammatory drugs that are licensed as combination inhalers with LABAs. The most common combinations of ICS and LABA in combination inhalers are fluticasone and salmeterol, and budesonide and formoterol. The most severe group of patients with advanced COPD may also benefit from treatment with the PDE4 inhibitor roflumilast which may reduce the risk of exacerbations (GOLD), alongside other beta2-agonists or anticholinergic agents and ICS, but these combinations are not considered in this review.

How the intervention might work

Long-acting muscarinic antagonists

Long-acting muscarinic antagonists (LAMA) are an anticholinergic agent, which blocks the action of the neurotransmitter acetylcholine. The LAMA tiotropium has gained widespread acceptance as a once-daily maintenance therapy in stable COPD for its effects on symptoms and exacerbations (Barr 2005; GOLD). Two newer LAMAs, aclidinium bromide and glycopyrronium bromide, have recently been licensed for the maintenance treatment of people with COPD. Anticholinergic side effects that may occur include dry mouth, constipation and tachycardia (Tashkin 2008).

Long-acting beta2-agonists

Inhaled long-acting beta2-agonists (LABA) activate beta2-receptors in the smooth muscle of the airway leading to a cascade of reactions resulting in bronchodilation. Commonly used LABAs include salmeterol and formoterol, and the ultra-long acting beta2-agonist (U-LABA) indacaterol. The duration of action for salmeterol and formoterol is approximately 12 hours, and therefore are usually taken twice daily. Indacaterol has a duration of action of 24 hours and can, therefore, be taken once daily. The mechanism for action differs between the LABAs, and different efficacy and safety profiles can be expected between the long-acting and ultra-long acting beta2-agonists. As with long-acting muscarinic antagonists, LABAs and U-LABAs are commonly used to control symptoms and reduce exacerbations in stable COPD (Moen 2010; Rodrigo 2008). Possible side effects of LABAs include cardiac effects such as arrhythmia and palpitations, muscle tremors, headache and dry mouth (Berger 2008).

Inhaled corticosteroids

Inhaled corticosteroids (ICS) are anti-inflammatory drugs. ICS are licensed as combination inhalers with LABA. The most common combinations of ICS and LABA in combination inhalers are fluticasone and salmeterol, and budesonide and formoterol. Combination inhalers have similar effects to LABA alone, reducing exacerbation rates and improving patients' quality of life. However, the difference is small (Rodrigo 2009) and ICS therapy, alone or in combination with beta2-agonists, is associated with an increased risk of pneumonia and osteoporotic fractures (GOLD; Loke 2011; Singh 2010).

Why it is important to do this overview

Several systematic reviews have looked at the risks and benefits of specific inhaled therapies compared to placebo or other inhaled therapies. However for patients or clinicians facing patients, the question is often which of the long-acting therapy options is the most beneficial treatment option for patients no longer obtaining symptom relief from short-acting therapies, but for whom PDE4 inhibitors or other combination therapies are not yet necessary. Two recent network meta-analyses have focused primarily on safety outcomes (Decramer 2013; Dong 2013).

Objectives

To assess the efficacy and safety of treatment options for patients whose chronic obstructive pulmonary disease cannot be controlled by short-acting therapies alone. The review will not look at combination therapies usually considered later in the course of the disease.

As part of this overview, we will address the following issues:

  1. How does the long-term efficacy compare between different pharmacological treatments for COPD?

  2. How does combining different pharmacological treatments affect the long-term efficacy?

  3. Are there limitations in the current evidence base which may compromise the conclusions drawn by this overview? If so, what are the implications for future research?

Methods

Criteria for considering reviews for inclusion

We will use existing Cochrane systematic reviews to identify RCTs that randomise patients with stable chronic obstructive pulmonary disease (COPD) to two or more treatment arms of interest (LAMA, LABA, ICS, LABA/ICS, placebo). Where Cochrane reviews do not exist for a particular comparison, or where the review does not include all recent trials, we will include individual RCTs assessing these comparisons.

Types of studies

We will include randomised control trials (RCTs) with a parallel group design and at least 24 weeks duration. We will not exclude studies on the basis of blinding. Cross-over trials will not be included as the pharmaceutical treatments under study can have long-acting effects.

Types of participants

We will include RCTs which recruited patients with a clinical diagnosis of COPD such as (ATS/ERS 2004):

  1. Forced expiratory volume after one second (FEV1)/forced vital capacity (FVC) ratio < 0.7, which confirms the presence of persistent airflow limitation;

  2. One or more of the following key indicators:

    • progressive and/or persistent dyspnoea;

    • chronic cough;

    • chronic sputum production;

    • history of exposure to risk factors (tobacco smoke, smoke from home cooking and heating fuels, occupational dusts and chemicals).

Types of interventions

We will include studies comparing any of the following therapies:

  • LABA (formoterol, salmeterol, indacaterol)

  • LAMA (tiotropium, aclidinium bromide, glycopyrronium bromide)

  • ICS (budesonide, fluticasone, mometasone)

  • LABA/ICS combination (formoterol/budesonide, formoterol/mometasone, salmeterol/fluticasone)

  • Placebo

Participants will be allowed other concomitant COPD medication as prescribed by their healthcare practitioner, provided they are not part of the trial treatment under study.

Types of outcomes

For studies of six months duration, we will use end of study as time of analysis for all outcomes. For longer studies, we will extract endpoint data and data reported at six and twelve month intervals where available. Two measures of efficacy were chosen as the outcomes since previous network meta-analyses have primarily assessed safety outcomes (mortality, Dong 2013; exacerbations and adverse events, Decramer 2013).

Primary outcomes
  • Quality of life (measured as change from baseline with the St George's Respiratory Questionnaire)

  • Trough FEV1

Cost-effectiveness

To supplement the main systematic review of effects, we will seek to identify economic evaluations which have compared the included interventions. These will be summarised in a short commentary in the discussion.

Search methods for identification of reviews

In order to avoid duplication of effort we will first identify RCTs to include by searching for relevant Cochrane systematic reviews. Cochrane systematic reviews use extensive search strategies that include several databases, manufacturers websites and hand searching of conference abstracts. We will search the Cochrane Database of Systematic Reviews (CDSR) in the Cochrane Library (latest issue) for all Cochrane systematic reviews on COPD using the search strategy in Appendix 1, and from those we will handpick the reviews that include relevant comparisons. From these reviews we will identify individual RCTs that meet our inclusion criteria.

In addition, we will run a search on the Cochrane Airways Group Register of trials (see Appendix 2 for details of the Register) to find any studies that may be missed in the review search (e.g. due to discrepancies in inclusion criteria between individual reviews and this overview, as a result of review searches more than 12 months out of date, or where no reviews exist for a particular comparison). The search will be done according to guidance in the Cochrane Handbook of Systematic Reviews of Interventions (Higgins 2011) and in consultation with an information specialist (see Appendix 3 for the search strategy). No date or language restrictions will apply. We will search NHS EED and HEED for economic evaluations using the strategy in Appendix 1, adapted as appropriate.

Data collection and analysis

Selection of reviews

Two review authors will independently assess all potentially eligible reviews retrieved through the search for inclusion in the overview, and all potentially eligible RCTs in these reviews. Any disagreements will be resolved by consulting a third reviewer.

Data extraction and management

Two review authors will independently extract information from all identified RCTs to a data extraction form for the following characteristics:

  • Trial arms of interest

  • Individual trial outcome data

  • Individual trial length, mean baseline lung function, and baseline exacerbation history

For outcomes specified in this overview which have not been studied in eligible intervention reviews, we will independently extract the data from individual trials. Any disagreements will be resolved by consulting a third reviewer.

Assessment of methodological quality of included reviews

Quality of included trials

While existing reviews will be used to identify RCTs, data and methodological quality will be dealt with at an individual trial level. Two review authors will independently assess risk of bias for the following domains in each study in accordance with recommendations made in Chapter 8 of the Cochrane Handbook of Systematic Reviews of Interventions (Higgins 2012).

  1. Random sequence generation (selection bias)

  2. Allocation concealment (selection bias)

  3. Blinding (performance bias and detection bias)

  4. Incomplete outcome data (attrition bias)

  5. Selective reporting

We will not exclude trials on the basis of risk of bias, but will conduct sensitivity analyses if applicable to explore the consequences of synthesising evidence of differing quality.

Data synthesis

Statistical analysis
Direct pairwise meta-analysis

We will analyse dichotomous data variables using Mantel-Haenzsel odds ratios with a 95% confidence interval (CI) and a fixed effect model. We will analyse continuous outcome data as fixed-effect mean differences (MDs) with a 95% CIs and a fixed effect model. In the presence of statistical heterogeneity (I2 > 30%) we will analyse the data using a random effects model and investigate possible sources. They could be of either a clinical and methodological nature, i.e. differences between individual studies in study design (inclusion/exclusion criteria, study duration), patients' baseline characteristics (disease severity, co-morbidities, age, gender), risk of bias (low versus high), or study sponsorship. The fixed effect model assumes that each study is estimating exactly the same intervention effect and the random effects model assumes that the estimated intervention effects are not all the same but follow a distribution across studies.

Network meta-analysis

We will conduct a network meta-analysis (NMA) using Markov chain Monte Carlo methods in WinBUGS to determine the relative effectiveness of LAMA, LABA, ICS, LABA/ICS and placebo against each other. The analyses will be based on a class model which assumes that effects of individual treatments within a class are exchangeable and distributed around a class mean. We will decide whether to use fixed or random effects based on model fit statistics and the Deviance Information Criteria (DIC) (Dias 2012; Spiegelhalter 2002), and the amount of heterogeneity present in the pairwise meta-analyses. NMA aims to provide a coherent set of treatment effect estimates across all comparisons by combining the direct and indirect evidence for any comparison between two treatments. Combining direct and indirect evidence may increase the precision of the comparison. NMA also allows comparisons of interventions not addressed within any of the individual primary trials and provides coherent estimates of the relative treatment effects, which are crucial to decide which treatment is best.

We will model the relative effectiveness of any two classes as a function of each class relative to a reference treatment (placebo). We pre-specify five unique classes of interventions (or nodes) in the network: LABA (salmeterol, formoterol and indacterol), LAMA (tiotropium, aclidinium bromide and glycopyrronium bromide), ICS (fluticasone, budesonide and mometasone), LABA/ICS (salmeterol/fluticasone, formoterol/budesonide and formoterol/mometasone), and placebo. We will estimate the probability that each class ranks at one of the five possible positions (e.g. the best, second best, third best etc). We will obtain estimates of each overall class effect, and also the effects of each treatment within the class compared to every other. Estimates for the within class variability in treatments effects, as well as for the between-class variability in treatment effects will be presented, as well as ranking probabilities in tables and figures as appropriate.

We will assess the extent to which direct and indirect evidence are consistent both qualitatively and statistically (Dias 2011; Lu 2006). Consistency refers to the agreement between direct and one or more indirect sources of evidence in a “closed loop” of trials (i.e., a path in which three or more trials are connected together, starting and ending with the same node) (Lu 2006). If excessive inconsistency is likely, due to differences in patient and design characteristics, we will assess consistency by comparing model fit from a consistency and an 'independent mean effects model' and by informally comparing the output from the NMA to the estimates from the pairwise meta-analyses. We will use the global test to determine the presence of inconsistency and locate areas in the network where large inconsistencies present. If evidence of inconsistency is found we will further investigate the potential sources of inconsistency using the node-split approach (Dias 2010), predictive cross-validation or combined loop and design inconsistency or both, depending on the structure of the evidence and clinical opinion (Dias 2011, Higgins 2012; White 2012). If substantial inconsistency is identified, we will explore factors, including patient and design characteristics that may contribute to inconsistency, and restrict our analysis to a subset of trials where the evidence might be more comparable.

Subgroup analyses and sensitivity analyses

If substantial heterogeneity is present and provided the network remains connected, we will perform the following subgroup analysis:

  • Baseline disease severity (proportion of patients with severe or very severe COPD as opposed to mild or moderate COPD)

  • Dose (analyse all doses separately)

For network meta-analysis, we will include the above factors as covariates as a way of exploring subgroup effects if sufficient data are available.

We will assess the robustness of our analyses by performing sensitivity analyses, excluding studies from the overall analysis of high risk of bias, and by considering studies with different durations separately.

Acknowledgements

We are grateful to Elizabeth Stovold for her help in designing the search strategy and to Milo Puhan and Sofia Dias for their feedback on the protocol. Charlotta Karner wrote the original version of this protocol. Milo Puhan was the Editor for this protocol and commented critically on the protocol.

CRG Funding Acknowledgement: The National Institute for Health Research (NIHR) is the largest single funder of the Cochrane Airways Group.

Disclaimer: The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health.

Appendices

Appendix 1. Cochrane Library search strategy

#1           MeSH descriptor Lung Diseases, Obstructive, this term only

#2           MeSH descriptor Pulmonary Disease, Chronic Obstructive explode all trees

#3           (obstruct*) near/3 (pulmonary or lung* or airway* or airflow* or bronch* or respirat*):ti,ab,kw

#4           COPD:ti,ab,kw

#5           (#1 OR #2 OR #3 OR #4)

Appendix 2. Sources and search methods used to compile the Cochrane Airways Group Specialised Register (CAGR)

Electronic searches: core databases

Database Frequency of search
CENTRAL (the Cochrane Library)Monthly
MEDLINE (Ovid)Weekly
EMBASE (Ovid)Weekly
PsycINFO (Ovid)Monthly
CINAHL (EBSCO)Monthly
AMED (EBSCO)Monthly

 

Hand-searches: core respiratory conference abstracts

Conference Years searched
American Academy of Allergy, Asthma and Immunology (AAAAI)2001 onwards
American Thoracic Society (ATS)2001 onwards
Asia Pacific Society of Respirology (APSR)2004 onwards
British Thoracic Society Winter Meeting (BTS)2000 onwards
Chest Meeting2003 onwards
European Respiratory Society (ERS)1992, 1994, 2000 onwards
International Primary Care Respiratory Group Congress (IPCRG)2002 onwards
Thoracic Society of Australia and New Zealand (TSANZ)1999 onwards

 

MEDLINE search strategy used to identify trials for the CAGR

COPD  search

1. Lung Diseases, Obstructive/

2. exp Pulmonary Disease, Chronic Obstructive/

3. emphysema$.mp.

4. (chronic$ adj3 bronchiti$).mp.

5. (obstruct$ adj3 (pulmonary or lung$ or airway$ or airflow$ or bronch$ or respirat$)).mp.

6. COPD.mp.

7. COAD.mp.

8. COBD.mp.

9. AECB.mp.

10. or/1-9

Filter to identify RCTs

1. exp "clinical trial [publication type]"/

2. (randomised or randomised).ab,ti.

3. placebo.ab,ti.

4. dt.fs.

5. randomly.ab,ti.

6. trial.ab,ti.

7. groups.ab,ti.

8. or/1-7

9. Animals/

10. Humans/

11. 9 not (9 and 10)

12. 8 not 11

The MEDLINE strategy and RCT filter are adapted to identify trials in other electronic databases

Appendix 3. Search strategy to identify trials from the CAGR

#1 MeSH DESCRIPTOR Pulmonary Disease, Chronic Obstructive Explode All

#2 MeSH DESCRIPTOR Bronchitis, Chronic

#3 (obstruct*) near3 (pulmonary or lung* or airway* or airflow* or bronch* or respirat*)

#4 COPD:MISC1

#5 (COPD OR COAD OR COBD):TI,AB,KW

#6 #1 OR #2 OR #3 OR #4 OR #5

#7 indacaterol or QAB149

#8 salmeterol

#9 *formoterol

#10 long* near (beta* near agonist*)

#11 budesonide

#12 fluticasone

#13 mometasone

#14 inhal* near (corticosteroid* or steroid*)

#15 tiotropium

#16 aclidinium or LAS34273

#17 Glycopyrronium or NVA237

#18 long* near muscarinic*

#19 umeclidinium or GSK573719

#20 vilanterol or GW642444

#21 (LABA or LAMA or ICS):TI,AB

#22 #7 or #8 or #9 or #10 or #11 or #12 or #13 or #14 or #15 or #16 or #17 or #18 or #19 or #20 or #21

#23 #6 and #22

[Note: in search line #4, MISC1 denotes the field in which the reference record has been coded for condition, in this case, COPD]

What's new

DateEventDescription
1 October 2013New citation required and major changesProtocol amended to reduce the number of treatments and outcomes to simplify the network meta-analysis. Newer bronchodilators added to included drugs within existing classes (indacaterol, aclidinium bromide and glycopyrronium bromide). PDE4 inhibitors excluded. Although based on a suite of Cochrane reviews, this review will now be a network meta-analysis review of trials and not an overview of Cochrane reviews. Search strategy updated. New author team.

Contributions of authors

Kayleigh Kew re-wrote this protocol, with feedback and methodological support from Tianjing Li.

Declarations of interest

None known

Sources of support

Internal sources

  • St George's University of London, UK.

External sources

  • NIHR, UK.

    Programme grant funding

Ancillary