Quantifying the real life risk profile of inhaled corticosteroids in COPD by record linkage analysis

Chronic obstructive pulmonary disease (COPD) causes significant morbidity and mortality and is the third leading cause of death worldwide [1]. The aim of COPD treatment is to mainly reduce symptoms [2] as no intervention other than smoking cessation and supplemental oxygen has consistently been shown to improve mortality [3],[4].

Inhaled corticosteroids (ICS), especially when prescribed in combination with long-acting β₂ agonists (LABA) improve quality of life (QoL), decrease exacerbations and hospitalisations, and have been associated with a trend towards a reduction in all-cause mortality [5]. However, unlike in asthma where the ICS dose is down titrated to the lowest possible that ensures symptom control, the ICS dose utilised in COPD can be quite high; a frequently used regime in the United Kingdom uses 500 μg fluticasone propionate twice daily [6]. A recent Cochrane review confirmed that ICS therapy is associated with increased pneumonic events [7]. However the effect of ICS on other complications such as osteoporotic fractures, onset and progression of diabetes, glaucoma and cataracts is less clear [8]-[11].

In order to determine which patients should be prescribed ICS, the adverse event profile of ICS must be properly defined. Knowledge of potential risks is especially important in situations where a drug is frequently used outwith the specific group of patients that it should be targeted at. This is especially the case with ICS, as for example in Scotland, the Scottish Medicines Consortium has consistently advised that ICS should not be used for patients with COPD and a FEV₁ > 50% of predicted [12],[13], however, they are nevertheless widely used in patients outside these strict spirometric parameters [14].

We aimed to investigate the association between use of ICS in COPD and development of incident diabetes or worsening of prevalent diabetes, and of other adverse events.

This was a record-linkage cohort study using databases from Tayside Scotland. Data from the Tayside Medicines Monitoring Unit (MEMO) database is held within the Health Informatics Centre (HIC) [15]. This system collects data from the Tayside; a compact Scottish geographical area with a population of over 400,000 people. Health care for the region is co-ordinated by Tayside Health Board, which maintains a computerised record of all patients registered with a general practitioner (GP). In brief, the MEMO database contains several datasets including all dispensed community prescriptions, hospital discharge data, demographic data and biochemistry results. These data can be linked to disease-specific databases such as TARDIS (Tayside Allergy and Respiratory Disease Information System), DARTS (The Diabetes Audit and Research in Tayside Scotland; now called SCIDC) and other routine clinical data, all of which are linked by a Community Health Index (CHI) number that is unique to each patient.

The primary outcome was either new cases of type 2 diabetes or worsening of pre-existing diabetes. These are defined below;

Secondary endpoints – hospitalisations coded as pneumonia, fractures and cataracts were obtained from SMR1. The relevant ICD10 admissions and OPCS4 procedural codes are listed in Table 1[18],[19].

We identified 4,305 subjects as being eligible for the study cohort. Figure 1 details the number of patient available on the TARDIS database and details on excluded patients. 3,243 were exposed to ICS for a total of 17,229 person-years of exposure, and 1,062 were unexposed with a follow-up of 4,508 years. A comparison of the baseline characteristics of the exposed and unexposed cohorts is shown in Table 2. Fluticasone was responsible for 67.7% of the ICS prescription exposure and beclometasone for 20.5%. The remaining ICS prescriptions (11.8%) were for budesonide. There were 239 cases of newly diagnosed and 265 cases of worsening of existing diabetes. For the secondary outcomes there were 550 admissions for pneumonia, 288 hospitalisations for fracture and 505 cataract related admissions. The number of events by exposure group and exposure time is shown in Table 3. This shows the nature of the risk for the two components of the primary endpoint to be quite different, with the new onset diabetes being uncommon across a large number of patients, whilst the worsening of diabetes outcome was extremely common across a small number of patients. For this reason these two endpoints were treated separately for the remaining analyses.

The results of the multivariate analyses are shown in Table 4. These show that there was no association between ICS use and either onset of new cases of diabetes or cases of worsening of existing diabetes. This was consistent across the whole range of sensitivity analyses that were run. For the secondary endpoints a consistent association was found between ICS and increased risk of both hospital admissions for pneumonia and cataract, but not fracture. The sensitivity analyses using models that incorporated various drug exposure screening periods found evidence of a carryover effect for the pneumonia outcome. This implies that the association between ICS use and hospitalisation for pneumonia continues to be present for some time after the ICS use has ceased (Tables 4 and 5). The population attributable risk associated with the use of ICS is an extra 7.4 pneumonia hospitalisation per 1,000 person years of exposure, with the results that of the 550 observed pneumonia hospitalisation in our study cohort 131 (23.8%) could be attributed to use of ICS. A statistically significant interaction between age and sex was found for the pneumonia outcome only; other interaction terms were not significant. Table 5 shows the association between fluticasone alone and other ICS with outcomes. This shows that there were no differences between steroid groups and incidence of diabetes or fractures however there are increased pneumonic and cataract hospitalisations in the patients treated with fluticasone. Analysing only the group of patients on ICS showed that fluticasone had a significantly increased risk of pneumonia hospitalisation (HRs no carryover 1.39 (1.06-1.82), 180 day carryover 1.43 (1.14-1.78)) when compared with individuals on other ICS.

The extent of steroid use via all routes is shown in Table 6. This shows that there was widespread use of steroids administered by other routes. Indeed the majority of patient received greater exposure to oral than inhaled steroid. Use of rectal steroids was not common and the true extent to which systemic absorption of topical steroids is an issue is hard to assess. However the addition of oral steroid exposure to the models had little impact on the point estimates of the hazard ratios for the primary and secondary endpoints. The other sensitivity analyses yielded results that had no impact of the main finding of this study. The inception cohort analyses resulted in a sufficiently small cohort that results tended to be non-significant. The propensity score analyses showed nothing to suggest that they offered any additional adjustment for confounding. Similarly the other sensitivity analyses undertaken showed the study findings to be robust.

Our results show that the use of ICS in our cohort was not associated with new onset of diabetes or worsening of existing diabetes. Although systemic corticosteroids have a well recognised role in increasing diabetes risk [21], the impact of ICS is less well characterised and our study adds to the body of evidence in this field. Initial studies did not show an association between ICS use and diabetes [22],[23], however a large population based study of 388,584 patients with respiratory disease (not just COPD) showed that ICS treatment was associated with a 34% increased risk of new onset diabetes (defined as initiation of an oral hypoglycaemic agent), with those on the highest ICS dose having the greatest risk [11]. More recently, a retrospective study of administrative claims data from the Australian Government Department of Veterans’ Affairs of more than 18,000 patients with diabetes, found there to be an increased risk of diabetes-related hospitalisations with the use of high-dose ICS [24]. Following this observational data, O’Byrne and colleagues examined double-blind, placebo-controlled, trials in patients ≥4 years of age with asthma or COPD involving budesonide or fluticasone to a lesser extent and did not find an association between inhaled corticosteroid treatment and increased risk of new onset diabetes mellitus or hyperglycaemia [25]. This is consistent with our findings and suggests that any effect of ICS on diabetes in COPD patients, if present at all, is unlikely to be clinically significant.

The relationship between ICS and pneumonia risk was first noted in TORCH with participants receiving ICS treatment having a two-fold higher rate of pneumonia when compared with those in the placebo arm [5]. These events were often diagnosed and managed in primary care, our results show that ICS use was also associated with hospitalisation for pneumonia. It has been suggested that ICS type may influence the risk of pneumonia, with a recent Cochrane review and studies such as PATHOS suggesting that fluticasone carries a higher risk than others such as budesonide; this difference is also seen in our study [7],[26]. Fluticasone’s increased immunosuppressant potency (10-fold higher than that of budesonide with regard to ex vivo inhibition of human alveolar macrophage innate immune response to bacterial triggers) [27] could potentially explain these findings. As with other datasets we have shown that ICS use is associated with cataract surgery but not hospitalisation for fractures suggesting that there is no clinically significant association with osteoporosis [9],[28]. Indeed a recent Cochrane review reported that ICS were not associated with an effect on fractures and bone mineral density [29] A previously unreported association was that fluticasone was more strongly associated with cataract surgery than other ICS, it is unclear why this may be the case however dose effect may be one explanation.

In order to justify prescribing ICS one must have data on the risk/benefit balance hence understanding the adverse effects of ICS is key. Although ICS have been shown to improve QoL, decrease exacerbations and hospitalisations and possibly improve mortality, evidence of benefit is limited to individuals with FEV₁ < 70% predicted [30]. Studies that solely recruited patients with milder disease did not show similarly improved outcomes [31] however several studies have shown that over half of ICS use in daily practice falls outwith strict spirometric parameters included in COPD guidelines [32].

The strengths of this study are that data were collected in routine care with minimal exclusions: this increases the likelihood that the results will be applicable to other populations. Another strength is that all COPD diagnoses were validated using spirometric data, to our knowledge this is the first observational study on the effects of ICS and diabetes in COPD that has done this. Despite data being collected prospectively according to predefined criteria, follow-up data are observational and therefore prone to the weaknesses of this type of study. Though we attempted to limit bias by adjusting for other potential confounders, bias due to unrecorded factors may remain.

ICS exposure in our cohort was not associated with new onset of diabetes, worsening of existing diabetes or fracture hospitalisation. There was however an association with increased cataracts and pneumonia hospitalisations. Knowing the adverse effect profile of ICS is especially important as they are often used in patients with no proven evidence of benefit.

All authors were involved in design of the study, analysis and interpretation of results, and preparation and revision of the manuscript. All authors read and approved the final manuscript.