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Metformin use & asthma outcomes in patients with concurrent diabetes & bronchial asthma: A systematic review & meta-analysis
For correspondence: Dr Joseph M. Pappachan, Faculty of Science, Manchester Metropolitan University, Manchester, United Kingdom e-mail: drpappachan@yahoo.co.in
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Received: ,
Accepted: ,
Abstract
Background & objectives
Limited data exist on the effects of metformin on asthma outcomes in patients having type 2 diabetes (T2D) along with asthma. This meta-analysis seeks to determine whether metformin influences asthma outcomes in these patients.
Methods
Studies involving adults with T2D and asthma, using metformin in the intervention group and other glucose-lowering drugs in the control group, were systematically searched through databases. The primary outcome was the adjusted risk of asthma exacerbations in metformin users (MU) vs. non-metformin users (non-MU). Other outcomes included asthma-related emergency room visits, hospitalisations, and the need for rescue steroids. Meta-analysis was conducted using RevMan with random-effects models. Outcomes were reported as hazard ratios (HRs) with 95 per cent confidence intervals (95% CI).
Results
Six retrospective cohort studies with moderate overall risk of bias, involving 317,905 patients, were included. The risk of asthma exacerbation was comparable in MU and non-MU (HR 0.95, 95% CI: 0.86, 1.04, P=0.27). The risk of asthma-related emergency room visits appeared lower in MU than in non-MU, though the difference did not gain statistical significance (HR 0.63, 95% CI: 0.39, 1.01, P=0.06). The two groups also had statistically identical risks of asthma-related hospitalisations (HR 0.76, 95% CI: 0.54, 1.07, P=0.12) and use of rescue steroids (HR 0.95, 95% CI: 0.87, 1.03, P=0.24). However, after excluding a study from Taiwan (n=115486), a significantly lower risk of asthma exacerbation (HR 0.89, 95% CI: 0.83-0.97, P=0.005) and asthma-related hospitalisations (HR 0.68, 95% CI: 0.49-0.93, P=0.02) was observed in MU.
Interpretation & conclusions
Metformin therapy for T2D does not influence asthma outcomes; however, certain outcomes appear to improve when a Taiwanese study is excluded. Such results must be considered cautiously, as the included studies are observational and have a moderate risk of bias. Randomised controlled trials with diverse global representation are essential for clarifying the relationship between metformin use and asthma outcomes.
Keywords
Asthma exacerbation
bronchial asthma
meta-analysis
metformin
type 2 diabetes
Bronchial asthma (BA) and type 2 diabetes (T2D) are two common chronic conditions that have significant implications for global health. BA, characterized by chronic airway inflammation, reversible airflow obstruction, and episodic exacerbations, affects over 300 million individuals worldwide1. Despite advancements in pharmacological therapies, many patients still experience uncontrolled symptoms and severe exacerbations, leading to increased morbidity and healthcare burden1. At the same time, T2D, a metabolic disorder characterized by insulin resistance and chronic hyperglycaemia, is gaining recognition for its systemic inflammatory effects that could adversely affect respiratory conditions like asthma2. The coexistence of these two diseases presents a complex pathophysiological interaction that warrants further investigation.
Metformin, the first-line therapy for T2D, has drawn attention to its broader effects beyond glycaemic control. Preclinical studies suggest that metformin may attenuate eosinophilic airway inflammation, improve pulmonary function, and modulate key inflammatory mediators in asthma exacerbations3. Clinical studies investigating the link between metformin use and asthma outcomes have produced mixed results. While some observational studies have highlighted a significant decline in asthma exacerbations and hospitalisations among metformin users, others have found no robust evidence, rendering its impact ambiguous4,5. In a recent systematic review and meta-analysis (SR/MA) by Rao et al6, the pooled results suggested a potential decrease in asthma-related hospitalisations [hazard ratio (HR)=0.41; 95% confidence interval (CI): 0.19-0.88] linked to metformin use. However, the reduced risks of developing new asthma (HR=0.9; 95% CI: 0.75-1.08), experiencing asthma exacerbations (HR=0.65; 95% CI: 0.28-1.48), visiting the emergency department for asthma-related issues (HR=0.57; 95% CI: 0.31-1.04), and receiving systemic corticosteroid prescriptions (HR= 0.97; 95% CI: 0.91-1.03) did not achieve statistical significance6. Similarly, another meta-analysis by Wen et al7 observed that metformin decreased the risk of asthma-related emergency room visits [odds ratio (OR)=0.81; 95% CI: 0.74-0.89] for patients having asthma and diabetes, but it did not affect the risk of asthma exacerbations (OR=0.65; 95% CI: 0.28-1.48) or asthma-related hospitalisations (OR=0.43; 95% CI: 0.14-1.29). Both meta-analyses exhibited significant heterogeneity for most outcomes, particularly in asthma exacerbations and asthma-related hospitalisations, indicating considerable variability in the study population, methodologies, and confounding factors among the included studies6,7. Further, new studies have been published since the publication of these two meta-analyses.
Given the constraints of earlier meta-analyses and the lack of robust data in the existing literature, a contemporary and thorough meta-analysis is essential to deepen our understanding of how metformin may influence the management of patients with both asthma and T2D, beyond merely regulating blood sugar levels. This meta-analysis seeks to fill this knowledge gap.
Materials & Methods
This systematic review adhered to the protocols specified in the Cochrane Handbook for Systematic Reviews of Interventions as well as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklists8,9. It was registered with PROSPERO (CRD42024648165), and the protocol summary is available online.
Search strategy
A systematic search was conducted across multiple databases and registers, including MEDLINE (via PubMed), Scopus, Web of Science, the Cochrane Central Register, and ClinicalTrials.gov. The search covered these sources from the inception of these sources until December 10, 2024. Using the Boolean operators ‘AND’ and ‘OR’ the following terms were searched - ‘metformin’, ‘bronchial asthma’, ‘asthma’, ‘Diabetes Mellitus, Type 2’, ‘type 2 diabetes’, ‘T2DM’, ‘type II diabetes mellitus’, and ‘T2D’. Search terms applied to all fields. The supplementary material 1 contains the detailed search strategies. Every clinical study, whether published or unpublished, in English during the specified search period was thoroughly and diligently searched. This search involved examining pertinent publications and references from the clinical trials included in this systematic review.
Study selection
The patient population (P) comprised adults diagnosed with both diabetes and bronchial asthma. The intervention (I) was metformin, while the comparison or control (C) group included participants who received either a placebo or glucose-lowering drugs (GLDs) other than metformin. The outcomes (O) measured were the risk of asthma exacerbation, emergency room visits related to asthma, hospitalisations, and prescriptions for rescue systemic corticosteroids.
The observational studies (prospective or cohort)or randomized controlled clinical trials (RCTs) with at least two treatment arms or groups – one receiving metformin, either alone or in combination with other GLDs (i.e., metformin users; MU), and the other receiving either a placebo or any GLDs except metformin (i.e., non-metformin users; non-MU) – were considered as the study type (S) for inclusion. Studies involving adults of both sexes, with a follow up duration of at least six months, were considered. We excluded trials that involved animals, healthy human subjects, letters to the editor, case reports, case series, post hoc analyses of clinical trials, conference presentations, articles lacking sufficient information or primary data, and trials lasting less than three months. The study selection process involved four independent review authors who, after removing duplicates, evaluated the titles and abstracts of all identified records based on the predefined inclusion and exclusion criteria. This initial screening eliminated studies that were clearly irrelevant, allowing only those that potentially met the criteria to proceed to the next stage. Once all the review authors reached a consensus, the full texts of the remaining articles were retrieved and reviewed independently by the authors to determine eligibility in greater detail. During the full-text screening, the reasons for exclusion were recorded for each article, as reported in the PRISMA flow diagram. Any disagreements during the screening or full-text review were resolved through consensus.
Outcomes analysed
The primary outcome was adjusted risk of asthma exacerbations. Secondary outcomes included adjusted risks of asthma-related emergency visits, hospitalisations, and prescriptions for rescue corticosteroids.
Data extraction
Four review authors performed data extraction independently, utilizing standardized forms. When several publications from a single study group were found, the results were merged, and pertinent data from each article were incorporated into the analysis. From each clinical trial, we collected the following information: first author, year of publication, type of the study, place of the study, major inclusion and exclusion criteria, sample size, the proportion of the male participants, mean age, baseline body weight, glycated haemoglobin (HbA1c), interventions used in the treatment and control groups, duration of follow up, and the statistical methods used in the trials. Furthermore, data on both primary and secondary outcomes were gathered, as previously mentioned. For the outcomes, we extracted the events or HR, as provided by the articles. Any disagreements were resolved by consensus.
Dealing with missing data
The required supplementary files for the articles were retrieved from the websites of the publishing journals. Further information, if needed, was collected from the corresponding authors of the relevant articles via email. All relevant information gathered this way was included in the meta-analysis. A thorough analysis of key numerical data was conducted, encompassing the number of individuals screened and randomized, as well as a meticulous evaluation of intention-to-treat, as-treated, and per-protocol populations. Furthermore, attrition rates—encompassing dropouts, losses to follow up, and withdrawals were carefully analysed.
Risk of bias assessment
Three authors independently conducted the risk of bias (RoB) assessment using the Risk Of Bias In Non-randomized Studies of Interventions, Version 2 (ROBINS-I V2) for the non-randomized intervention trials. The ROBINS-I V2 tool addresses seven distinct domains where bias may be introduced. Based on these responses to the signalling questions designed to elicit information relevant to the RoB judgment for the domain, the available options for a domain-level RoB judgment are ‘Low,’ ‘Moderate,’ ‘Serious,’ or ‘Critical’ risk of bias, along with an additional option of ‘No information’. The judgments in each domain contribute to an overall RoB judgment across bias domains for the outcome being assessed10. Any disagreements were resolved by consensus. The Risk-of-Bias Visualization (robvis) web app was used to create RoBplots11.
Statistical analysis
The outcomes were reported using HRs with 95 per cent CI. The forest plots illustrating the HR for the outcomes were generated using the Review Manager (RevMan) computer programme, version 7.2.012. The left side of the forest plot favoured MU, while the right favoured non-MU. Random-effects analysis models were chosen to address the anticipated variability arising from differences in population characteristics and trial duration variations. The inverse variance statistical method was applied in all instances. CI was calculated using the Wald-type method, while Tau2 was computed using the DerSimonian and Laird method. The meta-analysis included forest plots aggregating data from at least two studies. A significance level of P<0.05 was used.
Assessment of heterogeneity
The evaluation of heterogeneity began with an analysis of forest plots. After that, Chi-square test was carried out utilizing N-1 degrees of freedom and a significance level of 0.05 to assess statistical significance. The I2 test was also employed in the subsequent analysis13.The details of comprehending I2 values have been thoroughly discussed in other sources14.
Results
Search results
The process of selecting studies is illustrated in figure 1. The preliminary search yielded 866 articles, which were subsequently refined to nine through the screening of titles, abstracts, and detailed full-text evaluations. Finally, this SR/MA included six studies involving 317,905 patients that met all the prespecified criteria15-20. Three studies were excluded; two were animal studies, and the other did not have a non-metformin control group21-23.
- Flowchart on study retrieval and inclusion in the meta-analysis.
Characteristics of included studies
The baseline characteristics of the included studies and study participants are summarized in table I. All the studies were retrospective cohort studies using databases. Two studies were conducted in the United States of America, two in Taiwan, one in Japan, and the other in the United Kingdom. The study Lee 202516 applied two designs, each with different biases: a self-controlled case series and a metformin new user cohort with inverse probability of treatment weighting (IPTW)score methods. We have analysed the IPTW cohort of the study in this meta-analysis16. In all included studies, metformin users and non-users were matched, and adjustments for potential confounders were made with appropriate statistical testing. All but one study had two groups- the intervention cohort, which used metformin (MU), and the control cohort, which used any GLDs other than metformin (non-MU). The study, Kimura 202415, had three cohorts based on the comparators of metformin: the dipeptidyl peptidase-4 inhibitors (DPP-4i) cohort, the glucagon-like peptide-1 receptor agonists (GLP-1 RA) cohort, and the sodium-glucose cotransporter-2 inhibitors (SGLT-2i) cohort. For analysis, these cohorts were labelled Kimura 2024a, Kimura 2024b, and Kimura 2024c, respectively15. The follow up duration of the studies ranged from 0.8 to 6.7 yr. Supplementary table I summarizes the specifics of the excluded studies.
| Study ID, place | Study design, database used | Major inclusion criteria | Follow up duration | Groups | N | Female (%) | Age (yr) | Outcomes |
|---|---|---|---|---|---|---|---|---|
| Kimura 202415, Japan | Retrospective cohort, Japanese national administrative database | Adults (≥40 yr) with asthma & T2D. New users of metformin, DPP-4i, GLP-1 RA, or SGLT-2i. | Median 0.9 yr (IQR 0.3-2.2) yr | DPP-4i cohort: DPP-4i/Metformin users | 46,024/18,256 | 46.5/46.5 | 58.9±9.8/58.9±9.6 |
Primary: First asthma exacerbation requiring systemic corticosteroids. Secondary: Number of exacerbations requiring systemic corticosteroids during the follow up period, initial occurrence of exacerbation requiring hospitalisation, and number of exacerbations requiring hospitalisation during the follow up period. |
| GLP-1 RA cohort: GLP-1 RA/Metformin users | 1,948/20,914 | 55.4/55.4 | 56.2±9.5/56.2±9.5 | |||||
| SGLT-2i cohort: SGLT-2i/Metformin users | 35,397/35,648 | 44.7/44.7 | 59.6±9.7/59.6±9.8 | |||||
| Lee 202516, United Kingdom | Retrospective cohort, United Kingdom Clinical Practice Research Datalink | Adults (>17 yr) diagnosed with asthma (≥2 asthma codes within 2 yr) & new users of metformin with T2D. Only IPTW cohort were included for the meta-analysis | Median 365 (IQR, 220-365) days | Metformin users | 8,631 | 55.5 | 60.3± 13.8 | Asthma attack, defined as a short course of oral corticosteroids (5-7 days), asthma-related emergency department visit, hospital admission, or death. |
| Metformin non-users | 8,600 | 55.7 | 60.27± 13.36 | |||||
| Li 201617, Taiwan | Retrospective cohort, Taiwan National Health Insurance Research Database | Adult patients (aged ≥18 yr) with concurrent asthma and diabetes and at least one prescription for asthma and diabetes medication during the enrolment period | 3 yr | Metformin users | 444 | 60.4 | 64±10.1 | Asthma-related hospitalisation, asthma exacerbation |
| Metformin non-users | 888 | 60.4 | 64±10.1 | |||||
| Wu 201918, United States of America | Retrospective cohort, National administrative claims database | Adult participants (aged >18 yr) with both asthma &diabetes based on the recorded International Classification of Diseases | Median 0.84 (IQR 0.36-1.63) yr | Metformin users | 11,960 | 66 | 51.9±9.3 |
Asthma exacerbation, defined as an asthma-related systemic corticosteroid use |
| Metformin non-users | 11,960 | 68 | 51.9±9.9 | |||||
| Wu 202119, United States of America | Retrospective cohort, Johns Hopkins electronic health Record | Adult (age >18 yr) patients with diabetes and asthma on the basis of 2 separate outpatient or 1 inpatient diagnostic code. | Median 3.2 (1.4-4.4) yr | Metformin users | 861 | 74 | 53.3±13 |
Hospitalisation with a principal diagnosis of asthma, ED visit with a diagnosis of asthma in the first or second diagnostic position, and a new outpatient order for a systemic corticosteroid within 14 days of an encounter where asthma was a listed diagnosis. |
| Metformin non-users | 888 | 73 | 55.1±14.3 | |||||
| Yen 202220, Taiwan | Retrospective cohort, Taiwan’s National Health Insurance Research Database | T2D patients for at least 3 outpatient visits or one hospitalisation record | Mean: MU 6.67±4.41 yr, Non-MU 4.15±3.89 yr | Metformin users | 57,743 | 50.43 | 57.0±12.9 | Incidence rates of newly diagnosed asthma, acute asthma exacerbation and hospitalisation for asthma during the follow up period. |
| Metformin non-users | 57,743 | 50.51 | 57.0±12.9 |
Risk of bias in the included studies
All the included studies had moderate overall RoB, predominantly stemming from confounding, classification of interventions, deviations from intended interventions, and measurement of outcomes, as evaluated by the ROBINS-I assessment tool (Fig. 2). Publication bias was not assessed due to the insufficient number of studies (at least 10) in the forest plots24.
- (A) Risk of bias summary: Review authors’ judgments about each risk of bias item for each included study using the Risk Of Bias In Non-randomized Studies of Interventions, Version 2 (ROBINS-I V2); (B) Risk of bias graph: Review authors’ judgments about each risk of bias item presented as percentages across all included studies.
Primary outcome: risk of asthma exacerbation
Five studies15-18,20 (Kimura 202415 had three subgroups) evaluated the risk of asthma exacerbation in MU compared to non-MU. The risk was comparable in the two groups (HR 0.95, 95% CI: 0.86, 1.04, P=0.27, I2=91%; high heterogeneity) (Fig. 3). In the leave-one-out sensitivity analysis, the removal of the study Yen 202220 resulted in a statistically significant reduction in asthma exacerbation risk in MU compared to non-MU (HR 0.89, 95% CI: 0.83, 0.97, P=0.005, I2=86%) (Supplementary Table II).
- Forest plot highlighting the risk of asthma exacerbation in metformin users (MU) versus non-metformin users (Non-MU).
Secondary outcomes
The risk of asthma-related emergency room visits, reported by three studies, was lower in MU than in non-MU; however, the difference did not gain statistical significance [HR 0.63, 95% CI: 0.39, 1.01, P=0.06, I2=62% (moderate heterogeneity)] (Fig. 4). The two groups also had statistically comparable risks of asthma-related hospitalisations (in five studies) [HR 0.76, 95% CI: 0.54, 1.07, P=0.12, I2=87% (high heterogeneity)] (Fig. 4B), and prescriptions of rescue systemic corticosteroids (in two studies) [HR 0.95, 95% CI: 0.87, 1.03, P=0.24, I2=0% (not important heterogeneity)] (Fig. 4C).
- Forest plot highlighting the risk of secondary outcomes in MU versus Non-MU: (A) Risk of asthma-related emergency room visits, (B) Risk of asthma-related hospitalisations, (C) Prescriptions of systemic corticosteroids.
In a leave-one-out sensitivity analysis, removing either of the studies, Wu 201918 or Wu 202119, resulted in a statistically significant lowering of the risk of asthma-related emergency room visits in metformin users compared to non-users (HR 0.46, 95% CI: 0.28, 0.76, P=0.003, I2=0% & HR 0.81, 95% CI: 0.74, 0.88, P<0.00001, I2=0%, respectively). The heterogeneity among the included studies was also reduced if Wu 2019 (I2=80% to I2=0%) or Wu 2021 (I2=80% to I2=0%) was removed. The removal of the study Yen 202220 resulted in a statistically significant reduction in the risk of asthma-related hospitalisations among metformin users compared to non-users (HR 0.68, 95% CI: 0.49, 0.93, P=0.02, I2=77%) (Supplementary Table II).
Discussion
This systematic review and meta-analysis analysed pooled data from six retrospective cohort studies with follow up durations ranging from 0.8 to 6 yr and moderate overall RoB, including 317,905 participants. It suggests that metformin use in patients with T2DM may not influence the risk of asthma exacerbations or asthma-related hospitalisations. However, excluding the study by Yen et al20 from the analysis suggests that metformin may protect against asthma exacerbations and asthma-related hospitalisations. The risk of asthma-related emergency room visits was lower in MU than in non-MU, although the difference did not achieve statistical significance. Similarly, asthma-related hospitalisations and the need for systemic corticosteroids were similar.
Except for the study Yen 202220 from Taiwan, in all other studies included in this systematic review and meta-analysis, metformin appears to positively impact asthma-related respiratory outcomes, potentially from its immunomodulatory mechanisms on the respiratory tract. The discrepancy in asthma-related outcomes observed by Yen et al20 in the Taiwanese population is a matter of debate, as another study by Chen et al4 among Taiwanese patients with T2D suggests that metformin reduces the risk of asthma and its health-related outcomes. If the observation by Yen et al20 is correct, further research is needed to clarify the reasons for the same. Adiposity-related metabolic characteristics are unique to the Southeastern ethnic groups; therefore, the effects of metformin could also be different in such a population25.
Since metformin is the most prescribed GLD for patients with T2D, its therapeutic efficacy and safety for all diabetes-related outcomes and comorbidities should be properly appraised to ensure the most appropriate use of the drug. Obesity and metabolic syndrome (MetS) are inflammatory states that increase the risk of asthma; thus, the potential therapeutic benefits of metformin in reducing asthma-related outcomes in this SR/MA are especially significant and noteworthy26. This is important as other GLDs, including insulin, might either increase the risk of asthma exacerbation or have neutral effects (DPP-4i and SGLT-2i), except for drugs in the GLP-1RA class, which possess beneficial effects by reducing airway inflammation4,27-29.
The likelihood of protection from asthma exacerbations in patients with T2DM has important therapeutic implications. The administration of systemic steroids during asthma exacerbations is often necessary, but it can lead to steroid-induced hyperglycaemia, which carries an increased risk of both immediate and long-term diabetes-related health issues. In some cases, this may require more intensive inpatient glycaemic monitoring and aggressive management30. Therefore, reducing the risk of asthma exacerbations by 11 per cent, as mentioned above, has significant therapeutic and financial implications, especially given the high prevalence of asthma in at-risk populations with obesity, MetS, and T2D.
The tendency for reduced risk of emergency room visits with asthma exacerbations among metformin users also has similar societal and health-economic repercussions. The estimated net value of asthma care in the United Kingdom between 2022 and 2031 is £48 billion31. The observed reduction in asthma-related hospitalisations (excluding the Yen 2022 study20) also carries similar therapeutic and socio-economic implications, along with an improved quality of life for these individuals.
We acknowledge the following limitations of our systematic review and meta-analysis. The observational nature of the included studies with moderate RoB mostly limits the applicability of our results in drawing definitive scientific conclusions. Moreover, high heterogeneities were observed in the outcomes of asthma exacerbations and asthma-related hospitalisations, leading to significant uncertainty about the outcome measures. Such significant heterogeneity can arise from various factors, including clinical differences between studies, methodological variations, and statistical issues. Although asthma and diabetes are two common disorders worldwide, the populations in the included studies do not provide a true representation of global ethnic diversity, especially considering the very different outcomes observed among the Taiwanese cohort, which limits the generalizability of our systematic review and meta-analysis observations. Despite these limitations, the fairly large number of participants in this study, along with the relatively long follow up durations of the included studies, offers reasonable evidence for making meaningful conclusions.
In conclusion, this systematic review and meta-analysis suggests that, overall, metformin therapy for patients with T2D does not influence asthma outcomes. However, excluding data from a Taiwanese cohort study reduces risks of asthma exacerbations, emergency visits, and hospitalisations. The observational nature of the included studies, the insufficient representation of diverse ethnic groups and global regions, moderate RoB, and substantial heterogeneity in the results of the outcomes restrict the generalizability and robustness of our study results. RCTs that include diverse global representation are essential for clarifying the relationship between metformin use and asthma-related health outcomes in patients with T2D.
Financial support & sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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