Inhaled corticosteroids, COPD, and the incidence of lung cancer: a systematic review and dose response meta-analysis

Abstract

Background
There has been debate on whether inhaled corticosteroids (ICS) reduce the incidence of lung cancer amongst patients with Chronic Obstructive Lung Disease (COPD). We aimed to perform a systematic review and dose–response meta-analysis on available observational data.

Methods
We performed both a dose response and high versus low random effects meta-analysis on observational studies measuring whether lung cancer incidence was lower in patients using ICS with COPD. We report relative risk (RR) with 95% confidence intervals (CI), as well as risk difference. We use the GRADE framework to report our results.

Results
Our dose–response suggested a reduction in the incidence of lung cancer for every 500 ug/day of fluticasone equivalent ICS (RR 0.82 [95% 0.68–0.95]). Using a baseline risk of 7.2%, we calculated risk difference of 14 fewer cases per 1000 ([95% CI 24.7–3.8 fewer]). Similarly, our results suggested that for every 1000 ug/day of fluticasone equivalent ICS, there was a larger reduction in incidence of lung cancer (RR 0.68 [0.44–0.93]), with a risk difference of 24.7 fewer cases per 1000 ([95% CI 43.2–5.4 fewer]). The certainty of the evidence was low to very low, due to risk of bias and inconsistency.

Conclusion
There may be a reduction in the incidence for lung cancer in COPD patients who use ICS. However, the quality of the evidence is low to very low, therefore, we are limited in making strong claims about the true effect of ICS on lung cancer incidence.

Full text

Pitreetal. BMC Pulmonary Medicine (2022) 22:275
https://doi.org/10.1186/s12890-022-02072-1
RESEARCH
Inhaled corticosteroids, COPD,
andtheincidence oflung cancer: asystematic
review anddose response meta-analysis
Tyler Pitre1, Michel Kiflen2,7, Terence Ho3, Luis M. Seijo4, Dena Zeraatkar5*† and Juan P. de Torres6†
Abstract
Background: There has been debate on whether inhaled corticosteroids (ICS) reduce the incidence of lung cancer
amongst patients with Chronic Obstructive Lung Disease (COPD). We aimed to perform a systematic review and
dose–response meta-analysis on available observational data.
Methods: We performed both a dose response and high versus low random effects meta-analysis on observational
studies measuring whether lung cancer incidence was lower in patients using ICS with COPD. We report relative risk
(RR) with 95% confidence intervals (CI), as well as risk difference. We use the GRADE framework to report our results.
Results: Our dose–response suggested a reduction in the incidence of lung cancer for every 500 ug/day of flutica-
sone equivalent ICS (RR 0.82 [95% 0.68–0.95]). Using a baseline risk of 7.2%, we calculated risk difference of 14 fewer
cases per 1000 ([95% CI 24.7–3.8 fewer]). Similarly, our results suggested that for every 1000 ug/day of fluticasone
equivalent ICS, there was a larger reduction in incidence of lung cancer (RR 0.68 [0.44–0.93]), with a risk difference of
24.7 fewer cases per 1000 ([95% CI 43.2–5.4 fewer]). The certainty of the evidence was low to very low, due to risk of
bias and inconsistency.
Conclusion: There may be a reduction in the incidence for lung cancer in COPD patients who use ICS. However, the
quality of the evidence is low to very low, therefore, we are limited in making strong claims about the true effect of
ICS on lung cancer incidence.
Keywords: ICS, Lung cancer, COPD, Dose-response meta-analysis
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Introduction
Lung cancer remains one of the most common and
deadliest malignancies in the world [1]. Despite signifi-
cant research in therapies and screening, the progno-
sis for lung cancer remains poor [2]. Although reducing
cigarette smoke is amongst the most effective interven-
tions for reducing the risk of lung malignancy, for those
patients with a significant previous or active smoking his-
tory, and those who develop Chronic Obstructive Lung
Disease (COPD), the risk of lung malignancy remains
high [3–5].
Significant interest and debate surround inhaled cor-
ticosteroids (ICS) and their potential role in the chemo-
prevention of lung cancer [6, 7]. A recent systematic
review concluded that ICS use is associated with a
decreased risk of lung cancer in obstructive lung disease
[8]. Unfortunately, published cohorts are inconsistent
and existing reviews have not addressed many important
limitations of the evidence, such as risk of bias, nor have
Open Access
†Dena Zeraatkar and Juan P. de Torres have contributed equally as senior
authors
*Correspondence: Dena_Zeraatkar@hms.harvard.edu
5 Department of Bioinformatics, Harvard Medical School, Boston, MA, USA
Full list of author information is available at the end of the article
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Pitreetal. BMC Pulmonary Medicine (2022) 22:275
they assessed the certainty of evidence or explored a pos-
sible dose–response relationship.
Our objective is to perform a systematic review and
meta-analysis, including a dose response analysis, on the
effect of ICS for preventing lung malignancies in patients
with COPD and to assess the certainty of evidence using
the GRADE approach.
Methods
We registered our protocol on Open Science Framework
and present our results in accordance with the PRISMA
guidelines: https:// osf. io/ jrdzp [9].
Eligibility criteria
We included published and unpublished (abstracts, con-
ferences, pre-prints) cohort studies that compared ICS
with placebo/standard of care or different dosing regi-
mens of ICS in patients with COPD. We also included
mixed cohorts of asthma and COPD patients but
excluded studies enrolling only asthma patients. We did
not restrict study eligibility based on language or year of
publication.
Information sources
An experienced research librarian searched EMBASE,
MEDLINE, Cochrane Controlled Register of Trials
(CENTRAL), Web of Science, and MedRxiv databases
from inception to January 2022. Additional file1: Appen-
dix A1 describes our search strategy.
Data management andselection process
We uploaded citations to COVIDENCE, an online cita-
tion manager [10]. Pairs of reviewers, following calibra-
tion exercises to ensure sufficient agreement, worked
independently and in duplicate to screen titles and
abstracts of search records and subsequently the full texts
of records determined potentially eligible at the title and
abstract screening stage. Reviewers resolved discrep-
ancies by discussion or, when necessary, by third party
adjudication.
Data collection process
Pairs of reviewers, following calibration exercises to
ensure sufficient agreement, worked independently and
in duplicate to collect data from eligible studies. Review-
ers resolved discrepancies by discussion or, when neces-
sary, by third party adjudication.
Data items
We collected data on study characteristics (time and
country of recruitment), patient demographics (age,
sex), clinical characteristics (emphysema, bronchitis,
mixed, COPD/asthma overlap), and factors potentially
predictive of lung cancer (smoking status, duration of
smoking, duration of COPD, history of cancer, long
acting muscarinic antagonist/long acting beta agonist
(LAMA/LABA) use, chronic antibiotics therapies, home
oxygen therapy, non-invasive ventilation, and treatment
with roflumilast, theophylline, oral steroids and type and
dose of ICS). Our choice of co-variates was based on fac-
tors highly associated with the development of lung can-
cer [11].
Outcomes andprioritization
We collected data on all-cause mortality, cancer-associ-
ated mortality, and serious adverse events. However, we
only found data on the incidence of lung malignancy for
analysis.
Risk ofbias
We assessed the risk of bias independently and in dupli-
cate for each outcome using the risk of bias in non-ran-
domised studies of interventions (ROBINS-I) tool [12].
We rated each outcome as either (1) low risk of bias, (2)
moderate risk of bias, (3) serious risk of bias, and (4) crit-
ical risk of bias, across the following domains: bias due
to confounding, bias in selection of participants into the
study, bias in classification of interventions, bias due to
deviations from intended interventions, bias due to miss-
ing data, bias in measurement of outcomes, and bias in
selection of the reported result.
For studies to be rated as low risk of bias for confound-
ing required at a minimum, adjustment for: age, sex,
smoking (duration, pack years, quantity), COPD dura-
tion, socioeconomic status (employment, income, educa-
tion), history of previous lung cancer, obesity, other lung
disease (bronchiectasis, asthma, interstitial lung disease,
obstructive sleep apnea), use of LAMA, LABA or both,
treatment with oral corticosteroids and exposure to
radon, radiation, or asbestosis. Additional file1: Appen-
dix A2 presents additional details on our assessment of
risk of bias.
Data synthesis
We report relative risk (RR) with 95% confidence inter-
vals (CI) and risk differences per 1000 patients. To calcu-
late risk differences, we used the baseline risk inastudy
we found most credible based on our assessment of risk
of bias [13].
To compare the effects of lower versus higher doses
of ICS and risk of lung cancer, we conducted a random-
effects dose–response meta-analysis with the restricted
maximum likelihood estimator (REML) using methods
proposed by Greenland and Longnecker and Crippa and
Orsini [14, 15]. Dose–response meta-analysis summa-
rizes the quantitative relationship between doses of an
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Pitreetal. BMC Pulmonary Medicine (2022) 22:275
exposure and the outcome across studies. We tested for
nonlinearity using restricted cubic splines with knots at
10%, 50%, and 90% and a Wald-type test.
Because dose–response meta-analysis requires knowl-
edge of the total number of participants or person-years,
number of events, and mean or median dose across
each dose category, not all studies were eligible for
dose–response meta-analysis. Hence, we also present a
random-effects meta-analysis with the REML estimator
comparing the highest reported dose of ICS with the low-
est reported dose across studies.
Where studies reported other types of ICS, we con-
verted them to fluticasone equivalents. We used dose
equivalents from data published by the Canadian o-
racic Society [16]. We made assumptions about dosing
based on conversions and expert opinion from respirolo-
gist and consensus of the authors. For studies reporting
doses per prescription, we assumed one prescription to
be equivalent to 500 ug/day of fluticasone and two pre-
scriptions to be equivalent to approximately 1000 ug/day.
For studies reporting the dose of ICS as a range of values,
we assigned the midpoint of upper and lower bounda-
ries in each category as the average dose. If the highest
or lowest category were open ended, we assumed that the
open-ended interval is the same size as the most adjacent
interval.
We evaluated heterogeneity in part by inspecting the
I2 values: 0–39% as unimportant, 40–59% as moder-
ate, 60–74% as substantial, and 75–100% as consider-
able heterogeneity. We performed a subgroup analysis
for COPD only and asthma/COPD mixed cohorts. We
also performed a meta-regression using reported sex as a
moderator. No data was available on severity of COPD to
perform subgroup analysis. We used the ICEMAN tool
to assess the credibility of subgroups if the result was sta-
tistically significant [17].
We conducted all analysis using the meta, dosresmeta,
and rcs packages in R, version 4.0.3 [14].
Certainty oftheevidence
We assessed the certainty of the evidence using the
GRADE framework for observational studies and ROB-
INS-I [18, 19]. According to this approach, evidence
starts at high certainty and may be further downgraded
for risk of bias, inconsistency, indirectness, imprecision,
or publication bias and may be upgraded for large effect,
if suspected biases work against the observed direction of
effect, or for dose–response gradient.
Results
We identified 3964 citations and included thirteen stud-
ies with 268,363 patients. Figure 1 illustrates in more
detail the inclusion and exclusion process. All but three
studies reported only on COPD patients [20–22]. Studies
reported on patients from seven different countries and
three continents (Europe, Asia and North America) and
collected data between 1966 and 2014. Studies reported
primarily on elderly patients (median age: 66.4years) and
majority male. Two studies included only female patients
[23, 24].
We identified three studies reporting on the patients
from the Taiwan National Health Insurance Research
Database, with overlapping patients [23–25], only one of
which provided sufficient data for dose–response analy-
sis. We included the study rated at lowest risk of bias in
the highest versus lowest analysis [23].
Table 1 presents study characteristics [7, 21–24,
26–33].
We contacted authors from three studies for number of
participants and events across dose categories to facili-
tate dose–response meta-analysis [22, 26, 27, 31]. Two
study authors provided us with this data [26, 31].
Risk ofbias
All studies were at serious risk of bias, mostly due to
confounding and selection of the reported results. Most
studies did not adjust for smoking (either duration or
intensity), previous cancer diagnosis or relevant occupa-
tional (asbestos) or radon exposure. Nine studies were at
risk of selection bias, as most did not account for dura-
tion of either COPD or ICS treatment. Two studies were
at serious risk of bias due to classification of the inter-
vention for not providing sufficient data. Eight studies
were at moderate risk of bias due to deviations from the
intended interventions since most studies were not able
to confirm adherence to treatment. Two studies were at
serious risk of bias due to missing data and two studies
at moderate risk due to bias in the measurement of the
outcome. All studies were at risk of bias in selection of
the reported results for not having pre-specified proto-
cols or statistical analysis plans. Table2 summarizes our
individual risk of bias judgements by cohort.
Dose response meta‑analysis: incidence oflung cancer
Seven studies could be included in the dose–response
meta-analysis. Our dose–response suggested a reduc-
tion in the incidence of lung cancer for every 500 ug/day
of fluticasone equivalent ICS (RR 0.82 [95% 0.68–0.95]).
Using a baseline risk of 7.2%, we calculated risk difference
of 14 fewer cases per 1000 ([95% CI 24.7–3.8 fewer]).
Similarly, our results suggested that for every 1000 ug/day
of fluticasone equivalent ICS, there was a larger reduc-
tion in incidence of lung cancer (RR 0.68 [0.44–0.93]),
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Pitreetal. BMC Pulmonary Medicine (2022) 22:275
with a risk difference of 24.7 fewer cases ([95% CI 43.2–
5.4 fewer]).
e certainty of evidence was very low due to risk of
bias and inconsistency. Figure2 and Fig. 3 present the
results. We did not find evidence of non-linearity in the
analysis (p = 0.16).
High versuslow: incidence oflung cancer
Eleven studies could be included in the meta-analysis
comparing highest versus lowest ICS exposure and
lung cancer. Our meta-analysis suggested higher dose
ICS to reduce the risk of lung cancer (RR 0.70 [95%
0.52–0.96]), but there was substantial heterogene-
ity (I2 = 87.57%). Using a baseline risk of 7.2%, we cal-
culated a risk difference of 19.8 fewer cases per 1000
([95% CI 35–2.9]).
We rated this as very low certainty due to risk of bias
and inconsistency. Figure4 presents more details on
the high versus low ICS studies. We did not detect evi-
dence of publication bias using inspection of the funnel
plot and Egger’s statistical test (p = 0.07) (Fig.5).
Fig. 1 Flow diagram for inclusion and exclusion process
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Table 1 Study characteristics
Study Country Cohort database Years included Cohort size Age Male % COPD % Covariates adjusted Range of doses
Husebo 2019 Norway Bergen COPD Cohort Study
between 2006–2009 712 61.3 57.4 100 Age, sex, smoking status,
pack-years smoked, and body
composition
0 to 1000 ug/day
Hyun 2012 South Korea Korean National claims
database 2007–2010 46,225 NR NR Unknown (COPD/Asthma) NR NR
Kiri 2009 United Kingdom UK General Practice Research
Database 1989–2003 7079 70.8 64.5 100 Age, sex duration of COPD,
smoking, comorbidities includ-
ing asthma, inhaler, other
medications
NR
Lee 2018 South Korea National Health Insurance Ser-
vice–National Sample Cohort 2002–2013 1325 63.7 78 74 (COPD and Asthma) Age, sex, pack years, BMI,
income, comorbidities, dura-
tion of follow up
0–1000
Jian 2015 Taiwan National Health Insurance
Research Database (NHIRD) 2003–2010 3956 NR 87.4 NR (mixed; unspecified) Sex, comorbidities, disease
severity, previous lung cancer 0–2000 ug/day
Liu 2017 Taiwan Taiwan’s National Health Insur-
ance (NHI) database 1997–2009 13,868 NR 0 100 Age, income, and comorbidi-
ties by cox regression mode 0–2000 ug/day
Parimon 2007 United States Ambulatory Care Quality
Improvement Project (ACQUIP) 1996–2001 10,474 64.1 97 100 Age, smoking status, smoking
intensity, previous history of
non–lung cancer malignancy,
coexisting illnesses, and bron-
chodilator use
0 to > 1000 ug/day
Raymakers 2019 Canada Medical Services Plan data 1997–2007 39,676 70.7 46.6 100 Age, sex, neighbourhood
income quintile-based resi-
dence and British Columbia
health authority (regional
health service) in which the
patient resided
0–640 ug/day
Sandelin 2018 Sweden Department of Public Health
and Caring Sciences 1999–2009 19,894 68.02 52.4 100 Age at COPD diagnosis, gen-
der, asthma, education level,
marital status, income prior to
index, and time-dependent
covariates medication and
comorbidities
0–1000 ug/day
Sorli 2018 Norway Nord-Trøndelag Health Study 1984–2008 4136 59.1 55.5 100 Sex, age, smoking pack years
and FEV1% < 70 NR
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Table 1 (continued)
Study Country Cohort database Years included Cohort size Age Male % COPD % Covariates adjusted Range of doses
Suissa 2020 Canada Régie de l’Assurance Maladie
du Québec 2000–2014 63,267 71.5 52.5 100 Age, sex, COPD hospitalisa-
tion and exacerbation in the
year prior to cohort entry, as
well as comorbidity at cohort
entry, including cardiovascular
and cerebrovascular diseases,
diabetes, renal disease, other
cancers (not lung), dementia
and rheumatoid disease,
among others, duration of ICS
0 to > 1000 ug/day
Wu 2016 Taiwan Taiwan Health Insurance
database 2003–2010 44,065 NR 69 100 Sex, age, medications,
comorbidities, inpatient and
outpatient visits for respiratory
diseases, and urbanization
NR
Yang 2014 Taiwan Taiwan Health Insurance
database 1966–2011 13,686 NR 0 100 NR NR
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Subgroup analysis
We did not find a statistically significant difference in
results between mixed cohorts of COPD and asthma
versus COPD only cohorts (p = 0.36), nor was sex a
statistically significant moderator in a meta-regression
model (p = 0.5).
All‑cause mortality, cancer‑associated mortality,
andserious adverse events
Data was unavailable for these outcomes.
Discussion
Main ndings
Our review presents a comprehensive and rigorous anal-
ysis of the evidence addressing the relationship between
ICS treatment and lung cancer in COPD patients. We
not only explore evidence of a dose–response relation-
ship, but we summarize and appraise the quality of the
evidence using the GRADE approach.
e present meta-analysis found that there may be a
dose-dependent association between ICS treatment in
COPD patients and a reduction in the incidence of lung
cancer but the evidence is very uncertain. e risk of
bias of the studies, for example, was high, primarily due
to potential for confounding bias. Most cohorts were
unable to adjust for important predictors of lung cancer,
including smoking, or adherence to ICS treatment. ere
was considerable heterogeneity across studies highlight-
ing important differences between the included cohorts.
erefore, we are limited in our conclusions with regards
to the true effect of ICS on lung cancer incidence.
In relation toother ndings
e use of ICS as lung cancer chemoprevention has been
debated. ere have been no randomized trials designed
to investigate the impact of ICS on lung cancer incidence.
However, three trials randomized patients to ICS in other
contexts and reported on the incidence of lung cancer,
showing no benefit, though they were all underpowered
to answer this question [34–37].
Two previous systematic reviews and meta-analyses
compared high versus low ICS in COPD patients that
reported results that differed from our analysis [38, 39].
Both reviews compared high versus low ICS without a
dose response analysis. However, there are substantial
limitations that circumscribe their analysis and signifi-
cantly hinder their conclusions about the effectiveness
ICS in reducing the incidence of lung cancer in COPD
patients. First, neither reviews use a system for rating the
certainty of the evidence such as GRADE, making the
results less meaningful to evidence users. Second, the
reviews did not assess the risk of bias of the studies using
a recommended risk of bias tool for observational data.
For example, both reviews provide only quality ratings
for studies, not specific risk of bias assessments. ird,
the reviews did not present absolute effects. Fourth, the
reviews did not include as many cohorts as the present
meta-analysis. Both previous meta-analyses conclude
that ICS is effective at reducing lung cancer incidence.
Table 2 Risk of bias assessments based on the ROBINS-I assessment tool
1st Author Overall Risk of bias (ROBINS‑I)
Ranking Bias due to
confounding Bias due to
selection
bias
Bias due to
classication of
intervention
Bias due to
deviations from
the intended
intervention
Bias due
to missing
data
Bias in
measurement of
outcome
Bias in selection
of the reported
results
Yang Serious Serious Serious Low Moderate Low Low Serious
Parimon Serious Serious Serious Low Low Low Low Serious
Kiri Serious Serious Low Low Low Low Low Serious
Liu Serious Serious Serious Low Moderate Low Low Serious
Sandelin Serious Serious Serious Low Moderate Low Low Serious
Sorli Serious Serious Serious Low Moderate Low Low Serious
Raymakers Serious Serious Low Low Moderate Low Low Serious
Husebo Serious Serious Serious Low Moderate Low Low Serious
Suissa Serious Serious Low Low Low Low Low Serious
Lee Serious Serious Low Low Moderate Low Low Serious
Yang Serious Serious Serious Serious Serious Serious Moderate Serious
Wu Serious Serious Serious Low Moderate Low Low Serious
Hyun Serious Serious Serious Serious Serious Serious Moderate Serious
Jian Serious Serious Low Moderate Moderate Low Low Serious
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Our analysis shows that there is very low certainty evi-
dence for this conclusion and given the significant incon-
sistency and risk of bias, we caution making such strong
claims.
e inconsistency of the data is of particular concern.
Two studies showed harm with escalating doses of ICS
in COPD patients and one trial showed no effect [7, 22].
One of these studies included a large number of asthma
patients, which is typically thought to overestimate
the effect of ICS on lung cancer mortality, but instead
showed an increased risk of lung cancer incidence.
Limitations
e strengths of our review include use of two meta-
analytic methods, as well as rigorous and state-of-the-art
methods for rating the risk of bias assessment and the
certainty of the evidence [18].
Important limitations of our dose response analysis
include our estimation of ICS doses. We made crude
assumptions about fluticasone equivalence when not
directly reported and cannot be certain of the level of
adherence to ICS treatment in most studies. Further-
more, we were unable to include all studies in the dose
response analysis, potentially obfuscating the true dose
response effect. For example, one study that showed a
Fig. 2 Dose response meta-analysis per 500 µg/day
Fig. 3 Dose response meta-analysis per 1000 µg/day
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negative relationship between ICS and lung cancer could
not be included in the dose–response meta-analysis [22].
Another limitation is that we included three mixed
asthma/COPD cohorts. However, this was expected to
overestimate the effect of ICS on reducing lung cancer
incidence, but we found no difference in subgroups. Fur-
thermore, current evidence suggests that COPD is often
underdiagnosed and over treated. Ongoing modifications
to established guidelines recommending ICS treatment
for different COPD stages and phenotypes also make the
study of ICS effects in COPD a constantly moving target.
e clinical need for well designed, adequately powered,
randomized trials of lung cancer chemoprevention using
ICS, remains unmet. Finally, there were limited data to
perform subgroup analysis, including underlying disease
severity (GOLD classifications), COPD phenotypes and
lung function. Existing evidence linking COPD sever-
ity to varying degrees of risk for lung cancer suggests
that not all COPD patients may have comparable risks of
malignancy.
Conclusion
ICS treatment may reduce the incidence of lung cancer
in COPD patients, but the certainty of evidence is very
low. However, available data originates from cohorts at
serious risk of bias, plagued by inconsistency and hetero-
geneity. High quality cohort studies or randomized con-
trolled trials are needed to improve the certainty of the
evidence.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12890- 022- 02072-1.
Additional le1. A1. Search strategy for Medline 2. A2. Risk of bias tool
(ROBINS-I).
Author contributions
TP came up with the study idea, methods, as well as performed data collec-
tion and analysis. MK helped with data collection, read and approved the
Fig. 4 High versus low inhaled corticosteroids meta-analysis
Fig. 5 Funnel plot for high versus low inhaled corticosteroids
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manuscript. TH consulted on the methods, including choosing appropriate
doses and dose assumptions. He helped write and approved the final manu-
script. LMS provided expert commentary on the paper, as well as helped write
and approve the final manuscript. DZ performed the analysis, helped design
the methods and co-supervised the study. JPD co-supervised the study. He
helped with study conceptualization, methods, and helped write/approve the
final manuscript. All authors read and approved the final manuscript.
Funding
None.
Availability of data and materials
The datasets generated and analysed during the current study will be avail-
able in the Open Science Framework repository at https:// osf. io/ jrdzp/ upon
publication.
Declarations
Ethical approval and consent to participate
Not applicable, exempt.
Consent for publication
Not applicable.
Competing interests
None.
Author details
1 Division of Internal Medicine, McMaster University, 1280 Main Street West,
Hamilton, ON, Canada. 2 Temerty School of Medicine, University of Toronto,
Toronto, ON, Canada. 3 Department of Respirology, St. Joseph’s Hospital, Ham-
ilton, ON, Canada. 4 Department of Pulmonary Medicine, Clínica Universidad
de Navarra, Madrid, Spain. 5 Department of Bioinformatics, Harvard Medical
School, Boston, MA, USA. 6 Division of Respirology and Sleep Medicine, Queen’s
University, Kingston, ON, Canada. 7 Population Health Research Institute,
McMaster University, Hamilton, Canada.
Received: 2 March 2022 Accepted: 6 July 2022
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