Asthma_COPD_RiskFor_Arthritis_Journal_Club Cohort study

JOURNAL CLUB PRESENTATION
Kumar Nyaupane
Roll No : 607
MPH, 6th Batch
Patan Academy of Health Sciences
Asthma, Chronic Obstructive Pulmonary Disease,
and Subsequent Risk for Incident Rheumatoid
Arthritis among Women: A Prospective Cohort
Study
1

Presentation outline
• Brief about the journal
• About the article
• Introduction to cohort study design
Overview of the article and Critique based on STROBE checklist
• Title and Abstract
• Introduction
• Methods
• Results
• Discussion
• Other Information
• References
2

About the Journal
• Arthritis & Rheumatology is an official journal of the American College of
Rheumatology, is a peer-reviewed publication for scientists and clinicians
interested in the natural history, pathophysiology, treatment, and outcome of the
rheumatic diseases.
• It publishes review articles, editorials, and other
educational material intended for both researchers and
clinicians
• Impact factor : 15.483 (2021)
• Online ISSN : 2326-5205
• Indexing on : MEDLINE/PubMed (NLM), SCOPUS
(Elsevier), Global Health (CABI), Environmental Impact,
Natural Science Collection, Web of Science etc.
ISSIN :International Standard Serial Number 3

About the Article
Authors :
• Julia A. Ford (1,2)
• Xinyi Liu(1)
• Su H. Chu(1,2)
• Bing Lu(1,2)
• Michael H. Cho(1,2)
• Edwin K.
Silverman(1,2)
• Karen H.
Costenbader(1,2)
• Carlos A.
Camargo(1,2,3)
• Jeffrey A. Sparks(1,2)
Published in :
• Arthritis Rheumatol
• 2021 May 01.
DOI :
10.1002/art.41194.
Affiliations :
1. Brigham and Women’s Hospital, Boston, MA, USA
2. Harvard Medical School, Boston, MA, USA
3. Massachusetts General Hospital, Boston, MA, USA
4

Cohort Study
• The term “cohort” is derived from the Latin word “Cohors” – “a group of
soldiers”.
• It is a type of non experimental or observational study design.
• The term “cohort” refers to a group of people who have been included in a study
by an event that is based on the definition decided by the researcher.
• For example, a cohort of people born in Bajura in the year 1997. This will be
called a “birth cohort.”
• Another example of the cohort will be people who smoke.
• Other terms which may be used for these studies are “prospective studies” or
“longitudinal studies.”
Source : Methodology Series Module 1: Cohort Studies,Maninder Singh Setai
5

Design
• In a cohort study, the participants do not have the outcome of interest to begin
with.
• They are selected based on the exposure status of the individual.
• Thus, some of the participants may have the exposure and others do not have the
exposure at the time of initiation of the study.
• They are then followed over time to evaluate for the occurrence of the outcome of
interest.
6

Source : Bonita, Basic epidemiology
7

8
Population
From
NHS and NHS
II
(Registered
nurses)
Population
without
RA(Outcome),
the study
population were
excluded from
the study who
has RA and
connective tissue
disease (CTD)
Nurses with Ashma
and COPD
Nurses without
Ashma and COPD
Nurses with
Rheumatic Arthritis
Nurses without
Rheumatic Arthritis
Nurses with
Rheumatic Arthritis
Nurses without
Rheumatic Arthritis
(NHS) 1988 2014
(NHS II) 1991 2015
Figure : Study design for this study

Example of Cohort studies
1. Framingham cohort study : This cohort study was initiated in 1948 in
Framingham to assess the factors associated with cardiovascular disease (CVD).
2. Swiss HIV cohort study : It was Initiated in 1988. It was a longitudinal study of
HIV-infected individuals to conduct research on HIV pathogenesis, treatment,
immunology, and coinfections.
3. The Danish cohort study of psoriasis and depression : The study evaluated the
association between psoriasis and onset of depression. The participants in the
cohort were enrolled from national registries in Denmark.
9

Types of Cohort studies
1. Prospective cohort study : The investigator defines the population that will be
included in the cohort. They then measure the potential exposure of interest.
The participants are then classified as exposed or unexposed by the investigator.
The investigator then follows these participants, The investigator then assesses
the outcome of interest in these individuals.
2. Retrospective cohort study: In this type of cohort study, the data are collected
from records. Thus, the outcomes have occurred in the past. Even though the
outcomes have occurred in the past, the basic study design is essentially the same.
Thus, the investigator starts with the exposure and other variables at baseline
and at follow-up and then measures the outcome during the follow-up period.
3. Ambidirectional study
10

Strengths and limitations of cohort study
• Temporality : The temporality between exposure and outcome is well defined.
• A cohort study helps us to study multiple outcomes in the same exposure
• In a prospective cohort study, the exposure variable, other variables, and outcomes
may be measured more accurately.
• A retrospective cohort study can be completed fast and is relatively inexpensive
compared with a prospective cohort study.
Source : 1. Methodology Series Module 1: Cohort Studies,Maninder Singh Setai
2. Boston University,Module 4 - Epidemiologic Study Designs 1, sphweb.bumc.bu.edu
11

Limitations
• Its time consuming and costly
• In retrospective study Exposure data may be inadequate and there may be
inadequate data on confounding factors, old records were not designed to be used
for future studies
• Losses to follow up can bias the measure of association.
Source : 1. Methodology Series Module 1: Cohort Studies,Maninder Singh Setai
2. Boston University,Module 4 - Epidemiologic Study Designs 1, sphweb.bumc.bu.edu
12

Abstract
Objectives:
• Inflamed airways are hypothesized to contribute to rheumatoid arthritis (RA)
pathogenesis due to RA-related autoantibody production, and smoking is the strongest
environmental RA risk factor.
• However, the role of chronic airway diseases in RA development is unclear. We
investigated whether asthma or COPD were associated with RA.
Methods:
• We performed a prospective cohort study of 205,153 women in the Nurses’ Health
Study (NHS, 1988-2014) and NHSII (1991-2015).
• Exposures were self-reported physician-diagnosed asthma or COPD confirmed by
validated supplemental questionnaires. Outcomes were incident RA confirmed by
medical record review by 2 rheumatologists.
13

• Covariates (including smoking pack-years/status) were assessed via biennial
questionnaires. Multivariable hazard ratios (HRs) and 95% confidence intervals
(CIs) for RA were estimated using Cox regression
Results:
• We identified 15,148 women with confirmed asthma, 3,573 with confirmed COPD,
and 1,060 incident RA cases during 4,384,471 person-years of follow-up in NHS
and NHSII.
• Asthma was associated with increased RA risk (HR 1.53, 95%CI 1.24,1.88)
compared to no asthma/COPD after adjusting for covariates including smoking
pack-years/status.
• Asthma remained associated with increased RA risk among never-smokers only
(HR 1.53, 95%CI 1.14,2.05). COPD was also associated with increased RA risk
(HR 1.89, 95%CI 1.31,2.75).
14

• The association of COPD with RA was most pronounced in the subgroup of ever-
smokers aged >55 years (HR 2.20, 95%CI 1.38,3.51).
Conclusions:
• Asthma and COPD were each associated with increased risk for incident RA,
independent of smoking status/intensity and other potential confounders.
• These results provide support for the hypothesis that chronic airway inflammation
may be crucial in RA pathogenesis.
15

Critical appraisal of title and abstract
Item Description Response
Yes No Cannot
tell
Comments
Title and
abstract
Indicate the study’s design with a
commonly used term in the title or the
abstract
√ Prospective
cohort study
design is
mentioned
Provide in the abstract an informative
and balanced summary
√ Objective,
method result and
conclusion
clearly mentioned
in balance
16

Introduction
• Patients with rheumatoid arthritis (RA) have increased respiratory morbidity and
mortality. Pulmonary inflammation has been implicated in RA pathogenesis.
Whether diseases of chronic airway inflammation increase risk of developing RA,
however, is unclear.
• Asthma is a common disease characterized by chronic airway inflammation.
• Prior studies investigating an association between asthma and RA risk were
limited by small sample size, lack of adjustment for smoking (an established RA
risk factor), and inability to measure RA phenotypes characterized by
autoantibodies.
• Chronic obstructive pulmonary disease (COPD) is characterized by chronic
inflammation and narrowing of small airways, and smoking is a proven major risk
factor. While RA has been shown to increase risk of subsequent COPD.
17

• To our knowledge no prior prospective cohort studies have examined COPD as a
risk factor for incident RA.
• We investigated the associations between asthma, COPD and incident RA using
two large prospective cohorts, the Nurses’ Health Study (NHS) and NHSII. We
hypothesized that asthma and COPD would each increase risk of incident RA,
independent of smoking.
18

Critical Appraisal of Introduction
Item Description Response Comments
Yes No Cannot tell
Background
Specific background and
rationale of study
√ No prior prospective cohort studies
have examined COPD as a risk factor
for incident RA.
Include important details
and write concisely.
√ No more information about the
burden of AR and associated
factors are added on introduction.
Objectives General Objective √ There is no general objective
mention on introduction
State specific objectives,
including any pre specified
hypotheses
√ There is no specific objective
mention on introduction
19

Methods
Study population and design
• Prospective cohort study was conducted by pooling two Nurses’
Health Studies, prospective cohort studies of female registered nurses
in the United States.
• The NHS began in 1976 and enrolled 121,700 nurses aged 30-55 years.
• NHSII began in 1989 and enrolled 116,429 nurses aged 25-42 years.
• Participants completed baseline and biennial questionnaires detailing
lifestyle, health behaviors, medications, and diseases.
• Both cohorts have >90% follow-up response rates and only 5% of
person-time has been lost to follow-up.
20

NHS and NHS II
• The Nurses' Health Study (NHS) and the Nurses' Health Study II (NHS II) are
among the largest prospective investigations into the risk factors for major
chronic diseases in women.
• The Nurses' Health Study (NHS) was established by Dr. Frank Speizer in 1976
with continuous funding from the National Institutes of Health since that time.
• The primary motivation for the study was to investigate the potential long-term
consequences of oral contraceptives, which were being prescribed to hundreds of
millions of women.
• Nurses were selected as the study population because of their knowledge about
health and their ability to provide complete and accurate information regarding
various diseases, due to their nursing education.
21
Source : Nurses Health study , nurseshealthstudy.org

• NHS founders anticipated and found that nurses were able to respond with a high
degree of accuracy to brief, technically worded questionnaires.
• They were relatively easy to follow over time and were motivated to participate in a
long-term study.
• The cohort was limited to married women due to the sensitivity of questions about
contraceptive use at that time.
• Married registered nurses, aged 30 to 55 in 1976, who lived in the 11 most populous
states, and whose nursing boards agreed to supply NHS with their members' names and
addresses, were eligible to be enrolled in the cohort if they responded to the NHS
baseline questionnaire.
• The names and addresses of 238,026 nurses who fulfilled the eligibility criteria were
obtained in 1972 from the American Nurses' Association, with approval from the state
boards of nursing
22

• The Nurses' Health Study II (NHS II) was established by Dr. Walter Willett and
colleagues in 1989 with funding from the National Institutes of Health to study
oral contraceptives, diet, and lifestyle risk factors in a population younger than the
original NHS cohort.
• This younger generation of nurses included women who started using oral
contraceptives during adolescence and were thus maximally exposed during their
early reproductive life.
• Several case-control studies suggesting such exposures might be associated with
substantial increases in breast cancer risk provided a particularly strong
justification for investment in this large cohort.
23
Source : Nurses Health study , nurseshealthstudy.org

• Exclusion from study
• Participants who reported RA or other connective tissue disease (CTD) at study
baseline,
• Who had missing data related to smoking pack-years at baseline, or did not
return any follow-up questionnaire after study baseline were excluded.
24

• For the asthma analysis, we also excluded participants with self-reported COPD
at baseline.
• For the COPD analysis, excluded participants. 35 years old or younger who
reported COPD as in previous studies, since COPD is rarely diagnosed prior to 35
years of age.
• Flow diagrams of the analyzed study populations for both the asthma and COPD
analyses are presented in Supplemental Figure 1 and Supplemental Figure 2,
respectively.
• All participants provided informed consent and the study protocol was approved
by the institutional review boards of the Brigham and Women’s Hospital and
Harvard T.H. Chan School of Public Health.
25

Supplemental Fig 1. Flow diagram of study sample for the asthma analysis
26

Supplemental Fig 2. Flow diagram of study sample for the COPD analysis
28

Exposure variables: asthma and COPD
Asthma
• Beginning with the 1988 (NHS) and 1991 (NHSII) questionnaires, participants were
asked to report physician diagnosis of asthma.
• Positive responders were sent a previously validated supplemental respiratory
questionnaire with detailed questions regarding asthma symptoms, medications,
and diagnostic testing.
• The supplemental respiratory questionnaire categorized reported asthma according
to the following case definitions:
1: Possible asthma was considered confirmed if the participant reiterated a physician
diagnosis of asthma and reported using an asthma medication since diagnosis.
2 : Probable asthma was met if the participant fulfilled case definition 1 criteria and
reported use of a long-term preventive asthma medication in the past year.
30

3 : Definite asthma was met if all preceding criteria were met and participant
reported physician diagnosis of asthma was made within one month of symptom
onset.
• Camargo and colleagues validated case definition 2 within a random sample of 100
women in 1998 with high accuracy compared to the gold standard of presence of
asthma by medical record review from a physician.
• We considered asthma per case definition 2 or higher (“probable” or “definite”) as
confirmed asthma in our analyses.
• Participants who self-reported asthma but either failed to return the supplemental
respiratory questionnaire or were disconfirmed per the respiratory questionnaire
(did not meet criteria for case definition 2 or higher) were censored at time of initial
self-report.
• Asthma status was time-updated during study follow-up.
31

COPD
• Participants self-reported physician diagnosis of emphysema or chronic
bronchitis biennially starting in 1988 (NHS) and 1999 (NHSII), which was
confirmed with a validated supplemental respiratory questionnaire.
• The supplemental respiratory questionnaire classified participants as,
1. Possible COPD, if they answered affirmatively to having physician-diagnosed
chronic bronchitis or emphysema or COPD
2. Probable COPD, if criteria for “possible” case were met and the participant
reported having a diagnostic test at diagnosis such as pulmonary function testing,
chest radiograph, or chest computed tomography scan; or “
3. Definite COPD, if criteria for “possible” case were met and the participant
reported having pulmonary function testing within the past year demonstrating
forced expiratory volume in 1 second (FEV1) less than 80% predicted or
FEV1/FVC (forced vital capacity) less than 70%.
32

• Barr and colleagues validated these definitions in a cohort of 422 women finding a
positive predictive value of 88% for “probable” COPD against the gold standard of
medical record review by a physician.
• We considered a nurse who self-reported COPD to have confirmed COPD if the
criteria for probable or definite case was met.
• Participants who self-reported COPD but did not return the respiratory
questionnaire or were disconfirmed per the respiratory questionnaire (did not
meet criteria for probable or definite case) were censored at time of report.
• If a participant self-reported asthma (but asthma diagnosis was not validated by
questionnaire) prior to validated COPD diagnosis, she was included as an exposed
individual in the COPD analysis. COPD status was time-updated during study
follow-up
33

Non-exposed group:
• No asthma or COPD : For each analysis, subjects contributed person-time to the
non-exposed group until they self-reported asthma or COPD; if they were confirmed
on validated supplemental questionnaires as asthma/COPD, they contribute. Person-
time to that exposed group thereafter.
• If they reported asthma/COPD but did not return or were not validated by the
supplemental questionnaire, they were censored and no longer contributed person-
time to that analysis.
• Therefore, the non-exposed group never reported asthma or COPD up to each cycle
considered in all analyses.
34

Outcome: Incident RA
• Participants who self-reported a new diagnosis of RA were mailed the CTD
Screening Questionnaire (CSQ)(27).
• Medical records of participants with positive CSQ were obtained and reviewed
independently by two rheumatologists to identify RA cases meeting the 1987
American College of Rheumatology (ACR) or 2010 ACR/European League
Against Rheumatism RA classification criteria.
• Date of RA diagnosis and clinical laboratory results of rheumatoid factor (RF) and
anti-cyclic citrullinated peptide antibodies (CCP) were collected from medical
records.
• An RA case was determined to be seropositive if RF or CCP were above the upper
limit of normal of the laboratory assay documented.
35

Covariates
• Covariates were selected as potential confounders associated with asthma,
COPD, and RA based on prior literature and all covariates were time-updated.
• Sociodemographic covariates included age, race, geographic region, and
household income (categorized by quartile of US Census tract-based median
household income at ZIP code level).
• Potential reproductive confounders were parity/total breastfeeding duration,
menopausal status, and postmenopausal hormone (PMH) use.
• Dietary intake, including alcohol consumption, was assessed by a semi-
quantitative food frequency questionnaire, the Alternative Healthy Eating Index,
and categorized in quartiles .
• Considering healthcare utilization as a potential confounder, we assessed
whether the participant had a physical examination in the past two years on each
questionnaire.
36

• Given the associations between active and passive smoking with risk of
COPD(49–51), asthma(52,53), and RA(54–57), adjusting for these was an
important aspect of our analysis.
• On the baseline questionnaire, participants reported smoking status
(never/past/current) and age at which they started smoking.
• Current smokers reported the number of cigarettes typically smoked per day, and
past smokers provided the age at which they stopped smoking and the number of
cigarettes smoked per day before quitting.
• On subsequent questionnaires, women reported smoking status and intensity (1–
14, 15–24, ≥25 cigarettes/day).
• Smoking pack-years were derived by multiplying packs of cigarettes smoked per
day (20 cigarettes per pack) with number of years smoked.
37

• We used smoking pack-years and smoking pack-years squared as continuous
variables in our model, to include both a linear and quadratic term to account for
the impact of smoking intensity on RA risk.
• We also adjusted for smoking status (never/past/current). All smoking variables
were time-updated.
• To address passive smoking, participants were asked whether parents smoked in the
house when participant was growing up (yes/no) and whether she lived with a
smoker >1 year (ever/never).
38

Statistical analysis
• We performed separate analyses for the co-primary exposures of asthma and
COPD, each compared to participants without reported asthma or COPD.
• We pooled individual level data from the NHS and NHSII for statistical efficiency.
• We reported descriptive statistics for covariates at the baseline of this analysis
(NHS 1988, NHSII 1991) in three groups: asthma and no COPD, COPD (with or
without asthma), and no asthma or COPD.
• Person-years of follow-up for each participant accrued from the date of return of
the study baseline questionnaire
• For the asthma analysis, we also censored at date of self-reported COPD
diagnosis. For the COPD analysis, we included participants who self-reported
asthma prior to COPD that was not confirmed by supplemental questionnaire, with
the rationale that self-reported asthma prior to confirmed COPD diagnosis likely
represented COPD.
39

• We used Cox proportional hazards models to test for the association between
the exposure (asthma or COPD) for RA risk.
• Base models were adjusted for age, cohort, and questionnaire cycle (each cohort
pooled by similar calendar times; e.g., the 1988 cycle in the NHS was pooled with
the 1989 cycle in the NHSII).
• The multivariable model was additionally adjusted for the covariates discussed
above. Given the possibility of collinearity among certain covariates (such as
smoking status and pack-years), we initially considered partial models that
adjusted for smoking status and continuous smoking pack-years separately.
• Since smoking is known to be strongly related to COPD, we expected relatively
few women with COPD to be non-smokers. Therefore, we performed a subgroup
analysis among ever-smokers
40

• We further investigated the association between asthma and RA risk by analyzing
additional subgroups and asthma at study baseline.
• For COPD, we also investigated RA risk among participants who were ever-
smokers and >55 years old since the prevalence of COPD is highest in this
demographic.
• Finally, we analyzed COPD and RA risk among women with confirmed COPD
who never self-reported asthma.
• We tested the proportional hazards assumption by including an interaction term
between time after baseline and the RA outcomes and verified no statistically
significant interactions in all analyses. Two-sided p<0.05 was considered
statistically significant. Analyses were performed using SAS v.9.4.
41

Censoring
• Loss to follow-up is an endemic feature of time-to-event analyses that precludes
observation of the event of interest.
• cohort studies with encounters occurring at regular or irregular intervals, there is
no consensus on how to handle person-time between participants’ last study
encounter and the point at which they meet a definition of loss to follow-up.
• When the event of interest is captured outside of a study encounter (e.g., in a
registry), person-time should be censored when the study-defined criterion for loss
to follow-up is met (e.g., 1 year after last encounter), rather than at the last study
encounter.
• Conversely, when the event of interest must be measured within the context of a
study encounter (e.g.,a biomarker value), person-time should be censored at the
last study encounter.
• In inappropriate censoring scheme has the potential to result in substantial bias
that may not be easily corrected.
42
Source : Practice of Epidemiology, What is censor CatherineR.Lesko*, JessieK.Edwards,Stephen R.Cole,RichardD.Moore
,and BryanLau,American journal of epidemiology, 2017

• Censoring is an endemic feature of time-to-event analysis that precludes
observation of the event. Right-censoring occurs when an event may have
occurred after the last time a person was under observation, but the specific timing
of the event is unknown.
• Right-censoring may occur at the end of the study period (i.e., administrative
censoring) or when a person fails to return for a study visit (i.e., is lost to follow-
up (LTFU)).
• Types
• Point censoring
• Interval censoring
43
Source : Practice of Epidemiology, What is censor CatherineR.Lesko*, JessieK.Edwards,Stephen R.Cole,RichardD.Moore
,and BryanLau,American journal of epidemiology, 2017

44
Figure 1. Several illustrative study records for hypothetical individuals (numbered) in an interval cohort study
under ...

Multivariable model
• Multivariable analysis is a statistical tool for determining the unique
contributions of various factors to a single event or outcome.
• For example, numerous factors are associated with the development of coronary
heart disease, including smoking, obesity, sedentary lifestyle, diabetes, elevated
cholesterol level, and hypertension.
• These factors are called risk factors, independent variables, or explanatory
variables.
• Multivariable analysis allows us to determine the independent contribution of
each of these risk factors to the development of coronary heart disease (called the
outcome, the dependent variable, or the response variable).
• In many clinical situations, experimental manipulation of study groups would be
unfeasible, unethical, or impractical.
45
Source : Multivariable analysis : A primer for readers of medical research , Miychell H. Kartz, MD, Ann intern Med. 2003

• In these circumstances, multivariable analysis can be used to assess the
association between multiple risk factors and outcomes.
• For example, we cannot test whether smoking increases the likelihood of coronary
heart disease by randomly assigning persons to groups who smoke and groups
who do not smoke.
• Although bivariate analysis of longitudinal data demonstrates that smokers are
more likely than nonsmokers to develop coronary heart disease, this is weak
evidence of a causal association.
• Perhaps the only reason smokers are more likely to develop coronary heart disease
is that they are more likely to be male, live in poverty, and have a sedentary
lifestyle.
• In other words relationship between smoking and coronary artery disease may be
confounded by these other variables.
46

• Confounding occurs when the apparent association between a risk factor and an
outcome is affected by the relationship of a third variable to the risk factor and to the
outcome; the third variable is a confounder.
• Multivariable analysis is not the only statistical method for eliminating confounding.
Stratified analysis can also assess the effect of a risk factor on an outcome while
holding other variables constant, thereby eliminating confounding.
• For example, the effect of periodontitis on coronary heart disease can be examined
separately for men and women, which removes the effect of sex on the relationship
between these diseases.
• The three types of multivariable analysis that are commonly used in clinical research
are multiple linear regression, multiple logistic regression, and proportional
hazards(Cox) regression
47

Cox proportional hazards model
• The Cox proportional-hazards model (Cox, 1972) is essentially a regression model
commonly used statistical in medical research for investigating the association
between the survival time of patients and one or more predictor variables.
• In clinical investigations, there are many situations, where several known quantities
(known as covariates), potentially affect patient prognosis.
• The purpose of the model is to evaluate simultaneously the effect of several factors
on survival. In other words, it allows us to examine how specified factors
influence the rate of a particular event happening (e.g., infection, death) at a
particular point in time.
• This rate is commonly referred as the hazard rate. Predictor variables (or factors) are
usually termed covariates in the survival-analysis literature.
48
Source: Statistical tools for high throughput data analysis(STHDA), http://www.sthda.com/

• The Cox model is expressed by the hazard function denoted by h(t). Briefly, the hazard
function can be interpreted as the risk of dying at time t. It can be estimated as follow:
• Where,
• t represents the survival time
• h(t) is hazard function determined by set of p covariates (x1,x2,……)
• The coefficient (b1,b2,….bp) measure the impact of covariate
• The herm h0 is baseline hazard
• Hazard ratio above 1 indicates a covariate that is positively associated with the event
probability, and thus negatively associated with the length of survival.
49
Source: Statistical tools for high throughput data analysis(STHDA), http://www.sthda.com/

• HR = 1: No effect
• HR < 1: Reduction in the hazard
• HR > 1: Increase in Hazard
• The hazard ratio (HR) is analogous to odds ratio used in multiple logistic regression
analysis.
• It is the ratio of the total number of observed to expected events in two independent
comparison groups.
Source: Statistical tools for high throughput data analysis(STHDA), http://www.sthda.com/ 50

Critical appraisal of methods
Yes No Cannot tell
Study design Present key elements of study design early in the paper √
Setting Describe the setting, locations, and relevant dates,
exposure and data collection
√ The study setting, location time are
included in the study.
Participants Give the eligibility criteria, and the sources and methods of
selection of participants. Describe methods of follow-up
√ Case definition and selection of study
population is done
For matched studies, give matching criteria and number of
exposed and unexposed
√ Not mentioned
Variables Clearly define all outcomes, exposures, predictors,
potential confounders
√ Covariates are mentioned as confounders
which are : sociodemographic , dietary
and lifestyle factors.
Data
sources/meas
urement
For each variable of interest, give sources of data and
details of methods of assessment (Measurement)
√ Physician diagnosed asthma and
COPD, Supplementary questionnaire
Bias Describe any efforts to address potential sources of bias √ Confounders were addressed
Study size Explain how the study size was arrived at √ Baseline Exclusion criteria is mentioned.
51

Critical appraisal of methods
Yes No Cannot tell
Quantitative
variables
Explain how quantitative variables
were handled in the analyses
√ Handeling of data was not
mentioned
Statistical
methods
Describe all statistical methods,
including those used to control for
confounding
√ Multivariable model
Describe any methods used to
examine subgroups and interactions
√ Hazard ratio is analyzed based on
some sub groups(Ever smoker and
never smoker)
Explain how missing data were
addressed √ Not mentioned
If applicable, explain how loss to
follow-up was addressed
√ Loss to follow up at different stage
were recorded.
Describe any sensitivity analyses √ Sensitivity analysis were not
mentioned
52

Sample size, asthma/COPD exposures, and RA outcomes
• After baseline exclusions, there were a total of 196,409 participants included in
the asthma analysis and 205,153 participants included in the COPD analysis.
• We identified 15,148 women with confirmed asthma, 3,573 women with
confirmed COPD, and 1,060 incident RA cases (63% seropositive) during a total
of 4,384,471 person-years of follow-up (median 23.9 [IQR 18.3-24.5] years for
asthma analysis; median 24.0 [IQR 20.0-24.5] years for COPD analysis).
54

Characteristics of participants
• Table 1 displays pooled baseline characteristics of the NHS and NHSII study
participants categorized by exposure (asthma without COPD, COPD, and no
asthma or COPD).
• Women in the COPD group were older with mean age of 52.7 years (compared
to 42.5 in the asthma group, and 44.4 in the no asthma/COPD group).
• Those in the COPD group were also more likely to be postmenopausal (70.3%
in the COPD group compared to 30.4% in asthma, and 34.6% in the no
asthma/COPD group).
• Pooled baseline characteristics of the NHS and NHSII study participants included
in the asthma analysis are presented in Supplemental Table 1.
55

Table 1 .Pooled baseline characteristics of study sample in 1988 in the Nurses’ Health Study and
1991 in the Nurses’ Health Study II (n=205,153).
56

Asthma and RA risk
• Compared to women without asthma or COPD, the multivariable-adjusted HR for
developing RA was 1.53 (95%CI 1.24,1.88) among women with asthma (Table
2).
• Asthma was associated with both seropositive and seronegative RA, and HRs for
seropositive versus seronegative RA risk were not significantly different (p for
heterogeneity 0.45).
• We examined the relationship between asthma and RA risk stratified by never- and
ever-smoking (Table 3).
• Among never-smokers only, asthma was associated with all RA (HR 1.53, 95%CI
1.14,2.05) and seronegative RA (HR 1.90, 95%CI 1.22,2.96) but not with
seropositive RA (HR 1.32, 95%CI 0.88,1.96), compared to women without asthma
or COPD.
59

• Among ever-smokers only, asthma had HRs for all RA of 1.49 (95%CI 1.10,2.02),
for seropositive RA of 1.50 (95%CI 1.04,2.18), and for seronegative RA of 1.48
(95%CI 0.87,2.50).
• Table 4 shows the associations of prevalent asthma at study baseline (proxy for
childhood-onset) and incident asthma during follow-up (proxy for adult-onset) with
RA, compared to reference group of women without asthma or COPD.
• Overall RA risk was significantly increased in both prevalent asthma (HR 1.46,
95%CI 1.06,2.01) and incident asthma (HR 1.61, 95%CI 1.23,2.09).
60

Table 2 : Hazard ratios for incident rheumatoid arthritis (overall and by serologic phenotype) by time-
updated asthma compared to women without asthma or COPD in the Nurses’ Health Studies
(n=196,409).
61

Table 3 :Hazard ratios for incident rheumatoid arthritis (overall and by serologic phenotype) by time-updated
asthma compared to women without asthma or COPD in the Nurses’ Health Studies, stratified by never smoking
(n=110,872) or ever smoking (n=85,537).
62

Table 4:Hazard ratios for incident rheumatoid arthritis (overall and by serologic phenotype)
according to prevalent asthma at study baseline or incident asthma during follow-up, each compared
to women without asthma or COPD in the Nurses’ Health Studies (n=196,409).
65

COPD and RA risk
• Compared to women without asthma or COPD, the multivariable-adjusted HR for
developing RA was 1.89 (95%CI 1.31,2.75) among women with COPD (Table 5).
• COPD significantly increased risk for seropositive RA (HR 2.07, 95%CI 1.31,3.25)
but not seronegative RA (HR 1.59, 95%CI 0.83,3.05).
• Among the subgroup of ever-smokers aged >55 years, there was a stronger
association between COPD and seropositive RA (HR 2.85, 95%CI 1.63,4.99; Table
6).
• Among women with confirmed COPD who never self-reported asthma, COPD was
associated with RA (HR 2.57, 95%CI 1.51,4.39).
67

Table 5 :Hazard ratios for incident rheumatoid arthritis (overall and by serologic phenotype) by time-
updated COPD compared to women without asthma or COPD in the Nurses’ Health Studies
(n=205,153).
68

Table 6 :Hazard ratios for incident rheumatoid arthritis (overall and by serologic phenotype) by time-
updated COPD compared to women without asthma or COPD in the Nurses’ Health Studies among
ever smokers aged >55 years (n=21,525).
69

Critical appraisal of results
Yes No Cannot tell
Participants
Give reasons for non-participation at
each stage
√ Not mentioned
Report numbers of individuals at each
stage of study √ Not mentioned
Consider use of a flow diagram
√ Separate flow are included in
supplementary
Descriptive
data
Give characteristics of study
participants (e.g. demographic, clinical,
social)
√ Demographic characteristics are
mentioned
Information on exposures and potential
confounders
√ Information on exposure and
confounder is mentioned
Cohort study—Summarise follow-up
time (eg, average and total amount)
√ loss to follow up mentioned
Outcome
data
Report numbers of outcome events or
summary measures over time
√
70

Critical appraisal of results
Yes No Cannot
tell
Main
Result
Give unadjusted estimates and, if applicable,
confounder-adjusted estimates and their
precision [95% CI]
√ Multivariable model adjusted
covariate discussed above
Report category boundaries when continuous
variables were categorized √ Categories of variables were
mentioned.
If relevant, consider translating estimates of
relative risk into absolute risk for a
meaningful time period
√ Not mentioned
Other
analyses
Report other analyses done—e.g. Analyses of
subgroups and interactions, and sensitivity
analysis
√ The analysis is done on the
basis of sub groups
71

Discussion
• In this large prospective cohort study with lengthy follow-up, asthma was
associated with a greater than 50% increase in the risk of subsequent RA
compared to no asthma/COPD, independent of potential confounders, most
notably smoking status and duration/intensity.
• COPD conferred a nearly 90% increased risk of developing RA compared to no
asthma/COPD in this cohort after multivariable adjustment including adjustment
for smoking, with a greater than two-fold increased risk of RA among older
smokers.
• These findings identify asthma and COPD as risk factors for the development
of rheumatoid arthritis, and to our knowledge, this is the first prospective study
to examine asthma or COPD as RA risk factors
72

• One retrospective study of Israeli soldiers found an inverse association between
asthma and RA(12),
• The majority of the preexisting literature suggests asthma increases RA risk.
• Sheen et al(9) identified asthma via medical record review and RA outcomes using
International Classification of Disease codes in a population-based case-control
study, finding asthma had odds ratio (OR) 1.73 (95%CI 1.03,2.92) for RA
compared to matched controls.
• While this study adjusted for several factors including smoking status and had
high diagnostic accuracy for asthma, there was no adjustment for smoking
duration/intensity, and sample size limited ability to examine RA serologic status.
• Kronzer and colleagues(10) identified RA cases in a biobank population using a
rules-based algorithm, finding that self-reported asthma had increased OR 1.28
(95%CI 1.04,1.67) for RA compared to matched controls
73

• Similar to Sheen et al(9), the authors adjusted for smoking status but not
duration/intensity, and the results of this clinically sampled population may lack
generalizability. While our study similarly finds a positive association between
asthma and RA risk, our finding adds to the literature by nature of the prospective,
detailed data collection with time-updated adjustment for multiple covariates
including smoking status as well as smoking duration/intensity .
• Prior literature has demonstrated a positive association between RA and risk of
developing COPD(18–21).
• However, we identified only two studies examining COPD as an RA risk
factor, neither of which were prospective. A Swedish nested case-control
study(58) examined COPD (per GOLD Stage from spirometry performed for
research purposes) as a risk factor for RA, and ORs were non-significant, likely
due to small number of COPD exposures
74

• In the previously discussed case-control study by Sheen et al(9), COPD was not
associated with RA as an unadjusted baseline variable.
• RA-specific autoantibodies are increased in the sputum of unaffected first-degree
relatives of RA patients prior to detected elevation in the serum.
• In newly diagnosed RA patients, lymphoid aggregates are present near airways
and interstitium(5,6). These findings provided the biologic underpinning of our
hypotheses that asthma and COPD would increase RA risk.
• Our study has several key strengths. We used a validated method to identify
women with asthma and COPD throughout follow-up based on self-report and
then confirmed on a supplemental respiratory questionnaire
• The reference group had never reported asthma or COPD on every main
questionnaire.
75

• The limitations of this study include that the Nurses’ Health Studies included only
women, the majority white, limiting generalizability .
• There was some misclassification since both of the separate questionnaires were
by self-report
• Inclusion of women without true asthma or COPD in these analyses would be
expected to bias results to the null, and among ever-smokers aged >55 years (a
group at higher risk for COPD), we observed the strongest association with RA
risk
• Since data on clinical characteristics of asthma/COPD were only collected once,
we were unable to analyze how the disease course of asthma/COPD may impact
RA risk
• We also had limited ability to analyze asthma and COPD according to disease
severity, imaging/pulmonary function test abnormalities, medication use, or (in the
case of asthma) atopy.
76

• Women with confirmed COPD were older so were more likely to be
postmenopausal. It is possible that they may have had other differences related to
hormonal/reproductive factors that could also impact RA risk .
• Our multivariable analyses therefore included the following
hormonal/reproductive factors: parity, breastfeeding duration, menopausal status,
and postmenopausal hormone use .
• We further mitigated the possibility that the COPD results may have been
explained by hormonal differences by performing a secondary analysis for COPD
among only older women.
• This showed that COPD remained strongly associated with seropositive RA so is
unlikely that differences in menopause explained our results.
77

Critical appraisal of discussion
Yes No Can not
tell
Key results
Summarise key results with
reference to study objectives
√
Limitation
Discuss limitations of the study,
taking into account sources of
potential bias or imprecision.
Discuss both direction and
magnitude of any potential bias
√ Limitation of study is mentioned.
Study is based on only women,
majority white , limited
generalizability.
Possibility of misclassification of
cases
Interpretation Give a cautious overall interpretation
of results considering objectives,
limitations, multiplicity of analyses,
results from similar studies, and other
relevant evidence
√ Interpretation of findings an
comparison with findings of
other literature is done.
Generalizabilit
y
Discuss the generalisability (external
validity) of the study results
√ The limitation of study is included
and the study is mentioned as it
could not be generalized 78

• In this large prospective cohort study of women, asthma and COPD were risk
factors for subsequent rheumatoid arthritis after adjustment for multiple potential
confounders including smoking status and duration/intensity
• These novel findings further implicate chronic airway inflammation in the
pathogenesis of RA, and they identify populations at-risk for RA for the purposes
of research as well as informing clinical care .
• Providers caring for patients with asthma or COPD should be aware of increased
RA risk in these populations and have a low threshold to evaluate for RA in
asthma or COPD patients with inflammatory joint symptoms.
• Finally, inherent to any observational study is the possibility of unmeasured
confounding, particularly related to healthcare utilization.
79
Conclusion

Critical appraisal of other information
Yes No Cannot tell
Funding Source of
funding and
the role of the
funders for
the present
study
√
• Supported by the National Institutes of Health
(grant numbers R03 AR075886, K23
AR069688, L30 AR066953, R01 AR049880,
UM1 CA186107, UM1 CA176726, P30
AR070253, P30 AR072577, T32 A 007530,
and K24 AR066109).
• Funded by the Rheumatology Research
Foundation K Supplement Award and the
Brigham Research Institute
• The funders had no role in study design, data
collection, analysis, decision to publish, or
preparation of the manuscript 80

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