Abstract
Background:
Atopic dermatitis (AD) is thought to induce asthma via the atopic march, but the effects of AD on incident asthma and asthma severity have not been fully characterized.
Objective:
Determine risk of asthma, asthma exacerbations, and asthma-related hospitalizations among patients with AD.
Methods:
Cohort study using electronic health records data from U.K. general practices from 1994 to 2015. Children (<18 years old) and adults (≥18 years) with AD were matched on age, practice, and index date to patients without AD. AD severity was categorized using treatments and dermatologist referrals. Outcomes were incident asthma among all patients, and asthma exacerbation or hospitalization among asthmatic patients.
Results:
Comparing 409,341 children with AD (93.2% mild, 5.5% moderate, 1.3% severe) to 1,809,029 unaffected children, AD was associated with 2-fold greater risk of asthma compared to those without AD (HR 1.96 [95% CI 1.93–1.98]). Comparing 625,083 adults with AD (65.7% mild, 31.4% moderate, 2.9% severe) to 2,678,888 unaffected adults, AD was associated with a 38% higher risk of asthma (HR 1.38 [1.36–1.40]). Asthmatic patients with AD also had a 21–63% greater risk of asthma exacerbations and 20–64% greater risk of asthma-related hospitalizations compared to asthmatic patients without AD. Risk of asthma, asthma exacerbation, or asthma-related hospitalization increased with AD severity in a dose-dependent manner in both the pediatric and adult cohorts.
Conclusion:
AD, especially in children and when more severe, is associated with greater risk of asthma as well as greater risk of asthma exacerbations and hospitalizations among asthmatic patients.
Keywords: asthma, atopic dermatitis, atopy, eczema, epidemiology
Introduction
Atopic dermatitis (AD) affects about 10% of adults and 20% of children and is associated with other allergic disorders including asthma. (1, 2) The concept of the “atopic march” describes a progression from AD early in life to the subsequent development of other atopic conditions such as allergic rhinitis and asthma. (3) Several mechanisms may drive asthma development among AD patients. In the classic paradigm of the “atopic march,” allergic sensitization of the skin occurs in the setting of barrier defects and immune dysregulation in AD-affected skin, leading to allergic sensitization in the airways resulting in asthma. However, predisposition to both AD and asthma is likely driven by shared genetic and/or environmental factors; genome-wide association studies have identified many shared loci between AD and asthma, including variants in epidermal barrier and Th2 immune response genes. (4, 5)
An estimated 40% of AD patients subsequently develop asthma. (3, 6) However, most studies evaluating asthma risk among AD patients have been conducted in birth cohorts of preadolescent children younger than 3–11 years old. (7–13) One systematic review estimated a pooled odds ratio of 2.14 for asthma prevalence in children under 4 years old with AD. (7) Asthma risk may also depend on AD disease characteristics, with specific phenotypes of AD before age 6 years having been found to be more associated with developing asthma. (9) Additionally, while some observational studies suggest that more severe AD portends more severe asthma in children, (14) the effects of AD and AD severity on the severity of asthma have not been thoroughly characterized.
Less is known about asthma risk among older children and adults with AD. Increasing evidence suggests that adult-onset asthma may relate more to environmental exposures and comorbidities such as obesity compared to childhood-onset asthma. (15–18) Certain asthma subtypes may also be more highly associated with either pediatric or adult AD. (19) Previous studies examining the association of AD early in life with asthma later in life have primarily relied on surveys taken at specific time points. (20, 21) One such study found that childhood AD was associated with incident asthma in adolescence (HR 2.14) and adult life (HR 1.63). (21)
In this study, we use electronic health records data to further characterize the incidence of asthma, including risk of asthma exacerbations and hospitalizations, among both children and adults with AD in a population-based cohort.
Methods
We conducted a cohort study using The Health Improvement Network (THIN), an electronic medical records database of over 600 general practices in the U.K. that is broadly representative of the U.K. population. The general practitioner (GP) is the primary contact for medical care in the U.K., and diagnostic codes for many conditions, including AD, have been validated in THIN. (22, 23) As 96% of patients with AD are managed exclusively by GPs, a primary care database like THIN is generalizable to the greater population of patients with AD. (24) Data collected between 1994 and February 2015 were used.
The study population included all patients with AD, each matched to up to 5 patients without AD (non-AD) on age (+/−3 years), general practice, and an encounter within +/−6 months of the index date for the AD patient (defined as latter of registration and diagnosis dates). Patients aged <18 and ≥18 years were analyzed separately as pediatric and adult cohorts, respectively. Patients with AD were identified using a validated algorithm requiring at least one of five common diagnosis codes for AD and two AD-related therapy codes, which carries a positive predictive value of 90% (83–96%) and 82% (73–89%) for physician-confirmed AD diagnosis among children and adults, respectively. (22) Each non-AD patient was assigned a ‘diagnosis date’ based on an encounter within +/−6 months of the index date for the matched AD patient, in order to minimize bias by ensuring that AD and non-AD groups were followed during similar time periods. Follow-up time for AD patients began at the latest of AD diagnosis, practice registration, or Vision date [i.e., when Vision software was implemented for data transfer, thereby assuring good data quality]. For non-AD patients, follow-up time began at the latest of ‘diagnosis date’, registration date, or Vision date. Follow-up ended at the earliest of asthma development, transfer out of the practice, death, or end of study period. Patients with a history of asthma at time of cohort entry were excluded from the analysis of incident asthma.
We also identified a sub-cohort of asthmatic patients to evaluate the risk of asthma exacerbation and asthma-related hospitalization with respect to AD and AD severity. This sub-cohort included all non-AD and AD patients with a diagnosis of asthma at any time before or after entry into the larger cohort. Within this sub-cohort, follow-up time began at the latter of the original start date, as defined above, and date of first asthma code. Follow-up ended at the earliest of incident asthma exacerbation event, transfer out of the practice, death, or end of study period. Patients with history of asthma exacerbation events at start of follow-up were excluded from the analysis.
AD severity was defined as a time-updated variable using treatments as proxies. All patients with AD were considered to have mild disease by default. They were classified as having “moderate” AD at the first of: i) a second potent topical corticosteroid treatment within one year, or ii) a first topical calcineurin inhibitor treatment (which is reserved for moderate AD in the UK). (25) Patients were classified as having “severe” AD at the first of: i) systemic immunosuppressant treatment, ii) phototherapy use, or iii) referral to dermatology (as 96% of AD patients are managed exclusively by GPs). (24) Once defined as having moderate AD, patients remained as such unless they developed severe AD; once defined as having severe AD, patients remained as such for the remainder of follow-up. Therefore, patients belonged to one of three severity categories at any given time. Although not directly validated, this time-updated approach to defining AD severity has been previously used. (26, 27)
The primary outcomes were: i) incident asthma across the overall cohort, as well as ii) incident asthma exacerbation events and iii) asthma hospitalization events within the sub-cohort of asthmatic patients. We identified outcomes using READ diagnosis codes, which are a comprehensive numerical system analogous to the International Classification of Disease (ICD) codes used to record diagnoses in THIN. (28) Incident asthma was identified by having a READ diagnosis code for asthma in a patient with no prior history of an asthma diagnosis code. Asthma exacerbation was identified using READ diagnosis codes for asthma exacerbation in a patient with a history of asthma. Asthma-related hospitalizations were defined as having a hospitalization within 14 days of an asthma READ code.
Incidence rates were calculated for each outcome. Cox regression models were used to compare time to incident outcomes, adjusted for covariates determined a priori: age, sex, socioeconomic status (i.e. Townsend index, a measure of material deprivation) and history of allergic rhinitis. Body mass index (BMI), (16, 29) smoking status, (30, 31) and alcohol intake (32) were also adjusted for in adult models; missing data prevented these variables from being included in pediatric models. Covariates were defined at time of cohort entry; AD severity and age were time-updated. We did not include p-values to compare baseline characteristics between study groups, as small absolute differences may be statistically significant in the context of our large sample size but do not necessarily equate to clinically significant differences. We conducted several sensitivity analyses to address possible sources of bias. To address potential outcome misclassification, we used an alternative definition of asthma exacerbation to reflect an asthma diagnosis code with a systemic corticosteroid prescription within 3 days. To address short study follow-up duration, a sensitivity analysis restricted to patients with at least 5 years of follow-up was conducted. To address ascertainment bias, we also included another analysis restricted to patients seen at least yearly during follow-up. Sensitivity analyses restricting to childhood-onset asthma outcomes and stratifying by early and late childhood in the pediatric cohort were also conducted.
Results
Pediatric cohort
A total of 409,431 children with AD (93.2% mild, 5.5% moderate, 1.3% severe) were matched to 1,809,029 children without AD. The median age was 4 (IQR 1–8), 9 (4–14), 5 (1–10), and 4 (2–9) years for the mild, moderate, severe, and non-AD groups, respectively. Socioeconomic status was not meaningfully different between the AD and non-AD groups. Median follow-up duration was between 5 and 7 years (Table 1), and 18% of patients in the pediatric cohort had follow-up beyond the age of 18 years. The sub-cohort of asthmatic patients consisted of 169,679 non-AD patients (9.4% of the total non-AD pediatric cohort) and 57,098 AD patients (13.9% of the total AD pediatric cohort). Compared to the overall cohort, the asthmatic sub-cohort was older (median age 9–12 years old) and had longer follow-up time (7–10 years) (Table 2).
Table 1: Baseline characteristics of pediatric and adult cohorts in THIN database, 1994 to 2015 (n= 5,522,431 patients).
Patients with AD are reported within the highest severity group they belonged to during follow-up.
| Characteristic, N (%) | No AD | Mild AD | Moderate AD | Severe AD |
|---|---|---|---|---|
| Pediatric cohort | N=1,809,029 | N=381,678 | N=22,433 | N=5,320 |
| Age, median (IQR), y | 4 (2, 9) | 4 (1, 8) | 9 (4, 14) | 5 (1, 10) |
| Sex | ||||
| Female | 872,279 (48.22) | 184,682 (48.39) | 11,054 (49.28) | 2,335 (43.89) |
| Male | 936,750 (51.78) | 196,996 (51.61) | 11,379 (50.72) | 2,985 (56.11) |
| Townsend deprivation index | ||||
| 1-Lowest | 424,409 (24.71) | 89,820 (24.89) | 4,768 (22.55) | 1,251 (25.00) |
| 2-Low | 340,677 (19.84) | 71,979 (19.95) | 4,106 (19.42) | 1,069 (21.37) |
| 3-Moderate | 355,559 (20.70) | 75,261 (20.86) | 4,551 (21.52) | 1,033 (20.65) |
| 4-High | 339,336 (19.76) | 70,649 (19.58) | 4,316 (20.41) | 900 (17.99) |
| 5-Highest | 257,540 (14.99) | 53,113 (14.72) | 3,407 (16.11) | 750 (14.99) |
| Unknown | 91,508 (5.06) | 20,856 (5.46) | 1,285 (5.73) | 317 (5.96) |
| Person-time, median (IQR), y | 5.0 (2.0, 9.4) | 5.2 (2.1, 9.7) | 6.0 (2.6, 10.2) | 6.9 (2.7, 12.6) |
| History of asthma | 169,679 (9.38) | 49,782 (13.04) | 6,094 (27.17) | 1,222 (22.97) |
| History of allergic rhinitis | 75,050 (4.15) | 23,935 (6.27) | 2,870 (12.79) | 521 (9.79) |
| Adult cohort | N=2,678,888 | N=410,867 | N=196,101 | N=18,115 |
| Age, median (IQR), y | 47 (32, 64) | 45 (30, 63) | 50 (34, 68) | 47 (32, 63) |
| Sex | ||||
| Female | 1,445,589 (53.96) | 256,071 (62.32) | 109,404 (55.79) | 10,736 (59.27) |
| Male | 1,233,299 (46.04) | 154,796 (37.68) | 86,697 (44.21) | 7,379 (40.73) |
| Body mass index, kg/m2 | ||||
| Underweight (<18) | 72,655 (2.71) | 11,504 (2.80) | 4,150 (2.12) | 525 (2.90) |
| Normal (18.5–24.9) | 911,449 (34.02) | 152,480 (37.11) | 66,015 (33.66) | 6,972 (38.49) |
| Overweight (25–29.9) | 707,292 (26.40) | 109,693 (26.70) | 56,021 (28.57) | 4,799 (26.49) |
| Obese (30–34.9) | 285,567 (10.66) | 44,998 (10.95) | 24,088 (12.28) | 1,900 (10.49) |
| Severely Obese (35–39.9) | 94,373 (3.52) | 15,720 (3.83) | 8,486 (4.33) | 653 (3.60) |
| Morbidly Obese (>40) | 44,721 (1.67) | 8,341 (2.03) | 4,525 (2.31) | 343 (1.89) |
| Unknown | 562,831 (21.01) | 68,131 (16.58) | 32,816 (16.73) | 2,923 (16.14) |
| Smoking status | ||||
| Never | 1,293,811 (48.30) | 206,577 (50.28) | 89,588 (45.68) | 8,653 (47.77) |
| Current | 576,463 (21.52) | 84,855 (20.65) | 44,195 (22.54) | 3,914 (21.61) |
| Former | 548,828 (20.49) | 92,290 (22.46) | 48,636 (24.80) | 4,182 (23.09) |
| Unknown | 259,786 (9.70) | 27,145 (6.61) | 13,682 (6.98) | 1,366 (7.54) |
| Drinking status | ||||
| Never | 300,614 (11.22) | 51,208 (12.46) | 24,278 (12.38) | 2,338 (12.91) |
| Current | 1,655,958 (61.82) | 262,008 (63.77) | 125,921 (64.21) | 11,525 (63.62) |
| Former | 114,596 (4.28) | 19,708 (4.80) | 10,187 (5.19) | 965 (5.33) |
| Unknown | 607,720 (22.69) | 77,943 (18.97) | 35,715 (18.21) | 3,287 (18.15) |
| Townsend deprivation index | ||||
| 1-Lowest | 677,724 (26.39) | 102,924 (26.20) | 46,708 (24.99) | 4,685 (27.26) |
| 2-Low | 564,890 (22.00) | 84,924 (21.61) | 40,579 (21.71) | 3,821 (22.23) |
| 3-Moderate | 534,554 (20.82) | 81,331 (20.70) | 39,255 (21.00) | 3,566 (20.75) |
| 4-High | 468,773 (18.25) | 73,004 (18.58) | 35,452 (18.97) | 3,038 (17.67) |
| 5-Highest | 322,027 (12.54) | 50,711 (12.91) | 24,936 (13.34) | 2,079 (12.09) |
| Unknown | 110,920 (4.14) | 17,973 (4.37) | 9,171 (4.68) | 926 (5.11) |
| Person-time, median (IQR), y | 5.0 (2.1, 9.2) | 4.9 (2.1, 9.2) | 5.2 (2.2, 9.4) | 5.4 (2.1, 10.4) |
| History of asthma | 346,024 (12.92) | 80,267 (19.54) | 42,608 (21.73) | 4,584 (25.30) |
| History of allergic rhinitis | 266,083 (9.93) | 66,023 (16.07) | 29,926 (15.26) | 3,062 (16.90) |
Abbreviations: AD, atopic dermatitis; IQR, interquartile range; THIN, The Health Improvement Network
BMI, drinking, and smoking status were not examined in the pediatric cohort due to high rates of missing data
Table 2:
Baseline characteristics of sub-cohort of patients with history of asthma in THIN database, 1994 to 2015
| Characteristic, N (%) | No AD | Mild AD | Moderate AD | Severe AD |
|---|---|---|---|---|
| Pediatric cohort | N=169,679 | N=49,782 | N=6,094 | N=1,222 |
| Age, median (IQR), y | 9 (5, 13) | 9 (5, 13) | 12 (8, 15) | 9 (6, 12) |
| Sex | ||||
| Female | 67,278 (39.65) | 21,507 (43.20) | 2,786 (45.72) | 509 (41.65) |
| Male | 102,401 (60.35) | 28,275 (56.80) | 3,308 (54.28) | 713 (58.35) |
| Townsend deprivation index | ||||
| 1-Lowest | 36,036 (22.25) | 10,768 (22.75) | 1,250 (21.54) | 264 (22.78) |
| 2-Low | 31,356 (19.36) | 9,158 (19.35) | 1,161 (20.01) | 246 (21.23) |
| 3-Moderate | 33,461 (20.66) | 9,764 (20.63) | 1,229 (21.18) | 233 (20.10) |
| 4-High | 33,852 (20.90) | 10,029 (21.19) | 1,215 (20.94) | 215 (18.55) |
| 5-Highest | 27,248 (16.82) | 7,613 (16.08) | 948 (16.34) | 201 (17.34) |
| Unknown | 7,726 (4.55) | 2,450 (4.92) | 291 (4.78) | 63 (5.16) |
| Person-time, median (IQR), y | 6.8 (3.1, 11.5) | 7.2 (3.2, 11.8) | 6.8 (3.3, 11.0) | 10.2 (4.3, 14.2) |
| History of allergic rhinitis | 23,127 (13.63) | 9,422 (18.93) | 1,453 (23.84) | 292 (23.90) |
| History of asthma exacerbation* | 55,354 (32.62) | 17,356 (34.86) | 2,463 (40.42) | 596 (48.77) |
| Adult cohort | N=346,024 | N=80,267 | N=42,608 | N=4,584 |
| Age, median (IQR), y | 42 (27, 63) | 37 (25, 56) | 41 (28, 60) | 37 (26, 57) |
| Sex | ||||
| Female | 188,738 (54.54) | 50,416 (62.81) | 24,139 (56.65) | 2,669 (58.22) |
| Male | 157,286 (45.46) | 29,851 (37.19) | 18,469 (43.35) | 1,915 (41.78) |
| Body mass index, kg/m2 | ||||
| Underweight (<18) | 12,950 (3.74) | 2,898 (3.61) | 1,142 (2.68) | 174 (3.80) |
| Normal (18.5–24.9) | 113,365 (32.76) | 29,515 (36.77) | 14,721 (34.55) | 1,809 (39.46) |
| Overweight (25–29.9) | 90,852 (26.26) | 20,280 (25.27) | 11,504 (27.00) | 1,150 (25.09) |
| Obese (30–34.9) | 42,558 (12.30) | 9,630 (12.00) | 5,508 (12.93) | 493 (10.75) |
| Severely Obese (35–39.9) | 16,771 (4.85) | 3,970 (4.95) | 2,120 (4.98) | 198 (4.32) |
| Morbidly Obese (>40) | 9,521 (2.75) | 2,378 (2.96) | 1,383 (3.25) | 135 (2.95) |
| Unknown | 60,007 (17.34) | 11,596 (14.45) | 6,230 (14.62) | 625 (13.63) |
| Smoking status | ||||
| Never | 161,762 (46.75) | 39,282 (48.94) | 19,419 (45.58) | 2,278 (49.69) |
| Current | 76,044 (21.98) | 17,731 (22.09) | 9,719 (22.81) | 970 (21.16) |
| Former | 84,255 (24.35) | 19,035 (23.71) | 11,094 (26.04) | 1,070 (23.34) |
| Unknown | 23,963 (6.93) | 4,219 (5.26) | 2,376 (5.58) | 266 (5.80) |
| Drinking status | ||||
| Never | 38,259 (11.06) | 9,458 (11.78) | 5,037 (11.82) | 561 (12.24) |
| Current | 209,365 (60.51) | 50,317 (62.69) | 27,281 (64.03) | 2,917 (63.63) |
| Former | 17,548 (5.07) | 4,061 (5.06) | 2,245 (5.27) | 233 (5.08) |
| Unknown | 80,852 (23.37) | 16,431 (20.47) | 8,045 (18.88) | 873 (19.04) |
| Townsend deprivation index | ||||
| 1-Lowest | 81,095 (24.40) | 18,593 (24.25) | 9,543 (23.53) | 1,088 (25.21) |
| 2-Low | 69,645 (20.96) | 15,726 (20.51) | 8,339 (20.56) | 989 (22.91) |
| 3-Moderate | 70,289 (21.15) | 16,112 (21.02) | 8,566 (21.12) | 882 (20.44) |
| 4-High | 65,474 (19.70) | 15,308 (19.97) | 8,224 (20.27) | 808 (18.72) |
| 5-Highest | 45,843 (13.79) | 10,921 (14.25) | 5,891 (14.52) | 549 (12.72) |
| Unknown | 13,678 (3.95) | 3,607 (4.49) | 2,045 (4.80) | 268 (5.85) |
| Person-time, median (IQR), y | 4.5 (1.9, 8.3) | 4.4 (1.8, 8.6) | 4.8 (2.0, 8.9) | 4.9 (1.8, 9.9) |
| History of allergic rhinitis | 77,369 (22.36) | 24,300 (30.27) | 12,297 (28.86) | 1,456 (31.76) |
| History of asthma exacerbation* | 149,342 (43.16) | 34,467 (42.94) | 20,404 (47.89) | 2,806 (61.21) |
Abbreviations: AD, atopic dermatitis; IQR, interquartile range; THIN, The Health Improvement Network
Asthma exacerbation defined by specific diagnosis codes for asthma exacerbation
Incidence rates of asthma, asthma exacerbations, and asthma hospitalizations among children were higher in the presence of AD and increased with greater AD severity (Table 3). Of all incident asthma cases, 96% of cases occurred before the age of 18 years. Adjusted for age, sex, socioeconomic status, and history of allergic rhinitis, the risk of new-onset asthma was about 2-fold greater among children with AD compared to those without AD (HR 1.96 [95% CI 1.93–1.98]) (Figure 1A). When stratified by AD disease severity, there was a dose-response relationship whereby more severe AD was associated with an increasingly higher risk of asthma (mild AD: HR 1.82 [1.80–1.85]; moderate AD: 3.24 [3.13–3.35]; severe AD: 3.70 [3.50–3.92]). Among children with asthma, the risk of incident asthma exacerbation was 63% higher overall among those with AD versus those without AD (HR 1.63 [1.59–1.68]), with the greatest risk among children with moderate or severe AD (HRs 2.33 [2.21–2.47] and 2.69 [2.45–2.95], respectively) (Figure 1A). Relative to children without AD, the risk of asthma-related hospitalization was 64% higher among all children with AD but 163–195% higher among those with moderate or severe AD (Figure 1A). Overall, 3,862 excess asthma exacerbations and 1,381 excess asthma hospitalizations were attributable to AD.
Table 3:
Crude incidence rates per 1,000 person-years and 95% confidence intervals for new-onset asthma among patients in full cohort and for asthma exacerbation and asthma-related hospitalization events among asthmatic patients in sub-cohort
| Incidence rates, per 1,000 person-years | ||||||||
|---|---|---|---|---|---|---|---|---|
| Pediatric cohort | Adult cohort | |||||||
| Outcome | No AD | Mild AD | Moderate AD | Severe AD | No AD | Mild AD | Moderate AD | Severe AD |
| Asthma | 8.41 (8.35–8.47) | 17.16 (16.97–17.36) | 21.99 (21.31–22.69) | 30.40 (28.79–32.10) | 4.10 (4.06–4.13) | 5.53 (5.42–5.64) | 6.70 (6.55–6.85) | 6.73 (6.30–7.18) |
| Asthma exacerbation* | 10.09 (9.93–10.25) | 16.66 (16.27–17.05) | 20.22 (19.21–21.29) | 26.04 (23.80–28.49) | 12.80 (12.64–12.96) | 15.06 (14.66–15.46) | 17.05 (16.57–17.54) | 17.24 (15.99–18.58) |
| Asthma-related hospitalization^ | 3.00 (2.92–3.09) | 4.76 (4.57–4.96) | 6.76 (6.23–7.34) | 8.50 (7.37–9.80) | 6.09 (5.99–6.20) | 6.54 (6.30–6.79) | 7.89 (7.59–8.21) | 8.91 (8.09–9.81) |
Defined by specific diagnosis code for asthma exacerbation
Defined by hospitalization within 14 days after asthma diagnosis code
Figure 1: Adjusted risk of asthma, asthma exacerbations, and asthma-related hospitalizations in the pediatric and adult cohorts in THIN database, 1994 to 2015.
Pediatric models were adjusted for age, sex, allergic rhinitis, and Townsend index. Adult models were adjusted for age, sex, allergic rhinitis, Townsend index, body mass index, smoking, and alcohol status.
For all outcomes, sensitivity analyses restricted to patients seen at least annually during follow-up resulted in only slight attenuation of the effects observed in the primary analyses (Table 4). Similarly, sensitivity analyses restricted to patients with at least 5 years of follow-up or with at least 1 year of data prior to cohort entry resulted in nearly identical findings as the primary analyses. When asthma exacerbation was alternatively defined by the presence of an asthma diagnosis code with a systemic corticosteroid prescription within 3 days, the results also remained similar (Table 4). To distinguish adult-onset and pediatric-onset outcomes, we also included a sensitivity analysis restricting to only those with outcome onset prior to age 18 which showed similar results to the primary analysis (Table S1). An additional sensitivity analysis stratified by age <4 years and ≥4 years showed findings similar to the main effects (Table S2).
Table 4:
Sensitivity analyses for new-onset asthma among patients in full cohort, and for asthma exacerbation events among asthmatic patients in sub-cohort
| Adjusted hazard ratios* (95% CI) [ref: no AD] | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Pediatric cohort | Adult cohort | |||||||||
| Outcome | N | Overall AD | Mild AD | Moderate AD | Severe AD | N | Overall AD | Mild AD | Moderate AD | Severe AD |
| New-onset asthma in full cohort | ||||||||||
| Primary analysis | 1,888,247 | 1.96 (1.93, 1.98) | 1.82 (1.80, 1.85) | 3.24 (3.13, 3.35) | 3.70 (3.50, 3.92) | 2,711,096 | 1.38 (1.36, 1.40) | 1.27 (1.25, 1.30) | 1.52 (1.48, 1.55) | 1.58 (1.48, 1.69) |
| Restricted to patients seen at least yearly during follow-up | 1,639,134 | 1.85 (1.82, 1.87) | 1.72 (1.70, 1.75) | 2.97 (2.88, 3.07) | 3.43 (3.24, 3.63) | 2,493,235 | 1.35 (1.33, 1.37) | 1.25 (1.22, 1.27) | 1.48 (1.45, 1.52) | 1.54 (1.44, 1.64) |
| Restricted to patients with ≥5 years of follow-up | 941,729 | 1.97 (1.94, 2.00) | 1.82 (1.80, 1.85) | 3.26 (3.14, 3.38) | 3.72 (3.50, 3.96) | 1,384,225 | 1.36 (1.34, 1.39) | 1.26 (1.23, 1.29) | 1.49 (1.46, 1.54) | 1.57 (1.46, 1.69) |
| Restricted to patients followed for ≥1 year prior to cohort entry | 1,130,282 | 1.68 (1.65, 1.72) | 1.60 (1.56, 1.63) | 2.46 (2.34, 2.60) | 3.03 (2.73, 3.36) | 2,350,999 | 1.35 (1.33, 1.38) | 1.26 (1.23, 1.29) | 1.47 (1.43, 1.51) | 1.55 (1.44, 1.67) |
| Asthma exacerbation# in asthmatic sub-cohort | ||||||||||
| Primary analysis | 298,880 | 1.63 (1.59, 1.68) | 1.50 (1.46, 1.55) | 2.33 (2.21, 2.47) | 2.69 (2.45, 2.95) | 473,806 | 1.21 (1.18, 1.24) | 1.13 (1.10, 1.17) | 1.30 (1.26, 1.34) | 1.37 (1.27, 1.48) |
| Outcome defined by systemic corticosteroid prescription within 3 days of asthma code | 288,505 | 1.62 (1.58, 1.67) | 1.49 (1.44, 1.53) | 2.37 (2.24, 2.50) | 2.68 (2.44, 2.94) | 438,072 | 1.24 (1.22, 1.27) | 1.13 (1.10, 1.16) | 1.34 (1.30, 1.38) | 1.67 (1.56, 1.78) |
| Restricted to patients seen at least yearly during follow-up | 281,964 | 1.60 (1.55, 1.64) | 1.47 (1.43, 1.51) | 2.25 (2.12, 2.38) | 2.62 (2.38, 2.87) | 451,273 | 1.20 (1.17, 1.23) | 1.12 (1.09, 1.15) | 1.28 (1.24, 1.32) | 1.35 (1.25, 1.45) |
| Restricted to patients with ≥5 years of follow-up | 205,776 | 1.64 (1.59, 1.69) | 1.50 (1.45, 1.55) | 2.34 (2.20, 2.48) | 2.71 (2.46, 2.99) | 249,231 | 1.20 (1.17, 1.23) | 1.11 (1.08, 1.15) | 1.29 (1.24, 1.33) | 1.38 (1.27, 1.50) |
| Restricted to patients followed for ≥1 year prior to cohort entry | 221,082 | 1.46 (1.41, 1.51) | 1.32 (1.27, 1.37) | 2.19 (2.04, 2.35) | 2.43 (2.13, 2.77) | 403,848 | 1.19 (1.16, 1.22) | 1.12 (1.09, 1.16) | 1.27 (1.23, 1.31) | 1.31 (1.20, 1.44) |
| Asthma-related hospitalization^ in asthmatic sub-cohort | ||||||||||
| Primary analysis | 315,040 | 1.64 (1.56, 1.71) | 1.44 (1.37, 1.52) | 2.63 (2.41, 2.88) | 2.95 (2.54, 3.42) | 511,650 | 1.20 (1.16, 1.24) | 1.14 (1.09, 1.19) | 1.23 (1.18, 1.29) | 1.44 (1.31, 1.59) |
| Restricted to patients seen at least yearly during follow-up | 297,183 | 1.60 (1.53, 1.68) | 1.41 (1.34, 1.49) | 2.54 (2.33, 2.78) | 2.88 (2.49, 3.34) | 487,747 | 1.19 (1.15, 1.23) | 1.13 (1.08, 1.18) | 1.22 (1.17, 1.27) | 1.43 (1.29, 1.57) |
| Restricted to patients with ≥5 years of follow-up | 215,580 | 1.69 (1.60, 1.77) | 1.47 (1.39, 1.56) | 2.71 (2.46, 2.98) | 3.10 (2.66, 3.63) | 266,405 | 1.19 (1.15, 1.23) | 1.13 (1.07, 1.18) | 1.21 (1.16, 1.27) | 1.44 (1.30, 1.61) |
| Restricted to patients followed for ≥1 year prior to cohort entry | 235,002 | 1.42 (1.33, 1.51) | 1.24 (1.16, 1.33) | 2.21 (1.96, 2.49) | 2.69 (2.19, 3.30) | 436,086 | 1.15 (1.11, 1.19) | 1.10 (1.05, 1.15) | 1.18 (1.13, 1.24) | 1.36 (1.21, 1.52) |
Adjusted for age, sex, Townsend score, and history of allergic rhinitis in both pediatric and adult cohorts and additionally adjusted for body mass index, smoking and alcohol status in adult cohort
Defined by specific diagnosis code for asthma exacerbation
Defined by hospitalization within 14 days after asthma diagnosis code
Adult cohort
A total of 625,083 adults with AD (65.7% mild, 31.4% moderate, 2.9% severe) were matched to 2,678,888 adults without AD. The median age was 47 (IQR 32–64) years in the non AD group and between 45 and 50 years in the AD groups, and there was a female predominance within all groups (Table 1). BMI, smoking and drinking, and socioeconomic status were similar between patients with AD and those without AD. Duration of follow-up was 5 years on average, with slightly longer follow-up among those with severe AD. The sub-cohort of asthmatic patients included 346,024 non-AD patients (12.9% of the total non-AD adult cohort) and 127,459 AD patients (20.4% of the total AD adult cohort). Compared to the overall cohort, the asthmatic sub-cohort was slightly younger (median age 37 to 42 years) and had shorter follow-up time (4.4 to 4.9 years) (Table 2).
Incidence rates of asthma, asthma exacerbations, and asthma hospitalizations among adults were higher in the presence of AD and increased with greater AD severity (Table 3). Adjusted for age, sex, socioeconomic status, BMI, smoking and alcohol status, and history of allergic rhinitis, the risk of incident asthma was 38% higher overall among patients with AD compared to those without AD (HR 1.38 [95% CI 1.36–1.40]). When stratified by AD severity, patients with mild AD had a 27% greater risk of asthma while those with moderate or severe AD had a 52–58% greater risk of asthma (Figure 1B). Among adults with asthma, the risk of asthma exacerbation was 21% higher overall in adults with AD compared to those without AD, and more severe AD was associated with increasingly greater risk of asthma exacerbation (mild AD: HR 1.13 [1.10–1.17]; moderate AD: 1.30 [1.26–1.34]; severe AD: 1.37 [1.27–1.48]). Similar effects were observed for asthma-related hospitalization in the asthmatic sub-cohort (Figure 1B). Overall, 1,843 excess exacerbations and 891 excess hospitalizations were attributable to AD.
Similar to the pediatric cohort, when asthma exacerbation was alternatively defined by asthma diagnosis code with a systemic corticosteroid prescription, the effects of AD and AD severity on asthma exacerbation risk remained similar. Other sensitivity analyses also led to similar findings as the primary analyses (Table 4).
Discussion
In this study, we observed significantly higher risk of incident asthma, asthma exacerbations, and hospitalizations, among patients with AD. AD was associated with a 96% increased risk of asthma among children and a 38% increased risk among adults. The risk of asthma exacerbation or hospitalization was 50–195% higher in children and 13–44% higher in adults with AD compared to patients with asthma but without AD. Additionally, the magnitude of these risks increased in parallel with AD severity, whereby patients with moderate to severe AD had the highest risk for incident asthma and asthma exacerbation outcomes.
Our findings of increased risk of incident asthma diagnosis among children with AD align with the results of previous cohort studies including several birth cohorts. (7, 10, 20, 33) In one meta-analysis of 13 prospective cohort studies, the prevalence of asthma at 6 years of age was 30–36% among children with AD and the pooled odds ratio for asthma after AD onset was 2.14 (95% CI 1.67–2.75) among the birth cohort studies. (7) However, this systematic review focused primarily on cohort studies of young children who developed AD before 4 years old. We also observed an increasing risk of incident asthma with AD severity, similar to previous studies; however, previous studies that examined AD severity were primarily cohort studies that collected data via parent-reported symptoms, unlike our study which more objectively defined severity based on treatments and referrals. (13, 34, 35)
Unlike most previous cohort studies focused on pediatric populations, we also evaluated asthma risk among adults. While incident asthma risk remained significantly elevated among adults with AD compared to adults without AD, the magnitude of risk was lower than that in children, suggesting that the atopic march may occur less commonly among older patients with AD and also aligning with previous research showing lower risk of asthma among individuals with later-onset AD. (36, 37) It has been postulated that adult AD and pediatric AD are distinct endotypes, (38) and underlying molecular differences in cytokine activation and epidermal barrier changes could account for the variation in asthma risk between children and adults. It is also possible that asthma endotypes arising in adulthood are more heterogeneous, with only certain asthma subtypes being more associated with AD in adults. (39) In one of the few cohort studies investigating the atopic march in adulthood, childhood-onset AD was associated with new-onset ‘atopic’ asthma—defined by positive skin prick test to aeroallergen(s)—by middle age but not with ‘non-atopic’ asthma. (19) Finally, there may be overlap or misclassification between asthma and chronic obstructive pulmonary disease among adults which could have contributed to our findings.
Our findings suggest that the presence of AD, especially when more severe, increases not only the risk of developing asthma but also the severity of the asthma. Few previous studies have measured the risk of asthma exacerbation or hospitalization relative to AD and AD severity. One South Korean population-based cohort study using claims data showed AD was associated with more frequent asthma exacerbations among adults with mild or moderate asthma, though results in the severe asthma group were not statistically significant due to small sample size (n=233); however, this study did not examine the impact of AD severity or pediatric patients. (40) Previous cross-sectional studies have similarly found increased use of oral corticosteroids, increased emergency visits for asthma, and inadequate asthma control among children with AD. (41) Moreover, null mutations in the filaggrin gene (FLG), which are highly associated with AD and with more severe or persistent AD, appear to be associated with worse asthma severity. (42)
Asthma development is more common among patients with early-onset and persistent AD, null mutations in FLG, and allergic polysensitization, all of which likely contribute to the clinical severity of AD and progression through the atopic march. (9, 12, 34, 35, 43–45) Though the exact mechanisms underlying the atopic march require further characterization, shared pathophysiological links between asthma and AD likely contribute. (46) Thymic stromal lymphopoietin (TSLP), a Th2 cytokine expressed by keratinocytes and systemic biomarker of skin barrier defects, has been shown to trigger bronchial hyperresponsiveness, while its deletion prevents the atopic march from occurring. (46) Meanwhile, superantigen enterotoxin B, produced by Staphylococcus aureus which often colonizes the skin of AD patients, synergistically drives eczematous skin changes and promotes airway hyperreactivity and lung inflammation on allergen exposure. (46)
Although AD is traditionally considered an atopic disease akin to asthma, it has also been linked to many other non-atopic comorbidities. In other studies using the same or similar cohorts as in our current study, AD has been associated with an 18–52% increased risk of infectious outcomes such as herpes simplex virus or varicella zoster virus infection and serious infections (47); 19–27% increased risk of dementia; (48) 14–48% increased risk of depression, anxiety, and obsessive compulsive disorder (49, 50); 19–48% increased risk of lymphoma; (51) and 21–27% increased risk of myocardial infarction or stroke (52, 53) and 62% increased risk of mortality (54) in adults with severe AD. Notably, the 38–96% increased risk of asthma observed in our cohort of patients with AD is not exceedingly different than that of some of these non-atopic comorbidities. More research on the association of AD with non-atopic disorders, including non-atopic forms of asthma, may help clarify the degrees to which AD is a risk factor for both recognized atopic, and less recognized non-atopic, comorbidities.
Strengths of our study include its large sample size, longitudinal nature, examination of asthma risk by AD severity, and inclusion of both adults and children. Unlike prior cohort studies in children which focus on early-childhood onset AD, our study also analyzes risk in the later childhood years and how AD severity defined by treatment (rather than patient-reported symptoms) contributes to this risk. We additionally analyze asthma risk among adults, enabling direct comparisons of effect size between pediatric and adult populations. Finally, our study is one of the few cohort studies to measure risk of asthma exacerbations or hospitalizations in AD patients.
However, several potential limitations are noted. First, misclassification of AD severity is possible; however, using treatment as a proxy measure is a common approach since direct severity measures are unavailable in routinely collected electronic health data. (26, 51) The time-updated definitions for AD severity in this study may also result in misclassification for a waxing and waning disease like AD; some patients who are defined as having moderate or severe AD may experience subsequent improvement. Such misclassification would be expected to bias hazard ratios toward the null and may have impacted our findings, particularly for children who may experience improvement in AD symptoms over time. Ascertainment bias is another potential concern as patients with AD may have more frequent medical visits or tests which could lead to earlier diagnosis of asthma and related symptoms. However, sensitivity analyses limited to patients with annual GP visits led to similar findings. Finally, the duration of study follow-up is short, but sensitivity analyses restricted to patients with at least 5 years’ follow-up demonstrated similar results.
In summary, AD is associated with higher incident risk of asthma, consistent with the model of the atopic march, and both the presence and severity of AD increase risk for asthma-related exacerbation and hospitalization. However, these associations are much more pronounced in children than in adults. Further work is thus needed to understand the relationships between various endotypes of AD and asthma and how they may differ by age. As novel immunomodulatory medications for AD continue to emerge, their effects on asthma development and severity will be of great interest, with the hope that future therapies may curtail progression along the atopic march.
Supplementary Material
Highlights:
What is already known about this topic?
Atopic dermatitis (AD) is thought to predispose to asthma development via the atopic march, and birth cohort studies to date have supported this notion, finding a higher incidence of asthma in children with AD.
What does this article add to our knowledge?
Studies of AD and asthma that account for the impact of AD severity and the severity of asthma outcomes are limited. Our study further characterizes asthma risk related to AD in both children and adults.
How does this study impact current management guidelines?
Risk of asthma and subsequent asthma-related exacerbation and hospitalization increase with the presence and severity of AD, especially in children. Those with more severe AD may benefit from increased attention to control of their asthma.
Funding sources:
This study was supported by a contract from Pfizer, Inc. paid to the Trustees of the University of Pennsylvania (JMG). The academic authors designed and executed the study with input from the sponsor. The academic authors had final approval over the manuscript. Support for this work was provided by the Penn Skin Biology and Diseases Resource-based Center, funded by NIH/NIAMS grant P30-AR069589 and the University of Pennsylvania Perelman School of Medicine.
Conflicts of interest:
J.W. has received research and fellowship funding from Pfizer, Inc. (paid to Johns Hopkins University), research funding from the National Eczema Association (paid to Johns Hopkins University), and honoraria for serving as a consultant to Janssen and Sun Pharmaceuticals (DMC). M.S. has received fellowship funding from Pfizer, Inc. (paid to the University of Pennsylvania). K.A. has received research funding from Pfizer, Inc. and L’Oréal (paid to UCSF), and receives consulting fees for serving on the academic steering committee for TARGET RWE. A.R.L. is an employee of Pfizer, Inc. J.M.G. has served as a consultant for Abcentra, Abbvie, BMS, Boehringer Ingelheim, GSK, Lilly (DMC), Janssen Biologics, Novartis Corp, UCB (DSMB), Neuroderm (DSMB), Trevi, and Mindera Dx., receiving honoraria; and receives research grants (to the Trustees of the University of Pennsylvania) from Boehringer Ingelheim, and Pfizer Inc.; and received payment for continuing medical education work related to psoriasis that was supported indirectly by pharmaceutical sponsors; is a co-patent holder of resiquimod for treatment of cutaneous T cell lymphoma; serves as a Deputy Editor for the Journal of Investigative Dermatology receiving honoraria from the Society for Investigative Dermatology; is Chief Medical Editor for Healio Psoriatic Disease (receiving honoraria); and is a member of the Board of Directors for the International Psoriasis Council, receiving no honoraria. D.B.S. and S.W. have no disclosures to report.
Abbreviations:
- AD
atopic dermatitis
- BMI
body mass index
- CI
confidence interval
- HR
hazard ratio
- THIN
The Health Improvement Network
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Data sharing statement:
The data that support the findings of this study are available from Cegedim Health Data, which oversees The Health Improvement Network. Restrictions apply to the availability of these data, which were used under license for this study.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from Cegedim Health Data, which oversees The Health Improvement Network. Restrictions apply to the availability of these data, which were used under license for this study.