Epidemiology of Pertussis and Pertussis-Related Complications in Adults: A German Claims Data Analysis
verfasst von:
Bastian Surmann, Julian Witte, Manuel Batram, Carl Peter Criée, Christiane Hermann, Andreas Leischker, Jörg Schelling, Mirko Steinmüller, Klaus Wahle, Alexander F. Heiseke, Pavo Marijic
Pertussis is a highly contagious respiratory infection. It affects people of all ages, yet evidence of the impact of pertussis in adults with underlying conditions (UCs) is scarce. This study investigated the incidence and complication rate of pertussis in adult patients with and without UC.
Methods
A retrospective analysis was conducted using routinely collected German claims data between 2015 and 2019. Patients with and without different pneumological, cardiovascular, endocrinological, musculoskeletal, and psychological UCs were matched for incidence estimation. Logistic regression models were used to estimate the risk of pertussis depending on the presence of UCs. Negative binomial models were used to assess complication rates in patients with pertussis and with and without UC.
Results
In total, 4383 patients were diagnosed with pertussis during the study period. Patients with any UC had an increased risk for pertussis compared to matched patients without UC (odds ratio [OR] 1.72; 95% confidence interval [CI]1.60–1.84, p < 0.0001). Underlying asthma had the highest risk of pertussis (OR 2.70; 95% CI 2.50–2.91, p < 0.0001), followed by chronic obstructive pulmonary disease (OR 2.35; 95% CI 2.10–2.60, p < 0.0001) and depression (OR 2.08; 95% CI 1.95–2.22, p < 0.0001). Severe complications occurred in 10.8% of the pertussis cohort (13.4% with UC vs. 9.5% without UC). The UC-attributable effect on the risk of severe pertussis-related complications was significantly increased for any UC (incidence rate ratio [IRR] 1.29, 95% CI 1.19–1.39). The severe complication risk was also increased for patients aged 60+ (IRR 1.59, 95% CI 1.46–1.72).
Conclusion
This study shows that adults with certain UCs have an increased risk for pertussis and are more likely to have complications. These results provide further evidence that pertussis is a relevant and impactful infectious disease in adults with and without certain UC, indicating that these patients need to be considered when developing vaccination recommendations to avoid pertussis and its associated complications.
A graphical abstract is available with this article.
Alexander F. Heiseke and Pavo Marijic share last authorship.
Publisher's Note
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Key Summary Points
Why carry out this study?
Evidence on pertussis burden in patients with underlying conditions is scarce but needed for an accurate evaluation of vaccination recommendations and implementation of policy measures in at-risk populations.
This study aims to investigate the incidence and complication rate of pertussis in adults with and without underlying conditions.
What was learned from the study?
The risk of pertussis incidence and pertussis-associated complications is higher in patients with underlying conditions compared to other persons.
Patients with any considered underlying condition, but especially with asthma, chronic obstructive pulmonary disease, and depression, have a significant increased risk of pertussis.
Besides present underlying conditions, age (60+ years) is an additional risk factor for pertussis-related severe complications such as hospitalization.
Digital Features
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Introduction
Pertussis (also known as whooping cough) is a highly contagious bacterial disease caused by the bacterium Bordetella pertussis that mainly affects the upper respiratory tract [1]. Pertussis is widely considered a childhood disease. In adults, the disease often only manifests itself with atypical non-specific symptoms such as rhinitis, prolonged cough, and sometimes fever, which are usually associated with a common cold. Hence, these symptoms can be misinterpreted as a common cold, though the duration of pertussis is considerably longer and can last up to months [2].
Despite a recommendation of the German Standing Committee on Vaccination (STIKO) to vaccinate adults against pertussis, vaccination rates in adults are relatively low. Based on national vaccination coverage data, more than 50% do not receive a booster in adulthood and the incidence of pertussis remains high in all age groups, with more than 60% of all cases in patients aged 18 years and older, and more than 30% in patients aged 50 years and older [3]. Even fatal pertussis courses have recently been recorded in the 65+ age group [4]. In Germany, pertussis became notifiable in eastern federal states in 2002 and nationwide in March 2013. Yet, underreporting is expected to be around 21–40% [5] indicating that the real burden due to pertussis disease might be higher, given the challenges regarding detecting the disease, especially in adults: pertussis often shows atypical symptoms and, hence, likely underreporting in national surveillance statistics [6, 7].
International evidence suggests that patients 50+ years of age and patients with certain underlying conditions (UCs), i.e., chronic illnesses, are at increased risk of hospitalization and complications of pertussis [4, 8]. However, in most surveillance systems, there is little information about the characteristics of people affected by an infectious disease. For example, in the official national surveillance statistics of the use of German healthcare system [9], no differentiation between at-risk and non-at-risk populations can be made.
This study aims to determine the incidence of pertussis and pertussis-associated severe complications in adults with and without UCs. As evidence on the burden of pertussis in Germany among adults with UCs is lacking, we also aim to determine the disease burden of pertussis in adults with and without UCs.
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Material and Methods
Study Design
The study uses a retrospective, matched cohort design, and has been conducted in accordance with applicable subject privacy requirements and the guiding principles of the Declaration of Helsinki of 1964. The analysis was based on secondary claims data and, as such, the consultation of an ethics committee was not required [10].
Database
Analyses were based on anonymized routinely collected claims data from the German Statutory Health Insurance (SHI), covering the period of 2015–2019. The dataset comprises information on up to five million people insured at 19 sickness funds, representing 6.3% of the SHI population in Germany. The data is provided by GWQ ServicePlus AG, a joint venture of medium-sized health insurers in Germany. Overall, 87% of the German population is insured within the SHI system [11]. Based on comparison with official statistics published by the Germany Health Ministry on the German statutory health insurance (“KM6”), the dataset is representative of the German SHI population in terms of age and gender distribution [12]. Diagnostic data include all diagnoses documented during physician outpatient contacts and patient hospital stays. Laboratory or clinical parameters were not included. A general description of the claims database in the German setting can be found in Swart et al. [10].
Study Population
The initial dataset contained all adults aged 18 years and older in the years 2015–2019. Individual information on the year of birth is aggregated to 5-year intervals in the anonymization process. To ensure that all patients are at least 18 years of age, the age was computed as the difference between the year under study and the upper bound of the age interval.
Based on the literature and in consultation with a medical expert panel, the following UCs were defined as potential risks: asthma, chronic obstructive pulmonary disease (COPD), osteoporosis, rheumatoid arthritis, depression, immunodeficiency, heart failure (HF), chronic heart disease (CHD), chronic kidney disease (CKD), diabetes mellitus type 2 (DMT2), and diabetes mellitus type 1 (DMT1). While there may be other UCs with an impact on pertussis, in this manuscript UCs always refer to these risk constellations. For a detailed description of how these diagnoses were validated with the corresponding International Classification of Diseases (ICD), 10th revision, German Modification (ICD-10-GM) diagnosis codes and prescription codes (based on the Anatomical Therapeutic Chemical [ATC] Classification), see Table S1.
An individual was identified as having a specific UC if either an inpatient or an assured outpatient diagnosis was documented in at least two out of four quarters of two consecutive years. Patients were included in the study population if they were diagnosed with the respective UC in the years from 2016 to 2019. As the year under consideration always had to be validated by the previous year, data from 2015 was used as a wash-in period. A patient may belong to more than one UC group. A matched cohort design was adopted; patients with at least one UC were matched to controls without UC by exact matching. Matching variables also included age in 5-year intervals and sex of the patients. Matched pairs were observed for the same period of time (until one of them died or left the SHI).
Pertussis was broadly defined as having at least one diagnosis of ICD-10-GM A37.0 (Whooping cough due to Bordetella pertussis) or A37.9 (Whooping cough, unspecified). The diagnosis could either be in- or outpatient. As a sensitivity analysis, a narrow definition only considering the diagnosis of ICD-10 A37.0 is reported. Incident pertussis cases were defined as cases without a pertussis diagnosis in the preceding year; hence, information from 2015 was again used as washout period. The index quarter was defined as the quarter when pertussis was first observed.
A pertussis-associated complication was counted if it occurred in the index quarter and was not observed in the four quarters preceding the index quarter and, hence, was incident (except for hospital visits). We distinguished between severe and less severe complications. Severe complications comprised pneumonia, rib fractures, and all-cause hospitalizations but not including the following less severe complications. Otitis media, encephalopathy, abnormalities of breathing, seizures, inguinal and umbilical hernia, intracranial hemorrhage, incontinence, loss of weight, sarcopenia, and gait abnormality were counted as less severe complications (see Table S2 in the supplementary material for used ICD-10-GM codes). Results were also summarized as any complications that occurred. In the sensitivity analyses, the complication could also be diagnosed in the quarter prior to the index quarter and/or in the quarter following the index quarter. In the following, data based on the broad pertussis definition are presented unless described otherwise.
Statistical Analysis
In the analysis of pertussis incidence, rates were calculated for both the narrow and the broad definitions of pertussis and reported separately for patients with any UC, with no UC, and with one of the specific UCs, as well as for age groups (i) 18–49, (ii) 50–59, and (iii) 60 and older.
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To analyze the risk of pertussis for each UC, logistic regression models, controlled for age and sex, were fitted to the pooled data of the matched population (cases and controls) from 2016 to 2019. Separate models were fitted for patients with any UC, and for each UC compared to matched persons without UC respectively. In a sensitivity analysis, a model with all UCs as covariates was fitted to check the robustness of the results. As a result of small sample sizes for the narrow case definition, a model with a single coefficient for any UC was fitted, not considering each UC separately. The resulting odds ratios are reported with corresponding 95% confidence intervals (CIs).
In the analysis of pertussis-associated complications, patients with pertussis and UCs were compared to patients with pertussis and no UC. A complication was considered to be pertussis-associated, if it was observed in the same quarter as the pertussis. Complications were counted for all years under study and reported as complication rates in patients with pertussis and with UC and without UC. To estimate the incidence rate of complications, a negative binomial regression model controlled for age, sex, and any UCs was fitted to the number of individual complications in the pertussis cohort. The analyses for complications were rerun in sensitivity analyses, where complications could also be observed in the quarter before or after the pertussis quarter.
To assess whether there is an association between specific age groups and the risk of complications, a negative binomial regression model, including age groups 18–49, 50–59, and 60+ as covariates, was estimated.
All analyses were performed with R (version 4.1.3) using the MatchIt package for matching, the glm function for logistic regression models, and the glm.nb function of the MASS package for negative binomial regression models.
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Results
Study Cohort
The size and the characteristics of the study cohorts with and without UC are shown in Table 1. The number of patients with UC ranged from 787,123 in 2016 to 898,479 in 2019, and the number of patients without UC ranged from 2.5 million in 2016 to 2.7 million in 2019. The average age of patients without UC in the years of the study was between 43.1 and 44.6 years and was substantially lower than the age of patients with UC, which was between 60.3 and 60.7 years. The difference between the two study cohorts is also reflected in the proportions of the respective age groups. The percentage of women in the group of patients with UC was always slightly higher than in the group of patients without UC over the years. Table S3 in the supplementary material shows the proportions of patients with specific UCs.
Table 1
Patient characteristics of the study cohorts with and without underlying condition (prior to matching)
2016
2017
2018
2019
UC
No UC
UC
No UC
UC
No UC
UC
No UC
Number of patients
787,123
2,585,614
827,756
2,567,771
870,587
2,743,228
898,479
2,708,832
Age (years)
Mean (SD)
60.4 (16.7)
44.6 (15.7)
60.6 (16.6)
43.1 (15.6)
60.3 (17.1)
43.7 (16.6)
60.7 (16.9)
43.8 (16.9)
Age groups (%)
18–49
22.3%
60.7%
23.4%
61.5%
25.4%
65.3%
26.2%
66.1%
50–59
22.1%
21.5%
22.8%
21.3%
23.2%
19.4%
23.8%
19.2%
> 60
55.6%
17.8%
53.8%
17.1%
51.5%
15.2%
50.0%
14.7%
Sex (%)
Male
46.6%
51.7%
46.8%
41.7%
46.8%
51.7%
46.7%
51.7%
Female
53.4%
48.3%
53.2%
48.3%
53.2%
48.3%
53.3%
48.3%
UC Underlying condition, SD standard deviation
Pertussis Incidence in Patients With and Without Underlying Condition
The patients’ characteristics in the matched population are shown in Table S4, where all patients with UC could be matched. The total number of pertussis cases and the annual incidence of pertussis in patients with and without UCs in the matched cohort are shown in Table 2. In all study years, the incidence of pertussis in persons with any of the UCs was between 28% and 101% higher than in persons with no UCs. The incidence of pertussis was highest among patients with asthma, COPD, rheumatoid arthritis, and depression. Overall, the annual incidence of pertussis showed little variation over the years observed. In addition, there appears to be a decreasing trend in pertussis incidence overall and, apart from depression, COPD, and CHD in pertussis cases in each UC.
Table 2
Total pertussis cases and pertussis incidence (cases per 100,000) in persons with underlying condition per year in the matched cohort
Underlying condition
2016
2017
2018
2019
Total pertussis cases
1136
1274
1055
918
Cases per 100,000
Total
33.7
37.5
29.3
25.5
No UC
31.6
32.6
24.2
20.4
Any UC
40.4
52.8
45.5
41.1
Asthma
58.0
69.0
64.0
54.6
COPD
51.5
57.8
33.3
48.4
Osteoporosis
30.0
46.8
50.1
44.7
Rheumatoid arthritis
70.9
59.9
65.3
42.5
Depression
47.0
58.7
47.6
57.7
Immunodeficiency
45.9
52.7
49.5
37.5
Heart failure
NA
23.6
41.6
32.5
Chronic heart disease
27.5
33.0
28.2
31.4
Chronic kidney disease
30.8
43.5
34.1
21.3
Type 2 diabetes
28.5
39.6
31.7
21.1
Type 1 diabetes
NA
41.3
NA
NA
NA sample sizes in the database n < 8, COPD chronic obstructive pulmonary disease, UC underlying condition
In the matched population overall, the incidence of pertussis was highest in patients aged 18–49 years and decreased with increasing age (Table 3). Except for the group of 18–49 years (2016), patients with UC generally had a higher pertussis incidence than patients without UC in all age groups 50+ years. The older the patients, the greater was the difference in pertussis incidence between patients with UC and patients without UC.
Table 3
Pertussis incidence (cases per 100,000) in persons with underlying condition per year and age group
UC
2016
2017
2018
2019
18–49
50–59
60+
18–49
50–59
60+
18–49
50–59
60+
18–49
50–59
60+
Total
65.9
26.8
11.1
68.7
32.6
12.4
53.6
21.0
10.6
45.3
19.3
8.5
No UC
69.1
22.0
6.2
68.6
24.7
5.0
51.7
14.0
3.8
42.5
11.0
3.3
Any UC
54.7
43.8
28.5
68.9
58.7
37.0
59.9
45.0
33.8
54.5
46.3
25.5
UC underlying condition
The results of the narrow case definition are presented in Tables S5 and S6 in the supplementary material, showing comparable results.
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Risk of Pertussis Incidence in Persons with Underlying Condition
Except for heart failure and type 1 diabetes, all considered UCs were associated with a significantly higher risk for pertussis (Fig. 1). With a 2.7-fold increase in odds, patients with asthma had the highest risk of incident pertussis diagnosis compared to those without asthma. This is followed by patients with COPD and with depression.
Fig. 1
Risk of pertussis incidence for each underlying condition separately, adjusted for age and sex. Rolling UC prevalence and pertussis incidence cohort, 2016–2019. CI confidence interval, COPD chronic obstructive pulmonary disease, OR odds ratio, UC underlying condition. Logistic regression models were used to estimate the risk of pertussis incidence. For each underlying condition and for the “Any UC” group, separate models were estimated. All models controlled for age and sex, but here only adjusted ORs for the UCs are reported
×
If the narrow case definition was used, the risk of pertussis was also increased with a slightly higher odds ratio (OR 1.89; 95% CI 1.63–2.15, p < 0.0001) as compared to the OR for the broad case definition (OR 1.72; 95% CI 1.60–1.84, p < 0.0001) for patients with any UC vs. patients without UC.
In the model including all UCs as covariates, the results differ slightly from the main analyses (Fig. S1 in the supplementary material). No significant results were observed for rheumatoid arthritis, heart failure, and chronic kidney disease. All other estimates were significant but had slightly lower ORs compared to the main analysis.
Pertussis-Related Complications
Overall, 10.8% of the pertussis cohort experienced a severe complication, with the rate of complications being higher in patients with any UC compared to those without UC (13.4% vs. 9.5%). Less severe complications occurred also more frequently in patients with any UC (6.4% vs. 5.3%). Regardless of severity, the three most frequently observed pertussis-related complications were hospitalizations (36% of complications), abnormalities of breathing (22%), and pneumonia (21%). The largest differences between patients with and without UC were observed in patients with and without osteoporosis (28.7% vs. 16.2%) and in patients with and without heart failure (31.1% vs. 16.3%). Smaller differences were observed for patients with depression, rheumatoid arthritis, and immunodeficiency. The complication rates and the differences in complication rates with and without respective UC are shown in Table 4.
Table 4
Incidence (%) and absolute difference (percentage points) of pertussis-related complications in patients with pertussis and with or without UCs
UC
Severe complications
Less severe complications
Overall
Hospitalization
Pneumonia
Rib fractures
Overall
%
∆
%
∆
%
∆
%
∆
%
∆
Disregarded
–
10.8
–
7.1
–
4.1
–
0.5
-
5.7
–
Any
Yes
13.4
3.9
8.5
2.2
5.5
2.1
0.7
0.3
6.4
1.1
No
9.5
6.3
3.4
0.4
5.3
Asthma
Yes
10.8
0.0
7.4
0.3
4.5
0.4
NA
NA
9.8
4.5
No
10.8
7.1
4.1
NA
5.3
COPD
Yes
13.8
3.1
9.0
2.0
7.2
3.2
NA
NA
7.2
1.6
No
10.7
7.0
4.0
NA
5.6
Osteo
Yes
20.0
9.4
12.2
5.2
7.8
3.8
NA
NA
8.7
3.1
No
10.6
7.0
4.0
NA
5.6
RA
Yes
14.3
3.5
NA
NA
NA
NA
NA
NA
5.2
− 0.5
No
10.8
NA
NA
NA
5.7
Depr
Yes
12.6
2.1
8.0
1.1
4.6
0.5
NA
NA
6.4
0.8
No
10.5
6.9
4.1
NA
5.6
Immun
Yes
13.6
3.1
8.2
1.3
5.6
1.7
NA
NA
5.9
0.2
No
10.5
7.0
4.0
NA
5.7
HF
Yes
29.5
19.0
19.7
12.8
14.8
10.8
NA
NA
1.6
− 4.1
No
10.6
6.9
4.0
NA
5.7
CHD
Yes
16.6
6.0
10.4
3.5
9.2
5.3
NA
NA
5.5
− 0.2
No
10.6
7.0
3.9
NA
5.7
CKD
Yes
16.9
6.2
NA
NA
11.7
7.7
NA
NA
3.9
− 1.8
No
10.7
NA
4.0
NA
5.7
DMT2
Yes
17.0
6.6
9.9
3.0
9.1
5.3
NA
NA
5.9
0.3
No
10.4
6.9
3.8
NA
5.7
DMT1
Yes
9.1
− 1.7
NA
NA
NA
NA
NA
NA
9.1
3.4
No
10.8
NA
NA
NA
5.7
NA sample sizes in the database n < 8, CHD chronic heart disease, CKD chronic kidney disease, COPD chronic obstructive pulmonary disease, Depr depression, HF heart failure, Immun immunodeficiency, Osteo osteoporosis, RA rheumatoid arthritis, DMT1 type 1 diabetes mellitus, DMT2 type 2 diabetes mellitus, UC underlying condition
Based on the negative binomial regression model, the UC-attributable effect on the risk of pertussis-related severe complications for any UC was 1.29 (95% CI 1.19–1.40, p = 0.0085). The severe complication risk was also increased for patients aged 60+ (incidence rate ratio [IRR] 1.59, 95% CI 1.46–1.71, p = 0.0001, see Fig. S2 in the supplementary material).
In the sensitivity analysis, which also considers complications occurring in the quarter before and after the quarter of pertussis incidence, the complication rate was considerably increased for nearly all UCs. Only the difference in the complication rate for rheumatoid arthritis remained almost the same. The complication rate for patients with COPD was more than three times higher when the quarters before and after pertussis incidence were taken into account. Table S7 shows the complication rates and the difference of complication rate for each UC. In the negative binomial model, a higher risk of severe complications was observed for patients with any UC, when compared to the model in the main analysis (IRR 1.71; 95% CI 1.63–1.79, p < 0.0001). When accounting for the quarters before and after pertussis incidence, the risk for those aged 60+ was even higher (IRR 1.53, 95% CI 1.43–1.63, p < 0.0001) (see Fig. S3 in the supplementary material).
Discussion
The aim of this study was to determine the incidence of pertussis in patients with and without UCs, and to investigate whether there is an association between UCs in general or certain UCs in particular and the risk of pertussis. Additionally, this study analyzed the occurrence of pertussis-related complications among all patients, as well as patients with and without UCs. To our knowledge, this is the first study to investigate the epidemiology of pertussis in adult patients with various UCs based on a large representative claims dataset in Germany. The results showed an increased risk of incident pertussis diagnoses in patients with UCs in comparison to patients without UC. This concerned almost all investigated UCs, with the greatest risk in patients with asthma, COPD, and depression. Similar to other studies, the risk of being diagnosed with pertussis decreased with age [13, 14]. The general finding of a decreasing pertussis incidence is in line with other recently published results from the UK [13, 14] and with data from German official surveillance statistics [9]. However, the difference between age groups was smaller for patients with UCs than for those without UCs. This study also found an increased risk of pertussis-related complications among patients with UCs, with hospitalizations, breathing abnormalities, and pneumonia being the most common complications.
Evidence on the risk of pertussis in patients with UCs is scarce. Most previous studies included only small sample sizes, ranging between 33 and 524 pertussis cases in patients with UCs [13, 15‐23]. Asthma and COPD are the most common UCs considered in published studies that show some signs of association with the risk of pertussis incidence [4, 8]. For asthma and COPD, the associated adjusted relative risk between the UC and pertussis incidence ranges between 1.64 to 4.06 [15, 17, 20]. Aris et al. and Bhavsar et al. reported incidence rates of pertussis in patients with asthma [16] and COPD [13] based on UK primary care datasets. For COPD, the reported pertussis incidence rate varied by year, with an average incidence rate of 4.73 (95% CI 3.74–5.91) per 100,000 person-years and incidence rates tended to decrease with increasing age [13]. Patients with underlying asthma had a higher incidence rate of 9.6 (95% CI 8.6–10.7) per 100,000 person-years compared to matched controls without asthma. While other studies on the risk of pertussis in patients with asthma relied on patient-reported diagnosis of pertussis, we relied on physicians’ diagnoses. Interestingly, the obtained risks were generally consistent with our findings [8]. Other studies examined the association of pertussis incidence and underlying heart disease [15, 19‐22], physical disabilities [15, 20], or obesity [15, 20]; two studies evaluated multiple UCs concurrently [21, 24]. These studies cover additional data on the associated risk of underlying gastroesophageal reflux disease, renal disease, autoimmune disease, and hyperlipidemia. Two systematic literature reviews have also already described the association of pertussis and UCs [4, 8]. These systematic reviews show relatively consistent results but also an open need for further research, especially regarding pertussis-associated complications and excess resource use and costs.
While age is not a relevant risk factor for developing pertussis, increasing age plays an important role in the likelihood of experiencing pertussis-related complications. This is in line with the results of several other studies, which have shown that complications occur with greater frequency as age increases [22]. In particular, the pertussis-related rate of hospitalization, the complication most commonly observed in this study, is substantially higher in adults aged 65 and over, and even higher in adults aged 75 and older [20, 25, 26].
The study design and methods face some limitations. First, there is no information on history of pertussis or pertussis vaccination prior to the observational period available to validate an incident study population. As a result of the too small number of cases, we have refrained from differentiating further age groups. However, evidence from the UK suggests that our finding of an absent age-related risk association of pertussis incidence might be biased [13]. In this regard, the effect of UCs and age may be underestimated in our study, as these patients may be more likely to receive vaccination compared to patients without comorbidities and those who are younger and therefore more protected. Second, the underlying data are collected for billing purposes. As no clinical parameters, laboratory test results, or information on health behavior are available in claims data, the analysis of pertussis in patients with UCs is limited by the available data. This relates to the risk of underdiagnosed pertussis cases, especially in persons without UC who may not see a doctor regularly. A comparison of laboratory data, notification data, and claims diagnosis data (only the last of these can be the basis of the present study because of separate data pools) would be a desirable approach to address epidemiological uncertainty [27]. Yet, at least in Germany, these data are stored in separate data pools which cannot be merged, mostly because of data protection concerns. Additionally, matching was limited to age, sex, and UC. Potentially relevant variables such as the patient’s socioeconomic status is not available for analysis because of data protection reasons. Third, the potential for upcoding must be considered for some of the reflected UCs and complications [28]. However, owing to our strict case definition (i.e., the UC had to be present in two consecutive years), this effect should be small. Fourth, self-selection of patients is possible. For example, patients with a severe underlying health condition might be more likely to seek pertussis-associated treatment (and thus be documented in claims data) than patients with fewer health problems. Therefore, the likelihood of being diagnosed with pertussis or being diagnosed with pertussis-related complications might increase with more regular visits to a practitioner, especially in patient with multimorbidity. However, for the complications, this effect might be low, as those are severe and diagnosed by the physician, and therefore less likely to be influenced by self-selection. Fifth, small sample sizes might lead to an underestimation of the UC-attributable effect in patient with heart failure and DMT1 that show no increased risk of pertussis. The strong risk association of underlying depression could in turn be explained by the increased levels of endogenous corticoids. Corticoid levels are continuously elevated in depression causing immunosuppression.
One of the primary strengths of this study is the large dataset, which includes a high number of pertussis cases and cases with UCs, providing a comprehensive database for the risk analyses. Additionally, the long observational period of 5 years allowed a better estimate of the risk association between UCs and pertussis as well as pertussis-associated complications. This study indicates that patients with UCs are vulnerable to pertussis and could require more protection. In addition, age is associated with a higher risk of pertussis-related complications.
Conclusions
This is the first analysis on the incidence of pertussis for populations with different UCs in the German healthcare setting, based on a representative claims dataset. The results confirm the higher incidence of pertussis diagnoses in German patients with certain UCs, as previously reported in the international context. However, these studies mostly focused on respiratory UCs. The present study confirms the significantly increased risk of incident pertussis diagnoses in persons with COPD and asthma, but also extends the knowledge about other relevant UCs such as osteoporosis, rheumatism, depression, immunodeficiency, chronic kidney disease, and type 2 diabetes. Thus, our findings have potential clinical implications regarding the implementation of vaccination recommendations for at-risk populations, especially in practical care guidelines (disease management program, guidelines).
Considering the consistent, yet still scarce evidence, further research is needed on the observed risk in persons with UCs. Primary data from physician practices and laboratory reference centers represent the best possible additional data source but are not publicly available. For this purpose, data from disease management programs would be useful as clinical and laboratory variables are recorded. Additionally, the pathogenetic mechanisms for the observed risks in depression, which was also associated with an increased risk for herpes zoster [29], need further investigation.
Acknowledgements
Medical Writing/Editorial Assistance
The authors thank Magdalena Schwarz, Christa Geis and GSK internal editorial support staff for their contributions to this study and publication. The authors would also like to thank Julian Witte, Manuel Batram and Bastian Surmann for providing writing support (Vandage, on behalf of GSK) and Business & Decision Life Sciences Medical Communication Service Center for editorial assistance and manuscript coordination, on behalf of GSK.
Declarations
Conflict of Interest
Julian Witte and Manuel Batram own shares of Vandage GmbH. Vandage received funding from GSK to perform the study related to this manuscript. Vandage received payments from GSK, Janssen-Cilag GmbH, Sanofi-Aventis Deutschland GmbH, Viatris, Seqirus GmbH, MSD Sharp & Dohme GmbH and consulting fees and grants from AOK Rheinland/Hamburg, BARMER, DAK-Gesundheit, German G-BA, and Techniker Krankenkasse. Jörg Schelling declares receiving consulting fees and payments or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing, or educational events from Sanofi-Pasteur, GSK, MSD, Pfizer, Seqirus, Moderna, Biontech, AstraZeneca, Bavarian Nordic, Takeda and Novavax in the past 36 months. Jörg Schelling also declares participating on advisory boards for the companies listed above. Jörg Schelling has also received support for attending meetings and/or travel from Pfizer. Mirko Steinmüller declares having participated in an advisory board organized by GSK in relation with the current manuscript. Mirko Steinmüller also declares receiving payments or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing or educational events and support for attending meetings and/or travel from GSK, Pfizer, MSD and Seqirus. Mirko Steinmüller participated in advisory boards organized by the companies listed above. Andreas Leischker declares receiving honoraria for lectures, presentations, speakers’ bureaus, manuscript writing or educational events from Sanofi-Pasteur, GSK, Takeda, Pfizer Vaccines, participating in an advisory board organized by Pfizer Vaccines, Sanofi-Pasteur and GSK and receiving funding from GSK to participate in an expert meeting in Potsdam. Christiane Hermann declares having served on an advisory board organized by GSK and receiving fees for that. Alexander Heiseke and Pavo Marijic are employees of GSK. Alexander Heiseke holds stock options from GSK. Bastian Surmann is an employee of Vandage and participated in advisory boards on behalf of Vandage. Carl Peter Criée and Klaus Wahle declare no financial or non-financial relationships and activities and no conflicts of interest. Bastian Surmann, Julian Witte, Manuel Batram, Christiane Hermann, Andreas Leischker, Jörg Schelling, Mirko Steinmüller, Alexander Heiseke and Pavo Marijic declare no other financial or non-financial relationships and activities and no other conflicts of interest.
Ethical Approval
The analysis was based on secondary claims data and, as such, the consultation of an ethics committee was not required. This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments.
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Epidemiology of Pertussis and Pertussis-Related Complications in Adults: A German Claims Data Analysis
verfasst von
Bastian Surmann Julian Witte Manuel Batram Carl Peter Criée Christiane Hermann Andreas Leischker Jörg Schelling Mirko Steinmüller Klaus Wahle Alexander F. Heiseke Pavo Marijic
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