Abstract
Background Immunosuppression may worsen SARS-CoV-2 infection. We conducted a nationwide cohort study of the effect of exposure to immunosuppressants on the prognosis of SARS-CoV-2 infection in Denmark.
Methods We identified all SARS-CoV-2 test-positive patients from February to October 2020 and linked health care data from nationwide registers, including prescriptions for the exposure, immunosuppressant drugs. We estimated relative risks of hospital admission, intensive care unit (ICU) admission, and death (each studied independently up to 30 days from testing) with a log linear binomial regression adjusted for confounders using a propensity score-based matching weights model.
Results A composite immunosuppressant exposure was associated with a significantly increased risk of death (adjusted relative risk 1·56 [95% confidence interval 1.10–2.22]). The increased risk of death was mainly driven by exposure to systemic glucocorticoids (aRR 2.38 [95% CI 1.72–3.30]), which were also associated with an increased risk of hospital admission (aRR 1.34 [95% CI 1.10–1.62]), but not ICU admission (aRR 1.76 [95% CI [0.93–3.35]); these risks were greater for high cumulative doses of glucocorticoids than for moderate doses. Exposure to selective immunosuppressants, tumour necrosis factor inhibitors, or interleukin inhibitors, was not associated with an increased risk of hospitalisation, ICU admission, or death, nor was exposure to calcineurin inhibitors, other immunosuppressants, hydroxychloroquine, or chloroquine.
Conclusions Exposure to glucocorticoids was associated with increased risks of hospital admission and death. Further investigation is needed to determine the optimal management of COVID-19 in patients with pre-morbid glucocorticoid usage, specifically whether these patients require altered doses of glucocorticoids.
Abstract
In a nationwide cohort study of SARS-CoV-2 infections in Denmark, pre-morbid exposure to systemic glucocorticoids was associated with an increased risk of hospital admission and death, whereas other immunosuppressants were not.
Introduction
Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), manifests with varying clinical severity [1, 2]. An inflammatory response with virus-specific T cells clears the virus and leads to recovery in most patients, however an aberrant inflammatory response can lead to severe disease [3]. Severe cases are predominantly characterised by viral pneumonia and may feature multi-organ inflammatory involvement, including elevated pro-inflammatory cytokines such as interleukins IL-6 and IL-8, and tumour necrosis factor (TNF) [3–5]. Patients receiving immunosuppressant therapies for conditions including inflammatory diseases and solid organ transplantation are susceptible to intercurrent viral and bacterial infections [6, 7], and although evidence is lacking regarding their effect on COVID-19, expert groups concerned that immunosuppression may worsen the prognosis have advised withholding or reducing immunosuppressants during intercurrent COVID-19 [8–10].
Immunosuppressants differ in their mechanisms of action and may therefore have differing effects on the disease course of COVID-19, and effects may vary with the severity of disease, and timing in the disease course. Certain immunosuppressants may have beneficial effects in COVID-19 by regulating the elevated inflammatory response associated with severe disease. Randomised controlled trials (RCTs) have demonstrated improved survival of COVID-19 patients treated with corticosteroids [11, 12]. A number of clinical trials of biological immunosuppressants including anti-IL-6 agents have been performed without conclusive evidence of improved outcomes [13], but preliminary reports of a large RCT indicate improved survival in patients treated with tocilizumab [14]. The majority of RCTs and a meta-analysis of chloroquine or hydroxychloroquine to treat COVID-19 did not support efficacy [15].
In addition to efficacy studies of immunosuppressants as treatment for COVID-19, their safety also requires investigation to guide optimal management of comorbid diseases during the pandemic, as the presence of pre-existing immunosuppression may influence the prognosis of intercurrent COVID-19. Currently published studies of patients with COVID-19 receiving immunosuppressants for underlying conditions have been limited by small sample sizes or surveillance bias [16–19].
We therefore aimed to conduct a nationwide cohort study of the effect of exposure to immunosuppressants on the risk of hospital admission, intensive care unit (ICU) admission, and death among all SARS-CoV-2 test-positive patients in Denmark from February to October 2020.
Methods
Data sources
We conducted a nationwide cohort study using the Danish COVID-19 cohort [20], based on data from the Danish Microbiology Register, a national register of all test results from all clinical microbiology departments in Denmark [21]. We defined the cohort as all individuals with a positive result for SARS-CoV-2 polymerase chain reaction (PCR) on an oro- or nasopharyngeal swab or lower respiratory tract specimen, from the first detected case on 26 February until October 18, 2020 (30 days before data extraction on November 18, 2020). We used individuals’ first positive test date in the Danish Microbiology Register (the index date) and a pseudonymised unique identifier to link individual-level health care data from other Danish national registers. We obtained information on prescription drugs dispensed at retail pharmacies from the Danish National Prescription Register [22], and information on diagnoses, and medical procedures (including the administration of intravenous drugs) from the Danish National Patient Register, a register of hospital activities [23]. We obtained the date of death from the Danish Register of Causes of Death, if present [24].
Exposures and outcomes
The exposure was immunosuppressants drugs including hydroxychloroquine and chloroquine (immunomodulators which are suspected to alter the immune response in COVID-19), and systemic glucocorticoids, which in moderate to high doses can cause immunosuppression (see Appendix Table 1 for drug level ATC codes and procedure codes). The validity of the registration of immunosuppressants in our data sources has not been analysed, but studies have demonstrated a high validity of other procedures codes, such as antineoplastic procedures [25]. The exposure assessment window was 120 days preceding the index date, as packs contained up to 120 tablets, and treatments given more than 120 days before infection are unlikely to cause ongoing immunosuppression. We used a minimum daily dose of systemic glucocorticoids equivalent to 7.5 mg prednisone per day, to exclude doses unlikely to cause significant immunosuppression (Appendix Table 2) [26]. As the prescribed daily dose is not available in the Danish National Prescription Register [22], we estimated the daily dose as the sum of the amount of glucocorticoids dispensed to an individual during the exposure assessment window divided by the number of days from the first prescription to the index date. Unexposed patients did not receive any immunosuppressant during the exposure assessment window.
Characteristics of SARS-CoV-2 PCR test positive patients in Denmark, 26 February–18 October 2020, by exposure to immunosuppressants
The relative risk of severe outcomes of SARS-CoV-2 infection in patients exposed to immunosuppressants compared to unexposed
We studied immunosuppressants as a composite exposure in our main analysis. In secondary analyses, seeking to investigate the effect of classes of immunosuppressants, while maintaining sufficient sample size to detect an effect, we broke down immunosuppressants into smaller categories. Biological and targeted immunosuppressants indicated in severe immune-mediated inflammatory diseases (IMID) or to prevent transplant rejection (TNF inhibitors, interleukin inhibitors, selective immunosuppressants, and rituximab) comprised one group. Conventional disease modifying anti-rheumatic drugs, as well as other immunosuppressants (calcineurin inhibitors, other immunosuppressants, hydroxychloroquine, and chloroquine) formed a second group. Systemic glucocorticoids formed a third group.
The study outcomes were hospital admission, ICU admission, and death, each event studied separately and independently. We included events occurring up to 30 days from patients’ first positive test date, as well as hospital and ICU admission up to 7 days before that date to include relevant events occurring before testing, while reducing unrelated events occurring after recovery. Previous studies have indicated that a small percentage of patients were hospitalised before testing [27], and approximately 80% of deaths occur within 14 days of hospital admission [28].
Covariates
We controlled for confounding by including covariates for the exposure and outcomes in a propensity score (PS) model. These covariates were selected based on background knowledge, despite incomplete knowledge of the relation between all covariates, while excluding instrumental variables or mediators. We included demographic variables (age and sex), number of past hospital contacts, diagnoses, and co-medications (including medications as proxies for disease, such as for diabetes) as covariates of immunosuppressive treatment and prognosis of SARS-CoV-2 infection (ATC and ICD-10 codes listed in Appendix Table 3). To control for confounding by indication, we included diagnoses such as inflammatory diseases (included with in skin diseases, and gastrointestinal diseases categories), organ transplantation, and certain malignancies that indicate treatment with immunosuppressants. Procedures and non-immunosuppressant medications used to treat IMID were included as proxies of underlying disease severity.
Relative risk of severe outcomes of SARS-CoV-2 infection in patients exposed to subgroups of immunosuppressants compared to unexposed
Statistical methods
Clinical characteristics of the cohort were assessed, with standardised mean differences (SMD) less than 0.1 considered well balanced. We estimated the PS as the probability of treatment conditional on observed covariates [29]. We used a PS-weighting model where exposed subjects’ weights were calculated as (minimum(PS,1-PS))/PS, and unexposed subjects’ weights were calculated as (minimum(PS, 1-PS))/(1-PS), known as “matching weights”. This gave a better covariate balance than inverse probability of treatment weighting (IPTW) as initially planned (Appendix Figure 1 and Appendix Tables 13–20) [30]. Weights were truncated at the 1st and 99th centile. We removed antianaemic drugs from the final PS model due to imbalance; adjusting for it in the log binomial regression model gave similar results (Appendix Tables 4–12).
Relative risk of severe outcomes of SARS-CoV-2 infection in patients exposed to glucocorticoids, by cumulative prednisolone-equivalent dose <2000mg (moderate) or ≥2000mg (high)
We estimated crude and adjusted (weighted) relative risks (and 95% confidence intervals with robust variance estimates) of the outcomes for exposed patients compared to unexposed patients using a log linear binomial regression model. We preferred this model to a survival analysis with competing risks model because a high number of events such as death often occurred very close to the date of testing, and hospital and ICU admission could occur before testing, resulting in negative time-to-event. For the analyses of subgroups of immunosuppressants, we fitted separate PS models for each of the subgroups, selecting variables from the list of covariates (Appendix Table 21). Exposure to combinations of the described groups of immunosuppressants was relatively rare and unlikely to alter results, so we did not study their effect. We performed a post-hoc analysis of the dose-effect of systemic glucocorticoids. To create two exposure groups of approximately equal size to maintain statistical power, we categorised the prednisolone-equivalent cumulative dose within 120 days preceding the index date as moderate dose (<2000 mg) or high dose (≥2000 mg), which were each compared to unexposed patients.
Sensitivity analyses
To control for residual confounding, we performed an analysis comparing current users exposed 120 days preceding the index date to former users exposed to immunosuppressants 121–365 days preceding the index date. To study the effect of immunosuppressants in patients with more severe COVID-19, we restricted the cohort to hospital admissions coded with COVID-19 as the primary diagnosis, studying the outcomes ICU admission or death.
To reduce selection bias due to patients immunosuppressants, amongst other clinically vulnerable people, being prioritised for testing (mainly before a policy change in Denmark April 21, 2020), we made separate analyses of the cohort tested before or after April 21, 2020, and made calculations to estimate the effect of selection bias (see Appendix Methods). We used the statistical software Stata 16.1 (StataCorp LLC, College Station, TX).
Results
Characteristics of SARS-CoV-2 positive patients
From 26 February–18 October 2020, there were 36 727 individuals with positive SARS-CoV-2 PCR tests in Denmark, of which 527 were exposed to immunosuppressants and 36 200 were unexposed. There were 66 exposed to selective immunosuppressants, 105 to TNF inhibitors, 25 to interleukin inhibitors, 29 to calcineurin inhibitors, 218 to other immunosuppressants, 31 to hydroxychloroquine or chloroquine, 136 to systemic glucocorticoids, and zero to rituximab. The median age of exposed patients was 57 years (IQR 42 to 73), and the median age of unexposed patients was 39 years (IQR 23–55), with a greater prevalence of comorbid diagnoses in the exposed population (table 1). In total, there were 715 deaths, and 492 (69%) of those were during hospital stays. There were 425 ICU admissions, and 105 (25%) of those patients died, all occurring within 28 days of ICU admission. Few patients were exposed to both glucocorticoids and selective immunosuppressants (<5), TNF inhibitors (<5), interleukin inhibitors (<5), calcineurin inhibitors (<5), or other immunosuppressants (14).
Composite immunosuppressant exposure: relative risk of severe outcomes of SARS-CoV-2 infection
Among patients exposed to the composite measure of immunosuppressants there were 165 hospital admissions, 25 ICU admissions, and 57 deaths, and among the unexposed there were 3373 hospital admissions, 400 ICU admissions and 658 deaths (table 2 and Appendix Table 4). After weighting in our PS-based model, there were 346 exposed to immunosuppressants, and 339 unexposed, with a well-balanced distribution of covariates (table 1 and Appendix Figure 1). The distribution of antianaemic drug usage was not balanced in the weighting model, but including it as a variable in our regression model had little effect (Appendix Table 4), so we removed it from the final model. The crude relative risk of hospital admission was 3.36 (95% CI 2.95 to 3.83), of ICU admission was 4·29 (95% CI 2.89 to 6.37), and of death was 5.95 (95% CI 4.60 to 7.69) (table 2). The after weighting in our PS-based model, the adjusted relative risk (aRR) of hospital admission was 1.13 (95% CI 0.95 to 1.33), the aRR of ICU admission 1.16 (95% CI 0.66 to 2.03), and the aRR of death 1.56 (95% CI 1.10 to 2.22) (table 2).
Subgroups of immunosuppressants: relative risk of severe outcomes of SARS-CoV-2 infection
For patients exposed to selective immunosuppressants, TNF inhibitors or interleukin inhibitors, compared to unexposed patients, the aRR of hospital admission was 0.83 (95% CI 0.51 to 1.34), the aRR of ICU admission was 0.92 (95% CI 0.23 to 3.71), and the aRR of death was 1.17 (95% CI 0.38 to 3.62) (table 3 and Appendix Tables 5, 6, and 7). For patients exposed to calcineurin inhibitors, other immunosuppressants, hydroxychloroquine or chloroquine, compared to unexposed patients, the aRR of hospital admission was 0.82 (95% CI 0.60 to 1.12), the aRR for ICU admission was 1.03 (0.43 to 2.49), and the aRR for death was 0.93 (0.47 to 1.85). For patients exposed to systemic glucocorticoids, compared to unexposed patients, the aRR for hospital admission was 1.34 (95% CI 1.10 to 1.62), the aRR for ICU admission was 1.76 (95% CI 0.93 to 3.35), and the aRR for death was 2.38 (95% CI 1.72 to 3.30).
Relative risk of severe outcomes of SARS-CoV-2 infection in current users compared to former users of immunosuppressants
When cumulative glucocorticoid dose was categorised as moderate or high, compared to unexposed patients, the aRR of hospital admission was 1.20 (95% CI 0.89 to 1.62) and 1.47 (95% CI 1.15 to 1.89); the aRR of ICU admission 1.92 (95% CI 0.82 to 4.46) and 1.58 (95% CI 0.62 to 4.04); and the aRR of death was 1.84 (95% CI 1.08 to 3.13) and 2.91 (95% CI 1.92 to 4.39), respectively (table 4 and Appendix Table 8).
Sensitivity analyses: relative risk of severe outcomes of SARS-CoV-2 infection
Comparing current users of immunosuppressants to former users, the aRR of hospital admission was 1.13 (95% CI 0.83 to 1.52), the aRR of ICU admission was 1.21 (95% CI 0.68 to 2.15), and the aRR of death was 1.21 (95% CI 0.68 to 2.15) (table 5 and Appendix Table 9). When restricting to admitted patients with COVID-19 as their primary diagnosis, the risk of death was not significantly increased in patients exposed to immunosuppressants (aRR 1.30, 95% CI 0.94 to 1.82) nor was the risk of ICU admission (aRR 0.89, 95% CI 0.50 to 1.56) (Appendix Table 10).
Prior to the change in testing strategy on April 21, 2020, there were 199 exposed to immunosuppressants and 7794 unexposed; from 21 April-18 October 2020, there were 328 exposed, and 28 406 unexposed (Appendix Table 11 and 12). For hospital admission the aRR was 0.99 (95% CI 0.82 to 1.20) in the first period, and 1.34 (95% CI 1.00 to 1.80) in the second period, the aRR of ICU admission was 0·65 (95% CI 0.29 to 1.46) and 3.23 (95% CI 1.50–6.98), and the aRR of death was 1.06 (95% CI 0.70 to 1.63) and 2.60 (95% CI 1.52 to 4.46) respectively.
Discussion
Using a nationwide cohort of 36 727 individuals tested positive for SARS-CoV-2, of whom 527 were exposed to immunosuppressants, we assessed the effect of immunosuppressants on the prognosis of intercurrent SARS-CoV-2 infection. A composite immunosuppressant exposure was associated with a significantly increased risk of death, which was mainly driven by a doubling of risk associated with systemic glucocorticoids. Glucocorticoids were also associated with a 34% increased risk of hospital admission, while the risk of ICU admission was not significantly increased (table 3). The risks of hospitalisation, ICU admission, or death associated with selective immunosuppressants, TNF inhibitors, or interleukin inhibitors were not significantly increased or decreased, nor were they in patients exposed to calcineurin inhibitors, other immunosuppressants, hydroxychloroquine, or chloroquine (table 3). These findings are in agreement with two multinational studies of COVID-19 patients: glucocorticoids were associated increased risk of ICU admission or death in patients with comorbid inflammatory bowel diseases; glucocorticoids were associated with greater risk of hospital admission in patients with comorbid rheumatic diseases [18, 20].
The finding of an increased risk of death associated with glucocorticoids early in the course of COVID-19 contrasts with studies finding that high dose glucocorticoids reduces mortality in patients with severe disease [10, 11]. Nonetheless, patients not requiring supplemental oxygen in the RECOVERY trial did not benefit from dexamethasone and the effect could be compatible with harm (RR 1·19, 95% CI 0·91 to 1·55) [10]. This deleterious effect of glucocorticoids early in the disease course could be due to a suppressed adrenal stress-response, as well as their suppressive effect on interferon production, resulting in impaired innate responses to viral infection. Chronic glucocorticoid exposure also has pleiotropic metabolic effects including impaired glucose handling and skeletal muscle catabolism among other effects that may contribute to adverse outcomes. By contrast, the initiation of glucocorticoids in severe disease appears to suppress the dysregulated inflammatory response which otherwise leads to multi-organ involvement and coagulation. The effect seen in our study appears to be dose related, but these subgroups were small, so interpretation of dose effects must be tentative. By contrast, treatment with high dose glucocorticoids reduces mortality in patients with severe COVID-19 disease. The majority of patients in our study were not admitted to hospital, and would have had milder COVID-19 not requiring oxygen therapy, similar to that subset of the RECOVERY trial. These findings prompt the important question of how to improve outcomes of COVID-19 in patients taking glucocorticoids. Whether patients on glucocorticoids require increased doses during COVID-19, as in other intercurrent illnesses, or reduced doses, requires further investigation.
Important strengths of this nationwide cohort study include the use of prescription and hospital activity data from national registers. Our study reduced surveillance bias, which is the limitation of studies based on spontaneously reported cases, by including all of SARS-CoV-2 test positive person in Denmark. We maximised power by using the full cohort, without restricting to specific patient populations. This facilitated extensive control of confounders, including the diverse diseases that indicate the use of immunosuppressants and glucocorticoids, further improving the reliability of our results. Controlling for covariates using a propensity score weighting model optimised the covariate distribution in a subset of the population with clinical equipoise for immunosuppressant exposure. Our analysis of bias suggested that the risk associated with immunosuppressants may be greater than estimated, as selection bias that attenuated the relative risk estimates (see Appendix Methods). Selection bias had a greater effect in the period before 21 April, when patients on immunosuppressants were prioritised for testing, which may have contributed to the lower relative risks estimated compared to after that date (Appendix Table 9 and 10).
We also recognise limitations to our study. Our conclusions on the effects of classes of immunosuppressants are cautious, as the selected groups (other than glucocorticoids) included a number of drug classes, which may have divergent effects, impairing our ability to detect associations with individual drugs. As the number of exposed subjects was small, the matching weights model targeted the population average treatment effect in the treated, and this hinders the generalisability of the risk estimates to people without an underlying condition that could require immunosuppressant therapy. The number of covariates in our model was statistically limited by the number of outcome events, so there may be residual confounding caused by unmeasured disease severity. Residual confounding is suggested by the attenuation in the risk estimate for death associated with immunosuppressants when current users were compared to former users, which remained numerically increased but no longer statistically significant. Diagnostic coding is affected by differences in practices among clinicians, an inherent limitation when nationwide register data is used. Further studies may benefit from more detailed measures of severity. However, this is unlikely to completely account for the association of glucocorticoid exposure and severe outcomes, as other immunosuppressants such as TNF inhibitors are also treatments for severe IMIDs, but by contrast, those exposures were not significantly associated with severe outcomes.
In our cohort the majority of people with COVID-19 who died were never admitted to ICU, and a substantial number were not receiving hospital-based care when they died. Frailty may account for the greater number of deaths, and greater relative risks associated with immunosuppressants, compared to ICU admissions. Admission to ICU depends not only on clinical assessment of the admitted patient, but also on factors such as frailty, short life expectancy, as well as patient and family preferences; for example, a care home resident with such conditions might not be moved to hospital, thus would not be assessed for ICU admission. Further health system factors may also be important in the context of the pandemic [31].
In conclusion, this nationwide cohort study found that pre-morbid exposure to glucocorticoids was associated with a worsened prognosis of SARS-CoV-2 infection [18, 19]. Studies are warranted to determine whether altered doses are beneficial, with attention to the severity of COVID-19 at treatment initiation. While other pharmacological interventions remain relevant research candidates, evidence from multiple sources indicate the importance of glucocorticoids on prognosis, the effect of which may depend on timing in the disease course. Our findings that other immunosuppressants were not significantly associated with severe outcomes are tentative, but in context, they support the continued use of steroid-sparing immunosuppressants for a broad patient population with ongoing health care needs during the pandemic.
Support statement: Tine Jess received financial support from the Lundbeck Foundation (R349-2020-582). Lundbeckfonden; DOI: http://dx.doi.org/10.13039/501100003554; Grant: R349-2020-582.
Footnotes
This article has supplementary material available from erj.ersjournals.com
Conflict of interest: Daniel Ward has nothing to disclose.
Conflict of interest: Sanne Gørtz has nothing to disclose.
Conflict of interest: Martin Thomsen Ernst has nothing to disclose.
Conflict of interest: Nynne Nyboe Andersen has nothing to disclose.
Conflict of interest: Susanne K Kjær has nothing to disclose.
Conflict of interest: Jesper Hallas has nothing to disclose.
Conflict of interest: Steffen Christensen has nothing to disclose.
Conflict of interest: Christian Fynbo Christiansen has nothing to disclose.
Conflict of interest: Simone Bastrup Israelsen has nothing to disclose.
Conflict of interest: Thomas Benfield reports unrestricted grants to institution from Novo Nordisk Foundation, Simonsen Foundation, Lundbeck Foundation, Kai Foundation, Erik and Susanna Olesen's Charitable Fund, GSK, Pfizer, Gilead Sciences, MSD; grants from Boehringer Ingelheim, Roche, Novartis, Kancera AB; advisory board membership at GSK, Pfizer, Gilead Sciences, MSD, Pentabase; consulting fees from GSK, Pfizer; lecture fees from GSK, Pfizer, Gilead Sciences, Boehringer Ingelheim, Abbvie; and donation of trial medication (baricitinib) from Eli Lilly.
Conflict of interest: Anton Pottegård reports funds paid to the institution from Alcon, Almirall, Astellas, Astra-Zeneca, Boehringer-Ingelheim, Novo Nordisk, Servier, LEO Pharma, outside the submitted work.
Conflict of interest: Tine Jess reports COVID research grant from Lundbeck foundation.
- Received March 15, 2021.
- Accepted August 8, 2021.
- Copyright ©The authors 2021.
This version is distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0. For commercial reproduction rights and permissions contact permissions{at}ersnet.org
References
