Association of Infections and Use of Fluoroquinolones With the Risk of Aortic Aneurysm or Aortic Dissection | Infectious Diseases | JAMA Internal Medicine | JAMA Network
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Figure.  Risk of Aortic Aneurysm and Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections Restricted to Those With Potentially High-risk Characteristics
Risk of Aortic Aneurysm and Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections Restricted to Those With Potentially High-risk Characteristics

Odds ratios (ORs) are adjusted for matching factors of age, sex, duration of follow-up in the database, and type of infection and for baseline covariates, including hypertension, ischemic heart disease, valve disorder, ischemic stroke, disorders of lipid metabolism, chronic obstructive pulmonary disease, chronic kidney disease, Charlson comorbidity score, tobacco smoking, claims-based frailty index, any episodes of infections, any use of fluoroquinolones, and any use of nonfluoroquinolone antibiotics measured between cohort entry and 60 days before the index date.

Table 1.  Distribution of Baseline Covariates Between Cases and Matched Controls of AA or AD
Distribution of Baseline Covariates Between Cases and Matched Controls of AA or AD
Table 2.  Risk of AA or AD Associated With Indicated vs No Indicated Infections
Risk of AA or AD Associated With Indicated vs No Indicated Infections
Table 3.  Risk of AA or AD Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infectionsa
Risk of AA or AD Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infectionsa
Supplement.

eMethods. Data Source and Source Population, Selection of Comparison Antibiotics, and Analysis of Association Between Fluoroquinolones and Tendon Rupture Disorder

eFigure 1. Study Design

eFigure 2. Conceptual Time Sequence for Infections, Antibiotic Use, and Aortic Aneurysm or Aortic Dissection

eFigure 3. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections, Restricting to Those Without Any Use of Fluoroquinolones at Baseline

eFigure 4. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections, by Risk Window and Minimum Antibiotic Treatment Duration

eFigure 5. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections, by Treatment Setting

eFigure 6. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections, by Dosage Form

eFigure 7. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Extended-Spectrum Cephalosporin Monotherapy Among Patients With Indicated Infections, by Cephalosporin Generation and by Dosage Form

eFigure 8. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections, by Type of Infection

eFigure 9. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections Stratified by Subtype of Aortic Aneurysm or Aortic Dissection

eFigure 10. Risk of Aortic Aneurysm or Aortic Dissection Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections Stratified by Outcome Definition

eFigure 11. Risk of Tendon Rupture Outcomes Associated With Fluoroquinolone Monotherapy vs Comparison Antibiotic Monotherapy Among Patients With Indicated Infections

eFigure 12. Potential Directed Acyclic Graph for Infections, Antibiotic Use, and Aortic Aneurysm or Aortic Dissection

eTable 1. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) Diagnosis Codes Used to Identify the Outcomes of Interest

eTable 2. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) Procedure Codes, Taiwan Health Insurance Service Claims Codes, or Anatomical Therapeutic Chemical (ATC) Classification System Codes Used to Describe Clinical Management for Patients With Aortic Aneurysm or Aortic Dissection

eTable 3. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) Diagnosis Codes Used to Identify Episodes of Indicated Infections

eTable 4. Anatomical Therapeutic Chemical (ATC) Classification System Codes Used to Identify Study Antibiotics

eTable 5. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) Diagnosis Codes or Procedure Codes, Taiwan Health Insurance Service Claims Codes, or Anatomical Therapeutic Chemical (ATC) Classification System Codes Used to Identify Baseline Comorbidities, Indicated Infections, or Antibiotics, and to Define Patients With Cardiovascular Disease

eTable 6. Summary of Subgroup and Sensitivity Analyses

eTable 7. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) Diagnosis or Procedure Codes or Taiwan Health Insurance Service Claims Codes Used to Identify the Positive Control Outcome of Achilles Tendon Rupture and Any Type of Tendon Rupture

eTable 8. Study Cohort Assembly and Case Description

eTable 9. Risk of Aortic Aneurysm or Aortic Dissection Associated With Any Use of a Specific Antibiotic vs No Use of That Antibiotic

eTable 10. Distribution of Baseline Covariates Between Cases and Matched Controls of Aortic Aneurysm or Aortic Dissection Among Patients With Indicated Infections

eTable 11. Cases and Matched Controls Among Patients With Indicated Infections, Restricting to Those Without Any Use of Fluoroquinolones at Baseline

eTable 12. Cases and Matched Controls Among Patients With Indicated Infections by Risk Window and Minimum Antibiotic Treatment Duration

eTable 13. Cases and Matched Controls Among Patients With Indicated Infections, by Treatment Setting

eTable 14. Cases and Matched Controls Among Patients With Indicated Infections, by Dosage Form

eTable 15. Cases and Matched Controls Among Patients With Indicated Infections, by Cephalosporin Generation and by Dosage Form

eTable 16. Cases and Matched Controls Among Patients With Indicated Infections, by Type of Infection

eTable 17. Cases and Matched Controls Among Patients With Indicated Infections, Restricting to Those With Potentially High-Risk Characteristics

eTable 18. Cases and Matched Controls Among Patients With Indicated Infections, by Subtype of Aortic Aneurysm or Aortic Dissection

eTable 19. Cases and Matched Controls Among Patients With Indicated Infections, by Outcome Definition

eTable 20. Cases of Tendon Disorder and Matched Controls Among Patients With Indicated Infections

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    Original Investigation
    September 8, 2020

    Association of Infections and Use of Fluoroquinolones With the Risk of Aortic Aneurysm or Aortic Dissection

    Author Affiliations
    • 1Faculty of Pharmacy, National Yang-Ming University School of Pharmaceutical Science, Taipei, Taiwan
    • 2Institute of Public Health, National Yang-Ming University School of Medicine, Taipei, Taiwan
    • 3Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
    • 4Department of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
    • 5Institute of Epidemiology and Preventive Medicine, National Taiwan University College of Public Health, Taipei, Taiwan
    • 6Department of Internal Medicine, National Cheng Kung University Hospital, Tainan, Taiwan
    • 7Department of Medicine, National Cheng Kung University Medical College, Tainan, Taiwan
    • 8Department of Internal Medicine, National Taiwan University Hospital Yunlin Branch, Douliou City, Yunlin County, Taiwan
    • 9Cardiovascular Center, National Taiwan University Hospital Yunlin Branch, Douliou City, Yunlin County, Taiwan
    • 10Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
    JAMA Intern Med. 2020;180(12):1587-1595. doi:10.1001/jamainternmed.2020.4192
    Key Points

    Question  Is the risk of aortic aneurysm or aortic dissection independently associated with infections and fluoroquinolone use (vs other antibiotics with similar indication profiles)?

    Findings  In this nationwide, nested case-control study of 28 948 cases and 289 480 matched controls identified from 21 651 176 adult patients, the odds ratio (OR) of aortic aneurysm or aortic dissection for any indicated infections, adjusted for baseline confounders and concomitant antibiotic use, was 1.73 (95% CI, 1.66-1.81). Fluoroquinolones were not associated with an increased risk of aortic aneurysm or aortic dissection when compared with amoxicillin-clavulanate or ampicillin-sulbactam (OR, 1.01; 95% CI, 0.82-1.24) or extended-spectrum cephalosporins (OR, 0.88; 95% CI, 0.70-1.11) among patients with indicated infections.

    Meaning  These results highlight the importance of accounting for coexisting infections while examining the safety of antibiotics using real-world data; the concern about aortic aneurysm or aortic dissection should not deter fluoroquinolone use for patients with indicated infections.

    Abstract

    Importance  Prior observational studies have suggested that fluoroquinolone use may be associated with more than 2-fold increased risk of aortic aneurysm or aortic dissection (AA/AD). These studies, however, did not fully consider the role of coexisting infections and the risk of fluoroquinolones relative to other antibiotics.

    Objective  To estimate the risk of AA/AD associated with infections and to assess the comparative risk of AA/AD associated with fluoroquinolones vs other antibiotics with similar indication profiles among patients with the same types of infections.

    Designs, Settings, and Participants  This nested case-control study identified 21 651 176 adult patients from a nationwide population-based health insurance claims database from January 1, 2009, to November 30, 2015. Each incident case of AA/AD was matched with 10 control individuals by age, sex, and follow-up duration in the database using risk-set sampling. Analysis of the data was conducted from April 2019 to March 2020.

    Exposures  Infections and antibiotic use within a 60-day risk window before the occurrence of AA/AD.

    Main Outcomes and Measures  Conditional logistic regression was used to estimate the odds ratios (ORs) and 95% CIs comparing infections for which fluoroquinolones are commonly used with no infection within a 60-day risk window before outcome occurrence, adjusting for baseline confounders and concomitant antibiotic use. The adjusted ORs comparing fluoroquinolones with antibiotics with similar indication profiles within patients with indicated infections were also estimated.

    Results  A total of 28 948 cases and 289 480 matched controls were included (71.37% male; mean [SD] age, 67.41 [15.03] years). Among these, the adjusted OR of AA/AD for any indicated infections was 1.73 (95% CI, 1.66-1.81). Septicemia (OR, 3.16; 95% CI, 2.63-3.78) and intra-abdominal infection (OR, 2.99; 95% CI, 2.45-3.65) had the highest increased risk. Fluoroquinolones were not associated with an increased AA/AD risk when compared with combined amoxicillin-clavulanate or combined ampicillin-sulbactam (OR, 1.01; 95% CI, 0.82-1.24) or with extended-spectrum cephalosporins (OR, 0.88; 95% CI, 0.70-1.11) among patients with indicated infections. The null findings for fluoroquinolone use remained robust in different subgroup and sensitivity analyses.

    Conclusions and Relevance  These results highlight the importance of accounting for coexisting infections while examining the safety of antibiotics using real-world data; the findings suggest that concerns about AA/AD risk should not deter fluoroquinolone use for patients with indicated infections.

    Introduction

    Aortic aneurysm (AA) and aortic dissection (AD) are potentially fatal conditions. Population-based studies in the United States, European countries, and Taiwan estimated the annual incidence to be 2.4 to 14.8 per 100 000 persons for AA1-4 and 3.8 to 8.8 per 100 000 persons for AD.3,5-7 Although the incidence varied across countries, the number has universally increased over time.1-5,7 Without appropriate treatment of ruptured AA/AD, mortality can increase to 90%.8

    The known risk factors for AA/AD include congenital connective tissue disorders, older age, male sex, atherosclerotic cardiovascular disease, and tobacco smoking.8-11 Cumulative case reports and case series12-17 also suggested that endocarditis, septicemia, intra-abdominal infections, bone-related infections, genitourinary tract infections (GUTIs), and lower respiratory tract infections (LRTIs) may be associated with AA/AD.

    Past epidemiological studies18-21 observed more than 2-fold increased risk of AA/AD with oral fluoroquinolones that are commonly used in treating LRTIs and GUTIs.22 These findings prompted the US Food and Drug Administration23 and the European Medicines Agency24 to issue safety warnings about fluoroquinolones. However, these studies did not fully consider the role of infections on the risk of AA/AD.18-21 Most studies compared use vs nonuse of oral fluoroquinolones,18-20 which could be susceptible to confounding by indication and overestimate the risk with fluoroquinolones because patients receiving fluoroquinolones may have different infection types or severity compared with those not receiving fluoroquinolones. Using a nested case-control study design in a nationwide population-based database, we estimated the risk of AA/AD with infections and the comparative risk of AA/AD with fluoroquinolones vs other antibiotics with similar indication profiles.

    Methods
    Data Source and Source Population

    We used data from the Taiwan National Health Insurance Research Database, which included deidentified data of 23 million individuals covered by a national health insurance system.25,26 Our source population consisted of patients 20 years or older who entered the cohort from January 1, 2009, to November 30, 2015. The cohort entry date was the date patients reached 20 years of age. We excluded patients with ambiguous sex information, history of AA/AD (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM], code 441), or any congenital disorders that potentially predisposed them to AA/AD.8-11 We followed up patients from cohort entry to the earliest of AA/AD occurrence (defined below), death, or November 30, 2015 (see eMethods and eFigure 1 in the Supplement for detail). The National Yang-Ming University Research Ethics Committee approved the study and waived the need for informed consent for the use of deidentified data. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    Selection of Cases and Controls

    We defined the index date as the date of the first hospital admission or emergency department visit for AA/AD based on the ICD-9-CM code 441 in any diagnosis position for the cases (see eTable 1 in the Supplement for codes). The algorithm had positive predictive values of 89% to 100% for AA and 78% to 92% for AD based on prior studies.27,28 We determined how the cases were clinically managed by identifying imaging examinations and treatments for AA/AD within 30 days before and after the index date (see eTable 2 in the Supplement for codes). We also determined whether the diagnosis was in the primary diagnosis position, which indicated that AA/AD was the main reason for the encounter.

    We used risk-set sampling to identify controls among patients who remained free of the outcome at the time a case occurred. For each case, we randomly sampled as many as 10 controls matched on birth year, sex, and follow-up duration from cohort entry to the index date. The index date for the controls was the same as the index date for the case to which they were matched.

    Ascertainment of Infections and Antibiotic Use

    As in prior studies,19,20 we defined the risk window as 1 to 60 days before the index date. For the cases and matched controls, we identified inpatient and outpatient infection episodes that were potential indications for fluoroquinolones (termed indicated infections), including LRTIs only; GUTIs only; skin, soft tissue, and bone infections only; intra-abdominal infections only; or any combinations of aforementioned infections. We further included septicemia, which is also an indication for fluoroquinolone treatment in Taiwan and included infections without an identified source of infection. We classified the remaining patients as having no indicated infection. The positive predictive values of the algorithms were 70% to 97% for LRTIs; 73% to 100% for GUTIs; 74% to 92% for skin, soft tissue, and bone infections; 77% to 84% for intra-abdominal infections; and 80% to 100% for septicemia based on previous studies (see eTable 3 in the Supplement for codes).29-43

    We used inpatient and outpatient pharmacy dispensing claims to identify oral or injectable antibiotic use within the risk window. As in prior studies,19,20 we defined patients as being exposed to antibiotics if at least a 3-day supply of antibiotics was available within the window. We classified antibiotics into fluoroquinolones, combined amoxicillin-clavulanate or combined ampicillin-sulbactam, extended-spectrum cephalosporins (second-, third-, or fourth-generation cephalosporins), and miscellaneous antibiotics (see eTable 4 in the Supplement for codes). We selected amoxicillin-clavulanate or ampicillin-sulbactam and extended-spectrum cephalosporins as comparison antibiotics because their indication profiles are similar to that of fluoroquinolones based on the treatment guidelines in Taiwan (see eMethods in the Supplement for detail).44-46 Because patients could receive more than 1 antibiotic class, we further classified antibiotic exposure into mutually exclusive groups of fluoroquinolone monotherapy, comparison antibiotic monotherapy, other antibiotic regimens (any combination therapies of fluoroquinolones and comparison antibiotics or use of miscellaneous antibiotics), or no use of any antibiotics.

    Ascertainment of Baseline Covariates

    We identified potential baseline confounders between cohort entry and 60 days before the index date. These included individual comorbidities, Charlson comorbidity score (range, 0-33, with higher scores indicating greater number of comorbidities),47 tobacco smoking,48 a claims-based frailty index,49 any infection episodes defined above, and any use of fluoroquinolones or nonfluoroquinolone antibiotics for at least 1 day (see eTable 5 in the Supplement for codes).

    Statistical Analysis

    Analysis of the data was conducted from April 2019 to March 2020. We used conditional logistic regression to estimate the odds ratios (ORs) and 95% CIs for the association between infections and AA/AD. The first model only adjusted for the matching factors. The second model additionally adjusted for the potential baseline confounders. The third model further included any use of fluoroquinolones, comparison antibiotics, and other antibiotics for at least 3 days during the risk window to adjust for concomitant antibiotic use and to simultaneously estimate the effects of infections and antibiotics.

    To further reduce confounding by infection and infection severity on the association between fluoroquinolone use and risk of AA/AD, we performed another set of prespecified analyses restricted to patients with an indicated infection and using an active comparison approach. Specifically, we reidentified and rematched cases and controls on age, sex, follow-up duration, and infection type among patients with an indicated infection. We used 2 conditional logistic regression models to estimate the ORs and 95% CIs associated with fluoroquinolone monotherapy compared with amoxicillin-clavulanate or ampicillin-sulbactam monotherapy and extended-spectrum cephalosporin monotherapy; one model adjusted for the matching factors only, and the other adjusted for both matching factors and potential baseline confounders.

    Subgroup and Sensitivity Analysis

    We conducted additional analyses to examine the robustness of our findings for fluoroquinolones vs comparison antibiotics among patients with an indicated infection. Specifically, we (1) evaluated a possible duration-response association for fluoroquinolones; (2) mitigated potential spillover effects of fluoroquinolones initiated before the risk window; (3) evaluated the effects of the choice of risk window and minimum antibiotic treatment duration; (4) reduced potential reverse causation between fluoroquinolone use and AA/AD occurrence (see eFigure 2 in the Supplement for conceptual temporality of events); (5) mitigated potential confounding due to infection severity by classifying antibiotic use by treatment setting, dosage form, and cephalosporin generation; (6) examined potential effect measure modification by infection type and patient characteristic; (7) examined whether the risk varied by AA/AD subtype; (8) examined the effect of the operational definition of AA/AD; and (9) mitigated the concern about misdiagnosis of AA as LRTIs or GUTIs. eTable 6 in the Supplement gives additional details of each analysis.

    Examination of Positive Control Outcomes

    Previous studies showed an association between fluoroquinolones and tendon disorders, especially for Achilles tendon rupture or in older patients.50,51 Therefore, we selected Achilles tendon rupture and any type of tendon rupture as positive control outcomes, restricted the analyses to older patients if the sample size was sufficient, and examined whether our active comparison approach could identify an increased risk with fluoroquinolones. Details are given in the eMethods and eTable 7 in the Supplement.

    Results
    Eligible Cases and Controls

    Among 21 651 176 eligible patients, 28 948 cases and 289 480 matched controls were included in the analysis (71.37% male; 28.63% female; mean [SD] age, 67.41 [15.03] years; mean [SD] follow-up duration, 1303.82 [723.12] days). Among the cases, 88.89% received an imaging examination, 74.51% received treatment intervention, and 52.59% had a primary diagnosis (eTable 8 in the Supplement). The cases had more comorbidities (mean [SD] Charlson comorbidity score, 2.27 [2.41] vs 1.24 [2.00]), tended to be smokers (1.79% vs 0.87%), had a higher claims-based frailty index (mean [SD], 0.17 [0.05] vs 0.14 [0.05]), and had more prior infections (52.79% vs 34.22%) and antibiotic use (fluoroquinolones, 19.50% vs 10.24%; nonfluoroquinolone antibiotics: 75.35% vs 53.63%) compared with matched controls (Table 1).

    Risk of AA/AD Associated With Infections

    A total of 5391 cases (18.62%) and 17 084 matched controls (5.90%) had an episode of an indicated infection during the risk window. Lower respiratory tract infections (1511 [5.22%] in cases and 3891 [1.34%] in controls) and GUTIs (1665 [5.75%] in cases and 5663 [1.96%] in controls) accounted for most of the episodes. The OR of AA/AD comparing indicated infections with no indicated infection was 3.69 (95% CI, 3.57-3.81) when we only adjusted for the matching factors (Table 2). The OR lowered to 2.27 (95% CI, 2.19-2.36) after further adjustment for all baseline covariates.

    The OR further attenuated but remained elevated after additional adjustment for concomitant antibiotic use (1.73; 95% CI, 1.66-1.81). Septicemia was associated with the highest risk of AA/AD (OR, 3.16; 95% CI, 2.63-3.78), followed by intra-abdominal infections (OR, 2.99; 95% CI, 2.45-3.65), LRTIs (OR, 2.11; 95% CI, 1.96-2.27), GUTIs (OR, 1.77; 95% CI, 1.66-1.89), mixed infections (OR, 1.75; 95% CI, 1.57-1.95), and skin, soft tissue, or bone infections (OR, 1.27; 95% CI, 1.18-1.36). The adjusted ORs ranged from 1.32 (95% CI, 1.27-1.37) to 1.43 (95% CI, 1.32-1.54) in the same model comparing the use of a specific antibiotic vs nonuse of that antibiotic (eTable 9 in the Supplement).

    Risk of AA/AD Associated With Fluoroquinolone Use Among Patients With Indicated Infections

    We identified 5391 cases and 53 880 matched controls with the same age, sex, follow-up duration, and infection type. Compared with all the cases and matched controls (Table 1), the distributions of baseline covariates between cases and matched controls with indicated infections were more similar, although the cases still tended to have more disease burden than the controls (eg, the mean [SD] Charlson comorbidity score was 3.17 [2.65] for the cases and 2.98 [2.70] for the controls) (eTable 10 in the Supplement).

    Approximately 60% of the cases and controls received more than 2 classes of antibiotics during the risk window; only 200 cases (3.71%) and 1679 controls (3.12%) received fluoroquinolone monotherapy; 221 cases (4.10%) and 1823 controls (3.38%) received amoxicillin-clavulanate or ampicillin-sulbactam monotherapy; and 145 cases (2.69%) and 1071 controls (1.99%) received extended-spectrum cephalosporin monotherapy. The OR adjusting for matching factors and baseline covariates was 1.01 (95% CI, 0.82-1.24) comparing fluoroquinolone monotherapy with amoxicillin-clavulanate or ampicillin-sulbactam monotherapy and 0.88 (95% CI, 0.70-1.11) comparing fluoroquinolone monotherapy with extended-spectrum cephalosporin monotherapy (Table 3).

    Subgroup and Sensitivity Analysis

    We did not observe a duration-response association comparing fluoroquinolones with comparison antibiotics (Table 3). The analysis restricted to patients without any fluoroquinolone use at baseline did not show an increased risk with fluoroquinolones (eFigure 3 and eTable 11 in the Supplement). Use of different risk windows (1-60 or 1-30 days) and minimum antibiotic treatment durations (3 or 1 day) yielded similar results (eFigure 4 and eTable 12 in the Supplement). The ORs moved toward the null when we ignored antibiotic use within 1 to 3 days before the index date (eFigure 4 and eTable 12 in the Supplement).

    We did not observe an increased risk with fluoroquinolones by treatment setting (eFigure 5 and eTable 13 in the Supplement), dosage form (eFigure 6 and eTable 14 in the Supplement), or cephalosporin generation (eFigure 7 and eTable 15 in the Supplement). The results did not change materially when we stratified by infection type (eFigure 8 and eTable 16 in the Supplement) or patient characteristics (Figure and eTable 17 in the Supplement). We also did not observe an increased risk with fluoroquinolones in different AA/AD subtypes (eFigure 9 and eTable 18 in the Supplement) or with more specific outcome definitions (eFigure 10 and eTable 19 in the Supplement). The analysis comparing injectable fluoroquinolones vs injectable third- or fourth-generation cephalosporins also showed a null association (eFigure 7 and eTable 15 in the Supplement).

    Findings of Positive Control Outcomes

    Fluoroquinolone use was associated with a numerically increased risk of Achilles tendon rupture vs amoxicillin-clavulanate or ampicillin-sulbactam (OR, 1.56; 95% CI, 0.56-4.36) or vs extended-spectrum cephalosporins (OR, 2.33; 95% CI, 0.60-9.07) in adult patients. The limited sample size precluded an analysis restricted to older patients. Fluoroquinolone use was also associated with a higher risk of any type of tendon rupture compared with either amoxicillin-clavulanate or ampicillin-sulbactam (OR, 1.13; 95% CI, 0.72-1.77) or extended-spectrum cephalosporins (OR, 2.04; 95% CI, 1.08-3.84) in elderly patients (eFigure 11 and eTable 20 in the Supplement).

    Discussion

    This nationwide, nested case-control study examined the risk of AA/AD associated with infections and antibiotics. Infection was found to be a risk factor for AA/AD after we adjusted for baseline covariates and concomitant antibiotic use. In contrast, fluoroquinolones were not associated with an elevated risk of AA/AD vs antibiotics with similar indication profiles after accounting for coexisting infections. The null findings did not change materially in different subgroup and sensitivity analyses.

    Association Between Infections and AA/AD

    Infection has been suspected as a risk factor for AA for decades. Salmonella, Staphylococcus, and Streptococcus species are common microorganisms.13-17,52-56 Septic emboli, bacteremic seeding into the arterial wall, and infections from adjacent surroundings of the aorta are potential causes.57-59 During an infection episode, patients may have hemodynamic instability, impaired immunity, and systemic inflammation.57-59 Bacteremia may also produce collagenases that may break down aorta integrity.57-59 These common mechanisms may explain why we observed increased risk of AA associated with several indicated infections, although the magnitudes vary with infection type and severity. To our knowledge, our study is the first to quantify the magnitude of risk of AA/AD with various infections.

    Association Between Fluoroquinolones and AA/AD

    Several observational studies reported an elevated risk of AA/AD with oral fluoroquinolone use. Daneman et al18 found that fluoroquinolone use (vs nonuse) was associated with an increased AA risk in a cohort study of elderly Canadian patients (hazard ratio, 2.24; 95% CI, 2.02-2.49). Lee et al19,20 analyzed a random sample of 1 million individuals from the same database used in the current study using various designs and observed an elevated risk of AA/AD for fluoroquinolone use vs nonuse; the OR was 2.28 (95% CI, 1.67-3.13) in the nested case-control design, 2.71 (95% CI, 1.14-6.46) in the case-crossover design, and 3.61 (95% CI, 3.56-3.63) in the case-time-control design. In a Swedish cohort study with an active comparator design, Pasternak et al21 reported a greater risk of AA/AD when comparing fluoroquinolones with amoxicillin (hazard ratio, 1.66; 95% CI, 1.22-2.46). These studies might not have adequately adjusted for the effect of coexisting infections. The nonuser comparison approach is susceptible to confounding by indication60-62 because patients treated with fluoroquinolones may have different infection types or severity vs those not treated with fluoroquinolones.

    The present study analyzed a nationwide database and meticulously controlled for infections and infection severity. In the model that simultaneously included infections and concomitant antibiotic use, we also observed an increased risk of AA/AD with fluoroquinolone use (vs nonuse) as in the prior studies. However, the observed association was probably biased, as in those studies. Specifically, we observed an elevated risk of AA/AD with indicated infections and multiple other antibiotics in the model. All these antibiotics may have been associated with a greater risk of AA/AD, but a more plausible explanation would be that the associations were biased owing to residual confounding.

    Specifically, there could be residual confounding by risk factors for AA/AD, such as tobacco smoking, frailty, infections, and infection severity. Besides adjusting for multiple measured risk factors, we performed a series of analyses restricted to patients with indicated infections that matched cases and controls on infection type and that used an active comparison approach to further reduce confounding bias. These approaches have been shown to reduce measured and unmeasured confounding in observational studies.60-65 Fluoroquinolone use was not associated with a greater risk of AA/AD vs comparison antibiotics. On the other hand, our approach replicated the known association between fluoroquinolone use and tendon rupture disorder,50,51 which lends support to our choice of active comparators.

    Reverse causation may be one of the possibilities leading to fluoroquinolones being the apparent cause of AA. Specifically, patients may have infections followed by the onset of AA and fluoroquinolone use within a short period, and the diagnosis of AA was confirmed only after clinical workup (eFigure 2 in the Supplement). The hypothesis was partly supported by the attenuated risk estimates for fluoroquinolones when we ignored antibiotic use within 1 to 3 days before the index date.

    Despite these concerns, we could not fully rule out an actual causal relation between fluoroquinolones and AA/AD in certain patients. Ciprofloxacin hydrochloride, a commonly used fluoroquinolone, may increase matrix metalloproteinase levels and degrade collagen.66,67 One animal model showed that oral administration of ciprofloxacin hydrochloride (100 mg/kg/d for 4 weeks) did not increase the risk of aortic destruction or enlargement or of AA/AD in mice receiving a normal diet and saline infusion, but conferred a higher adverse consequence in mice receiving a high-fat diet and angiotensin infusion mimicking high exogenous stress.68 However, we did not observe a higher risk of AA/AD with fluoroquinolone use in several high-risk subgroups.

    Limitations

    Our study has limitations. First, previous studies generally examined the risk for any use of fluoroquinolones without accounting for concomitant use of other antibiotics.18-21 To reduce drug exposure misclassification, we examined the risk with monotherapy of fluoroquinolones and comparison antibiotics suggested by the treatment guidelines in Taiwan. However, this approach yielded a limited sample size in some subgroup analyses. Second, although we used a validated outcome algorithm, we could not rule out the possibility of outcome misclassification because coding practice may vary by country. However, our results were robust under various outcome definitions.

    Third, although claims databases offer a sufficient sample size to examine rare adverse events, they lack important clinical information, such as image findings, microbiology testing results, and laboratory data. This may lead to missing or misclassified AA/AD, infections, infection severity, and other confounders. However, we applied validated claims-based algorithms to identify indicated infections. Among our cohort patients, approximately 4% of antibiotics were dispensed without an accompanying infection diagnosis. This indicated that undercoding of infection diagnoses may be minimal in the present study. We could not rule out potential misdiagnosis of AA as intra-abdominal infections resulting in the observed positive association. However, contiguous infections, such as intra-abdominal infections, have been reported as a possible cause leading to AA. Our findings are consistent with biological plausibility.57-59 Similarly, potential misdiagnosis of AA as LRTIs or GUTIs may raise concerns about more frequent use of comparison antibiotics and underestimation of the risk with fluoroquinolones. However, the analysis comparing injectable forms of fluoroquinolones and third- or fourth-generation cephalosporins, which are usually used in the presence of strong evidence of infections, yielded null findings. In terms of potential confounding due to infection severity, the analyses stratified by proxy of infection severity, such as treatment setting, dosage form, or cephalosporin generation, produced consistent null associations.

    Finally, although we applied rigorous designs to disentangle the roles of infections and antibiotics on AA/AD, we recognize that this is challenging to do in real-world settings (see eFigure 12 in the Supplement for a plausible directed acyclic graph). Specifically, if there was still residual confounding between antibiotic use and AA/AD due to tobacco smoking, frailty, or other unmeasured confounders, the observed association between infections and AA/AD in the model that adjusted for concomitant antibiotic use could be biased owing to improper adjustment for an intermediate variable.69 However, we would expect the bias to lead to a greater (or spurious) effect of infections and not an attenuation of effect as observed in our analysis.

    Conclusions

    This study’s results emphasize the importance of considering coexisting infections while examining the safety of antibiotics using real-world data. Concern about AA/AD should not preclude patients with indicated infections from necessary treatment with fluoroquinolones.

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    Article Information

    Accepted for Publication: April 27, 2020.

    Corresponding Authors: Chia-Hsuin Chang, MD, ScD, Department of Internal Medicine, National Taiwan University Hospital, Seven Chung-Shan S Rd, Taipei City, 100 Taiwan (chiahsuin@yahoo.com); Yaa-Hui Dong, PhD, Faculty of Pharmacy, National Yang-Ming University School of Pharmaceutical Science, 155 Sec 2 Linong St, Taipei City, 112 Taiwan (yaahuidong@gmail.com).

    Published Online: September 8, 2020. doi:10.1001/jamainternmed.2020.4192

    Author Contributions: Drs Dong and Chang had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Dong, Chang, Wang, Lin, Toh.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Dong, Chang, Wu, Lin, Toh.

    Critical revision of the manuscript for important intellectual content: Dong, Chang, Wang, Lin, Toh.

    Statistical analysis: Dong, Chang, Wu, Lin, Toh.

    Obtained funding: Dong, Chang, Lin.

    Administrative, technical, or material support: Chang, Wang, Lin.

    Supervision: Chang, Lin, Toh.

    Conflict of Interest Disclosures: Dr Chang reported receiving grants from the Ministry of Science and Technology, Taiwan, during the conduct of the study and outside the submitted work. No other disclosures were reported.

    Funding/Support: The study was partly supported by research grant 107F016-3 from National Yang-Ming University, grant YLH106.A001 from National Taiwan University Hospital Yunlin Branch, and grant CI-109-28 from Yen Tjing Ling Medical Foundation.

    Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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