Inflammation is associated with incident hypertension in patients with axial spondyloarthritis: A longitudinal cohort study

ABSTRACT

Objectives

To elucidate the risk factors for the development of incident hypertension (IHT) in patients with axial spondyloarthritis (axSpA).

Methods

We conducted a retrospective cohort study in axSpA patients who were recruited from 2001 to 2019 from a university clinic in Hong Kong. Patients with HT and/or anti-hypertensive drug use at baseline were excluded. They were followed until the end of 2020. The outcome was IHT, defined by a diagnosis and a prescription for an antihypertensive drug. Baseline and time-varying Cox regression analyses adjusting for age, sex, and body mass index (BMI), were used to assess the relationship between drug use, inflammatory burden, and IHT.

Results

Four hundred and thirteen patients [age: 34(25–43) years, male: 319 (77.2%)] were recruited. After a median follow-up of 12 (6–17) years, 58 patients (14%) developed IHT (IHT+group). Among all the baseline variables, disease duration and delay in diagnosis were the independent predictors for IHT based on the Cox regression model. In the multivariate Cox regression analysis, baseline disease duration, delay in diagnosis and time-varying ESR levels were independent predictors associated with an increased risk of IHT. IHT risk was significantly increased in patients with disease duration >5 years. The use of anti-inflammatory drugs was not associated with the development of IHT.

Conclusion

Higher inflammatory burden as reflected by a longer disease duration, delay diagnosis and higher ESR levels, were predictors associated with IHT after adjusting for traditional CV risk factors. These data support routine screening for hypertension in axSpA patients, especially those with longer disease duration.

KEY MESSAGES

What is already known about this subject?

• Patients with axial spondyloarthritis (axSpA) have a higher risk of cardiovascular (CV) disease compared with the general population. Hypertension (HT) is one of the most important modifiable risk factors. Whether increased inflammatory pathways or the use of anti-inflammatory therapies contribute toward the increased prevalence of HT in axSpA remained controversial.

What does this study add?

• First, higher inflammatory burden as reflected by a longer baseline disease duration, delay in diagnosis and higher ESR levels were predictors of incident HT (IHT) after adjusting for traditional CV risk factors in axSpA. Second, IHTrisk was significantly increased in pati\ents with disease duration >5 years.

How might this impact on clinical practice or future developments?

• Early diagnosis and adequate control of systematic inflammation may be important to prevent the development of HT. Routine screening for hypertension in axSpA patients should be considered, especially in patients with longer disease duration.

KEYWORDS:

• Axial spondyloarthritis
• incident hypertension
• cardiovascular disease

Introduction

Patients with radiographic axial spondyloarthritis (r-axSpA), also known as ankylosing spondylitis (AS), had increased incidence of cardiovascular events (CVE) and mortality compared to the general population (1–3), probably due to the interaction between inflammation, traditional CV risk factors and treatment. In a recent study, association between CVE in axSpA patients and the persistency of an inflammatory state, as reflected by an increased C-reactive protein (CRP) level (HR = 1.03), AS disease activity score (ASDAS) > 2.1 (HR = 1.014), and Bath AS disease activity index (BASDAI) >4 (HR 1.019) during follow-up, was demonstrated after adjustment for age, sex, and diabetes (4).

Recent meta-analysis reported an increased prevalence of hypertension (HT) in axSpA patients compared with controls (5) HT is the most prevalent comorbidity (pooled prevalence 23%) in axSpA (18), and is one of the strongest predictors for accelerated atherosclerosis and atherosclerotic vascular events in the general population (6). The mechanisms underlying this increased prevalence of HT in SpA might be related to increased inflammatory pathways (7). Systemic inflammation accelerates the development of premature atherosclerosis in axSpA patients (8), resulting in endothelial dysfunction, arterial stiffness, and impaired vascular wall homeostasis, which subsequently lead to elevated blood pressure (BP) and cardiac damage (9). In addition, decreased mobility due to stiffness leading to increased sedentarism may predispose to the development of HT in patients with high disease activity or damage. In a large cross-sectional study, the Assessment in AS (ASAS)-COMOrbidities in SpA (COMOSPA) study, disease duration and delay in diagnosis in SpA were found to be associated with a higher risk of developing HT (10). Nonetheless, this association would need to be confirmed in longitudinal studies incorporating data on inflammatory markers, disease activity, and drug use. Furthermore, early diagnosis is a global challenge. According to a recent meta-analysis, the pooled mean delay was 6.7 years (95% CI 6.2, 7.2) globally (11), but ranges between 5 and 14 years in the United States (USA) (12). In the COMOSPA study, the delay in diagnosis was rather short [1.1 years (0.0–5.9)]. How delay in diagnosis from different world regions, e.g. Southeast Asia and China, with a mean delay of 6.38 and 4.32 years respectively (11), may play a role in IHT would be of great interest.

Drugs used to target inflammation in axSpA and the risk of developing HT was also controversial. In the ASAS-COMOSPA study, no significant association between non-steroidal anti-inflammatory drugs (NSAIDs) use and HT was found (10). In contrast, longitudinal data from the Prospective Study of Outcomes in AS (PSOAS) cohort demonstrated that continuous NSAIDs use was associated with 12% increased risk in developing incident hypertension (IHT) (13). While a trend was observed between tumor necrosis factor inhibitors (TNFi) use and IHT (13), subsequent analysis from the same cohort did not find any conclusive evidence of such association (10). There is an urgent need to clarify how treatment choices, particularly the long-term use of NSAIDs and TNFi, may impact the risk of IHT in axSpA would need to be explored.

We hypothesize that chronic inflammation and delay of diagnosis are associated with the development of IHT in axSpA independent of anti-inflammatory drug use. We aimed to identify the time-varying effect of (1) inflammatory burden (including inflammatory markers [erythrocyte sedimentation rate and C-reactive protein levels] and disease activity according to Bath AS disease activity index [BASDAI]) (2), time of delay in diagnosing axSpA and (3) drug exposure on the risk of IHT in axSpA patients.

Methods

Study design and patients

This study was part of a retrospective cohort study to address the prevalence and risk factors for CVE in axSpA. Data on the association between inflammatory burden and CVE in this cohort (n = 463) has been published (15). Briefly, consecutive patients aged≥18 and fulfilling the 2009 ASAS classification criteria (16) without established CV events (angina, myocardial infaction, ischemic heart disease, ischemic and hemorrhagic stroke, acute and chronic heart failure, transient ischemic attack, surgery including percutaneous transluminal coronary angioplasty or carotid endarterectomy) were recruited from the rheumatology clinic at the Prince of Wales Hospital from 2001 to 2019, and were followed until 2020. Other exclusion criteria for this study include preexisting HT and/or on antihypertensives; or other risk factors which may increase the risk of HT or precluding the use of NSAIDs (end-stage renal disease, anemia, gastrointestinal bleeding, and congenital vascular disease) (n = 50). They were followed until the occurrence of IHT, end of study (December 2020), or loss to follow-up. For patients who were diagnosed with axSpA before 2001 (n = 127), the baseline visit was defined as the first clinic visit in the year 2001; for patients diagnosed with axSpA from 2001 onwards (n = 286), the baseline visit was defined as the first clinic visit.

The study was approved by the Ethics Committee (EC) of the Chinese University of Hong Kong (CUHK) and the Hospital Authority (HA) (No. 2020. 519) and conducted in compliance with the Declaration of Helsinki and ICH guideline for Good Clinical Practice (GCP). Written informed consents were waived.

Clinical assessment

At baseline, CV risk factors (age, height, weight, BP, history of diabetes mellitus [DM], dyslipidemia, drinking, and smoking habits) were recorded. Symptom duration was defined as the duration from symptom onset to baseline visit. Disease duration was defined as the duration from the clinical diagnosis to baseline visit. Delay in diagnosis was defined as the interval between the onset of musculoskeletal symptoms (such as the earliest onset of back pain, peripheral joint pain, dactylitis, or enthesitis), and the diagnosis of axSpA. Inflammatory markers were measured including erythrocyte sedimentation rate (ESR) and CRP. Disease activity and functional ability were assessed using the BASDAI (17) and Bath AS Functional Index (BASFI) (18), respectively. Baseline clinical and demographic data, drug history, and traditional CV risk factors were retrieved from case notes and the citywide electronic medical record system (Clinical Management System [CMS]). A follow-up was scheduled every 6–12 months and clinical data including BP, disease activity, inflammatory markers and drug use were regularly updated.

BP was measured by a nurse or trained healthcare assistant in the non-dominant arm using a digital automatic blood pressure monitor (Colin 8800 NIBP monitor with a cuff of the appropriate size, which was subsequently replaced by the A&D Medical TM-2657-P) following standard recommended procedures. Measurement was initiated after a 5-min rest. If the BP reading was suboptimal, an extra measurement would be subsequently implemented. If both blood pressure readings were suboptimal, clinicians may measure extra blood pressure readings for the patients and select the most appropriate blood pressure reading based on clinical judgment.

NSAID usage was quantified according to the NSAID index (19). Briefly, patient taking on NSAID and full recommended dosage of an NSAID in the 6 months preceding the study visit would receive an NSAID index of 0 and 100, respectively. In our analyses, NSAID use was dichotomized as continuous use (NSAID index ≥ 50, defined as 50% of the maximum recommended dose, taken daily) vs on demand/no use (NSAID index <50) (13).

Time-varying inflammatory burden (BASDAI and inflammatory markers) and drug exposure (disease modifying antirheumatic drugs [DMARDs] including biologic DMARDs [bDMARDs], conventional synthetic DMARDs [csDMARDs], NSAIDs, and paracetamol) were also retrieved from CMS at yearly intervals starting from baseline visit till the end of study. In the time-varying analysis, inflammatory marker was added as a continuous variable (ESR/CRP levels) and as a dichotomous variable: pro-inflammatory response (yes/no). The cutoff value for the presence of pro-inflammatory response was defined as CRP >3 mg/L which was suggested to be associated with elevated CV risk in the general population (20). The cutoff for ESR was ≥20 mm/hr.

Endpoint

The outcome was the diagnosis of new onset IHT, defined as either systolic BP (SBP) ≥140 mm Hg or diastolic BP (DBP) ≥90 mm Hg on two consecutive visits, or the initiation of antihypertensive medication during subsequent follow-up, according to the seventh Joint National Committee (JNC7) guidelines (21).

Statistical analysis

Descriptive statistics were expressed as mean ± SD for normally distributed data, median, and interquartile range (IQR) for non-normally distributed data or number with percentage. Differences in baseline clinical and demographic features between the two groups who either remained normotensive or developed IHT were assessed using Student’s t-test, Mann–Whitney U test or χ2 test. Univaraite and multivarite Cox proportional hazard regressions were used to investigate the associations between baseline disease duration, delay in diagnosis, the presence of uveitis, SBP and DBP, and the time-varying inflammatory burden (inflammatory makers [CRP and ESR] and disease activity [BASDAI]) and medications exposures (NSAIDs and DMARDs), and the development of IHT after adjusting for the baseline age, sex, and BMI. Inflammatory markers were measured regularly (every 6–12 months), and a yearly interval was maintained for the time-dependent analyses. Different kinds of NSAIDs, bDMARDs, paracetamol use was conflated respectively to form a mutually exclusive group of either user or non-user for each interval of follow-up. Intervals with missing data were dropped from the analysis. Time-varying variables with a p-value<.05 in the univariable analysis were included in the mutivariate models. Time-varying Cox proportional hazard regression analyses was performed using R version 4.1.3 (https://www.r-project.org/) in the “survival” package. Other statistical analyses were performed using SPSS V.26.0 for Windows. A p-value <.05 was considered statistically significant.

Results

Baseline characteristics

Four hundred and thirteen patients were enrolled in this study (median age of 34 [25–43] years, 319 were male [77.2%]). Most patients had short disease duration (0–5 years in 346 [83.8%] [297 were newly diagnosed], 5–10 years in 36 [8.7%] and >10 years in 31 [7.5%]). After a median follow-up of 12 (6–17) years, 58 patients (14%) developed IHT (IHT+group). At baseline, the IHT+ve group had a significantly higher prevalence of CV risk factors (including older age, higher SBP and DBP, cholesterol, and fasting glucose levels and traditional CV risk scores) and inflammatory burden (longer disease duration and delay in diagnosis, higher ESR level, and prevalence of active disease with BASDAI ≥ 4) (Table 1). History of uveitis and drug use was similar between the two groups (Table 1).

Table 1. Baseline characteristics of entire cohort, the subgroups of patients who developed incident hypertension or remained normotensive during subsequent follow-up.

	Entire cohort (N = 413)	Normotensive group (N = 355)	Incident hypertension group (N = 58)	P value
Cardiovascular risk factors
Sex (male), n (%)	319 (77.2)	271 (76.3)	48 (82.8)	0.28
Age (years)	34 (25-43)	32 (24-41)	43 (33-49)	<.001*
BMI (kg/m^2)	27 (5)	26 (5)	28 (5)	0.31
Systolic blood pressure (mmHg)	119 (109-130)	117 (108-127)	134 (122-137)	<.001*
Diastolic blood pressure (mmHg)	73 (67–80)	72 (65–79)	83 (73–90)	<.001*
Smoker (current), n (%)	108 (26.2)	96 (27)	12 (20.7)	0.307
Drinker, n (%)	89 (21.5)	75 (21.1)	14 (24.1)	0.605
Diabetes, n (%)	5 (1.2)	3 (0.8)	2 (3.4)	0.093
Dyslipidemia, n (%)	12 (2.9)	10 (2.8)	2 (3.4)	0.791
Total cholesterol (mmol/L)	4.7 (4.1–5.2)	4.6 (4–5.2)	5 (4.2–5.6)	0.031*
Triglyceride (mmol/L)	0.9 (0.7–1.3)	0.9 (0.7–1.3)	1.1 (0.8–1.6)	0.001*
HDL (mmol/L)	1.3 (1.1–1.7)	1.4 (1.2–1.7)	1.3 (1.1–1.6)	0.282
LDL (mmol/L)	2.7 (2.3–3.2)	2.7 (2.3–3.1)	3.1 (2.4–3.6)	0.013*
Fasting glucose (mmol/L)	5.1 (4.8–5.4)	5 (4.8–5.3)	5.2 (4.9–5.6)	0.016*
TC/HDL ratio	3.3 (2.8–4.1)	3.2 (2.7–3.8)	3.8 (3–4.7)	0.008*
FRS @	2.1 (0.7–4.5)	1.7 (0.6–4)	4.5 (2.7–7.5)	<.001*
QRISK3 @	0.8 (0.2–2.2)	0.8 (0.2–2.2)	1.2 (0.4–2.1)	0.136
SCORE @	1 (1–2)	1 (1–1)	2 (1–3)	<.001*
Disease related parameters
Baseline disease duration (years)	0 (0–1)	0 (0–0)	1 (0–9)	<.001*
Delay in diagnosis (years)	1 (0–3)	1 (0–3)	2 (1–6)	<.001*
Family history of spondyloarthritis, n (%)	73 (17.7)	61 (17.2)	12 (20.7)	0.516
Radiographic axSpA, n (%)	334 (80.9)	280 (78.9)	54 (93.1)	0.011*
Juvenile onset, n (%)	74 (17.9)	68 (19.2)	5 (10.3)	0.105
HLA-B27+ve, n (%)	263 (63.7)	239 (67.3)	24 (41.4)	0.001*
BASDAI (0–10), n (%)	4.9 (3–6.5)	4.7 (3–6.5)	6.1 (3.3–6.9)	0.041*
—BASDAI≥4, n (%) —BASDAI≥5, n (%) —BASDAI≥6, n (%)	266 (64.4) 200 (48.4) 142 (34.4)	223 (62.8) 163 (45.9) 112 (31.5)	43 (74.1) 37 (63.8) 30 (51.7)	0.095 0.012* 0.003*
BASFI (0–10)	4.1 (2–6)	3.9 (1.9–6)	5.3 (3–6.5)	0.005*
Peripheral arthritis, n (%)	97 (23.5)	86 (24.2)	11 (20)	0.381
Enthesitis, n (%)	56 (13.6)	51 (14.4)	5 (8.6)	0.236
Dactylitis, n (%)	12 (2.9)	9 (2.5)	3 (5.2)	0.268
Uveitis, n (%)	66 (12)	56 (15.8)	10 (17.2)	0.777
CRP (mg/L)	11 (3.6–26)	11 (3.6–26.4)	10.7 (3.6–25.7)	0.829
ESR (mm/first hour) —ESR≥20, n (%)	27 (12–47) 261 (63.2)	26 (12–46) 218 (61.4)	33.5 (18–55) 43 (74.1)	0.044* 0.062
Medications
NSAIDs, n (%)	345 (83.5)	292 (82.3)	53 (91.4)	0.082
Continuous NSAIDs, n (%)	150 (36.3)	127 (35.8)	23 (39.7)	0.569
Cox2, n (%)	54 (13.1)	50 (14.1)	4 (6.9)	0.132
csDMARDs, n (%)	87 (21.1)	78 (22)	9 (15.5)	0.264
bDMARDs, n (%)	69 (16.7)	59 (16.6)	10 (17.2)	0.906
Metformin, n (%)	1 (0.2)	1 (0.3)	0 (0)	0.686
Steroids, n (%)	10 (2.4)	9 (2.5)	1 (1.7)	0.709
Statin, n (%)	8 (1.9)	8 (2.3)	0 (0)	0.248

*Statistically significant at p < .05.

@ Baseline data of 413 and 412 patients were available for calculating the FRS and SCORE, respectively.

Data are expressed as n (%) or mean (SD) or median (IQR).

IHT+ve, patients who developed incident HBP during subsequent follow-up; IHT−ve, patients who did not develop incident HBP during subsequent follow-up; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; BASFI: Bath Ankylosing Spondylitis Disease Functional Index; CRP: C-Reactive Protein; ESR: Erythrocyte Sedimentation Rate; HDL: High-density Lipoprotein; LDL: Low-density Lipoprotein; FRS: Framingham Risk Score; SCORE: Systematic Coronary Risk Evaluation; NSAIDs: Nonsteroidal anti-inflammatory drugs; Cox2: Cyclooxygenase-2 inhibitor; csDMARDs: Conventional synthetic Disease-Modifying Antirheumatic Drugs; SSZ: Sulfasalazine; MTX: Methotrexate; bDMARDS: Biological Disease-Modifying Antirheumatic Drugs.

Baseline predictors for the development of IHT

Univariate Cox proportional hazard regression model revealed that higher baseline inflammatory burden duration (longer disease duration), longer delay in axSpA diagnosis and worse function (higher BASFI) were significant predictors of developing IHT (Table 2). In the multivariate Cox regression models, BLDD (HR: 1.15, 95 CI: 1.02–1.30, p=0.022) and delay in diagnosis (HR: 1.51, 95 CI: 1.15–1.97, p=0.003) remained significant after adjusted for age, sex, and BMI and basline SBP; BLDD (HR: 1.14, 95 CI: 1.03–1.27, p=0.017) and delay in diagnosis (HR: 1.46, 95 CI: 1.13–1.88, p=0.004) remained significant after adjusted for age, sex, and BMI and basline DBP (Table 2). Kaplan–Meier curves stratified by baseline disease duration (0 to <5 years, 5 to ≤10 years and >10 years) are shown in Figure 1. Significantly lower HT-free survival probability was observed in axSpA patients with longer disease duration (Log-rank = 42.13, p < .001) (Figure 1).

Figure 1. Kaplan-Meier curve for the incident hypertension (IHT)-free survival probability of patients stratified by baseline disease duration in the entire cohort. (BLDD: baseline disease duration).

Table 2. Multivariate analysis with Cox proportional hazard regression for the predictors of incident hypertension in entire cohort at baseline.

Univariable

Multivariable

Multivariable

Multivariable

Multivariable

Model 1

Model 2

Model 1

Model 2

Table 2

HR 95% CI

p-value

HR 95% CI

p-value

HR 95% CI

p-value

HR 95% CI

p-value

HR 95% CI

p-value

BLDD

1.06 (1.03, 1.10)

<.001*

1.15 (1.02, 1.30)

0.022*

–

–

1.14 (1.03, 1.27)

0.017*

–

–

Delay in diagnosis

1.17 (1.07, 1.28)

0.001*

–

–

1.51 (1.15, 1.97)

0.003*

–

–

1.46 (1.13, 1.88)

0.004*

r-axSpA

2.53 (0.90, 7.00)

0.074

–

–

–

–

–

–

–

–

HLA-B27

0.46 (0.11, 1.93)

0.286

–

–

–

–

–

–

–

–

BASFI

1.13 (1.02, 1.25)

0.018*

1.26 (0.99, 1.61)

0.064

1.32 (1.2 1.70)

0.032*

1.24 (0.97, 1.57)

0.088

1.30 (1.01, 1.68)

0.04*

Age

1.06 (1.04, 1.08)

<.001*

1.03 (0.98, 1.08)

0.295

1.06 (1.01, 1.12)

0.024*

1.02 (0.97, 1.07)

0.401

1.06 (1.01, 1.12)

0.03*

Sex

1.37 (0.69, 2.71)

0.364

130468282 (0.00,)

0.998

127708063 (0.00,)

0.997

150987520 (0.00,)

0.998

149064858 (0.00,)

0.997

BMI

1.14 (1.06, 1.22)

<.001*

1.13 (1.01, 1.27)

0.038*

1.12 (0.99, 1.26)

0.075

1.14 (1.02, 1.29)

0.25*

1.12 (0.99, 1.26)

0.068

Baseline SBP

1.10 (1.07, 1.14)

<.001*

1.07 (1.01, 1.13)

0.038*

1.10 (1.03, 1.17)

0.005*

–

–

–

–

Baseline DBP

1.12 (1.07, 1.16)

<.001*

–

–

–

–

1.09 (1.01, 1.18)

0.028*

1.11 (1.03, 1.20)

0.008*

*Statistically significant at p < .05.

Parameters with a p-value of<0.05 in univariable analysis are included in the multivariable analysis.

HR, Hazard ratio; r-axSpA: radiographic axial spondyloarthritis; BLDD: Baseline disease duration; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; BASFI: Bath Ankylosing Spondylitis Disease Functional Index; ESR: Erythrocyte Sedimentation Rate; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BMI: Body mass index.

Drug use over time

At baseline, 345 (83.5%), 69 (16.7%), 26 (6.3%) and 69 (16.7%) patients were NSAIDs, sulphasalazine (SSZ), methotrexate (MTX) and bDMARDs users (supplementary Figure S1). A further nine (total 354, 85.7%), 92 (total 161, 39.0%), 38 (total 64, 15.5%) and 90 (total 159, 38.5%) patients were identified as using NSAIDs, SSZ, MTX and bDMARDs during follow-up. The mean duration of NSAIDs, SSZ, MTX and bDMARDs exposure during the period of this study, estimated from the number of study assessments where use of these drugs was reported, was 4.7 ± 4 years, 1.18 ± 2.4 years, 0.3 ± 1.1 years and 0.6 ± 1.8 years respectively.

Of these 413 individuals, 150 (36.3%) reported continuous NSAID use (continuous NSAID group) according to the NSAID index, and 263 (63.7%) reported low-dose or no NSAID use (non-continuous NSAID group). At baseline, patients from the continuous NSAID group had significantly higher disease activity (larger proportion of patients with BASDAI≥4/BASDAI≥6; higher BASDAI, CRP and ESR levels) (Supplementary Table S1). Proportion of patients receiving bDMARDs in both groups were similar.

Time-dependent effects of inflammatory burden and drug exposure on risk of developing IHT

In the univariate Cox regression, higher levels of inflammation (ESR level and ESR ≥ 20) over time were predictor of IHT with hazard ratios (HR) of 1.02 (95% CI: 1.00–1.03) and 2.77 (95% CI: 1.29–5.94), respectively (Table 3). Regarding the effects of drugs, increased exposure to paracetamol and csDMARDs (especially SSZ) were significantly associated with a higher risk of developing IHT; while NSAIDs, other csDMARDs or bDMARD use was not associated with the development of IHT.

Table 3. Univariate analysis with time-dependent Cox proportional hazard regression for the predictors of incident hypertension.

Variable^#	Total person-time interval	Time-dependent HR (95%CI)	P-value
ESR mm/first hour	2532	1.02 (1.00, 1.03)	0.021*
ESR≥20 mm/first hour		2.77 (1.29, 5.94)	0.009*
CRP mg/l	2663	1.01 (0.99, 1.03)	0.39
CRP>3 mg/l		1.65 (0.74, 3.67)	0.221
BASDAI	1702	1.00 (0.94, 1.07)	0.895
BASDAI≥4		1.11 (0.50, 2.47)	0.806
Paracetamol	4639	2.55 (1.49, 4.34)	<.001*
NSAIDs	4639	1.52 (0.89, 2.57)	0.123
–Cox2		1.79 (0.81, 3.98)	0.151
–NonCox2		1.52 (0.90, 2.58)	0.12
Continuous NSAIDs	4639	1.18 (0.69, 2.03)	0.551
bDMARDs	4570	0.59 (0.14, 2.43)	0.464
csDMARDs	4570	2.33 (1.25, 4.39)	0.008*
–SSZ		2.18 (1.12, 4.24)	0.022*
–MTX		2.64 (0.82, 8.54)	0.097
–LEF		2.34 (0.32, 17.08)	0.403

*Statistically significant at p < .05.

^Parameters with a p-value of <0.05 are included in the multivariable analysis.

^#Variables are time-varying unless otherwise specified.

HR, Hazard ratio; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; CRP: C-Reactive Protein; ESR: Erythrocyte Sedimentation Rate; NSAIDs: Nonsteroidal anti-inflammatory drugs; Cox2: Cyclooxygenase-2 inhibitor; csDMARDs: Conventional synthetic Disease-Modifying Antirheumatic Drugs; bDMARDS: Biological Disease-Modifying Antirheumatic Drugs; SSZ: Sulfasalazine; MTX: Methotrexate; LEF: Leflunomide; BMI: Body mass index.

In the time-varying multivariate Cox regression models (Table 4a), BLDD (Model 1and 2: HR: 1.17-1.18) and delay in diagnosis (Model 3 and 4: HR: 1.51) were significant predictors of IHT after adjusting for age, sex, BMI and baseline SBP. In table 4b, BLDD (Model 1-2: HR: 1.17-1.18) and delay in diagnosis (Model 3-4: HR: 1.51) were significant predictors of IHT after adjusting for age, sex, BMI and baseline DBP. In the fully adjusted model, BLDD (HR: 1.14), delay in diagnosis (HR: 1.45-1.48), and higher ESR levels (HR: 1.03) were significantly associated with higher risk of developing IHT (Table 5, Model 2 to 4).

Table 4. Multivariate analysis with time-dependent Cox proportional hazard regression for the predictors of incident hypertension in entire cohort.

Table 4a		Model 1		Model 2		Model 3		Model 4
	Time-dependent HR (95%CI)	p-value	Time-dependent HR (95%CI)	P-value	Time-dependent HR (95%CI)	P-value	Time-dependent HR (95%CI)	P-value
ESR	1.02 (0.99, 1.05)	0.119	1.03 (1.00, 1.05)	0.096	1.02 (0.99, 1.05)	0.193	1.02 (0.99, 1.05)	0.156
csDMARDs	1.30 (0.24, 7.06)	0.764			2.06 (0.45, 9.48)	0.354
SSZ			8.49 (0.11, 6.31)	0.873			1.65 (0.27, 9.88)	0.586
BLDD	1.17 (1.04, 1.32)	0.008*	1.18 (1.05, 1.32)	0.007*
Delay in diagnosis					1.51 (1.13, 2.03)	0.006*	1.51 (1.12, 2.03)	0.006*
Paracetamol	8.23 (0.21, 3.27)	0.782	8.08 (0.20, 3.19)	0.761	1.07 (0.30, 3.84)	0.918	1.03 (0.29, 3.67)	0.961
Age	1.04 (0.99, 1.10)	0.142	1.04 (0.98, 1.10)	0.199	1.08 (1.02, 1.14)	0.007*	1.08 (1.02, 1.15)	0.012*
Sex	1.71 (0,)	0.999	1.56 (0,)	0.999	2.86 (0,)	0.999	2.96 (0,)	0.999
BMI	1.10 (0.97, 1.26)	0.142	1.12 (0.98, 1.28)	0.098	1.07 (0.95, 1.20)	0.282	1.08 (0.95, 1.22)	0.225
Baseline SBP	1.05 (0.97, 1.12)	0.217	1.04 (0.97, 1.12)	0.218	1.05 (0.98, 1.12)	0.165	1.05 (0.98, 1.12)	0.192
Table 4b ESR	1.02 (0.99, 1.05)	0.124	1.02 (0.99, 1.06)	0.115	1.02 (0.99, 1.05)	0.162	1.02 (0.99, 1.05)	0.142
csDMARDs	9.95 (0.19, 5.18)	0.995			1.97 (0.43, 8.95)	0.378
SSZ			7.98 (0.10, 6.31)	0.830			1.88 (0.29, 12.09)	0.505
BLDD	1.17 (1.05, 1.31)	0.005*	1.18 (1.05, 1.32)	0.005*
Delay in diagnosis					1.55 (1.15, 2.08)	0.004*	1.54 (1.15, 2.06)	0.004*
Paracetamol	8.33 (0.21, 3.29)	0.795	8.27 (0.21, 3.24)	0.785	1.10 (0.31, 3.91)	0.875	1.06 (0.30, 3.69)	0.928
Age	1.04 (0.98, 1.09)	0.208	1.03 (0.98, 1.10)	0.256	1.08 (1.02, 1.15)	0.01*	1.08 (1.02, 1.15)	0.013*
Sex	7.86 (0,)	0.998	7.46 (0,)	0.998	3.06 (0,)	0.999	3.26 (0,)	0.999
BMI	1.12 (0.98, 1.27)	0.101	1.13 (0.98, ^†1.29)	0.097	1.06 (0.94, 1.20)	0.357	1.06 (0.93, 1.22)	0.384
Baseline DBP	1.07 (0.98, 1.18)	0.149	1.07 (0.98, 1.18)	0.143	1.09 (0.99, 1.20)	0.091	1.09 (0.99, 1.20)	0.094

*Statistically significant at p < .05.

HR, Hazard ratio; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; CRP: C-Reactive Protein; ESR: Erythrocyte Sedimentation Rate; csDMARDs: Conventional synthetic Disease-Modifying Antirheumatic Drugs; SSZ: Sulfasalazine; BLDD: Baseline disease duration; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BMI: Body mass index.

Table 5. Multivariate analysis with time-dependent Cox proportional hazard regression for the predictors of incident hypertension in entire cohort.

		Model 1		Model 2		Model 3		Model 4
	Time-dependent HR (95%CI)	p-value	Time-dependent HR (95%CI)	P-value	Time-dependent HR (95%CI)	P-value	Time-dependent HR (95%CI)	P-value
ESR	1.03 (1.00, 1.07)	0.057	1.03 (1.00, 1.07)	0.043*	1.03 (1.00, 1.07)	0.049*	1.03 (1.00, 1.07)	0.042*
csDMARDs	1.61 (0.30, 8.51)	0.576			1.53 (0.29, 8.02)	0.617
SSZ			1.20 (0.16, 9.22)	0.863			1.26 (0.15, 10.30)	0.829
BLDD	1.14 (1.01, 1.27)	0.03*	1.14 (1.02, 1.28)	0.026*	1.14 (1.01, 1.27)	0.027*	1.14 (1.01, 1.28)	0.027*
Delay in diagnosis	1.46 (1.08, 1.97)	0.015*	1.45 (1.07, 1.97)	0.017*	1.47 (1.09, 1.99)	0.013*	1.46 (1.08, 1.98)	0.014*
Paracetamol	9.87 (0.25, 3.96)	0.985	9.62 (0.24, 3.83)	0.956	1.02 (0.26, 3.97)	0.982	9.89 (0.26, 3.81)	0.986
Age	1.07 (1.00, 1.13)	0.039*	1.07 (1.00, 1.14)	0.06	1.07 (1.00, 1.14)	0.054	1.06 (0.99, 1.14)	0.072
Sex	9.51 (0,)	0.998	7.48 (0,)	0.998	2.07 (0,)	0.999	1.72 (0,)	0.999
BMI	1.08 (0.96, 1.23)	0.205	1.10 (0.96, 1.25)	0.178	1.08 (0.95, 1.23)	0.253	1.09 (0.94, 1.25)	0.250
Baseline SBP	1.03 (0.96, 1.10)	0.420	1.03 (0.96, 1.10)	0.449
Baseline DBP					1.07 (0.97, 1.18)	0.205	1.07 (0.97, 1.18)	0.206

*Statistically significant at p < .05.

HR, Hazard ratio; csDMARDs: Conventional synthetic Disease-Modifying Antirheumatic Drugs; SSZ: Sulfasalazine; BLDD: Baseline disease duration; ESR: Erythrocyte Sedimentation Rate; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BMI: Body mass index.

We conducted a sensitivity analysis by including BLDD as an ordinal variable (<5 years, 5–10 years, and >10 years, in Table 6). Patients with BLDD between 5 and 10 years (HR 5.72 to 6.15 in Model 1 and 2) and BLDD >10 years (HR 1.41 to 1.42 in Models 1 and 2) had significantly increased risk of IHT compared with those with BLDD <5 years adjusting for baseline SBP and covariates in Table 6a; BLDD between 5 and 10 years (HR 4.33 to 4.49 in Model 1 and 2) and BLDD >10 years (HR: 1.88 in Models 1 and 2) had significantly increased risk of IHT compared with those with BLDD <5 years adjusting for baseline SBP and covariates in Table 6b. In the fully adjusted model, BLDD >10 years (HR: 1.59 in Model 3 and 4) and delay in diagnosis (HR 1.41-1.42 in Model 3 and 4) remained as significant predictors for the development of IHT adjuasting for baseline SBP and covariates (Table 6a); BLDD >10 years (HR 1.24-1.26 in Model 3 and 4) and delay in diagnosis (HR 1.46-1.48 in Model 3 and 4) remained as significant predictors for the development of IHT adjuasting for baseline DBP and covariates (Table 6b). Higher ESR level (HR 1.03–1.04 in all models) was also significantly associated with the development of IHT; while exposure to csDMARDs (or SSZ) and paracetamol were no longer significant.

Table 6. Multivariate analysis with time-dependent Cox proportional hazard regression for the predictors of incident hypertension stratified by baseline disease duration in entire cohort.

Table 6a		Model 1		Model 2		Model 3		Model 4
	Time-dependent HR (95%CI)	p-value	Time-dependent HR (95%CI)	P-value	Time-dependent HR (95%CI)	P-value	Time-dependent HR (95%CI)	P-value
ESR	1.03 (1.00, 1.06)	0.08	1.03 (1.00, 1.06)	0.067	1.03 (1.00, 1.07)	0.041*	1.04 (1.01, 1.07)	0.021*
csDMARDs	1.29 (0.23, 7.37)	0.776			1.85 (0.33, 10.48)	0.456
SSZ			9.27 (0.12, 7.30)	0.942			1.39 (0.17, 11.14)	0.758
BLDD<5y	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
5<BLDD<=10y	5.72 (1.01, 32.5)	0.049*	6.15 (1.15, 32.99)	0.034*	2.67 (0.40, 18.04)	0.313	2.99 (0.46, 19.34)	0.249
BLDD>10y	2.36 (3.48, 159.9)	0.001*	2.38 (3.48, 162.96)	0.001*	1.59 (2.20, 114.96)	0.006*	1.59 (2.20, 115.03)	0.006*
Delay in diagnosis					1.42 (1.04, 1.95)	0.028*	1.41 (1.03, 1.94)	0.034*
Paracetamol	6.58 (0.15, 2.72)	0.563	6.42 (0.16, 2.63)	0.537	9.06 (0.21, 3.88)	0.894	8.69 (0.20, 3.69)	0.85
Age	1.04 (0.99, 1.10)	0.14	1.04 (0.98, 1.10)	0.186	1.07 (1.00, 1.13)	0.039*	1.07 (1.00, 1.14)	0.058
Sex	9.91 (0,)	0.999	1.06 (0,)	0.999	1.97 (0,)	0.999	2.62 (0,)	0.999
BMI	1.09 (0.96, 1.24)	0.185	1.11 (0.96, 1.27)	0.154	1.07 (0.95, 1.22)	0.269	1.08 (0.95, 1.24)	0.249
Baseline SBP	1.07 (1.00, 1.15)	0.08	1.07 (0.99, 1.15)	0.081	1.05 (0.97, 1.12)	0.213	1.04 (0.97, 1.12)	0.238
Table 6b ESR	1.03 (1.00, 1.06)	0.077	1.03 (1.00, 1.06)	0.081	1.04 (1.00, 1.07)	0.039*	1.04 (1.00, 1.07)	0.032*
csDMARDs	9.78 (0.17, 5.46)	0.980			1.82 (0.32, 10.23)	0.499
SSZ			1.04 (0.14, 7.79)	0.972			1.68 (0.21, 13.08)	0.622
BLDD<5y	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
5<BLDD<=10y	4.53 (0.80, 25.73)	0.088	4.49 (0.86, 23.52)	0.076	2.16 (0.34, 13.66)	0.413	2.47 (0.42, 14.36)	0.315
BLDD>10y	1.88 (2.88, 123.01)	0.002*	1.88 (2.88, 122.90)	0.002*	1.26 (1.70, 93.12)	0.013*	1.24 (1.68, 91.12)	0.014*
Delay in diagnosis					1.48 (1.09, 2.01)	0.013*	1.46 (1.08, 1.99)	0.016*
Paracetamol	8.33 (0.21, 3.25)	0.792	8.36 (0.22, 3.21)	0.794	1.07 (0.26, 4.47)	0.928	1.01 (0.25, 4.13)	0.985
Age	1.04 (0.99, 1.10)	0.157	1.04 (0.98, 1.10)	0.173	1.07 (1.00, 1.14)	0.036*	1.07 (1.00, 1.14)	0.044*
Sex	1.32 (0,)	0.998	1.40 (0,)	0.999	1.98 (0,)	0.999	2.19 (0,)	0.999
BMI	1.11 (0.98, 1.26)	0.109	1.11 (0.97, 1.27)	0.137	1.07 (0.94, 1.22)	0.305	1.07 (0.93, 1.23)	0.349
Baseline DBP	1.07 (0.97, 1.18)	0.206	1.07 (0.97, 1.17)	0.204^†	1.06 (0.96, 1.18)	0.234	1.06 (0.96, 1.18)	0.237

*Statistically significant at p < .05.

^†HR, Hazard ratio; csDMARDs: Conventional synthetic Disease-Modifying Antirheumatic Drugs; SSZ: Sulfasalazine; BLDD: baseline disease duration; ESR: Erythrocyte Sedimentation Rate; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BMI: Body mass index.

Discussion

This is the first longitudinal study which comprehensively assessed risk factors for IHT in axSpA patients, majority (83.8%) of them with short disease duration (≤5 years). We have demonstrated that longer BLDD and delay in diagnosis were the strongest risk factors for developing IHT after adjusting for traditional CV risk factors including age, sex and BMI, with the odds of having a diagnosis of IHT increased by 16% and 48% per year, respectively. More importantly, BLDD longer than 5 years conferred significantly higher risk of developing IHT. Higher ESR levels over time may also contribute toward the increased risk of developing IHT. In contrast, no significant association was observed between drug exposure and risk of developing IHT, suggesting that inflammatory burden (as reflected by the BLDD, delay diagnosis and high ESR level) is the main driver of developing IHT, confirming the results from the cross-sectional ASAS-COMOSPA study (10).

It is well established that traditional CV risk factors are more prevalent in axSpA patients than in the general population, of which the prevalence of HT ranges around 20%–40% (22–24). Previous studies have shown that patients with SpA, especially those with uveitis history and axial involvement, were associated with HT (10, 25). Our present study reinforced the role of inflammation on the development of HT. Cumulative inflammatory burden as reflected by the BLDD was significantly correlated with IHT indicating that persistent, low-grade, systemic Inflammation in axSpA leads to increased endothelial damage (either directly or indirectly), as demonstrated by the significantly impaired flow medicated dilatation compared to controls (26). Coupled with dysfunctional vascular repair, as reflected by the significantly lower serum levels of endothelial progenitor cells, a serum marker of vascular endothelium repair, in patients with AS compared with healthy controls (27), ultimately resulting in increase in arterial stiffness (28) and thus accounting for the excess HT risk. These mechanisms seem to be active from the very early stage of the disease as we have demonstrated the association of IHT with delay in diagnosis, which is equivalent to the duration from symptom onset to diagnosis, similar to data from a large cross-sectional study (10). The HR of developing IHT for the delay from symptom onset to axSpA diagnosis was even higher than that of disease duration (1.48 vs 1.16 respectively, Table 5), probably because it represents the period of inflammation without specific therapy, while the latter represents the cumulative amount of time the patient has had the disease and therapies, and therefore represents a surrogate of the state of partially suppressed inflammatory burden. ESR level may reflect the residual inflammatory burden after treatment with anti-inflammatory agents. Indeed, ESR level has been associated with HT-mediated organ damage in the general population (29), and we have also demonstrated that ESR≥20 mm/h was associated with a significantly higher risk of CVE in axSpA (15). All these data highlighted the importance of early diagnosis and treatment in minimizing not only joint damage, but also CV risk. It is noteworthy that the risk of IHT was significantly increased in patients with disease duration of >5 years, suggesting that routine screening for HT should be considered, especially in patients with longer disease duration.

NSAIDs induce HT by the inhibition of COX enzymes in the kidney (30). Adverse effects of NSAIDs on BP largely reflect inhibition of renal vasodilator prostaglandins (PGI2 and PGE2), whose role in the regulation of BP has long been known in the largest randomized controlled NSAID trial (31). The role of the COX enzymes in the kidney is complex with opposing actions depending on when and where the enzymes are expressed. For example, COX-2-dependent vasodilator prostaglandins (PGI2 and PGE2) formed in renal medullary interstitial cells play an important role in the adaptive regulation of arterial pressure driven by medullary perfusion (32). Prostaglandins, such as PGE2 and PGI2, are formed predominantly by COX-2, under renoprival conditions (33). However, inhibition of COX-2 in the macula densa system can also have a BP lowering effect, depending on context and timing, as it is a component of the tubuloglomerular feedback mechanism controlling renin release (34). NSAID use in older individuals may depress medullary blood flow and increase BP (35). In younger, healthy individuals, in most of whom both nonselective COX inhibition and selective COX-2 inhibition have no effects on arterial pressure. Further studies are required to address whether there are differential effects of nonselective NSAIDs vs COX2 inhibition on IHT in this group of young patients with axSpA.

A previous study report that continuous NSAID use was associated with an increased risk for IHT compared to noncontinuous or no use, and this association did not differ in subgroups defined by age, body mass index, biologic use, or disease activity (13). Nevertheless, they did not adjust for the inflammatory burden including disease duration and delay in diagnosis, which were found to be the main risk factors for the development of IHT in our cohort. Moreover, the increased BP level by NSAIDs (elevated supine mean blood pressure by 5.0 mm Hg [95% CI, 1.2 to 8.7 mm Hg]) (36) may not be clinically significant in this patient group who were relatively young with mean SBP 119 (109–130) and DBP 73 (67–80) at baseline, to meet the criteria for the diagnosis of HT. We were not able to analyze the differential effects of nonselective NSAIDs vs COX2 inhibition on IHT in this group of young patients. Therefore, further studies are clearly needed to confirm or refute the effects of NSAIDs on IHT development in these young patients. With regards to the effects of bDMARDs, prior studies have suggested that TNFi improves endothelial dysfunction and stabilize or slow down the progression of subclinical atherosclerosis and arterial stiffness as inflammation regresses in AS patients (37–39), although previous study did not observe significant changes in risk of IHT (14) which concurred with our findings.

To date, this is the first longitudinal cohort to investigate the associations between inflammatory burden and hypertension in axSpA with more than 10 years of follow-up. We were able to analyze the effects of time-varying covariate (inflammatory markers, disease activity index and drug use) on IHT, in addition to the baseline covariates. BP was routinely measured during each clinic visit and therefore readings of BP can be found in all patients and at all clinical visits in our cohort, which minimized bias and loss of data during follow-up.Moreover, we used the validated IHT definition rather than self-reported diagnosis (13,14) which should provide a more accurate diagnosis. Nevertheless, our study has some limitations. First, unfortunately, patient global assessment was not routinely performed in our cohort and therefore ASDAS cannot be computed. Whether ASDAS may be a better disease activity marker associated with IHT would need to be addressed in future study. Second, one limitation of our study is the low exposure to bDMARDs in Hong Kong due to the lack of reimbursement by the government. The Samaritan Fund Program provides financial assistance only to eligible patients who pass the financial assessment. As a result, patients who may benefit from bDMARD treatment may not be able to afford as most patients need to pay out-of-pocket. The relatively low exposure of bDMARDs in our cohort might restrict the power to show the significant difference use of NSAIDs in bDMARDs user and non-user at baseline (supplementary table S2). Last but not least, we were not able to analyze the differential effects of nonselective NSAIDs vs COX2 inhibition on IHT in this group of young patients.

In conclusion, axSpA patients with a higher inflammatory burden, reflected by a higher ESR level, a longer delay in diagnosis and BLDD, especially BLDD over 5 years, was significantly associated with an increased risk of developing IHT after adjusting for traditional CV risk factors and drug exposures. Early diagnosis and adequate control of systematic inflammation may be important to prevent the development of HT. Routine screening for HT in axSpA patients should be considered, especially in patients with longer disease duration.

Contributors

All authors critically revised the manuscript for important intellectual content. Specific roles included: study design (LS Tam, LH Shi, Steven Lam), data collection (LS Tam, H So, Tena Li, LH Shi, Steven Lam). Data analysis (LH Shi, Steven Lam, Crystal Chan), drafting of manuscript (LH Shi, LS Tam).

The Joint Chinese University of Hong Kong – New Territories East Cluster Clinical Research Ethics Committee (No. 2020. 519). Written informed consent was waived.

Patient and publicinvolvement

Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Acknowledgments

We would like to show our gratitude to all medical staffs, research assistants. Furthermore, we would like to thank all the support from family members.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors reported there is no funding associated with the work featured in this article.