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ORIGINAL ARTICLE
Ahead of print publication  

Burden of associated comorbidities in autoimmune rheumatic diseases in Indian population: An interim report based on the Indian rheumatology association database


1 Chanre Rheumatology and Immunology Center and Research, Bengaluru, India
2 Medical Director & consultant Rheumatologist, Centre for Arthritis & Rheumatism Excellence (CARE), Cochin, Kerala, India
3 Professor, & HOD of Rheumatology, All India Institute of Medical Science, New Delhi, India
4 Rheumatic Disease Clinic, Rheumatic Disease Clinic, 4th floor, Vedanta Institute of Medical Science, Commerce college road, Navrangpura, Ahmedabad, Gujarat, India
5 HOD of clinical Immunology & Rheumatology, Clinical Immunology & Rheumatology Institute of Post Graduate, Medical Education and Research, Kolkata, India

Date of Submission18-Jun-2021
Date of Acceptance21-Oct-2021
Date of Web Publication01-Jun-2022

Correspondence Address:
S Chandrashekara,
Chanre Rheumatology and Immunology Center and Research, Bengaluru
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/injr.injr_125_21

  Abstract 


Aim: The present study is intended to analyze the preliminary interim data to understand the burden of associated comorbidities in autoimmune rheumatic diseases (AIRDS) in the Indian population from the Indian Rheumatology Association database.
Materials and Methods: The independent prospective, multicenter, observational study evaluated the preliminary data obtained from 5 centers across India. The data pertaining to comorbidities were collected, as per the definition of the new International Classification Diseases-10 version of the Charlson Comorbidity Index. The details such as socioeconomic status, impairment in the working capability, and their capacity to cope with their job after developing the disease were gathered for selected patients. The patients were broadly classified into five based on diagnosed AIRDS namely rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), seronegative spondyloarthropathy (SpA), psoriasis arthritis (PsA), and scleroderma. The prevalence of different comorbidities was compared between the groups using Chi-square or Fischer-exact test for nonparametric data and analysis of variance for continuous variables.
Results: The study considered the data of 1885 for the analysis and 129 patients were excluded due to missing variables and data inconsistency. The socioeconomic distribution of AIRDS indicated that SLE was more prevalent among upper-middle-class followed by SpA (60.3% and 50.94%, respectively). RA and systemic sclerosis (SSc) were more common among the lower-income group, and PsA was common among the upper socioeconomic group. The most common comorbidity found in patients with RA and PsA was hypertension (20.97%, 17.14%), SLE and SSc was thyroid disease (21.49%, 17.78%), and SpA was diabetes (2.96%).
Conclusion: AIRDs are associated with the significant burden of comorbidities. Further studies are needed to understand the pattern of prevalence of comorbidities across different age groups.

Keywords: Autoimmune rheumatic diseases, co-morbidities, rheumatoid arthritis



How to cite this URL:
Chandrashekara S, Shenoy P, Kumar U, Pandya S, Ghosh A. Burden of associated comorbidities in autoimmune rheumatic diseases in Indian population: An interim report based on the Indian rheumatology association database. Indian J Rheumatol [Epub ahead of print] [cited 2022 Aug 14]. Available from: https://www.indianjrheumatol.com/preprintarticle.asp?id=349446




  Introduction Top


Rheumatic disorders are one of the most prevalent chronic noncommunicable diseases affecting the musculoskeletal system in a wide range of age groups. Although nearly one-third of hospitalized patients with autoimmune rheumatic diseases (AIRDS) may need intensive care unit admission, the associated disease burden and its impact on the quality of life are often underestimated.[1] The presence of comorbidity influences both the treatment and disease outcomes. The term comorbidity is defined as any condition associated or co-existing with the primary disease or index disease.[2] Estimation of the prevalence of comorbidities in the index case is essential to understand the overall impact and to design the proper disease management guidelines.[3]

Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), seronegative spondyloarthropathy (SpA), psoriasis arthritis (PsA), and scleroderma are the five prototypes of AIRDs. The worldwide prevalence of RA varies between 0.3% and 1%. As per COPCORD study, the estimated prevalence in India ranged from 0.2 to 0.4% and estimates for different zones were as follows: Jammu 0.3%; Delhi 0.2%; Bikaner 0.8%; Kolkata 0.4%; Guwahati 0.4%, Manipur 0.2%, Pune 0.3%; Calicut 0.2%; Hyderabad 0.3%, and Trivandrum 0.4%. The overall burden of RA was high with point prevalence of 0.7%.[4] The patients with RA have several comorbidities. The most prevalent comorbidities noted in Karnataka Rheumatoid Arthritis Comorbidity (KRAC) study in a cohort from south India were hypertension (20.7%), diabetes mellitus (14.4%), and thyroid disease (18.3%).[5]

Similarly, the estimated point prevalence of SLE was 3.2/100,000 population in India.[6] SLE patients tend to have an increased risk for neurological involvement, and mortality due to renal and cardiovascular involvement.[7] Several studies have reported that patients with SLE had the lower health-related quality of life with an impact on patients' psychological and emotional states, vitality, general health, and social lives.[8] The prevalence of obesity in SLE patients ranges from 28.3% to 49.7%.[9] The prevalence of psoriasis was estimated to be 2.3% in India and that of psoriatic arthritis among patients with psoriasis was 8.7%.[10],[11] The commonly reported comorbidities in patients with PsA include unspecified arthritis, hypertension, depression, diabetes, heart disease, and obesity.[12] The worldwide prevalence of systemic sclerosis (SSc) ranges from 7 cases to 489 cases per million. Osteoporosis is a common comorbidity in SSc with a prevalence of 32.5% in the lumbar spine and 51.1% in the femoral neck.[13] The prevalence of coronary artery disease in patients with SSc is estimated to range between 10% and 56%.[14] Seronegative SpA is a group of chronic inflammatory diseases comprising ankylosing spondylitis (AS), PsA, inflammatory bowel disease (IBD) associated arthritis, reactive arthritis (formerly Reiter syndrome, ReA), and undifferentiated SpA. The worldwide prevalence of SpA is estimated to be between 0.4% and 1.9%.[15] The corresponding prevalence of ReA, IBD and undifferentiated SpA noted were 0.2%, 0.1% and 0.07%.[16] The commonly noted comorbidities in SpA patients were osteoporosis (13%) and gastroduodenal ulcer (11%). The most frequent risk factors noted for rheumatic and musculoskeletal diseases were hypertension (34%), smoking (29%), and hypercholesterolemia (27%).[17]

In view of the limited epidemiological evidence/data available on the AIRDS-associated comorbidities in India, we did interim analysis from the national database has been developed by the Indian Rheumatology Association (IRA) with the prime objective to evaluate the clinical spectrum of the AIRDs across the country. The sample size was adequate for evaluating the least prevalent comorbidity in primary disease and the present study has focused on the prevalence of comorbidities in different AIRDs. The study findings are based on preliminary interim data and this is touted as the first demographic study assessing comorbidities and their screening related to AIRD in a nationwide population.


  Materials and Methods Top


Registry/database design and study population

The independent prospective, multicentre, observational study, conducted across India, included 5 centers in the preliminary analysis. The centers were chosen based on geographic location. Totally 7 centers are active and some more will be included shortly (not part of the present report). The database recruited patients suffering from six diseases including RA, SpA, PsA, SLE, scleroderma, and Sjogren's syndrome. The patients fulfilling disease-specific criteria, and those aged >18 (except for SLE), were recruited. Both newly diagnosed as well the patients in follow-up were considered. The database was launched in April 2020, with a target enrolment of 6000 patients, depending on the scope of the database. The data were captured in two separately structured pro forma. The first one collected the details related to common demographic, socioeconomic profile, functional impairment, obstetrics and health-related parameters, and the second one collected details of disease-specific parameters. All the participating centers had obtained consent from the respective institutional ethical committees (list enclosed as appendix). The written informed consent was taken from all the patients before the study, as per the respective institutional recommendation.

Sample size calculation for registry

The minimum number of subjects to be recruited was calculated with a primary objective to evaluate the clinical and laboratory profile of the AIRDs under consideration based on the reported prevalence of the individual diseases. The estimated number of patients to be recruited for analysis was 6500.[18]

Data collection and definition

The data pertaining to comorbidities were collected as per the definition of the new International Classification Diseases (ICD)-10 version of the Charlson Comorbidity Index.[19] The comorbidity details were collected based on the patients' reporting and from the data chart. The comorbidities considered were myocardial infarction, congestive heart failure, congenital heart disease, rheumatic heart disease, peripheral vascular disease, migraine, cerebrovascular disease (stroke, transient ischemic attack), cerebrovascular (hemiplegia) event, dementia, Parkinson or other degenerative neurological disease, chronic pulmonary disease, bronchial asthma, rheumatologic disease, psoriasis, osteoporosis, fibromyalgia, osteoarthritis, peptic ulcer disease, recurrent diarrhea (unknown cause), IBD, mild liver disease, gout, hyperlipidemia, diabetes, diabetes with chronic complications, moderate-to-severe renal disease, cancer without metastases, leukemia, lymphoma, moderate or severe liver disease, metastatic solid tumor, acquired immunodeficiency syndrome/HIV infection, allergic diathesis including asthma, hypothyroidism/hyperthyroidism, tuberculosis, hepatitis B and C, psychiatric disease, neurosis, depression and other comorbidities noted by the principle investigator. The definitions were used as per the ICD code and the trained experts at the sites proactively evaluated the occurrence of comorbidities. The presence of comorbidity was confirmed based on the evaluation done in patients' previous visit to the site or by the previously treated physician. The socioeconomic status was classified based on the Kuppuswamy classification.[19] The impairment in the working capability was assessed on decade basis using patient's perception in performing what he/she was engaged in previous to developing the disease. The patients were enquired about their occupation, and household jobs or homemaking was also considered as an occupational engagement. The patients were asked to grade their ability to perform daily activities, and their capacity to cope with their job (with a lot of difficulties or with minimal difficulty) after developing the disease.

Statistical analysis

For analysis purposes, the patients were broadly classified into 5 based on diagnosed AIRDS namely RA, SLE, seronegative SpA, PsA, and scleroderma. The descriptive data was analyzed amongst the groups. The prevalence of different comorbidities as well the demographics between the five AIRDs were compared using Chi-square or Fischer-exact test for nonparametric data, and analysis of variance (ANOVA) for continuous variables. They were performed using one-way ANOVA as well Chi-square and Fisher exact tests were performed using Vassarstat.[20],[21] Study power was calculated for the least reported comorbidity of cardiovascular disease (CVD) using the power calculator.[18]


  Results Top


A total of 2015 patients were recruited based on the records retrieved from IRA database till February 2021. The study included 1885 for analysis and 129 patients were excluded due to missing variables and data inconsistency. The corresponding number of excluded subjects were as follows: 57 in RA, 42 in SLE, 9 in psoriasis, 1 in SpA and all patients with Sjogren syndrome. The mean age of the study participants was 49.09 (+14.14) years and the overall female-to-male ratio noted was 7:2. Demographic characteristics, the number of patients with each comorbidity, and the details of their socioeconomic status are briefed in [Table 1]. State-wise recruitment and the details of other nonsignificant comorbidities are provided in the [Figure 1] and [Table 2]. Age-wise distribution has demonstrated that mean age was highest for subjects with RA (52.32), followed by PsA (48.65). However, SLE and SpA were prevalent among the younger age group (36.06 and 32.37, respectively). Both PsA and SpA were more prevalent among male patients when compared to RA, SLE, and SSc. The socioeconomic distribution of AIRDS indicated that SLE was more prevalent among the upper middle class followed by SpA (60.3% and 50.94%, respectively). Whereas, RA and SSc were more common among the lower-income group and PsA was common among the upper socioeconomic group.
Figure 1: Patients recruitment centres for Indian Rheumatology Association database and state-wise distribution of patients

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Table 1: Demographic details including number of co-morbidities and socioeconomic status of the population

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Table 2: The different comorbidities recorded for different autoimmune rheumatic diseases

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Asthma, thyroid disease, hypertension, tuberculosis, and diabetes were the most common comorbidities noted in patients with the 5 AIRDs. The most common comorbidity found in patients with RA and PsA was hypertension (20.97%, 17.14%), those with SLE and SSc was thyroid disease (21.49%, 17.78%), and SpA was diabetes (2.96%). Details of the other less predominant comorbidities are presented in the [Table 2]. The prevalence of hyperlipidemia and CVD was found to be relatively small among the study population. Thyroid disease was seen in all the three autoantibody-associated AIRDs namely SLE, scleroderma and RA, and significantly lesser proportion in PsA and SpA. Hypertension, and diabetes were more prevalent in subjects with PsA and RA respectively. RA had significant lesser impact on job-related activities, whereas SpA and PsA had moderate to significant impairment. The marital status of the majority of the SpA and SLE patients was single, as opposed to subjects with RA, PsA, and SSc.


  Discussion Top


The current study has noted thyroid disorder, hypertension, and diabetes as the common comorbidities noted in patients with AIRDS. The prevalence of asthma, CVD, renal disease, and COPD was <1% in the study population. The overall prevalence of one or more comorbidities in patients with SpA and SSc was 9.47% and 52.22%, respectively. The prevalence of comorbidities in patients with RA, SLE, and PsA was >30%. Except for SpA, the disease in the younger population, and the burden of comorbidities substantially added to the care of index disease. The report more or less falls in line with the reports published elsewhere.

There is substantial literature evidence corroborating the present study findings. The 2017 KRAC study from south India has noted that nearly 40% of patients with RA had one or more comorbidities. The corresponding prevalence of hypertension, dyslipidemia, and diabetes mellitus noted were 20.7%, 18.9%, and 14.3%, respectively.[22] A similar study by the same group of researchers had noted the occurrence of one or more co-morbidities in 42% of the patients with PsA.[23] The observation in PsA patients is slightly higher than that reported in the current cohort (31%). The prevalence of AIRDs and comorbidities are more or less comparable. The minor differences noted in different studies could be attributed to the regional difference in the patient pool across India.

According to the study by Rao et al., the corresponding self-reported prevalence of CVD, heart disease and diabetes noted in India were 12%, 4% (7% urban and 3% rural) and 6% (10% in urban and 4% in rural).[24] In contrast to these findings, the CVD cases reported in the current study were comparatively lesser. The sample of the present study has adequate power to substantiate the difference in prevalence.[18] The reported number of CVD cases by KRAC study (representative of the south Indian population) was <0.7%.[5] As per the literature evidence, the prevalence of CVD in RA patients varies in different countries (1% in Morocco and 17% in Hungary).[25] The reduced prevalence of CVD noted in the present stu dy, in contrast to western literature and the general population, may be attributed to the younger age of the patients enrolled as study cohort (mean age 52.32 (±11.89) years) and the use of hydroxychloroquine. The cohort size enrolled in the Consortium of Rheumatology Researchers of North America International registries from India had also reported reduced prevalence of hypertension, hyperlipidemia, and prior CVD in RA patients, as opposed to the data from the US and other ex-US regions.[26] It is necessary to further investigate the reduced prevalence reported in these studies.

Studies have demonstrated that the prevalence of hypertension and diabetes increases with advancing age and this is more prominent in RA and PsA patients.[24] The corresponding prevalence noted in the present study cohort of RA (21% and 12%) and PsA (17% and 16%) patients were significantly higher than the national average.[27] The prevalence of hypertension in RA noted in the present study was higher in contrast to diabetes in PsA. Previous studies have noted increased prevalence of diabetes in PsA patients, whereas the prevalence of RA was comparatively lower. These studies have also reported increased risk of diabetes in PsA patients, especially in patients with onset of psoriasis after 40, thereby highlighting the need for careful evaluation.[28] There is substantial literature evidence corroborating the number of studies showing the direct association between insulin resistance and increase in RA. A very large study based on health insurance claims has reported the odds ratio for diabetes among RA patients to be 1.4 compared to healthy controls. In contrast, a longitudinal cohort study based on medical records study has found that the increased risk for diabetes was trivial.[29]

A multicenter observational study by Wasko et al. has concluded that the use of hydroxychloroquine is associated with reduction in the prevalence of DM in RA.[30] The reported national average of hypertension in a mean age population of 53 years was 22.7% and that of diabetes was 6%–7%.[31] If the rule of half is applied in reporting hypertension, in the present study, the details of hypertension were collected as reported by the patient and/or medication used. Hence, the reported proportion of patients might be higher than the actual cases. Whereas, the comparison of data with the published Indian population studies was by proactive screening for hypertension and diabetes. However, the incidence of diabetes was higher in PsA (16%) compared to that reported in the general population (7.3%).[32]

A cross-sectional study conducted by Nissen et al. has reported increased prevalence of hypertension in patients with AS than RA.[33] In contrast, the current study showed a lower prevalence of hypertension in SpA. The difference between PsA and RA prevalence could be presumed due to differences in the age group of the population.

When compared to the general population, the prevalence of hypothyroidism was significantly higher in patients with three major AIRDs namely RA (13.7%), SLE (6.61%), and SSc (17.8%). The prevalence of hypothyroidism was around 10.7% in India.[34] In contrast, SpA (59%) and PsA (4.76%) had less prevalence. The current study has reported <1% of fibromyalgia cases, in contrast to previous published study by Dhir et al., reporting 15% prevalence of fibromyalgia. However, the prevalence noted by Dhir et al. was significantly higher in RA patients than in the general population (2%).[35] The difference in prevalence could be due to the proactive reporting of fibromyalgia cases by Dhir et al., in contrast to the current study where the prevalence reporting was based on previously confirmed diagnosis or cases managed by treating physicians.

Although certain pattern of distribution has been noted with regard to the socio-economic status of patients with five AIRDs, the number and other influencing factors were not analyzed hence, it is difficult to comment with the current number of patients in each group. The present study has noted a significant association between the burden of SLE and SpA and marriage status, which is more because of the younger disease onset at marriable age.

The major limitation is the use of only interim data, and due to the COVID pandemic, certain sites could not recruit the patients. Though data was collected across India, there is a significant skewing to the south, hence the generalization of the data for the whole of India is not possible with this report. In due course of time, the data along with other sociodemographic data will help. In the current study, the presence of comorbidity was ascertained based on the patients' reporting as well as chart or document-based confirmation of disease and not on the basis of proactive evaluation. This would have underestimated the occurrence of some of the comorbidities. However, since these patients were cared for routinely at a tertiary care center, the study findings reflect real-life scenarios. The major strengths are multi-center data collection and involvement of both academic and private settings. Hence, the study represented individuals with different socioeconomic status. Moreover, the selection of centers based on the geographic distribution of population is an added strength. The power of the study is adequate to validate the current findings.

m

AIRDs are associated with the significant burden of comorbidities. Further studies may help in better understanding the pattern of prevalence of comorbidities across different age groups and to develop guidelines on optimization of management strategies.

Author contributions

All the authors have contributed equally to the conceptualization, data capturing and developing the content.

Acknowledgements

Dr. Debhashish Dhanda and Dr. Aman Sharma for their participation in administrative role in IRA database. The authors acknowledge the help of Research Assist (http://www.research-assist.com) for editing and formatting the manuscript.

Funding

Educational and research grants from Novartis India.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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