
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39232120
71633
10.1038/s41598-024-71633-7
Article
Incidence and prevalence of idiopathic inflammatory myopathies in Thailand from the Ministry of Public Health data analysis
Onchan Tippawan
Foocharoen Chingching
Pongkulkiat Patnarin
Suwannaroj Siraphop
Mahakkanukrauh Ajanee majanee@yahoo.com

https://ror.org/03cq4gr50 grid.9786.0 0000 0004 0470 0856 Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002 Thailand
4 9 2024
4 9 2024
2024
14 206461 3 2024
29 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
The epidemiology of idiopathic inflammatory myopathies (IIMs) varies by country. Investigating the epidemiological profile among Thai IIMs could help to inform public health policy, potentially leading to cost-reducing strategies. We aimed to assess the prevalence and incidence of IIM in the Thai population between 2017 and 2020. A descriptive epidemiological study was conducted on patients 18 or older, using data from the Information and Communication Technology Center, Ministry of Public Health, with a primary diagnosis of dermatopolymyositis, as indicated by the ICD-10 codes M33. The prevalence and incidence of IIMs were analyzed with their 95% confidence intervals (CIs) and then categorized by sex and region. In 2017, the IIM cases numbered 9,074 among 65,204,797 Thais, resulting in a prevalence of 13.9 per 100,000 population (95% CI 13.6–14.2). IIMs were slightly more prevalent among women than men (16.8 vs 10.9 per 100,000). Between 2018 and 2020, the incidence of IIMs slightly declined from 5.09 (95% CI 4.92–5.27) in 2017 and 4.92 (95% CI 4.76–5.10) in 2019 to 4.43 (95% CI 4.27–4.60) per 100,000 person-years in 2020. The peak age group was 50–69 years. Between 2018 and 2020, the majority of cases occurred in southern Thailand, with incidence rates of 7.60, 8.34, and 8.74 per 100,000 person-years. IIMs are uncommon among Thais, with a peak incidence in individuals between 60 and 69, especially in southern Thailand. The incidence of IIMs decreased between 2019 and 2020, most likely due to the COVID-19 pandemic, which reduced reports and investigations.

Keywords

Epidemiology
Incidence
Prevalence
Polymyositis
Dermatomyositis
Subject terms

Diseases
Health care
Rheumatology
The Thailand National Science, Research, and Innovation Fundissue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Idiopathic inflammatory myopathies (IIMs) are a group of connective tissue diseases characterized by muscle inflammation, pain, or weakness, that include dermatomyositis (DM), polymyositis (PM), overlap myositis (OM), sporadic inclusion body myositis (IBM), and necrotizing autoimmune myopathy (NAM)1. IIM patients have lower survival rates than the general population2. The early mortality rate was found to be high, ranging between 7.8 and 45%. Infections and cancers were the primary causes of death3.

The prevalence, incidence, and characteristics of IIMs vary by country. Extensive epidemiological studies have been conducted in various countries to determine the incidence of IIMs3–19. The studies conducted in Asia, Singapore, and Israel reported an incidence of 7.7 and 2.18 cases per million per year, respectively14,15. A systematic review found that the incidence of inflammatory myopathies ranged from 1.16 to 19 cases per million people per year, with a prevalence of 2.4 to 33.8 cases per 100,000. Although there was a significant variation in the results, no obvious geographical disparities were identified17,20. However, no research has been done to determine the prevalence of IIMs in Asia.

To date, there have been no epidemiological studies on the IIMs conducted in Thailand. Additionally, managing refractory IIMs presents challenges due to the high cost of intravenous immunoglobulin (IVIG) and rituximab treatments1. Thus, the purpose of this study was to assess the prevalence and incidence of IIMs in the Thai population between 2017 and 2020 using the ICD 10 codes obtained from the Ministry of Public Health’s Information and Communication Technology Center. These findings could then be used to inform and improve public health policies governing the care of individuals with IIMs, as well as to help reduce costs by allocating appropriate budgets.

Methods

A descriptive epidemiological study was carried out on the entire population of patients 18 years and up whose data had been recorded in the Information and Communication Technology Center, a database managed by the Ministry of Public Health (https://www.moph.go.th). This study focused on individuals from 1st January 2017 to 31th December2020 who had a primary diagnosis of dermatopolymyositis, as indicated by ICD-10 codes M33, including juvenile dermatomyositis, other dermatomyositis, polymyositis, and unspecified dermatopolymyositis. The diagnosis of dermatopolymyositis was made by the physicians who follow up with the patients. The dataset included data from a variety of healthcare providers, including the National Health Security Office (NHSO), the Civil Servants Benefit System from the Comptroller General’s Department, the Social Security Office, and cases involving self-payment. These hospitals maintained databases and the data was submitted and analyzed. The primary diagnosis for each patient was coded according to the International Classification of Disease, Tenth Revision (ICD-10). Demographic variables including age, sex, year of visit, hospital name, Amphoe (district), and province were incorporated into the collected data to prevent data duplication.

Statistical analysis

The analyzed data were presented from both a regional (northern, central, northeastern, eastern, western, and southern) and national perspective. Categorical data were presented as numbers and percentages, and the continuous data were expressed as means and standard deviations (SDs). The prevalence and incidence of IIMs were analyzed, along with their corresponding 95% confidence intervals (CIs). All patients were included to enhance the statistical power of the test. All data analyses were performed using the statistical software STATA (version 16.0; StataCorp, College Station, TX, USA).

Results

The Information and Communication Technology Center, Ministry of Public Health, reported 9074 cases of IIMs in 2017 among 65,204,797 Thais, with 3478 (38.3 percent) men and 5596 (61.7 percent) women. These cases were diagnosed with dermatopolymyositis (ICD-10 codes M33). The female-to-male ratio in 2017 was 1.6:1, which remained stable between 2018 and 2020. During this time, there were 3332, 3228 and 2900 cases of IIM among 65,406,320, 65,557,054, and 65,421,139 Thai citizens, respectively. The peak age range was 50 to 59 years, accounting for 22.9%, 23.6%, 24.7%, and 23.5% of cases between 2017 and 2020, respectively. In 2017, the majority of patients (49.5%) were from northeastern Thailand, with an average age of 48.60 (± 18.06) years (Table 1). Table 1 Case information for ICD-10 code M33 from 2017 to 2020.

Variable	Year	
2017a
n = 9074
n (%)	2018b
n = 3332
n (%)	2019b
n = 3228
n (%)	2020b
n = 2900
n (%)	
Total population	65,204,797	65,406,320	65,557,054	65,421,139	
Age (years)	
 ≤ 29	1441 (15.88)	549 (16.48)	521 (16.14)	417 (14.38)	
 30 to 39	1222 (12.36)	369 (11.07)	369 (11.43)	326 (11.24)	
 40 to 49	1909 (21.04)	657 (19.72)	666 (20.63)	550 (18.97)	
 50 to 59	2073 (22.85)	785 (23.56)	797 (24.69)	682 (23.52)	
 60 to 69	1564 (17.24)	578 (17.35)	512 (15.86)	539 (18.59)	
  > 70	965 (10.63)	394 (11.82)	363 (11.25)	386 (13.31)	
 Mean ± SD	48.60 ± 18.06	49.12 ± 18.46	48.68 ± 18.30	50.41 ± 17.97	
Sex	
 Male	3478 (38.33)	1345 (40.37)	1247 (38.63)	1110 (38.28)	
 Female	5596 (61.67)	1987 (59.63)	1981 (61.37)	1790 (61.72)	
Region	
 Northern	513 (5.65)	185 (5.55)	202 (6.26)	175 (6.03)	
 Central	2141 (23.59)	850 (25.51)	1038 (32.16)	777 (26.79)	
 Northeastern	4492 (49.50)	1581 (47.48)	1306 (40.46)	1243 (42.86)	
 Eastern	593 (6.54)	218 (6.54)	189 (5.86)	203 (7.0)	
 Western	656 (7.23)	211 (8.61)	176 (5.45)	169 (5.83)	
 Southern	679 (7.48)	287 (8.61)	317 (9.82)	333 (11.48)	
aPrevalence cases.

bIncidence cases.

In 2017, the prevalence of IIMs was 13.93 per 100,000 (95% CI 13.63–14.21), with a higher rate among women compared to men (16.84 (95% CI 16.4–17.28) vs 10.88 (95% CI 10.52–11.25) per 100,000) (Table 2). In 2017, the northeastern region had the highest number of IIM cases per 100,000 Thai population (20.49) (95% CI 19.89–21.10). The peak prevalence occurred between 60 and 69 years, with a rate of 26.82 per 100,000 (95% CI 25.51–28.19). Table 2 Prevalence and incidence of IIMs per 100,000 person-years in Thailand from 2017 to 2020.

Variable	Year	
2017	2018	2019	2020	
N	Prevalence (95% CI)	N	Incidence (95% CI)	N	Incidence (95% CI)	N	Incidence (95% CI)	
Total	65,204,797	13.93 (13.63–14.21)	65,406,320	5.09 (4.92–5.27)	65,557,054	4.92 (4.76–5.10)	65,421,139	4.43 (4.27–4.60)	
Age (years)a	
 ≤ 29	24,924,019	5.78 (5.49–6.09)	24,667,116	2.23 (2.04–2.42)	24,356,422	2.14 (1.96–2.3)	23,979,631	1.74 (1.58–1.91)	
 30 to 39	9,804,544	12.46 (11.77–13.18)	9,667,494	3.82 (3.44–4.23)	9,517,260	3.88 (3.49–4.29)	9,408,601	3.46 (3.10–3.86)	
 40 to 49	10,473,467	18.23 (17.42–19.06)	10,374,192	6.33 (5.86–6.84)	10,342,715	6.44 (5.96–6.95)	10,293,850	5.34 (4.91–5.81)	
 50 to 59	9,200,113	22.53 (21.57–23.52)	9,441,220	8.31 (7.74–8.92)	9,576,697	8.32 (7.75–8.92)	9,692,194	7.04 (6.52–7.59)	
 60 to 69	5,830,611	26.82 (25.51–28.19)	6,068,469	9.52 (8.78–10.33)	6,313,454	8.11 (7.42–8.84)	6,579,893	8.19 (7.51–8.91)	
 > 70	4,394,711	21.96 (20.59–23.39)	4,598,334	8.57 (7.74–9.46)	4,822,605	7.53 (6.77–8.34)	5,053,295	7.64 (6.90–8.44)	
Gender	
 Male	31,966,108	10.88 (10.52–11.25)	32,043,770	4.20 (3.98–4.43)	32,094,943	3.89 (3.67–4.11)	31,992,542	3.47 (3.27–3.68)	
 Female	33,238,689	16.84 (16.4–17.28)	33,362,550	5.96 (5.70–6.22)	33,462,111	5.92 (5.66–6.19)	33,428,597	5.35 (5.11–5.61)	
Region	
 Northern	11,670,987	4.40 (4.02–4.79)	11,677,636	1.58 (1.36–1.83)	11,671,188	1.73 (1.50–1.99)	11,607,754	1.51 (1.29–1.75)	
 Central	17,373,692	12.32 (11.81–12.86)	17,427,846	4.88 (4.55–5.22)	17,474,244	5.94 (5.58–6.31)	17,442,982	4.45 (4.15–4.78)	
 Northeastern	21,925,925	20.49 (19.89–21.10)	21,958,131	7.20 (6.85–7.56)	21,967,951	5.95 (5.63–6.28)	21,882,786	5.68 (5.37–6.01)	
 Eastern	4,919,656	12.05 (11.10–13.06)	4,976,443	4.38 (3.82–5.0)	5,033,484	3.75 (3.24–4.33)	5,071,123	4.0 (3.47–4.59)	
 Western	5,565,256	11.79 (10.90–12.72)	5,588,577	3.78 (3.28–4.32)	5,607,281	3.14 (5.69–3.64)	5,606,153	2.01 (2.58–3.50)	
 Southern	3,749,281	18.11 (16.77–19.52)	3,777,687	7.60 (6.74–8.53)	3,802,906	8.34 (7.44–9.31)	3,810,341	8.74 (7.83–9.73)	
aThe analysis excluded approximately 0.9 percent of the population because the National Statistical Office of Thailand did not define a specific age.

Between 2018 and 2020, the incidence of IIMs per 100,000 person-years was 5.09 (95% CI 4.92–5.27), 4.92 (95% CI 4.76–5.10), and 4.43 (95% CI 4.27–4.60), respectively. The majority of IIM cases were reported in southern Thailand, with rates of 7.60 (95% CI 6.74–8.53), 8.34 (95% CI 7.44–9.31), and 8.74 (95% CI 7.83–9.73) per 100,000 person-years from 2018 to 2020, respectively. Peak prevalence was observed in the age groups of 60 and 69 years in 2018 and 2020, with rates of 9.52 (95% CI 8.78–10.33) and 8.19 (95% CI 7.51–8.91) per 100,000 person-years, respectively. In 2019, the peak was between 50 and 59 years, with a rate of 8.32 (95% CI 7.75–8.92) per 100,000 person-years (Table 2).

In 2017, the northeastern region had the highest rate of IIM visits per 100,000 Thai population, with 4,492 cases (49.5%), while the central region followed with 2,141 cases (23.6%) (Fig. 1A). In subsequent years, the number of new IIM cases was 1,581 cases (47.5%) in 2018 (Fig. 1B), 1,306 cases (40.5%) in 2019 (Fig. 1C), and 1,243 cases (42.9%) in 2020 (Fig. 1D). The majority of these cases were concentrated in the northeastern region, particularly in the provinces of Surin, Roi-et, Nong Bua Lamphu, and Chaiyaphum.Fig. 1 The number of IIMs per 100,000 Thais by hospital was calculated based on the visit (the maps were generated using QGIS version 3.8.2, an open source, free geographic data system software; https://www.qgis.org/en/site/). (A) Number of IIMs in 2017 (prevalence cases), (B) incidence cases in 2018, (C) incidence cases in 2019, (D) incidence cases in 2020.

Discussion

A limited number of epidemiological studies have been published as a result of the rarity of IIMs. This is the first epidemiological investigation in Thailand to specifically examine IIMs. For this comprehensive population study, the National Information and Communication Technology Center, a database of the Ministry of Public Health that includes all healthcare providers, provided the data. The purpose of this study was to ascertain the incidence and prevalence of IIMs among Thais throughout the COVID-19 pandemic.

The current study determined that the prevalence of IIMs among Thais was similar to that of the majority of IIMs worldwide, with a rate of 13.93 per 100,000 (95 percent CI 13.63–14.21) in 2017 and a general rate of 14 per 100,000 (95 percent CI 12.84–15.46)17. Essouma et al. likewise reported a prevalence of 11.49 cases per 100,000 in Africa in their systematic review3. Conversely, the majority of IIMs in the United States ranged between 3.45 and 21.42 cases per 100,0004–6,8,9, suggesting that subtypes and reporting locations varied. Northern Spain had a prevalence of 3 per 100,000, whereas England and France had 29.97 cases per 100,000 people, more than twice as many as Thais. Greece had the highest documented prevalence of IIMs, with 58 cases per 100,000 (triple the prevalence in Thailand)16,17,21. Meanwhile, no research has been conducted to determine the prevalence of IIMs in Asia.

Our study reveals a decline in the incidence of IIMs among Thais from 2017 to 2020, with rates lower than those reported in the United States between 2003 and 20084,5. We observed only a slightly decrease incidence that would not be significant between 2018 and 2019. The decrease in the number of new cases from 2019 to 2020 could be attributed to the COVID-19 pandemic, which resulted in fewer reported cases and investigations involving IIMs. In contrast, our study showed a higher incidence of IIMs than studies conducted in Israel15. Furthermore, studies focusing on IIMs indicated that the incidence in Africa (in 2020), Australia (1980–2009), and Singapore (1986–1991) were comparable to our findings3,10,12–14, while England and France had the highest incidence rate from 1966 to 201317. These findings confirm the variability of the findings.

Female cases predominate among IIMs in Thailand, which is consistent with previous research (Table 3). Our study revealed a female-to-male ratio of 1.6:1. In contrast, Lynn et al. reported a higher female-to-male ratio of 4:110. However, Benbassat et al. found a male predominance15. According to the reported prevalence, PM and DM are more common in women, whereas IBM is more prevalent in men21–24. Dermatomyositis is more common in women than in men, and they can exhibit differences in certain manifestations, such as alopecia. The exact reason for this gender disparity is not yet known, but it is hypothesized to result from a combination of genetic, hormonal, and immunological factors28–30. Table 3 Literature review of prevalence and incidence of IIMs.

Report	Place	Year	Subtype	Incidence per million person-year	Prevalence per 100,000	Female to male	Age ± SD (years)	
Africa	
 Essouma et al.3a	Africa	2020	IIMs/DM/PM	7.5/1.2/8.8	11.5(IIMs)/11(PM)	1:1	20–57.2 (NA)	
US	
 Furst et al.4	United States	2003–2008	IIMs	58–79	14–17.4	1.7:1	49 (NA)	
 Smoyer-Tomic et al.5	United States	2004–2008	IIMs/DM/PM/interstitial myositis	42.7/15.2/24.6/7.3	20.6–25.3(IIMs)	1.9:1	55–64 (NA)	
 Rosa et al.6	Argentina	1999–2009	IIMs/DM/ PM	10.7/3.2/7.5	17.4/10.2/7.2	1.4:1	46.6 (18.4)	
 Oddis et al.7	Pennsylvania	1963–1982	DM/PM	5.5	NA	2.2:1	NA	
 Wilson et al.8	Minnesota	1981–2000	PM/IBM	4.1/7.9	3.5/7.1	NA	NA	
 Bendewald et al.9	Minnesota	1976–2007	DM/CADM	9.6/2.1	21.4/NA	3.2:1	57.4 (30.5–95)	
Australia	
 Lynn et al.10	New Zealand	1989–2001	DM/PM/ IBM	8.7	NA	4:1	57 (NA)	
 Limaye et al.11	South Australia	1990–2005	DM/PM	0.9/4.4	NA	1.6:1	49.7 (18.4)	
 Tan et al.12	South Australia	1980–2009	DM/PM/IBM	8(IIMs)	NA	2.8:1 (DM)	51.1 (DM)	
 Patrick et al.13	Victoria	1989–1991	IIM	7.4	NA	NA	67.5 (IBM) NA	
Asia	
 Koh et al.14	Singapore	1986–1991	DM/PM	7.7	NA	1.9:1	50.7 (16.7)	
 Benbassat et al.15	Israel	1960–1976	DM/PM	2.2	NA	0.7:1	NA	
UK and EU	
 Prieto-Pena et al.16	Northern Spain	2016–2021	IMNM	6	3	1.7:1	64.9 (7.3)	
 Alain Meyer et al.17a	England France	1966–2013	IIM	1.2–19	2.4–33.8	NA	NA	
 Kaipainiene-Seppänen et al.18	Finland	1990	DM/PM/IBM	4/4/1	NA	NA	NA	
 Anagnostopoulos et al.26	Greece	2007–2008	DM	NA	58	NA	NA	
 Weitoft et al.19	Sweden	1984–1993	DM/PM/IBM	7.6	NA	1.1:1	61.5 (45–71)	
 Svensson J et al.27	Sweden	2007–2011	IIM	11	14	1.3:1	501.6 (15.2)	
 Doblog C et al.21	Norway	2003–2012	DM/PM	6–10	8.7	2.1:1 (DM)	56.0 (14.9)	
NA no data available.

aSystematic review.

IIMs are most common in the late-middle-aged group, which is consistent with our findings. Our research revealed that the peak prevalence of IIMs occurs between 60 and 69 years. Patrick et al. demonstrated that IBM has a higher prevalence in the elderly population than DM and PM13. IBM is the most common subtype in men over the age of 50, while DM is more common than PM in individuals under the age of 50. Furthermore, IBM is more difficult to treat than PM and DM25, which can result in higher long-term treatment costs. However, it is important to note that our study does not include data on the subtypes.

Geographic factors may explain the differences between our findings and those of other studies. Aguilar-Vazquez et al. investigated the reported prevalence of myositis-specific antibodies (MSA) or myositis-associated antibodies (MAA) based on geographical location and UV radiation. According to their systematic review, the prevalence of anti-PL7, anti-Ro52, anti-La, and anti-Ku UV radiation levels and other environmental factors in IIM research. These findings indicate that geographical latitude remains a significant factor in the prevalence of certain myositis autoantibodies20. Since the majority of cases were concentrated in northeastern Thailand, more research is needed to investigate the association between geographic factors and MSA or MAA, as well as the potential impact on the clinical manifestation of IIMs in Thais.

This study has a few limitations. First, there is no comprehensive demonstration of IIM clinical subtypes or serology. Second, the classification criteria for diagnosing IIMs vary, potentially leading to misdiagnosis and underestimation of IIM cases. Third, cases may be overestimated when ICD-10 codes are used to identify IIMs because not all patients may meet the classification criteria. Furthermore, the decrease in both the frequency and quantity of records, as well as the reduction in ICD-10 records, could potentially be ascribed to the COVID-19 pandemic.

Our study possesses a number of strengths. It is the first epidemiological study among Thais to examine IIMs. Second, the extensive database administered by the Ministry of Public Health is regarded as reliable. Furthermore, our findings can be applied to other countries with similar geographic characteristics. However, further investigation is needed to explore the specifics of clinical subtypes, serology, response to treatment, prognosis, and cost-effectiveness. This research will help to inform advanced public policy in Thailand and improve our understanding of the disease.

Conclusion

The presence of IIMs in Thailand is unusual. It peaks among people aged 60 to 69, especially in southern Thailand. Furthermore, the frequency of IIM cases decreased significantly between 2019 and 2020, which was most likely influenced by the COVID-19 pandemic. As a result of this decline, fewer IIM-related cases and investigations have been reported.

Acknowledgements

The authors thank (a) the Scleroderma Research Group and Faculty of Medicine, Khon Kaen University, for its support, (b) the Information and Communication Technology Centre, Ministry of Public Health, for access to the database, (c) Mr. Bryan Roderick Hamman—under the aegis of the Publication Clinic at Khon Kaen University, Thailand—for assistance in editing with the English-language presentation.

Author contributions

Conceptualization: TO, CF, AM Data curation: CF, SS, AM Formal analysis: CF Funding acquisition: TO, AM Methodology: CF Writing-original draft: TO, CF Writing-review & editing: TO, CF, PP, SS, AM. The authors consent to publication and grant the Publisher exclusive full copyright license.

Funding

The Thailand National Science, Research, and Innovation Fund funded this study.

Data availability

Data and materials are available from the correspondence author upon reasonable request.

Ethics approval and consent to participate

The Khon Kaen University Ethics Committee approved the study for Human Research based on the Declaration of Helsinki and the ICH Good Clinical Practice Guidelines (HE661116). The Human Research Ethics Committee of Khon Kaen University waived the requirement for informed consent because of the retrospective nature of the study. All subjects' data has been anonymized to protect their privacy.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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