Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Comorbidity profiles of psoriasis in Taiwan: A latent class analysis

  • Chen-Yi Wu ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Writing – original draft

    chenyiok@gmail.com

    Affiliations Department of Dermatology, Taipei Veterans General Hospital, Taipei, Taiwan, Institute of Public Health and Department of Public Health, National Yang-Ming University, Taipei, Taiwan, Department of Dermatology, National Yang-Ming University, Taipei, Taiwan

  • Hsiao-Yun Hu,

    Roles Data curation, Formal analysis, Investigation

    Affiliations Institute of Public Health and Department of Public Health, National Yang-Ming University, Taipei, Taiwan, Department of Education and Research, Taipei City Hospital, Taipei, Taiwan

  • Chung-Pin Li,

    Roles Funding acquisition, Investigation, Resources, Writing – review & editing

    Affiliations Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, National Yang-Ming University School of Medicine, Taipei, Taiwan

  • Yiing-Jeng Chou,

    Roles Data curation, Resources, Software

    Affiliation Institute of Public Health and Department of Public Health, National Yang-Ming University, Taipei, Taiwan

  • Yun-Ting Chang

    Roles Data curation, Funding acquisition, Resources

    Affiliations Department of Dermatology, Taipei Veterans General Hospital, Taipei, Taiwan, Department of Dermatology, National Yang-Ming University, Taipei, Taiwan

Abstract

Background

Psoriasis is associated with many comorbidities. An understanding of these comorbidity patterns can help foster better care of patients with psoriasis.

Objective

To identify the heterogeneity of psoriasis comorbidities using latent class analysis (LCA).

Methods

LCA was used to empirically identify psoriasis comorbidity patterns in a nationwide sample of 110,729 incident cases of psoriasis (2002–2012) from the National Health Insurance database in Taiwan.

Results

The mean age of incident psoriasis was 46.1 years. Hypertension (28.8%), dyslipidemia (18.9%), and chronic liver disease/cirrhosis/hepatitis (18.1%) were the top three comorbidities in patients with psoriasis. LCA identified four distinct comorbidity classes among these patients, including 9.9% of patients in the “multi-comorbidity” class, 17.9% in the “metabolic syndrome” class, 11.3% in the “hypertension and chronic obstructive pulmonary disease (COPD)” class, and 60.9% in the “relatively healthy” class. Psoriatic arthritis was evenly distributed among each class. Relative to membership in the “relative healthy” class, an increase of one year of age had a higher probability of membership in the “multi-comorbidity” (odds ratio [OR], 1.25), “metabolic syndrome” (OR, 1.11), or “hypertension and COPD” (OR, 1.34) classes. Relative to membership in the “relative healthy” class, compared to women, men had a higher probability of membership in the “multi-comorbidity” (OR, 1.39), “metabolic syndrome” (OR, 1.77), or “hypertension and COPD” (OR, 1.22) classes.

Conclusion

We observed four distinct classes of psoriasis comorbidities, including the “multi-comorbidity”, “metabolic syndrome”, “hypertension and COPD”, and “relatively healthy” classes, as well as the clustering of liver diseases with metabolic syndrome and clustering of COPD with hypertension.

Introduction

Psoriasis is a chronic inflammatory disease of the skin with a worldwide prevalence of 0.5–5.5% [1]. The occurrence of psoriasis varies according to age and geographic region, occurring more frequently in countries more distant from the equator [2]. Psoriasis was previously considered to be a disease limited to the skin and joints, but recent evidence suggests that it has far-reaching systemic effects [3]. Psoriasis is associated with various diseases that are characterized by chronic inflammation, including hypertension [4], diabetes mellitus [5], metabolic syndrome [6], stroke [7], coronary artery disease [8], renal disease, liver disease, cancer, and chronic obstructive pulmonary disease (COPD) [3, 9, 10].

Multiple chronic diseases are increasingly placing a greater burden on patients with psoriasis, and these have been investigated individually relative to their association with psoriasis. Such investigations have led to an increasing acknowledgment of the propensity of diseases to occur together, leading to a hypothesis in the “common pathways” implicated in the clustering of diseases [11]. The potential for disease coexistence and clustering should give rise to more attention, as the features of comorbid diseases can be much more complicated than a simple aggregation of individual diseases [12]. Although the need to understand the patterns of disease combinations and their associated complexities is recognized, research on these issues among patients with psoriasis remains limited.

A person-centered approach, such as a latent class analysis (LCA), allows for the examination of how diseases cluster together among individuals, permitting a broader understanding of comorbidity patterns associated with psoriasis. The LCA model has been applied in many domains, including psychology, education, sociology, and behavioral research [1315]. Latent variable modelling allows investigators to hypothesize the existence of an underlying trait that is not directly measured or observed, but the presence of which can be indirectly inferred by the existence of different observed variables [16]. LCA, which takes multiple diseases into account, enables modelling that is able to holistically scrutinize multiple comorbidities.

This study aimed to identify the distinct profiles of multiple diseases among patients with psoriasis. To accomplish this goal, we applied LCA to a nationwide population of patients with incident psoriasis and analyzed their comorbidity patterns. This person-centered approach took into account the unobserved heterogeneity that is believed to be valuable in understanding the medical burdens faced by patients with psoriasis, and provides new perspectives for physicians to monitor patient need for care and improve the quality of care provided. This knowledge further offer different viewpoints and epidemiological evidences for possible pathophysiological links among psoriasis and comorbidities.

Materials and methods

Data sources

The National Health Insurance (NHI) is a mandatory universal health insurance program offering comprehensive medical care coverage to all residents of Taiwan. The NHI program was launched in 1995 to provide health care to all residents, and currently services more than 23 million people, representing approximately 99% of Taiwan’s population. The NHI database contains registration files and original claims data for care reimbursements for all enrollees, making it one of the world’s largest and most complete nation-wide, population-based health care services datasets [17, 18]. In this dataset, the diagnostic codes are formatted according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). Further, the accuracy of major disease diagnoses, such as hypertension, diabetes mellitus, and stroke, has been validated [19, 20]. All information that allows a specific individual patient to be identified is encrypted; thus, the confidentiality of the data abides by the data regulations of the National Health Insurance Administration, Ministry of Health and Welfare, Taiwan. This study was performed in accordance with the Helsinki Declaration and was approved by the National Health Research Institutes and the Institutional Review Board of Taipei Veterans General Hospital (IRB: 2015-02-011CC).

Nationwide psoriasis cohort

Between 2000 and 2012, we identified a total of 110,729 patients with a first-time diagnosis of psoriasis (ICD-9-CM codes: 696.0 and 696.1). We included cases where the patients had been diagnosed with psoriasis at least three times at outpatient clinics, or were admitted at least once. Baseline data included socioeconomic status (low, medium, and high) and residence location (urban, suburban, and rural) of patients.

Comorbidities

Information was collected from the NHI dataset. Twelve common chronic diseases were used to determine the latent comorbidity classes. These diseases were identified if they had been diagnosed at least three times previously in the patient or at the same time as the incident psoriasis diagnosis, and included hypertension (ICD-9-CM codes: 401–405), diabetes mellitus (ICD-9-CM codes: 250), dyslipidemia (ICD-9-CM codes: 272), coronary artery disease (ICD-9-CM codes: 410–414), cerebrovascular disease (ICD-9-CM codes: 430–438), connective tissue disease and rheumatoid arthritis (ICD-9-CM codes: 710, 714), renal disease (ICD-9-CM codes: 580–589), chronic liver disease/cirrhosis/hepatitis (ICD-9-CM codes: 571 and 070), COPD (ICD-9-CM codes: 491–496), cancer (ICD-9-CM codes: 140–208), depression and anxiety (ICD-9-CM codes: 296.2, 296.3, 300, and 311), and psoriasis arthritis (ICD-9-CM codes: 696.0).

Latent class analysis (LCA)

LCA is a statistical method which postulates the homogenous, unobserved subgroups can be identified within a heterogeneous group using a set of observed variables.[16] LCA estimates the response probability for each observed disease according to latent class membership. It also estimates the proportion of individuals that are expected to belong to each latent class. Using information on the comorbidities of patients with psoriasis, LCA was empirically used to identify and estimate the prevalence of diseases patterns. Sex and age were incorporated into the LCA, using logistic regression, as covariates that predict latent class membership.

Statistical analyses

The demographics of male and female patients were compared using a chi-square test for categorical variables. To identify the optimal LCA model, a sequence of models was examined using two classes, three classes, and so on. A range of indices was used for model selection, including the likelihood ratio G2 statistic, Akaike information criterion, and Bayesian information criterion; model interpretability was also considered. Distinguishability of each class from the others was contemplated on the basis of item-response probabilities; size triviality, such that that no class had a near-zero probability of membership; and the parsimony of the models. Sensitivity analyses were done to perform another LCA that included the existence of comorbidities before and during the 13 years of observation after the incident psoriasis diagnosis. The sensitivity analyses were conducted to examine whether the main findings were robust under different conditions. We used SAS 9.1 (SAS Institute, Cary, NC, USA) to link the data, and Stata 13 (StataCorp, College Station, TX, USA) to perform the LCA, using the Stata LCA plugin [21].

Results

Study population characteristics

A total of 110,729 incident cases of psoriasis were identified, including 65,471 (59.1%) men and 45,258 (40.9%) women (Table 1). The mean age of incident psoriasis was 46.1 years (standard deviation [SD], 19.6), with a mean age of 47.6 years (SD, 19.2) for men and 43.9 (SD, 20.0) years for women. Among these patients, 28.8% had hypertension; 14.5% had diabetes mellitus; 18.9% had dyslipidemia; 12.7% had coronary artery disease; 18.1% had chronic liver disease, cirrhosis, and hepatitis; 17% had chronic obstruction pulmonary disease; and 17.1% had depression and anxiety. Compared to psoriatic women, psoriatic men had the most comorbidities. Men had a significantly higher prevalence of hypertension, diabetes mellitus, dyslipidemia, coronary artery disease, cerebrovascular disease, renal diseases, chronic liver disease, cirrhosis, and hepatitis, COPD, and cancer (all, P < 0.001); men also had a lower prevalence of connective tissue disease and rheumatoid arthritis as well as a lower prevalence of depression and anxiety (all, P < 0.001), and psoriatic arthritis (P = 0.008).

thumbnail
Table 1. Baseline characteristics of incident psoriatic patients.

https://doi.org/10.1371/journal.pone.0192537.t001

Four classes identified using LCA

Having considered the model fit information (Table 2) and model interpretability, the four-class model was selected. The estimated probability of an individual comorbid disease in each class is shown in Fig 1.

thumbnail
Table 2. Model fit information for competing latent class models.

https://doi.org/10.1371/journal.pone.0192537.t002

thumbnail
Fig 1. Probabilities of individual disease comorbidities, by latent class.

Blue line: class of multi-comorbidity, orange line: class of metabolic syndrome, grey line: class of hypertension and chronic obstructive pulmonary disease (COPD), yellow line: class of relatively healthy.

https://doi.org/10.1371/journal.pone.0192537.g001

A label was assigned to each class based on comparisons of the conditional item response probabilities. Four classes were distinguished (Table 3). The first group was characterized by high probabilities of various chronic diseases, including hypertension (95%), diabetes mellitus (58%), dyslipidemia (72%), coronary artery disease (68%), cerebrovascular disease (39%), chronic liver disease and cirrhosis (42%), COPD (52%), and depression and anxiety (49%). Because of the high number of comorbidities, we labeled this group as the “multi-comorbidity” group. The second group was the “metabolic syndrome” group due to the relatively high probability of hypertension (50%), diabetes mellitus (39%), dyslipidemia (60%), as well as chronic liver disease, cirrhosis, and hepatitis (40%). In the third group, “hypertension and COPD,” the individuals had high probabilities of hypertension (69%) and COPD (45%). The last group was the “relatively healthy” group, which was distinguished by a low probability of comorbidities. In total, the four classes of patients with psoriasis, in this study, included 10,962 (9.9%) individuals in the “multi-comorbidity” class, 19,820 (17.9%) in the “metabolic syndrome” class, 12,512 (11.3%) in the “hypertension and COPD” class, and 67,434 (60.9%) in the “relatively healthy” class.

thumbnail
Table 3. Item-response probabilities for four class models of total samples: Probability of individual disease in latent class.

https://doi.org/10.1371/journal.pone.0192537.t003

Predictors of latent class membership

Table 4 shows the LCA multinomial regression analyses used to examine predictors of latent class membership, with the “relative healthy” class specified as the reference group. This class was used because it was the largest class (60.9% of the participants), representing the majority of the population. Relative to membership in the “relatively healthy” class, an increase of one year of age was more likely to result in the individual being included in the “multi-comorbidity” class (odds ratio [OR], 1.25; 95% confidence interval [CI], 1.25–1.26), “metabolic syndrome” class (OR, 1.11; 95% CI, 1.11–1.11), or “hypertension and COPD” class (OR, 1.34, 95% CI, 1.33–1.35). Relative to membership in the “relatively healthy” class and compared with women, men were more likely to be included in the “multi-comorbidity” class (OR, 1.39; 95% CI, 1.33–1.44), “metabolic syndrome” class (OR, 1.77; 95% CI, 1.68–1.86), or “hypertension and COPD” class (OR, 1.22; 95% CI, 1.13–1.32).

Sensitivity analysis

The results of the sensitivity analyses that were used to perform LCAs that included the existence of comorbidities before or during the 13 years of observation after the incident psoriasis diagnosis were robust. The four classes remained distinguished. The four classes of patients with psoriasis included 18,270 (16.5%) in the “multi-comorbidity” class, 18,602 (16.8%) in the “metabolic syndrome” class, 20,263 (18.30%) in the “hypertension and COPD” class, and 53,593 (48.4%) in the “relatively healthy” class.

Discussion

The findings of this large-scale, nationwide study explored the heterogeneity of comorbidity patterns in patients with psoriasis. We observed four distinct classes of psoriatic comorbidities, including the “multi-comorbidity”, “metabolic syndrome”, “hypertension and COPD”, and “relatively healthy” classes. Fortunately, about 60% of the patients were relatively healthy, with few comorbidities, when they were first diagnosed with psoriasis. In the sensitivity tests that included an observation period of over 13 years, about half (48.4%) of the psoriatic patients remained relatively healthy. Patients with psoriasis and arthritis were almost evenly distributed among the four latent classes. Considerable heterogeneity remained in the remaining psoriatic patients, and these were classified by the LCA into three distinct comorbidity groups. To explore the unobserved heterogeneity by LCA, we observed the clustering of liver diseases with metabolic syndrome, also clustering of COPD with hypertension in psoriatic patients.

In the “multi-comorbidity” class, this class had a high prevalence of hypertension, metabolic syndrome, coronary artery disease, cerebrovascular disease, renal disease, COPD, and psychiatric morbidity. However, cancer and psoriatic arthritis were not particularly clustered into this class. This observation might provide a clue regarding the further evaluation of linkages or pathophysiological mechanisms between these diseases. Also noteworthy is the observation that about half of the patients in the “multi-comorbidity” class presented with depression and anxiety. Further psychiatric evaluations should be considered when caring for patients with psoriasis and multiple comorbidities.

Metabolic syndrome is associated with patients with psoriasis [6, 22]. The “metabolic syndrome” class was the second largest class in our study, and comprised almost one-fifth of the patients with psoriasis. Clustering of liver diseases was also prominent in this class. Interactions linking skin inflammation, non-alcoholic fatty liver disease, and metabolic syndrome have been postulated and studied [23, 24]. All of these diseases share an underlying inflammatory process, and treatment might rely on possible modifiable risk factors, such as sedentary lifestyle, smoking, and alcohol consumption.

Hypertension, having a prevalence of approximately 29% in our study, was observed to be the most common comorbidity in patients with psoriasis. We observed a distinct clustering of “hypertension and COPD”, whereas hypertension alone, without other traditional components of metabolic syndrome, was clustered with COPD. A previous meta-analysis study revealed an increased risk of COPD among patients with psoriasis [25]. Further study might be needed to investigate the epidemiology and possible pathophysiological links among psoriasis, hypertension, and COPD.

Strong psychiatric morbidity has been reported in patients with psoriasis [26, 27]. In one cross-sectional study, about 10–13% of patients with psoriasis also screened positive for major depressive disorder and anxiety disorder [28]. In our study, almost one-fifth of the psoriasis patients presented with depression and anxiety. The majority of these patients clustered into the “multi-comorbidity”, “metabolic syndrome”, and “hypertension and COPD” classes.

Patients with psoriasis and arthritis have been noted to suffer from more severe atherosclerotic disease, metabolic syndrome, and cardiovascular events than patients without arthritis, possibly due to the combination of skin and joint diseases that result in greater systemic inflammation [29, 30]. Psoriatic arthritis patients have heterogeneous clinical presentations. In our study, 5.4% of incident psoriasis patients had presented with psoriatic arthritis. However, they were almost evenly distributed among the four latent classes, including in the “relatively healthy” class. This finding prompts us to examine the possibility of arthritis even in relative healthy patients with psoriasis.

Increased age increases the risks of multiple chronic diseases. A one-year increase in age also resulted in a higher possibility of the individual being classified into the “multi-comorbidity”, “metabolic syndrome”, or “hypertension and COPD” classes. Men with psoriasis also had higher prevalences of most of the comorbidities than did women with psoriasis. In the LCA model, compared to women, men were observed to have higher possibilities of being classified into the “multi-comorbidity”, “metabolic syndrome”, and “hypertension and COPD” classes. This observation reminds physicians to evaluate comorbid conditions, especially when caring for older people or men with psoriasis.

The strength of this study is that our findings are based on a large, contemporary, national cohort of patients with psoriasis. We had a sufficiently large sample size (n = 11,0729) to identify four distinct comorbidity patterns and identify the characteristics associated with each of them. The findings from this person-centered approach, using LCA modelling, provide new perspectives for physicians monitoring comorbidity patterns in patients with psoriasis. As a multi-organ pathology, psoriasis needs a multidisciplinary approach and clinicians should assess it using a holistic view to promptly identify and manage psoriasis comorbidities.

The results of this research should be viewed in light of several limitations. First, the administrative data are subject to possible coding errors and under- or over- coding problems, and this may have affected the prevalence estimates for the different disease patterns. Another limitation is that the LCA model did not examine variations in the longitudinal patterns of the progressing diseases. However, in the sensitivity test that included the existence of comorbidities before or after incident psoriasis, the four classes remained distinguished. Finally, this study was set in Taiwan, the results should be interpreted cautiously as they might not generalize to other races or more heterogeneous populations.

In conclusion, we observed four distinct classes of psoriasis comorbidities, including the “multi-comorbidity”, “metabolic syndrome”, “hypertension and COPD”, and “relatively healthy” classes. As comorbidities are increasingly recognized as being important in the care and management of psoriatic patients, this area requires more attention and better research. The identification of distinct comorbidity patterns offers physicians valuable information that may lead to more appropriate health care, including the exploration of possible pathophysiological associations.

Acknowledgments

The authors thank the National Health Insurance Administration, Ministry of Health and Welfare, Taiwan for providing the database used in this study.

References

  1. 1. Raychaudhuri SP, Farber EM. The prevalence of psoriasis in the world. J Eur Acad Dermatol Venereol. 2001;15(1):16–7. pmid:11451313.
  2. 2. Parisi R, Symmons DP, Griffiths CE, Ashcroft DM, Identification, Management of P, et al. Global epidemiology of psoriasis: a systematic review of incidence and prevalence. J Invest Dermatol. 2013;133(2):377–85. pmid:23014338.
  3. 3. Tsai TF, Wang TS, Hung ST, Tsai PI, Schenkel B, Zhang M, et al. Epidemiology and comorbidities of psoriasis patients in a national database in Taiwan. J Dermatol Sci. 2011;63(1):40–6. pmid:21543188.
  4. 4. Armstrong AW, Harskamp CT, Armstrong EJ. The association between psoriasis and hypertension: a systematic review and meta-analysis of observational studies. J Hypertens. 2013;31(3):433–42; discussion 42–3. pmid:23249828.
  5. 5. Boehncke S, Thaci D, Beschmann H, Ludwig RJ, Ackermann H, Badenhoop K, et al. Psoriasis patients show signs of insulin resistance. Br J Dermatol. 2007;157(6):1249–51. pmid:17916217.
  6. 6. Love TJ, Qureshi AA, Karlson EW, Gelfand JM, Choi HK. Prevalence of the metabolic syndrome in psoriasis: results from the National Health and Nutrition Examination Survey, 2003–2006. Arch Dermatol. 2011;147(4):419–24. pmid:21173301.
  7. 7. Gelfand JM, Dommasch ED, Shin DB, Azfar RS, Kurd SK, Wang X, et al. The risk of stroke in patients with psoriasis. J Invest Dermatol. 2009;129(10):2411–8. pmid:19458634.
  8. 8. Prodanovich S, Kirsner RS, Kravetz JD, Ma F, Martinez L, Federman DG. Association of psoriasis with coronary artery, cerebrovascular, and peripheral vascular diseases and mortality. Arch Dermatol. 2009;145(6):700–3. pmid:19528427.
  9. 9. Yang YW, Keller JJ, Lin HC. Medical comorbidity associated with psoriasis in adults: a population-based study. Br J Dermatol. 2011;165(5):1037–43. pmid:21711339.
  10. 10. Chiu HY, Huang HL, Li CH, Yin YJ, Chen HA, Hsu ST, et al. Increased risk of glomerulonephritis and chronic kidney disease in relation to the severity of psoriasis, concomitant medication, and comorbidity: a nationwide population-based cohort study. Br J Dermatol. 2015;173(1):146–54. pmid:25511692.
  11. 11. Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med. 2009;7(4):357–63. pmid:19597174.
  12. 12. Starfield B. Threads and yarns: weaving the tapestry of comorbidity. Ann Fam Med. 2006;4(2):101–3. pmid:16569711.
  13. 13. Fitzpatrick KE, Gray R, Quigley MA. Women’s Longitudinal Patterns of Smoking during the Pre-Conception, Pregnancy and Postnatal Period: Evidence from the UK Infant Feeding Survey. PLoS One. 2016;11(4):e0153447. pmid:27111661.
  14. 14. Kim Y, Barreira TV, Kang M. Concurrent Associations of Physical Activity and Screen-Based Sedentary Behavior on Obesity Among US Adolescents: A Latent Class Analysis. J Epidemiol. 2016;26(3):137–44. pmid:26477996.
  15. 15. Evans-Polce R, Lanza S, Maggs J. Heterogeneity of alcohol, tobacco, and other substance use behaviors in U.S. college students: A latent class analysis. Addict Behav. 2016;53:80–5. pmid:26476004.
  16. 16. Collins LM, Lanza S.T.. Laten class and latent transition analysis for the social, behavioral, and health scoences. New York: Wiley. 2010.
  17. 17. Wang JP, Kao FY, Wu CY, Hung YP, Chao Y, Chou YJ, et al. Nucleos(t)ide analogues associated with a reduced risk of hepatocellular carcinoma in hepatitis B patients: a population-based cohort study. Cancer. 2015;121(9):1446–55. pmid:25537961.
  18. 18. Wu CY, Hu HY, Chow LH, Chou YJ, Huang N, Wang PN, et al. The Effects of Anti-Dementia and Nootropic Treatments on the Mortality of Patients with Dementia: A Population-Based Cohort Study in Taiwan. PLoS One. 2015;10(6):e0130993. pmid:26098910.
  19. 19. Cheng CL, Kao YH, Lin SJ, Lee CH, Lai ML. Validation of the National Health Insurance Research Database with ischemic stroke cases in Taiwan. Pharmacoepidemiol Drug Saf. 2011;20(3):236–42. pmid:21351304.
  20. 20. Lin CC, Lai MS, Syu CY, Chang SC, Tseng FY. Accuracy of diabetes diagnosis in health insurance claims data in Taiwan. J Formos Med Assoc. 2005;104(3):157–63. pmid:15818428.
  21. 21. Lanza ST DJ, Huang L, Wagner AT, Collins LM. LCA stata plugin users’ guide version 1.2. University park: The Methodology Center, Penn State Available from methodologypsuedu.
  22. 22. Sommer DM, Jenisch S, Suchan M, Christophers E, Weichenthal M. Increased prevalence of the metabolic syndrome in patients with moderate to severe psoriasis. Arch Dermatol Res. 2006;298(7):321–8. pmid:17021763.
  23. 23. Ganzetti G, Campanati A, Molinelli E, Offidani A. Psoriasis, non-alcoholic fatty liver disease, and cardiovascular disease: Three different diseases on a unique background. World J Cardiol. 2016;8(2):120–31. pmid:26981209.
  24. 24. Kulkarni NM, Jaji MS, Shetty P, Kurhe YV, Chaudhary S, Vijaykant G, et al. A novel animal model of metabolic syndrome with non-alcoholic fatty liver disease and skin inflammation. Pharm Biol. 2015;53(8):1110–7. pmid:25430922.
  25. 25. Ungprasert P, Srivali N, Thongprayoon C. Association between psoriasis and chronic obstructive pulmonary disease: A systematic review and meta-analysis. J Dermatolog Treat. 2016;27(4):316–21. pmid:26458363.
  26. 26. Tee SI, Lim ZV, Theng CT, Chan KL, Giam YC. A prospective cross-sectional study of anxiety and depression in patients with psoriasis in Singapore. J Eur Acad Dermatol Venereol. 2016;30(7):1159–64. pmid:27027485.
  27. 27. Cohen BE, Martires KJ, Ho RS. Psoriasis and the Risk of Depression in the US Population: National Health and Nutrition Examination Survey 2009–2012. JAMA Dermatol. 2016;152(1):73–9. pmid:26421371.
  28. 28. Lamb RC, Matcham F, Turner MA, Rayner L, Simpson A, Hotopf M, et al. Screening for anxiety and depression in people with psoriasis: a cross-sectional study in a tertiary referral setting. Br J Dermatol. 2016. pmid:27363600.
  29. 29. Husted JA, Thavaneswaran A, Chandran V, Eder L, Rosen CF, Cook RJ, et al. Cardiovascular and other comorbidities in patients with psoriatic arthritis: a comparison with patients with psoriasis. Arthritis Care Res (Hoboken). 2011;63(12):1729–35. pmid:21905258.
  30. 30. Eder L, Jayakar J, Shanmugarajah S, Thavaneswaran A, Pereira D, Chandran V, et al. The burden of carotid artery plaques is higher in patients with psoriatic arthritis compared with those with psoriasis alone. Ann Rheum Dis. 2013;72(5):715–20. pmid:22736087.