Impacto do tempo de convivência com a psoríase em pacientes de um centro de referência na Paraíba: análise de comorbidades e fatores de risco

Abstract

Psoriasis is a systemic, chronic, and immune-mediated disease that affects approximately 0.5% to 11.4% of adults and approximately 1.4% of children worldwide. In Brazil, the prevalence of psoriasis is estimated at 1.31%, with 1.15% in women and 1.47% in men. Psoriasis has a multifactorial etiology, which associates genetic factors as a determinant and environmental factor. The systemic manifestation of the disease results in comorbidities such as metabolic syndrome, cardiovascular events, psoriatic arthritis, depression, anxiety, and cancer. The objective of the study is to investigate the impact of time living with psoriasis in patients treated at a reference center in Paraíba, their comorbidities, and risk factors. This is a quantitative, observational, cross-sectional, and ecological study using secondary data collected from the research records of the Reference Center in Paraíba. The study was approved by the CEP/CCM, with opinion number 7.208.756 and data collection began shortly after. As this is documentary research, it does not require a Free and Informed Consent Form (FICF) and/or a Free and Informed Assent Form (FICF). The study presents variables related to the sociodemographic profile, clinical information/comorbidities and indices for assessing psoriasis severity, risk for psoriatic arthritis and quality of life. The Jamovi and R software were used for statistical analysis. Jamovi was used to generate descriptive statistics of the quantitative data and for the categorical variables the data were presented with relative values and percentages. Due to the high percentage of missing data in the complete database (n=1178), it was decided to omit them, generating a new database with n=274. In Jamovi, the regression model was applied including all the variables of the new database and through the stepwise method we arrived at significant variables, so that in R we could apply the logistic regression model. Regarding clinical data/comorbidities, we observed a low prevalence of family history (35.8%), smokers (11.8%), alcoholics (6.4%), latent TB (15.19%) and oral lesions (11.29%), a significant representation of hypertensive (40.3%) and diabetic (21.4%) individuals, but a high percentage of plaque psoriasis (80.8%), arthralgia (63.41%) and sedentary lifestyle (70.3%) in the sample. According to the risk classification presented, it is possible that many of the individuals have metabolic syndrome associated with psoriasis. The severity of psoriasis in the sample was considered moderate to severe (14.10), with a low risk of developing psoriatic arthritis (34) and moderate impact on quality of life (8.0). Regression model analysis revealed that individuals with large plaque psoriasis were 2.23 times more likely to have had the disease for more than 10 years compared to those without large plaques (OD = 2.23; CI [0.80–1.29]) and (PR = 1.02; CI [0.80–1.29]). Furthermore, individuals with a family history of the disease were 2.54 times more likely to have had psoriasis for more than 10 years than those without a family history (OD = 2.54; CI [1.34–5.04]), presenting a statistically significant prevalence ratio (PR = 1.39; CI [1.12–1.72]). Finally, those who reported arthralgia were 1.92 times more likely to have had psoriasis for more than 10 years compared to those who did not have this symptom (OD = 1.92; CI [1.02–3.60]) and (PR = 1.29; CI [0.99–1.67]). The results of this study contribute to our understanding of the epidemiological profile of patients with psoriasis who are users of the Reference Center in Paraíba, and to identify risk factors and comorbidities that are present in this population. A limitation of the study was the use of a small database (n=274), due to the high number of missing data in the original database (n=1178). This scenario highlights the need to improve the recording of information in the medical records used by the Reference Center, aiming at data completeness. In addition to the data, we must look at individuals who live with a chronic and stigmatizing disease that requires public policies based on early diagnosis and treatment and humanized and multidisciplinary care.