Abstract
Background
Approximately 15.5% of patients with psoriatic arthritis (PsA) are currently not diagnosed or experience delayed diagnosis with negative outcomes. This retrospective, cross-sectional study evaluated patients with psoriasis to determine what factors were associated with diagnosis of PsA.
Methods
A retrospective chart review was performed using electronic medical record from primary care clinics across the northeast Georgia region. The study population included patients with psoriasis evaluated in the clinic between January 1, 2017 and December 31, 2022. Patients with PsA were compared to those without PsA to assess for factors associated with the diagnosis of PsA.
Results
The probability of diagnosis of PsA increased with increasing number of clinic encounters (odds ratio [OR], 1.18; P < .05). Males (OR, 0.634; P < .001) were less likely to be diagnosed compared to females. Patients with Medicare (adjusted OR, 1.707; 95% confidence interval [CI], 1.027–2.837; P < .05) and commercial/private insurances (adjusted OR, 2.043; 95% CI, 1.28–3.258; P < .01) had a higher chance of being diagnosed in comparison to patients with Medicaid. Black patients were less likely to be diagnosed compared to White patients (OR, 0.231; P < .001). Hispanic patients were less likely to be diagnosed with PsA compared to patients who were not Hispanic (OR, 0.2; 95% CI, 0.07–0.51; P < .05).
Conclusions
The study highlighted potential factors associated with the diagnosis of PsA among patients with psoriasis. Sex, race, ethnicity, number of clinic encounters, and insurance type were all found to have associations with likelihood of receiving a PsA diagnosis. These findings were hypothesis-generating and suggest potential disparities in care, particularly for diverse populations, warranting further research.
Keywords: Psoriasis, Psoriatic Arthritis, Diagnostic Gaps, Race, Ethnicity, Healthcare Access
Introduction
Psoriasis, a chronic inflammatory condition primarily affecting the skin, is driven by immune-mediated mechanisms and presents with lesions in areas such as the umbilical, gluteal, elbow, and knee joint regions. Affecting approximately 2% to 3% of the global population, 1 psoriasis leads to psoriatic arthritis (PsA) in about 20% to 30% of cases. 2 However, PsA remains frequently underdiagnosed, partly due to the overlap of arthritis symptoms across multiple conditions. This leads to a delay in diagnosis exceeding 4 years in roughly 15.5% of patients with PsA. 3
Diagnosing PsA presents challenges due to the absence of specific biomarkers, definitive diagnostic criteria, and different presenting pictures. Despite increasing PsA prevalence in recent years, substantial gaps persist in screening and diagnosis, impacting patients’ health and quality of life. Contributing factors include symptom overlap with other joint diseases, demographic influences affecting patient understanding and communication with health care practitioners, and barriers to accessing care. 4
As mentioned previously, the clinical picture and joint involvement vary, with 3 primary clinical patterns: Oligoarticular (affecting 4 or fewer joints), polyarticular (involving more than 5 joints), and axial disease. Other manifestations, including distal interphalangeal arthritis and arthritis mutilans, may arise, alongside hallmark symptoms such as enthesitis and dactylitis. 5 Additionally, some patients may present with distal extremity swelling and pitting edema in the hands or feet, 6 while the most common extra-articular symptom is unilateral acute iridocyclitis, occurring in about 10% of the cases. 7
Another major challenge in PsA diagnosis and treatment lies in the disparities observed in both research representation and health care access. The majority (81%) of randomized, clinical trials predominantly have featured White populations, potentially limiting insights into PsA risk factors across diverse groups. 8 A study found Black patients were significantly less likely to receive a PsA diagnosis (30%) compared to White patients (64.5%), 9 and they faced longer delays in receiving disease-modifying antirheumatic drugs. 10 Additionally, socioeconomic factors, including insurance status, contribute to diagnostic disparities. In a particular study, psoriatic patients with private insurance or Medicare were more likely to seek care than uninsured patients, who had fewer office visits and lower odds of being evaluated for PsA. 11 These findings have underscored the importance of implementing multimodal interventions to improve health care access and education.
The current literature provides limited insight into how demographic factors are associated with PsA diagnosis and treatment outcomes. Diagnostic and treatment disparities can place a substantial lifetime burden on patients with PsA, impacting their quality of life. This retrospective, cross-sectional study aimed to identify factors associated with the diagnosis of PsA among patients with psoriasis, evaluating the role of race, ethnicity, insurance type, age, and clinic engagement on PsA diagnosis. By evaluating these factors, this study attempted to highlight factors that may be associated with diagnostic gaps in PsA care.
Methods
Study Design and Setting
All patients included in the study were seen at a medium-sized health system in northeast Georgia that serves both rural and urban counties. This study received ethical approval from the institutional review board at Brenau University and was conducted in compliance with the Declaration of Helsinki. Due to this study’s retrospective nature, it did not acquire consent for participation, as all information collected from this study was done via chart abstraction.
Study Population
All patients who were included in the study were 18 years of age or older, diagnosed with psoriasis, and evaluated in northeast Georgia health system primary care clinics between January 1, 2017, and December 31, 2022. For the scope of this study, no exclusions were made to the study population.
Data Collection
All electronic medical record information pertaining to this study was abstracted using the International Classification of Diseases, 10th Revision, and the Current Procedural Terminology codes to include the following information: Sex, ethnicity, primary language, financial class, age at the time of diagnosis of psoriasis, and whether they received a diagnosis of PsA. All participants were then allocated into 2 groups of those that were diagnosed with PsA or those who did not receive a diagnosis of PsA. A manual validation of 10% of cases abstracted was completed to ensure the accuracy of the dataset and that the selected patients properly met the inclusion criteria.
Statistical Analysis
The primary research question was to determine which factors were associated with the diagnosis of PsA. All nonparametric data were reported in frequencies and the percentage of their occurrence, and all parametric data were reported as mean and standard deviation. A binary logistic regression was used to assess the adjusted odds of PsA diagnosis. The statistical analysis was conducted using IBM SPSS 22. A parsimonious model with only statistically significant contributions was retained, resulting in inclusion of gender, ethnicity, race, and insurance.
Results
Demographics
In total, 3661 patients met the study criteria of receiving the diagnosis of psoriasis and thus formed the study population. Of the 3661 patients, 22.9% (n = 837) were diagnosed with PsA. The study population included mostly female (n = 2079, 57.0%) and White (n = 3274, 89.4%) participants, and the majority of the patients had commercial insurance (n = 2430, 66.4%). Demographic data by each psoriasis type can be seen in Table 1, along with the P values for the association between the psoriasis type and each variable based on the crosstabulations test with Bonferroni adjustment, as also seen in Table 1. The mean age at diagnosis for patients with psoriasis was 53.9 years (range 37–69 years), and the mean age of diagnosis of PsA was 57.8 years (range 46–70 years).
Table 1:
Demographics of patient population
| Category | Psoriasis type | Total | P value | ||
|---|---|---|---|---|---|
| Psoriasis | PsA | ||||
| Sex | |||||
| Female | Count | 1550a | 529b | 2079 | P < .001 |
| % within type | 54.9% | 63.2% | 56.8% | ||
| Male | Count | 1274a | 308b | 1582 | |
| % within type | 45.1% | 36.8% | 43.2% | ||
| Total | Count | 2824 | 837 | 3661 | |
| % within type | 100.0% | 100.0% | 100.0% | ||
| Ethnicity | |||||
| Not Hispanic | Count | 2589a | 804b | 3393 | P < .001 |
| % within type | 96.9% | 99.3% | 97.4% | ||
| Hispanic | Count | 83a | 6b | 89 | |
| % within type | 3.1% | 0.7% | 2.6% | ||
| Total | Count | 2672 | 810 | 3482 | |
| % within type | 100.0% | 100.0% | 100.0% | ||
| Race | |||||
| White | Count | 2488a | 786b | 3274 | P < .001 |
| % within type | 89.4% | 94.4% | 90.5% | ||
| Black | Count | 112a | 9b | 121 | |
| % within type | 4.0% | 1.1% | 3.3% | ||
| American Indian | Count | 3a | 6b | 9 | |
| % within type | 0.1% | 0.7% | 0.2% | ||
| Other | Count | 135a | 27b | 162 | |
| % within type | 4.8% | 3.2% | 4.5% | ||
| Asian | Count | 46a | 5b | 51 | |
| % within type | 1.7% | 0.6% | 1.4% | ||
| Total | Count | 2784 | 833 | 3617 | |
| % within type | 100.0% | 100.0% | 100.0% | ||
| Insurance | |||||
| Medicaid | Count | 195a | 27b | 222 | P < .001 |
| % within type | 7.0% | 3.3% | 6.1% | ||
| Medicare | Count | 564a | 183a | 747 | |
| % within type | 20.2% | 22.0% | 20.6% | ||
| Self-pay | Count | 194a | 34b | 228 | |
| % within type | 6.9% | 4.1% | 6.3% | ||
| Commercial | Count | 1844a | 586b | 2430 | |
| % within type | 65.9% | 70.6% | 67.0% | ||
| Total | Count | 2797 | 830 | 3627 | |
| % within type | 100.0% | 100.0% | 100.0% | ||
Note: Each subscript letter denotes a subset of psoriasis-type categories whose column proportions do not differ significantly from each other at the .05 level.
PsA, psoriatic arthritis.
The factors associated with the diagnosis of PsA
Based on binary logistic regression, independent variables of race, sex, insurance type, age, and number of encounters were associated with PsA diagnosis (P < .001). These associations are highlighted in the Figure.
Figure:
Association of factors with the diagnosis of psoriatic arthritis. Dx = diagnosis.
The probability of being diagnosed with PsA slightly increased with advancing age (adjusted [Adj] odds ratio [OR], 1.01; 95% confidence interval [CI], 1.004–1.017; P < .05), and it also was found to increase with higher number of clinical encounters (Adj OR, 1.18; 95% CI, 1.11–1.15; P < .05). Males (Adj OR, 0.634; 95% CI, 0.534–0.754; P < .001) were less likely to be diagnosed compared with females.
Patients with Medicaid were less likely to be diagnosed with PsA among other insurance categories and were used as the reference. Patients with self-pay were not associated with PsA diagnosis (P = .307). By contrast, patients with Medicare (Adj OR, 1.707; 95% CI, 1.027–2.837; P < .05) and commercial/private insurances (Adj OR, 2.043; 95% CI, 1.28–3.258; P < .01) had a higher chance of being diagnosed. These findings are highlighted in Table 2.
Table 2:
The impact of insurance on psoriatic arthritis
| Category | Medicaid | Medicare | Self-pay | Commercial | |
|---|---|---|---|---|---|
| Psoriasis, never diagnosed with PsA | Count (N) | 195 | 564 | 194 | 1844 |
| % within insurance subcategory | 87.8% | 75.5% | 85.1% | 75.9% | |
| PsA | Count (N) | 27 | 183 | 34 | 586 |
| % within insurance subcategory | 12.2% | 24.5% | 14.9% | 24.1% | |
PsA, psoriatic arthritis.
The impact of race on PsA diagnosis was assessed, showing that Black participants were less likely to be diagnosed (Adj OR, 0.231; 95% CI, 0.11–0.488; P < .001) compared to White participants (used as the reference), as seen in Table 3. American Indian participants had a higher Adj OR of PsA diagnosis (Adj OR, 8.232; 95% CI, 1.471–46.059; P < .05) compared with White participants. However, the sample size of American Indian participants was notably smaller compared with all other race categories. Meanwhile, Asian and Asian American (referred to as Asian) participants were less likely to be diagnosed with PsA (Adj OR, 0.316; 95% CI, 0.119–0.842; P < .05).
Table 3:
The impact of race on diagnosis of psoriatic arthritis
| Category | White | Black | American Indian | Asian | Other | |
|---|---|---|---|---|---|---|
| Psoriasis, never diagnosed with PsA | Count (N) | 2488 | 112 | 3 | 46 | 175 |
| % of total within race category | 76.0% | 92.6% | 33.3% | 90.2% | 85% | |
| PsA | Count (N) | 786 | 9 | 6 | 5 | 31 |
| % of total within race category | 24.0% | 7.4% | 66.7% | 9.8% | 15% | |
PsA, psoriatic arthritis.
Finally, ethnicity was seen to also have a significant association with the diagnosis of PsA. Hispanic participants were less likely to be diagnosed with PsA compared with participants who were not Hispanic (Adj OR, 0.2; 95% CI, 0.07–0.51; P < .001) (Table 4).
Table 4:
The impact of ethnicity on diagnosis of psoriatic arthritis
| Category | Not Hispanic | Hispanic | |
|---|---|---|---|
| Psoriasis, never diagnosed with PsA | Count (N) | 2589 | 83 |
| % within ethnicity subcategory | 76.3% | 93.3% | |
| PsA | Count (N) | 804 | 6 |
| % within ethnicity subcategory | 23.7% | 6.7% | |
PsA, psoriatic arthritis.
Discussion
This retrospective, cross-sectional study was conducted to determine which risk factors were most likely to be associated with the diagnosis of PsA. This study identified a PsA diagnosis rate of 22.9% among patients with psoriasis in northeast Georgia, closely aligning with global averages (22.7%) but exceeding the US average (19.5%). 2 The global prevalence of PsA among patients psoriasis is highly variable, with rates ranging from 6% to 42% in clinic-based studies, depending on diagnostic criteria, patient populations, and health care access. 12 This variability underscores the importance of localized studies to understand regional diagnostic trends and gaps. This report demonstrated that sex, race and ethnicity, number of clinical encounters, and insurance type may be associated with disparities in the diagnosis of PsA.
Sex and gender disparities in PsA diagnosis and disease burden are well-documented. Prior meta-analyses, such as an analysis reviewing 36 observational and clinical studies, reported near-equal prevalence (24.0% in women vs 23.3% in men), 2 although other studies have suggested a higher prevalence in men or women, depending on the population and methodology. 13 In this study, women were 1.6 times more likely to be diagnosed with PsA. This finding may reflect behavioral differences, such as women’s higher likelihood of seeking medical care, as well as study-specific factors like design, evaluation periods, or population demographics. Age influences PsA diagnosis rates, although its effects vary across studies. A cross-sectional study conducted at the University of California San Diego found that for every 1-year increase in the age of psoriasis onset, the odds of developing PsA decreased by 3%. 14 The authors’ data showed that older age was associated with only a slightly higher likelihood of diagnosis (OR, 1.01).
Racial and ethnic disparities in PsA prevalence and diagnosis have been found to be significant. Previous research has demonstrated that White patients have higher PsA diagnostic rates compared to other racial groups, regardless of insurance type. 9,15 This finding aligns with this study, where Black and Asian populations had lower adjusted odds of diagnosis (OR, 0.23 and 0.32, respectively), while American Indian populations had significantly higher odds (OR, 8.23). Human Leukocyte Antigen B27, a genetic marker associated with psoriatic disease, was more prevalent among White participants who were not Hispanic (7.5%) compared to all other US racial and ethnic groups combined (3.5%), 16 potentially contributing to these differences. Additionally, psoriasis is more challenging to recognize in darker skin phenotypes, which may delay or reduce diagnosis in these populations. 17 The elevated odds of PsA diagnosis among American Indian patients in the study mirror findings in Canadian Indigenous populations, where a higher prevalence of psoriatic disease was reported (relative risk = 1.5) despite fewer specialty visits. 18
Insurance type plays a critical role in access to diagnosis and care. A large retrospective study using Medicaid and Optum databases found that PsA prevalence in the United States was highest among patients using Medicare (0.32%), followed by commercially insured patients (0.23%) and patients using Medicaid (0.13%). 15 Similarly, the findings showed the highest diagnostic rates among patients using Medicare (24.5%) and the lowest among patients using Medicaid (12.2%). Reduced access to specialty care (driven by limited practiotiner availability, financial constraints, and restricted insurance coverage) likely contributes to underdiagnosis in lower-income populations. The data also highlighted the fact that fewer psoriasis-related health care encounters were associated with lower PsA diagnostic rates, emphasizing the need to address barriers to care.
Northeast Georgia serves a diverse population, including many uninsured and underinsured individuals with low health literacy. These factors contribute to delays in recognizing chronic diseases and obtaining appropriate diagnoses. To address these barriers, in the next phase of the study, initiatives such as implementing PsA screening questionnaires, improving health care access, and raising community awareness will be planned. These efforts will be designed to reduce the proportion of undiagnosed PsA cases and improve long-term patient outcomes.
This study offered valuable insights into diagnostic disparities in PsA care within northeast Georgia. However, several limitations should be acknowledged. The retrospective cross-sectional study design and use of PsA diagnosis by the clinician inherently restricted causal inferences and relied on the accuracy of diagnosis and completeness of existing medical records, which may have introduced information bias. Furthermore, the study’s regional focus and predominantly White population may have limited its generalizability to populations with differing health care systems, demographic compositions, or socioeconomic contexts. Although the authors adjusted for key demographic variables, unmeasured confounders such as genetic predispositions, environmental factors, or undocumented health care behaviors could have influenced the results. Additionally, the study population only had small sizes for certain racial and ethnic groups. Selection bias may have also existed, as individuals engaging with the health care system tend to be more likely to receive a diagnosis, potentially underrepresenting underserved populations. Future studies should employ prospective designs with more diverse populations to validate these findings and further explore the complex interplay of demographic, clinical, and socioeconomic factors in PsA diagnosis and care.
Conclusion
This study emphasized the importance of understanding factors associated with PsA diagnosis and care. It provided a potential hypothesis for disparities in the diagnosis and care of patients with PsA, raising awareness to reduce diagnostic gaps. Future research should focus on diverse populations, prospective designs, and evaluating strategies to enhance equity and outcomes in PsA care.
Acknowledgments
The authors would like to thank Louise Jones, PhD, the director of graduate medical education research at Northeast Georgia Medical Center, for her coordination of research teams and her guidance throughout the development of this project and manuscript. Also, the authors would like to thank Jake Slaton, MS, at the research department of Northeast Georgia Medical Center for his help in creating the figure in the result section.
Footnotes
Author Contributions: Romina Faridizad, MD, was involved in substantial contributions to the interpretation of the data and preparing tables to represent the data analysis, as well as providing final approval of the version to be published. Brent A Flickinger, MD, was involved in substantial contributions to the conception and design of the study, as well as reviewing the manuscript. Ania Izabela Rynarzewska, PhD, was involved in substantial contributions to the analysis of the project, as well as drafting and reviewing the manuscript. Sarah Ross, DO, was involved in substantial contributions to the conception of the study. Shane Robinson, MS, was involved in substantial contributions to the conception and design of the study, acquisition and interpretation of the data, and reviewing the manuscript. Aditya Kumar Ghosh, MD, was involved in substantial contributions to the conception of the study design, acquisition of the data, interpretation of the data, drafting and reviewing the manuscript, and final approval of the version to be published.
Conflicts of Interest: None declared
Funding: None declared
Data-Sharing Statement: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
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