The Effects of Cardiometabolic Comorbidities on Biologic Treatment for Psoriasis with Respect to PASI Scores: A Qualitative Systematic Review

Introduction

Psoriasis is a chronic, immune-mediated, inflammatory disease of the skin and joints. Psoriatic disease commonly involves systemic inflammation, dysmetabolism, and increased comorbid disease burden.^1–5 The management of moderate to severe psoriasis has undergone significant advancements with the availability of biologic therapies,⁶ which include tumor necrosis factor-inhibitors (TNFi) [etanercept, infliximab, adalimumab, certolizumab], interleukin (IL) 12/23 inhibitors (IL-12/23i) [ustekinumab], IL-17 inhibitors (IL-17i) [secukinumab, ixekizumab, brodalumab], and IL-23 inhibitors (IL-23i) [guselkumab, tildrakizumab, risankizumab].¹ In Phase III clinical trials, approximately 65% of patients treated with IL-17i⁷ have demonstrated 90% improvement in Psoriasis Area and Severity Index (PASI90) after 12 weeks of therapy, and approximately 74% of individuals treated with IL-23i achieved PASI90 after 16 weeks.⁸ Despite the effectiveness of these therapies in clinical trials, response to biologics is not universal in a real-world setting.⁹ Reasons for these variations in response to biologic therapies are not fully understood.

Treatment algorithms for managing moderate-to-severe psoriasis with biologics often are dependent on characteristics from specific patient populations (eg, pregnancy) and the presence or risk of exacerbation of comorbid diseases (eg psoriatic arthritis, chronic infections, inflammatory bowel disease, demyelinating disease, or heart failure).^10,11 Psoriasis is often accompanied by cardiometabolic-risk factor-type diseases that are similarly associated with chronic, systemic inflammation, such as type 2 diabetes mellitus, hypertension, hyperlipidemia, obesity.¹² Aside from contributing to poorer health, cardiometabolic risk factors have been shown to decrease biologic efficacy for various conditions.^13,14 Subanalyses of randomized controlled clinical trials indicate reduced efficacy of fixed-dose TNFi in the treatment of psoriasis among overweight and obese patients.^15–17 In contrast, randomized controlled clinical trials for IL-17i, IL-23i, and IL-12/23i have demonstrated equal effectiveness irrespective of body weight.^18–20 Although these trials offer valuable insights for clinicians, it is crucial to acknowledge that the observed favorable responses in the referenced studies may not be universal for everyone.

While biologic therapies may decrease incidence of myocardial infarctions²¹ and onset of diabetes mellitus,²² little research has been focused on how the presence of cardiometabolic comorbidities might be associated with response to biologic therapies. The purpose of this systematic review is to provide a qualitative evaluation of studies that have assessed PASI scores in patients with cardiometabolic comorbidities treated with biologic therapies.

Materials and Methods

This systematic review was conducted according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.²³ A comprehensive literature search was performed for all studies evaluating psoriasis treatment with respect to cardiometabolic factors. All studies published from inception until January 2023 were identified in the PubMed, Medline (OVID), and Web of Science databases. The following search terms were used:

(psoriasis) OR (psoriatic) OR (psoriatic disease) OR (plaque psoriasis) OR (nail psoriasis) OR (scalp psoriasis)

AND

(comorbid) OR (comorbid disease) OR (cardiometabolic) OR (type 2 diabetes) OR (TIID) OR (metabolic syndrome) OR (diabetic) OR (diabetes) OR (obesity) OR (overweight) OR (nonalcoholic fatty liver disease) OR (metabolic disease) OR (comorbidities)

AND

(biologics) OR (biologic treatment) OR (certolizumab pegol) OR (Cimzia) OR (Cosentyx) OR (secukinumab) OR (enbrel) OR (etanercept) OR (humira) OR (adalimumab) OR (Ilumya) OR (tildrakizumab) OR (remicade) OR (infliximab) OR (Siliq) OR (brodalumab) OR (Skyrizi) OR (risankizumab) OR (Stelara) OR (ustekinumab) OR (Taltz) OR (ixekizumab) OR (tremfya) OR (guselkumab)

Article screening was completed by two independent investigators (A.O and A.T). Duplicate studies were removed, and the rest of the articles were screened by title and abstract. Peer-reviewed publications were included that were published in English, isolated psoriasis patients with cardiometabolic comorbidities, reported a PASI score, and reported any associations between patients with cardiometabolic comorbidities and disease progression when treated with biologics. Articles that did not isolate data for biologic treatments reported a PASI score, and did not isolate data on patients with cardiometabolic comorbidities were excluded. Similarly, articles that only evaluated the effects of biologics on cardiometabolic factors and not vice versa were excluded.

Included studies had the following categories of data collected: study design, patient demographics, study quality, study length, biologic drug used (if reported), cardiometabolic factor, effect on PASI score, type of psoriasis (if reported), and follow-up intervals (if reported).

Non-randomized studies were evaluated for study quality using the Methodological Index for Non-Randomized Studies (MINORS) score.²⁴ Categories were scored as 0 (not reported), 1 (reported but inadequate), or 2 (reported and adequate). Noncomparative studies featured 8 questions for the MINORS score with total scores ranging from 0 (poor study quality) to 16 (high study quality), while comparative studies featured 12 questions with total scores ranging from 0 to 24.

Due to heterogeneity of the data, only qualitative analysis was possible. Study demographics, biologic treatment, and PASI outcomes were reported separately for each study (Tables 1–3).

Table 1 Study Demographics and Study Quality of Included Studies

Table 2 Findings of Included Studies

Table 3 Findings of Post-Hoc Analyses

Results

Overall, 4756 articles were identified from databases. After removal of duplicates, 2305 articles were considered for inclusion. A total of 23 studies were included in the qualitative analysis (Figure 1). Eighteen of the 24 studies were not posthoc analyses for which the MINORS score was able to be calculated (Table 1). The average MINORS score for the included studies was 14.3 ± 3.1.

Figure 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Diagram of Included Studies. Notes: PRISMA figure adapted from Liberati A, Altman DG, Tetzlaff J et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700. Creative Commons.23

A total of 18 studies met inclusion criteria. Most studies (13/18) were published within the past five years (2018–2023). Plaque psoriasis was the primary analyzed form of psoriasis. Two studies included patients with psoriatic arthritis,^26,39 and one study included patients with psoriasis vulgaris and generalized pustular psoriasis.³⁹ A total of 7936 patients across all studies were evaluated for biologic efficacy and response. Follow-up time/intervals ranged from 3 months – 4 years to analyze long-term drug efficacy.

A total of 17 studies evaluated obesity/BMI as a cardiometabolic factor,^{25–30,32–40,44} 4 studies evaluated diabetes,^25,29,31,34 4 studies evaluated hypertension^25,29,31,34 and 4 studies evaluated lipid disorders.^25,29,31,34 Most of the studies tested drug efficacy for the IL-12/IL-23 inhibitors.^{25,33,36,38–40,45} Seven papers also analyzed TNF inhibitors,^{25,26,32–34,37,45} 5 analyzed IL-17 inhibitors^{25,28,31,33,35} One study did not specify the class of the biologic and instead referred to treatment as biological agents.²⁹ Outcomes of each study are summarized in Table 2.

Several post-hoc analyses of randomized control trials were identified in the literature review. Posthoc analyses of the following randomized control trials were included: FIXTURE, ERASURE, CLEAR, reSURFACE 1, reSURFACE 2, AMAGINE 2, AMAGINE 3, and UNCOVER 1–3. Findings of each post-hoc analyses are shown in Table 3.

A total of 5 post-hoc analyses analyzed obesity/bodyweight/BMI.^{18,19,41–43} Metabolic syndrome and T2D were the second most common cardiometabolic factor analyzed, with a total of 3 articles.^20,41,43 Finally, one posthoc analysis looked at hypertension in addition to metabolic syndrome and BMI.⁴¹ Relevant outcomes of each posthoc analysis are summarized in Table 3.

Discussion

Here, in a qualitative systematic review of 23 manuscripts, we highlight response to biologics among patients with concurrent metabolic comorbidity. The average MINORS score of the non-randomized was a 14.2/24, indicating weaknesses in the methodology of some included studies.

Most of our included studies have assessed psoriasis treatment outcomes in patients with a high BMI/obesity,^{25–30,32–40,44} which overwhelmingly highlight lower rates of achieving both PASI75 and PASI90. The majority of studies reported proportions of participants achieving PASI75, PASI90, and/or PASI100 based on BMI. Multiple studies also reported the effect of confounders on the odds of achieving PASI, with a focus on factors such as smoking, previous biologic treatment, alcohol consumption, and presence of a family history of psoriasis. One study calculated odds ratios of achieving PASI 75 and 90 based on associated comorbidities.²⁵ These results were found in almost all biologics used in the included studies, with some exceptions found during the use of Risankizumab,²⁷ infliximab,³² brodalumab,¹⁸ and in some cases adalimumab.³³ Pirro et al additionally found that patients with obesity had much higher rates of discontinuation of the drug, most likely due to the decreased levels of efficacy.³³ A posthoc analysis done by Lebwohl et al¹⁹ demonstrated that patients weighing above 100kg benefited from the 90 mg dose of ustekinumab compared to the 45 mg dose. Aside from needing dosing adjustments, obese patients were also shown to have a slower response.³⁸ Hung et al found that although obese patients demonstrated a diminished response initially, this was no longer the case after four weeks of treatment with Guselkumab.³⁸ Further studies should be done that evaluate drug response in obese patients over a longer period, similarly to the reSURFACE clinical trial used to evaluate long-term impacts of metabolic syndrome.²⁰

Type II Diabetes/Metabolic Syndrome were also commonly studied, with nearly every study finding lower frequencies of achieving PASI75 & PASI90 in patients with these comorbidities. In the post-hoc analysis conducted by Pinter et al, etanercept specifically showed a diminished response in patients with metabolic syndrome.⁴¹ The same result was found for tildrakizumab in the post-hoc analysis conducted by Fernandez et al.²⁰ Enos et al found that patients with a history of diabetes showed decreased odds of PASI75 and PASI90 at 6 months following biologic initiation.²⁵

Of the studies evaluating hypertension, two found an association between diminished drug responses and hypertension.^25,41 Using real-world data, Enos et al found that, overall, patients with hypertension had lower odds ratios of achieving PASI75.²⁵ Additionally, Pinter et al conducted a post-hoc analysis of multiple randomized control trials finding that patients in the lower response category to secukinumab had higher rates of ongoing hypertension.⁴¹ Due to hypertension often being one of the many symptoms of metabolic syndrome, it is difficult to say how much hypertension specifically is related to poorer drug response. Future studies should isolate hypertensive patients when looking at odds of achieving a proper biologic response.

Only two of the studies included in this review analyzed hyperlipidemia as a cardiometabolic factor. Neither study found an association between hyperlipidemia and a biologic response. Similar to hypertension, hyperlipidemia is often one of the many symptoms of metabolic syndrome, making it difficult to assess how much of a direct effect it had in the studies evaluating metabolic syndrome.

Overall, psoriasis patients with cardiometabolic factors less frequently achieved PASI75 and PASI90 response when treated with biologics. An overwhelming number of studies focus on obesity/increased BMI. Future studies should explore other cardiometabolic factors such as diabetes mellitus, hypertension, and hyperlipidemia to assess for associations with treatment response to biologics. Such studies could aid in a more tailored care plan for patients on an individual level.

Limitations

Due to heterogeneity of the data, only a qualitative analysis of the data was possible. Additionally, all systematic reviews have an element of selection bias based on the keywords and journals selected by the primary and co-investigators. Additionally, the included studies had a low average MINORS score, indicating limitations in the methodology of the studies. Few studies factored in lifestyle factors, treatment adherence, or other confounding variables in their analysis of the results. Other limitations of this review are that few studies assess multiple agents, the population size varies for each study, and there is a difference in follow-up for each study included in this review.

Conclusion

Multiple published studies have demonstrated a poorer response to biologic treatment of psoriasis in the presence of cardiometabolic factors such as obesity, hypertension, type II diabetes, and other cardiometabolic disorders. With multiple studies pointing to a diminished rate of achieving PASI scores in the presence of cardiometabolic comorbidities, and the observed benefit of weight-based dosing for ustekinumab and infliximab in the presence of obesity,¹⁹ future clinical investigations should focus on designing trials with biologic dose adjustments when comorbidities are present. Additional further research is also needed to understand the underlying mechanisms behind the associations of cardiometabolic risk factors and poorer response to biologic therapies. It is recommended that clinicians assess the comorbid disease status of psoriasis patients when developing a therapeutic care plan to optimize their care.