Model-Based Meta-Analysis in Psoriasis: A Quantitative Comparison of Biologics and Small Targeted Molecules

Quantitative evaluation of the time-course and efficacy of targeted agents for ulcerative colitis

Background

Targeted agents are widely utilized in the treatment of ulcerative colitis (UC). Hence, a comprehensive understanding of comparative drug efficacy in UC is of great importance for drug development and clinical practice. Our objective was the quantitative evaluation of the comparative efficacy of targeted agents for UC.

Methods

Three mathematical models were developed based on data from randomized controlled trials in patients with moderate-to-severe UC to describe the time-course and dose-response of efficacy defined as clinical remission, clinical response, and endoscopic improvement, as well as the placebo effect. The covariate effects were further evaluated. Model simulation was performed in a hypothetical population to compare the efficacies across different drugs.

Results

The analysis dataset was composed of data from 35 trials of 12 drugs in UC. Time-response relationships were evaluated that indicated a gradual onset of drug efficacy in adalimumab, ozanimod, and Janus kinase (JAK) inhibitors. The dose-response relationships were estimated for each drug respectively. Patient age, disease duration, baseline weight, prior tumor necrosis factor (TNF) inhibitor exposure, and current treatment with corticosteroid showed an impact on efficacy, suggesting that younger patients with shorter UC duration without prior anti-TNF treatment and current corticosteroids therapy tend to display greater treatment effects.

Conclusion

This study developed three longitudinal models for UC to quantitatively describe the efficacy of targeted agents, as well as the influencing factors of efficacy. Infliximab and upadacitinib were determined to be the most effective biological and small targeted molecules, respectively. These findings may provide valuable implications for guiding future decision-making in clinical practice and drug development for UC.

Comparative Effectiveness of Bimekizumab in Psoriatic Arthritis: A Model-Based Meta-Analysis of American College of Rheumatology Response Criteria

A model-based meta-analysis (MBMA) was conducted to compare the efficacy of bimekizumab with other psoriatic arthritis (PsA) treatment regimens using ≥  20%/50%/70% improvements in American College of Rheumatology (ACR) criteria (ACR20/50/70) for patients with PsA. Forty-nine trials of 16 drugs were identified in the literature, comprising 21,340 patients. Trial-level covariates, including prior biologic use, concomitant methotrexate use, time since diagnosis, trial completion year, and active comparator were considered for exploratory models. The final model was selected using leave-one-out cross-validation (LOO CV) to assess predictive performance based on prespecified criteria. LOO CV was conducted for 15 trials; the final model demonstrated that 91.5% (952/1,040) of the observed treatment differences, and 96.1% of the observed ACR20/50/70 response rates were within the 95% prediction interval (PI). Median ACR50 response rates (95% PI) at week 16 in biologic-naïve patients were predicted to be 44% (40-49%) for bimekizumab 160 mg, among the highest of all treatments analyzed. Response rates for secukinumab 150 mg and risankizumab 150 mg were 28% (25-32%) and 27% (24-31%), respectively. The MBMA was also used to predict the probability of success (PoS) of potential head-to-head trials using ACR50 response as the end point with varying sample sizes: vs. secukinumab 150 mg, the PoS for bimekizumab 160 mg was 62% (N = 200) and 90% (N = 400). Versus risankizumab 150 mg, the PoS for bimekizumab 160 mg was 68% (N = 200) and 94% (N = 400). In summary, a predictive MBMA described ACR20/50/70 outcomes in PsA, allowing accurate and precise treatment comparisons and robust PoS calculations.

Comparing Meta-Analyses with ChatGPT in the Evaluation of the Effectiveness and Tolerance of Systemic Therapies in Moderate-to-Severe Plaque Psoriasis

BACKGROUND

Meta-analyses (MAs) and network meta-analyses (NMAs) are high-quality studies for assessing drug efficacy, but they are time-consuming and may be affected by biases. The capacity of artificial intelligence to aggregate huge amounts of information is emerging as particularly interesting for processing the volume of information needed to generate MAs. In this study, we analyzed whether the chatbot ChatGPT is able to summarize information in a useful fashion for providers and patients in a way that matches up with the results of MAs/NMAs.

METHODS

We included 16 studies (13 NMAs and 3 MAs) that evaluate biologics (n = 6) and both biologic and systemic treatment (n = 10) for moderate-to-severe psoriasis, published between January 2021 and May 2023.

RESULTS

The conclusions of the MAs/NMAs were compared to ChatGPT's answers to queries about the molecules evaluated in the selected MAs/NMAs. The reproducibility between the results of ChatGPT and the MAs/NMAs was random regarding drug safety. Regarding efficacy, ChatGPT reached the same conclusion as 5 out of the 16 studies (four out of four studies when three molecules were compared), gave acceptable answers in 7 out of 16 studies, and was inconclusive in 4 out of 16 studies.

CONCLUSIONS

ChatGPT can generate conclusions that are similar to MAs when the efficacy of fewer drugs is compared but is still unable to summarize information in a way that matches up to the results of MAs/NMAs when more than three molecules are compared.

Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis

BACKGROUND

Psoriasis is an immune-mediated disease with either skin or joints manifestations, or both, and it has a major impact on quality of life. Although there is currently no cure for psoriasis, various treatment strategies allow sustained control of disease signs and symptoms. The relative benefit of these treatments remains unclear due to the limited number of trials comparing them directly head-to-head, which is why we chose to conduct a network meta-analysis.

OBJECTIVES

To compare the benefits and harms of non-biological systemic agents, small molecules, and biologics for people with moderate-to-severe psoriasis using a network meta-analysis, and to provide a ranking of these treatments according to their benefits and harms.

SEARCH METHODS

For this update of the living systematic review, we updated our searches of the following databases monthly to October 2022: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and Embase.

SELECTION CRITERIA

Randomised controlled trials (RCTs) of systemic treatments in adults over 18 years with moderate-to-severe plaque psoriasis, at any stage of treatment, compared to placebo or another active agent. The primary outcomes were: proportion of participants who achieved clear or almost clear skin, that is, at least Psoriasis Area and Severity Index (PASI) 90; proportion of participants with serious adverse events (SAEs) at induction phase (8 to 24 weeks after randomisation).

DATA COLLECTION AND ANALYSIS

We conducted duplicate study selection, data extraction, risk of bias assessment, and analyses. We synthesised data using pairwise and network meta-analysis (NMA) to compare treatments and rank them according to effectiveness (PASI 90 score) and acceptability (inverse of SAEs). We assessed the certainty of NMA evidence for the two primary outcomes and all comparisons using CINeMA, as very low, low, moderate, or high. We contacted study authors when data were unclear or missing. We used the surface under the cumulative ranking curve (SUCRA) to infer treatment hierarchy, from 0% (worst for effectiveness or safety) to 100% (best for effectiveness or safety).

MAIN RESULTS

This update includes an additional 12 studies, taking the total number of included studies to 179, and randomised participants to 62,339, 67.1% men, mainly recruited from hospitals. Average age was 44.6 years, mean PASI score at baseline was 20.4 (range: 9.5 to 39). Most studies were placebo-controlled (56%). We assessed a total of 20 treatments. Most (152) trials were multicentric (two to 231 centres). One-third of the studies (65/179) had high risk of bias, 24 unclear risk, and most (90) low risk. Most studies (138/179) declared funding by a pharmaceutical company, and 24 studies did not report a funding source. Network meta-analysis at class level showed that all interventions (non-biological systemic agents, small molecules, and biological treatments) showed a higher proportion of patients reaching PASI 90 than placebo. Anti-IL17 treatment showed a higher proportion of patients reaching PASI 90 compared to all the interventions. Biologic treatments anti-IL17, anti-IL12/23, anti-IL23, and anti-TNF alpha showed a higher proportion of patients reaching PASI 90 than the non-biological systemic agents. For reaching PASI 90, the most effective drugs when compared to placebo were (SUCRA rank order, all high-certainty evidence): infliximab (risk ratio (RR) 49.16, 95% CI 20.49 to 117.95), bimekizumab (RR 27.86, 95% CI 23.56 to 32.94), ixekizumab (RR 27.35, 95% CI 23.15 to 32.29), risankizumab (RR 26.16, 95% CI 22.03 to 31.07). Clinical effectiveness of these drugs was similar when compared against each other. Bimekizumab and ixekizumab were significantly more likely to reach PASI 90 than secukinumab. Bimekizumab, ixekizumab, and risankizumab were significantly more likely to reach PASI 90 than brodalumab and guselkumab. Infliximab, anti-IL17 drugs (bimekizumab, ixekizumab, secukinumab, and brodalumab), and anti-IL23 drugs except tildrakizumab were significantly more likely to reach PASI 90 than ustekinumab, three anti-TNF alpha agents, and deucravacitinib. Ustekinumab was superior to certolizumab. Adalimumab, tildrakizumab, and ustekinumab were superior to etanercept. No significant difference was shown between apremilast and two non-biological drugs: ciclosporin and methotrexate. We found no significant difference between any of the interventions and the placebo for the risk of SAEs. The risk of SAEs was significantly lower for participants on methotrexate compared with most of the interventions. Nevertheless, the SAE analyses were based on a very low number of events with very low- to moderate-certainty evidence for all the comparisons. The findings therefore have to be viewed with caution. For other efficacy outcomes (PASI 75 and Physician Global Assessment (PGA) 0/1), the results were similar to the results for PASI 90. Information on quality of life was often poorly reported and was absent for several of the interventions.

AUTHORS' CONCLUSIONS

Our review shows that, compared to placebo, the biologics infliximab, bimekizumab, ixekizumab, and risankizumab were the most effective treatments for achieving PASI 90 in people with moderate-to-severe psoriasis on the basis of high-certainty evidence. This NMA evidence is limited to induction therapy (outcomes measured from 8 to 24 weeks after randomisation), and is not sufficient for evaluating longer-term outcomes in this chronic disease. Moreover, we found low numbers of studies for some of the interventions, and the young age (mean 44.6 years) and high level of disease severity (PASI 20.4 at baseline) may not be typical of patients seen in daily clinical practice. We found no significant difference in the assessed interventions and placebo in terms of SAEs, and the safety evidence for most interventions was very low to moderate quality. More randomised trials directly comparing active agents are needed, and these should include systematic subgroup analyses (sex, age, ethnicity, comorbidities, psoriatic arthritis). To provide long-term information on the safety of treatments included in this review, an evaluation of non-randomised studies is needed. Editorial note: This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Comparation of time-course, dose-effect, influencing factors and adverse events of biologics in the treatment of adults with moderate to severe plaque psoriasis

Introduction

Biologics is used for treating moderate to severe plaque psoriasis (MSPP), which represent one of the foremost therapeutic advancements in disease of dermatology. Up to now, the relative efficacy and safety across approved andinvestigational biologics for MSPP is still unclear.

Methods

This study aimed to comparative effectiveness of various biological treatments for MSPP measured by PASI75, PASI90 and PASI100 (The ratio of patients whose Psoriasis Area and Severity Index score (PASI) decreased by ≥ 75%, 90% and 100% compared with baseline, respectively). In addition, random models were used together with a Bayesian method to compare direct and indirect Adverse Events (AEs) of biologics with placebo, to make probabilistic statements and predictions on their AEs. The analytic data set was made up of summarized data from 54 trials, including 27,808 patients, with treatment of 17 biologics. Three mathematic models with nonparametric placebo evaluations were established to characterize the longitudinal direction profile for the three efficacy measures as above mentioned.

Results

Our results showed significant differences among treatments. Bimekizumab, sonelokimab, and ixekizumab were found to be the most effective treatments among the biologics. The effects of covariate were further evaluated, patients' age, body weight, duration of disease and percentage of patients previously treated with a biological therapy showed impact on the efficacy. In addition, we found that ixekizumab and risankizumab displayed relatively stable as for efficacy and safety.

Discussion

Our findings provide valuable insights into the comparative effectiveness and safety of biologics for MSPP treatment. These results may aid in clinical decision-making and ultimately improve patient outcomes.

Blocking interleukin-17 in psoriasis: Real-world experience from the PsoPlus cohort

BACKGROUND

Real-world studies on the use of biologics in psoriasis (Pso) are increasing, but still scarce. Trough concentrations (C_t s) of interleukin-17 inhibitors (IL-17i) seem promising for clinical decision-making, but their value in daily practice has yet to be proven.

OBJECTIVES

To report on IL-17i effectiveness, treatment modifications and C_t use in our clinic.

METHODS

Data were collected from IL-17i-treated Pso patients followed up in the PsoPlus clinic at the Dermatology department, Ghent University Hospital, Belgium. Descriptive statistics and Kaplan-Meier analysis were performed.

RESULTS

A total of 111 patients were included, counting for 134 IL-17i courses (secukinumab, ixekizumab, and brodalumab). Fifty-five per cent of the patients were bio-naive prior to IL-17i initiation. During maintenance, merely 97.0% and 77% achieved near-complete and complete skin clearance, respectively. Major reasons for treatment modification were suboptimal response (63.0%) and safety issues (9.3%). Reported modifications were switch (25.4%), dose escalation (11.9%), dose de-escalation (6.7%), treatment association (6.0%) and IL-17i stop (3.0%). Overall drug survival was 69.0 months, without difference between the different IL-17i (p = 0.078). Ixekizumab tended to have the highest survival. Drug survival was higher in bio-naive subjects compared to bio-experienced subjects (p = 0.011). C_t was measured in 20 patients and interpreted post hoc. In 85%, the clinical decision was in accordance with the C_t (e.g. substantiated need for dose escalation). For the other cases, the C_t would have led to another clinical decision if known at that time.

CONCLUSIONS

This real-world study showed that IL-17i are very effective drugs for Pso, with ixekizumab as leading biologic. Prior bio-experience seemed to impact IL-17i drug survival. Treatment modifications were mainly performed in case of insufficient response, primarily via switch and dose escalation, and least frequently in ixekizumab patients. C_t might rationalize clinical decision-making; however, there is need for standardized algorithms to corroborate its use.

Applications of Model-Based Meta-Analysis in Drug Development

Model-based meta-analysis (MBMA) is a quantitative approach that leverages published summary data along with internal data and can be applied to inform key drug development decisions, including the benefit-risk assessment of a treatment under investigation. These risk-benefit assessments may involve determining an optimal dose compared against historic external comparators of a particular disease indication. MBMA can provide a flexible framework for interpreting aggregated data from historic reference studies and therefore should be a standard tool for the model-informed drug development (MIDD) framework.In addition to pairwise and network meta-analyses, MBMA provides further contributions in the quantitative approaches with its ability to incorporate longitudinal data and the pharmacologic concept of dose-response relationship, as well as to combine individual- and summary-level data and routinely incorporate covariates in the analysis.A common application of MBMA is the selection of optimal dose and dosing regimen of the internal investigational molecule to evaluate external benchmarking and to support comparator selection. Two case studies provided examples in applications of MBMA in biologics (durvalumab + tremelimumab for safety) and small molecule (fenebrutinib for efficacy) to support drug development decision-making in two different but well-studied disease areas, i.e., oncology and rheumatoid arthritis, respectively.Important to the future directions of MBMA include additional recognition and engagement from drug development stakeholders for the MBMA approach, stronger collaboration between pharmacometrics and statistics, expanded data access, and the use of machine learning for database building. Timely, cost-effective, and successful application of MBMA should be part of providing an integrated view of MIDD.