Biological treatments for moderate-to-severe psoriasis: indirect comparison
Bibliographic record
Abstract
WHAT IS KNOWN AND OBJECTIVE: Psoriasis is a chronic skin disease for which there is an increasing range of treatment options. Biological agents (ustekinumab, adalimumab, infliximab and etanercept) are indicated for moderate-to-severe plaque-type psoriasis in adults who fail to respond to, have a contraindication to, or are intolerant to other systemic therapies including cyclosporine, methotrexate and PUVA Unfortunately, with new drugs, the pivotal trials leading to their licensing are often placebo-controlled trials rather than comparative trials vs. established therapies. Therefore, inference on comparative effectiveness of the newer agents must be derived indirectly, through estimation of effects of the new agents vs. a common comparator. The objective of this study is to compare the relative efficacy of the biological agents through a systematic review of the indirect clinical trial evidence. METHODS: A systematic literature search was performed for clinical trials of biological agents in psoriasis. Pivotal, randomized, double-blind, controlled (placebo) trials using intention-to-treat analysis were selected for detailed analysis. Trials must include PASI 75 as a primary end point. The indirect comparison was performed using the method of Bucher adjusted with the ITC calculator (Indirect Treatment Comparisons of the Canadian Agency for Drugs and Technologies in Health), etanercept being the reference drug. We defined delta value for therapeutic equivalence as a difference in the efficacy of 25% among the different treatment options. RESULTS AND DISCUSSION: Fourteen studies (four for ustekinumab, three for adalimumab, three for infliximab and four for etanercept) were included. The indirect comparison results reveal that ustekinumab, adalimumab and infliximab were statistically superior to etanercept with an absolute risk difference for PASI 75 of 12% (95% CI = 5·9-18%), 11% (95% CI = 5·3-16·7%) and 24% (29·7-18·3%) respectively. However, in all situations, the 95% confidence interval does not achieve clinical relevance as no delta exceeds the previously set value (25%). WHAT IS NEW AND CONCLUSION: Ustekinumab, adalimumab, infliximab and etanercept can be regarded as clinical equivalents for the treatment of psoriasis. Choice between these agents therefore depends on their relative safety profiles, individual contra-indications and cost effectiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".