Biologic Treatment in Elderly Patients With Psoriasis: A Systematic Review
Bibliographic record
Abstract
With our aging population, an increasing number of psoriasis patients are classified as elderly. However, psoriasis treatment in older adults can be challenging, given an increased number of comorbid conditions and immunosenescence. Biologic agents present a solution to this treatment dilemma because of their high efficacy and favorable tolerability. The objective of this systematic review was to summarize the findings of clinical trial and real-world studies exploring the safety and efficacy of biologic agents in elderly patients with moderate-to-severe psoriasis. We searched MEDLINE, Embase, the Cochrane Library, and clinical trial databases. Studies analyzing biologics for psoriasis were included if elderly patients were the main population of interest or were a separate subgroup in their analysis. Eighteen articles met inclusion criteria after screening. Across all biologic classes, efficacy for biologics between nonelderly adult patient and elderly patients was similar. Adverse events (AEs) and infections occured at a similar frequency between both groups. However, serious AEs were more common in the elderly. The available literature on the safety and efficacy of biologic agents in elderly patients supports the use of these agents in this population. However, serious AEs and discontinuation due to AEs were more common in older patients. As elderly patients have a higher burden of comorbid conditions and an increased baseline vulnerability for AE, physicians should continue to be prudent in screening before initiating biologics and monitor patients more closely as AEs tend to be more severe.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".