Tildrakizumab in real-world Chinese psoriasis: efficacy-safety profiles from a 28-week retrospective cohort with geriatric, late-onset and metabolic syndrome stratification
Bibliographic record
Abstract
Objective To assess the real-world efficacy and safety of tildrakizumab in Chinese patients with psoriasis stratified by age, age of psoriasis onset and MetS status.Methods This two-center retrospective cohort study evaluated tildrakizumab’s efficacy and safety over 28 weeks in 80 Chinese adults with moderate-to-severe plaque psoriasis, with subgroup analyses by age and age of psoriasis onset and metabolic syndrome (MetS).Results Mean PASI scores showed progressive improvement, declining from 9.3 ± 5.1 at baseline to 1.0 ± 1.4 at week 28 (p < 0.001). A high proportion of patients responded by week 16 (78.4% achieving PASI ≤ 3; 48.6% PASI ≤ 1), with further improvement at week 28 (88.6% and 62.0%, respectively). Dermatology Life Quality Index (DLQI) scores paralleled clinical gains, decreasing from 7.7 ± 4.6 to 0.9 ± 1.8 (p < 0.001), reflecting an 88.3% reduction in quality-of-life impairment. Geriatric patients showed superior PASI 100 responses (81.8% vs 38.6%, p < 0.001) while late-onset patients also represented higher PASI 90 responses (81.5% vs 55.8%, p = 0.027) at week 28. The MetS status did not affect therapeutic response (PASI 100 response: 52.6% vs 45.5%, p = 0.622) at week 28. Safety monitoring identified 4 (5.0%) treatment-emergent adverse events, with no treatment discontinuation for psoriasis exacerbation.Conclusion Tildrakizumab demonstrated sustained efficacy in real-world management of moderate-to-severe psoriasis and supported broad applicability across diverse psoriasis subtypes.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".