Strategies for improving the quality of care in psoriasis with the use of treatment goals – a report on an implementation meeting
Bibliographic record
Abstract
Targeted treatment, early intervention and the use of treatment goals is a new approach in medicine that has been implemented across several disciplines (e.g. diabetes, pulmonary arterial hypertension and rheumatoid arthritis) over the last 5-10 years. As in other chronic diseases, well-defined treatment goals may be helpful in guiding physicians in their care of patients with psoriasis, thereby obviating poor outcomes. Individual treatment goals were recently developed for the first time in psoriasis by a European Consensus group of experts from 19 European countries to supplement guidelines and promote the consistent use of available therapies to improve patient care. Goal-oriented therapy involves treating according to a treatment algorithm, regularly monitoring therapeutic response and prompt modification of therapy if goals are not met. In the absence of hard outcomes in psoriasis (e.g. biomarkers or biomedical predictors of clinical response), the European Consensus group based their treatment goals on changes in Psoriasis Area Severity Index and Dermatology Life Quality Index scores. Further evidence generation is important to determine whether surrogate markers for disease progression (e.g. co-morbidities) or predictors of clinical response can be identified for psoriasis. Furthermore, psoriasis may have a potential cumulative effect on the life course of patients, the understanding of which is likely to provide the rationale for earlier treatment strategies in psoriasis. For the work of the European Consensus group to have an impact on clinical care, transmission of treatment goals into guidelines, along with implementation of treatment goals at both the regional and national level is needed. Thus, dermatology experts from Europe, the Middle East, Australia and Canada gathered in Frankfurt, 2010, for a 1.5 day educational meeting run by the Progressive Psoriasis Initiative to discuss how treatment goals in psoriasis might best be implemented in clinical practice. The meeting conclusions are presented here.
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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 | 0.057 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".