327 Optimizing the management of atopic dermatitis with a new minimal disease activity concept and criteria and consensus-based recommendations for systemic therapy
Bibliographic record
Abstract
Abstract Inconsistent criteria are used to identify patients with atopic dermatitis (AD) who are candidates for systemic therapy and assess their response to systemic therapy. This may lead to undertreatment and treatment dissatisfaction. A treat-to-target (T2T) framework was previously proposed to guide systemic treatment decisions in patients with moderate-to-severe AD.1 While patient representatives were included in the T2T consensus voting process, no patient or caregiver stakeholders were included in the development of the T2T recommendations. Additionally, a recent analysis of the cross-sectional, 28-country MEASURE-AD study suggests that the treatment targets in the T2T criteria may be insufficient to ensure optimal treatment outcomes.2 To develop optimized and practical criteria for identifying patients who should receive systemic therapy, including definitions of treatment goals, treatment failure and disease severity. An executive steering committee (ESC) of seven international experts was formed in January 2021 to provide insights and perspectives on how to optimize the identification of patients who would most benefit from systemic therapy for AD. After discussing the gaps and needs in current AD management, the ESC agreed that there was a lack of evidence on patients’ treatment goals, needs, and expectations. The ESC, therefore, initiated a global, ethically and culturally diverse patient research study (N = 88) to collect these insights. Subsequently, nine regional sub-committees (SCs) were created to gain clinical perspectives from different regions worldwide (covering the USA and Puerto Rico, Latin America, Western Europe and Canada, Eastern Europe and Russia, the Middle East, Asia, and Australia and New Zealand). Overall, 87 experts from 44 countries contributed to the initiative, and 46 virtual ESC and SC meetings took place to discuss how to improve the lives of patients with AD. A virtual secure platform allowed discussions and contributions to continue outside these meetings. In April 2022, all experts rated their agreement with a series of recommendations regarding the identification and monitoring of patients eligible for systemic therapy, using a 10-point Likert scale in a modified eDelphi voting process. The consensus was pre-defined as ≥70% of all respondents rating agreement as 7 (‘mildly agree’), 8 (‘moderately agree’), 9 (‘agree’) or 10 (‘strongly agree’) with a recommendation. A strong consensus was defined as ≥90% agreement. Expert perspectives and patient insights led to the development of 34 patient-focused clinical recommendations on disease severity assessments, treatment goals and targets for clinician- and patient-reported outcomes, long-term disease control and a novel minimal disease activity (MDA) concept. A consensus of ≥80% was reached for all recommendations in one round of voting, with 88% of the recommendations reaching a ‘strong’ consensus. The MDA concept combines T2T principles with shared patient/clinician treatment decision-making principles. Patients are asked to select 1–3 feature(s) of AD which are most important to them (from the itch, skin appearance/condition, sleep disturbance, mental health, skin pain and impact on daily life). The clinician is asked to choose an objective measure of disease (from the Eczema Area and Severity Index [EASI], SCORing AD and/or the Investigator’s Global Assessment and body surface area). Treatment targets are then chosen from a list of ‘moderate’ and ‘optimal’ targets based on discussions between the clinician and patient. Optimal treatment targets include ≥90% improvement in EASI and a numeric rating scale of ≤ 1 for peak pruritus, sleep, and pain. Achievement of ‘optimal’ targets is defined as MDA. This international group of AD experts developed a novel MDA concept and criteria, which builds upon existing T2T work by providing a patient-centric approach to the optimal treatment of AD. The criteria and patient-focused clinical recommendations will help to identify and monitor patients with AD who could benefit from systemic therapy.
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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 | 0.100 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".