Trends in Hidradenitis Suppurativa Disease Severity and Quality of Life Outcome Measures: Scoping Review
Bibliographic record
Abstract
BACKGROUND: Although there has been an increase in the number of randomized controlled trials evaluating treatment efficacy for hidradenitis suppurativa (HS), instrument measurements of disease severity and quality of life (QoL) are varied, making the compilation of data and comparisons between studies a challenge for clinicians. OBJECTIVE: We aimed to perform a systematic literature search to examine the recent trends in the use of disease severity and QoL outcome instruments in randomized controlled trials that have been conducted on patients with HS. METHODS: A scoping review was conducted in February 2021. The PubMed, Embase, Web of Science, and Cochrane databases were used to identify all articles published from January 1964 to February 2021. In total, 41 articles were included in this systematic review. RESULTS: The HS Clinical Response (HiSCR) score (18/41, 44%) was the most commonly used instrument for disease severity, followed by the Sartorius and Modified Sartorius scales (combined: 16/41, 39%). The Dermatology Life Quality Index (18/41, 44%) and visual analogue pain scales (12/41, 29%) were the most commonly used QoL outcome instruments in HS research. CONCLUSIONS: Randomized controlled trials conducted from 2013 onward commonly used the validated HiSCR score, while older studies were more heterogeneous and less likely to use a validated scale. A few (6/18, 33%) QoL measures were validated instruments but were not specific to HS; therefore, they may not be representative of all factors that impact patients with HS. TRIAL REGISTRATION: National Institute of Health Research PROSPERO CRD42020209582; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020209582.
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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 | 0.032 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.029 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".