Failure of scabies treatment: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Treatment failure is considered to be an important factor in relation to the increase in scabies incidence over the last decade. However, the regional and temporal differences, in addition to the predictors of therapy failure, are unclear. OBJECTIVES: We aimed to conduct a systematic review of the prevalence of treatment failure in patients with scabies and investigation of associated factors. METHODS: We searched MEDLINE, EMBASE, CINAHL, Web of Science, Scopus, Global Health and the Cochrane Central Register of Controlled Trials from inception to August 2021 for randomized and quasi-randomized trials, in addition to observational studies that enrolled children or adults diagnosed with confirmed or clinical scabies treated with permethrin, ivermectin, crotamiton, benzyl benzoate, malathion, sulfur or lindane, and measured treatment failure or factors associated with treatment failure. We performed a random effects meta-analysis for all outcomes reported by at least two studies. RESULTS: A total of 147 studies were eligible for inclusion in the systematic review. The overall prevalence of treatment failure was 15.2% [95% confidence interval (CI) 12.9-17.6; I2 = 95.3%, moderate-certainty evidence] with regional differences between World Health Organization regions (P = 0.003) being highest in the Western Pacific region (26.9%, 95% CI 14.5-41.2). Oral ivermectin (11.8%, 95% CI 8.4-15.4), topical ivermectin (9.3%, 95% CI 5.1-14.3) and permethrin (10.8%, 95% CI 7.5-14.5) had relatively lower failure prevalence compared with the overall prevalence. Failure prevalence was lower in patients treated with two doses of oral ivermectin (7.1%, 95% CI 3.1-12.3) compared with those treated with one dose (15.2%, 95% CI 10.8-20.2; P = 0.021). Overall and permethrin treatment failure prevalence in the included studies (1983-2021) increased by 0.27% and 0.58% per year, respectively. Only three studies conducted a multivariable risk factor analysis; no studies assessed resistance. CONCLUSIONS: A second dose of ivermectin showed lower failure prevalence than single-dose ivermectin, which should be considered in all guidelines. The increase in treatment failure over time hints at decreasing mite susceptibility for several drugs, but reasons for failure are rarely assessed. Ideally, scabicide susceptibility testing should be implemented in future studies.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.051 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".