Systematic review of real‐world persistence and adherence in subcutaneous allergen immunotherapy
Bibliographic record
Abstract
BACKGROUND: Given that subcutaneous immunotherapy (SCIT) adherence in the literature is often studied in closely monitored trials, few studies report real-world SCIT adherence. The purpose of this review is to assess SCIT adherence in real-world settings. METHODS: A literature search of PubMed, Embase, Cochrane Library, Web of Science, and Scopus for real-world studies examining SCIT adherence was performed. Paired investigators independently reviewed all articles. For this review, "persistence" was defined as continuing therapy and not being lost to follow-up after initiating SCIT, and "adherence" defined as persistence in accordance with prescribed SCIT dose, dosing schedule, and duration. Article quality was first assessed using a modified Newcastle-Ottawa scale and then converted to Agency for Healthcare Research and Quality standards (good, fair, and poor). RESULTS: The search yielded 1596 nonduplicate abstracts, from which 17 articles (n = 263,221 patients) met inclusion criteria. Fourteen (82%) studies reported persistence rates, ranging from 16.0% to 93.7%. Seven (41%) studies reported adherence rates, ranging from 15.1% to 99%. Five (29%) studies (n = 416 patients) collected original data on reasons for discontinuing SCIT, of which inconvenience was most cited. All studies were Oxford level of evidence 2b and of good (n = 10) to fair (n = 7) quality. CONCLUSION: Real-world SCIT persistence and adherence rates are poor, with the majority of included studies reporting rates <80%; however, they range widely, explained in part by inter-study differences in measuring and reporting adherence-related findings. Future studies on SCIT adherence may benefit from following concordant definitions of persistence and adherence in addition to standardized reporting metrics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 teacher head, 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".