Immunotherapy (oral and sublingual) for food allergy to fruits
Bibliographic record
Abstract
BACKGROUND: Food allergy is an abnormal immunological response following exposure (usually ingestion) to a food. Elimination of the allergen is the principle treatment for food allergy, including allergy to fruit. Accidental ingestion of allergenic foods can result in severe anaphylactic reactions. Allergen-specific immunotherapy (SIT) is a specific treatment, when the avoidance of allergenic foods is problematic. Recently, studies have been conducted on different types of immunotherapy for the treatment of food allergy, including oral (OIT) and sublingual immunotherapy (SLIT). OBJECTIVES: To determine the efficacy and safety of oral and sublingual immunotherapy in children and adults with food allergy to fruits, when compared with placebo or an elimination strategy. SEARCH METHODS: The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, CINAHL, and AMED were searched for published results along with trial registries and the Journal of Negative Results in BioMedicine for grey literature. The date of the most recent search was July 2015. SELECTION CRITERIA: Randomised controlled trials (RCTs) comparing OIT or SLIT with placebo or an elimination diet were included. Participants were children or adults diagnosed with food allergy who presented immediate fruit reactions. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by the Cochrane Collaboration. We assessed treatment effect through risk ratios (RRs) for dichotomous outcomes. MAIN RESULTS: We identified two RCTs (N=89) eligible for inclusion. These RCTs addressed oral or sublingual immunotherapy, both in adults, with an allergy to apple or peach respectively. Both studies enrolled a small number of participants and used different methods to provide these differing types of immunotherapy. Both studies were judged to be at high risk of bias in at least one domain. Overall, the quality of evidence was judged to be very low due to the small number of studies and participants and possible bias. The studies were clinically heterogeneous and hence we did not pool the results. A study comparing SLIT with placebo for allergy to peach did not detect a significant difference between the number of patients desensitised at six months following a double-blind placebo-controlled food challenge (RR 1.16, 95% confidence interval (CI) 0.49 to 2.74). The second study, comparing OIT versus no treatment for apple allergy, found an effect on desensitisation in favour of the intervention using an oral provocation test at eight months, but results were imprecise (RR 17.50, 95% CI 1.13 to 270.19). Neither study reported data on evidence of immunologic tolerance. In both studies, the incidence of mild and moderate adverse events was higher in the intervention groups than in the controls. In the study comparing SLIT with placebo, patients in the intervention group experienced significantly more local adverse reactions than participants in the control group (RR 3.21, 95% CI 1.51 to 6.82), though there was not a significant difference in the number of participants experiencing systemic adverse reactions (RR 0.81, 95% CI 0.22 to 3.02). In the study of OIT, two of the 25 participants in the intervention group reported relevant side effects, whereas no participants in the control group reported relevant side effects. AUTHORS' CONCLUSIONS: There is insufficient evidence for using OIT or SLIT to treat allergy to fruit, specifically related to peach and apple. Mild or moderate adverse reactions were reported more frequently in people receiving OIT or SLIT. However, these reactions could be treated successfully with medications.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".