Anti-IgE monoclonal antibody therapy for the treatment of chronic rhinosinusitis: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Several options are available for the treatment of chronic rhinosinusitis (CRS), but disease control remains elusive for many patients. Recently, literature has emerged describing anti-IgE monoclonal antibody as a potential therapy for CRS. However, its effectiveness and safety are not well known. The purpose of this systematic review was to assess the effectiveness and safety of anti-IgE therapy and to identify evidence gaps that will guide future research for the management of CRS. METHODS: Methodology was registered with PROSPERO (No. CRD42014007600). A comprehensive search was performed of standard bibliographic databases, Google Scholar, and clinical trials registries. Only randomized controlled trials assessing anti-IgE therapy in adult patients for the treatment of CRS were included. Two independent reviewers extracted data using a pre-defined extraction form and performed quality assessment using the Cochrane risk of bias tool and the GRADE framework. RESULTS: Two studies met our inclusion criteria. When comparing anti-IgE therapy to placebo, there was a significant difference in Lund-McKay score (p = 0.04) while no difference was seen for percent opacification on computed tomography (CT). At 16 weeks, treatment led to a decrease in clinical polyp score. No significant difference was seen with regard to quality of life (Total Nasal Symptom Severity (TNSS), p < 0.21; Sinonasal Outcome Test 20 (SNOT-20), p < 0.60), and no serious complications were reported in either trial. Based on the quality assessment, studies were deemed to be of moderate risk of bias and a low overall quality of evidence. CONCLUSIONS: There is currently insufficient evidence to determine the effectiveness of anti-IgE monoclonal antibody therapy for the treatment of CRS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.024 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it