Peak Nasal Inspiratory Flow and the Association with Nasal Obstruction in Patients with Severe CRSwNP from the SINUS-24/-52 Studies
Bibliographic record
Abstract
Nasal congestion/obstruction (NC) contributes to the high disease burden in patients with severe chronic rhinosinusitis with nasal polyps (CRSwNP). Patient perception of NC may not accurately reflect nasal patency, while peak nasal inspiratory flow (PNIF) is an objective method with established thresholds for normal nasal airflow. This analysis evaluated the association between NC and PNIF and the impact of baseline PNIF on dupilumab efficacy in patients with severe CRSwNP. This was a post hoc analysis of patients treated with placebo or dupilumab 300 mg every 2 weeks in the SINUS-24 (NCT02912468) and SINUS-52 (NCT02898454) phase III studies. Patients provided daily e-diary measures of PNIF (L/min) using PNIF meters, and NC by patient-reported evaluation of severity (scored 0–3). Other assessed outcomes were nasal polyp score (NPS), 22-item Sinonasal Outcome Test (SNOT-22), loss of smell (LoS), University of Pennsylvania Smell Identification Test (UPSIT), and Lund–Mackay computed tomography. Outcomes were assessed in two subgroups: baseline PNIF < 120 L/min and ≥ 120 L/min. Of 724 patients, 552 (76%) had PNIF < 120 L/min and 172 (24%) had PNIF ≥ 120 L/min at baseline. The PNIF < 120 L/min subgroup had higher mean scores for NPS and SNOT-22 and more smell impairment (LoS and UPSIT). PNIF weakly correlated with NC at baseline (Spearman coefficient − 0.348 [95% CI − 0.410, − 0.282], P < 0.0001). Correlations between change from baseline in PNIF and NC at week 24 were weak in the dupilumab group (− 0.390 [− 0.468, − 0.305], P < 0.0001) and moderate in the placebo group (− 0.497 [− 0.582, − 0.399], P < 0.0001). These results confirm PNIF as a valuable method for assessing nasal obstruction in patients with severe CRSwNP. The degree of nasal flow impairment at baseline does not impact dupilumab’s efficacy. A graphical abstract and video abstract are available for this article. Chronic rhinosinusitis with nasal polyps (CRSwNP) causes narrowing, and sometimes complete blockage, of the air passages in the nose, making it difficult to breathe. This can impact a person’s ability to smell, taste, sleep, and perform daily activities, which in turn negatively impacts their overall quality of life. Measures of nasal congestion and loss of smell rely on people’s self-perceptions, which can vary and may not reflect the actual level of congestion seen when cameras are inserted into the nose. This article looks at a measure of nasal airflow called peak nasal inspiratory flow (PNIF), a non-invasive method for directly measuring airflow through the nose, and how this compares with the patient-reported measures nasal congestion and loss of smell. Data from two studies (SINUS-24 and SINUS-52) assessing the effects of a drug called dupilumab in people with severe CRSwNP were used. Patients were grouped according to their PNIF scores at recruitment (a PNIF measure of less than 120 L per minute indicated poor nasal airflow). Results showed a relationship between low PNIF and severe nasal congestion and loss of smell, suggesting PNIF may be a useful and convenient method for directly assessing nasal airflow. The study also shows that dupilumab was effective for patients with severe CRSwNP regardless of nasal airflow quality at the beginning of the 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".