<p>The CHRONICLE Study of US Adults with Subspecialist-Treated Severe Asthma: Objectives, Design, and Initial Results</p>
Bibliographic record
Abstract
Background: Approximately 5– 10% of patients with asthma have severe disease. High-quality real-world studies are needed to identify areas for improved management. Objective: Aligned with the International Severe Asthma Registry, the CHRONICLE study (ClinicalTrials.gov: NCT03373045) was developed to address this need in the US. Study Design: Learnings from prior studies were applied to develop a real-world, prospective, noninterventional study of US patients with confirmed severe asthma who are treated by subspecialist physicians and require biologic or maintenance systemic immunosuppressant therapy or who are uncontrolled by high-dosage inhaled corticosteroids and additional controllers. Target enrollment is 4000 patients, with patient observation for ≥ 3 years. A geographically diverse sample of allergist/immunologist and pulmonologist sites approach all eligible patients under their care and report patient characteristics, treatment, and health outcomes every 6 months. Patients complete online surveys every 1– 6 months. Initial Results: From February 2018 to February 2019, 102 sites screened 1428 eligible patients; 936 patients enrolled. Study sites (40% allergist/immunologist, 42% pulmonologist, 18% both) were similar to other US asthma subspecialist samples. Enrolled patients were 67% female with median ages at enrollment and diagnosis of 55 (range: 18– 89) and 26 (0– 80) years, respectively. Median body mass index was 31 kg/m 2 ; 3% and 29% were current or former smokers, respectively, and > 60% reported ≥ 1 exacerbation in the prior year and suboptimal symptom control. Conclusion: CHRONICLE will provide high-quality provider- and patient-reported data from a large, real-world cohort of US adults with subspecialist-treated severe asthma. Keywords: asthma exacerbations, longitudinal studies, allergists, pulmonologists, biologic therapy
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".