<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 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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".