Ten Commandments for Randomized Trials of Pharmacological Therapy for COPD and Other Lung Diseases
Bibliographic record
Abstract
The randomized controlled trial is the quintessential scientific tool to evaluate the effectiveness and safety of medications. While early trials of drugs used for the treatment of chronic obstructive pulmonary disease (COPD) and other respiratory diseases were generally unambiguous, more recent studies have been controversial. It has become evident that the conduct, design and analysis of these trials were highly variable and may have been responsible for incoherencies in results and interpretation. With the advent of new studies, the need for guiding principles for the conduct of future randomized trials has become manifest. We describe the concept of the counterfactual principle as it applies to the treatment of patients and to the randomized trial. We then present ten methodological tenets for the design and statistical aspects of randomized controlled trials evaluating the effectiveness of drugs used in the treatment of several respiratory diseases. They include eight study design and two statistical analysis principles: 1) Study question; 2) Intervention; 3) Study population; 4) Blinding; 5) Run-in period; 6) Follow-up; 7) Outcome; 8) Safety; 9) Intent-to-treat; 10) Covariate adjustment. These tenets are described using mainly examples from trials of pharmacological treatments for COPD, as well as some from asthma and idiopathic pulmonary fibrosis, conducted over the last 30 years. The careful application of these principles in the conduct of randomized trials will provide rigorous studies and improve the validity of results. The ensuing clearer interpretation of findings will permit their well-founded contribution to treatment guidelines and optimal clinical management.
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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 | 0.792 | 0.794 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.018 | 0.014 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.008 | 0.078 |
| Scholarly communication | 0.029 | 0.022 |
| Open science | 0.012 | 0.014 |
| Research integrity | 0.033 | 0.076 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".