Scientific, societal, and economic consequences of releasing interim data from clinical trials
Bibliographic record
Abstract
When interim clinical trial data are released, vigorous discussion frequently ensues, either supporting or lamenting the decision. Two recent early terminations of clinical trials in obesity and hypertension opened heated discussions about the scientific, societal, and economic consequences of prematurely stopping on-going studies and releasing interim clinical trial data. The Cardiovascular Outcomes Study of Naltrexone SR/Bupropion SR in Overweight and Obese Subjects with Cardiovascular Risk Factors (LIGHT Study), sponsored by Orexigen and Takeda (https://clinicaltrials.gov/ct2/show/NCT01601704?term=contrave&rank=5 (accessed 17 May 2016)) randomized 8910 obese individuals with risk factors for cardiovascular disease to Contrave (combination Naltrexone SR and Buproprion) vs. placebo. The primary endpoint was time to major adverse cardiovascular events (MACE). Controversy arose when these confidential interim results were released in a patent filing, after 25% of MACE events occurred, claiming that Contrave caused a 41% reduction in MACE (P < 0.0001). At the time of the interim analysis, the mean duration of drug exposure was 26.84 weeks in the placebo arm and 30.47 weeks in the Contrave arm; patients were to be enrolled on treatment for 3–4 years. The release of this information was not authorized by the trial executive steering committee or the independent data monitoring committee (IDMC) and violated the FDA confidentiality terms of agreement. When 50% of MACE events occurred, the cardiovascular benefit seen earlier was gone (HR 0.88, 95% CI 0.66–1.17). The trial steering committee halted the study, and the FDA required a second trial to be conducted (http://my.clevelandclinic.org/about-cleveland-clinic/newsroom/releases-videos-newsletters/2015-5-12-clinical-trial-testing-safety-of-obesity-drug-contrave-halted (accessed 17 May 2016)).
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.
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 | 0.419 | 0.696 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.025 | 0.031 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".