Methodology, results, and publication of oncology clinical trials: Insights from all the world’s randomized controlled trials (RCTs) 2014-2017.
Bibliographic record
Abstract
2019 Background: Clinical cancer research is now a global effort. Most published overviews of oncology trials are restricted to a specific disease site or cohort of high-profile journals. Here we describe authorship, trial characteristics, design, and results of all oncology RCTs published globally during 2014-2017. Methods: A structured literature search was designed using PUBMED to identify all RCTs evaluating anti-cancer therapies published during 2014-2017. Data were captured regarding authorship, participants, study characteristics, design, and results. Among superiority RCTs that met the primary endpoint (i.e. statistically “positive”), we calculated the ESMO-MCBS to identify trials with substantial clinical benefit (MCBS scores 4/5 or A/B). Outcomes were compared with Chi Square or Fisher’s Exact tests. Results: The study cohort included 694 RCTs. The most common cancers evaluated were breast (17%, 121/694), lung (15%, 104/694) and colorectal (8%, 58/694). Treatment intent was curative, adjuvant/neoadjuvant, and palliative in 10% (68/694), 25% (176/694), and 65% (448/694) of trials respectively. Median sample size was 443 (IQR 246-718). Seventy percent (488/694) of RCTs were supported by industry; 87% (601/694) of experimental arms tested systemic therapy. Ninety-two percent (636/694) of RCTs were led by investigators in 28 high-income countries; the most common countries leading these trials were US (27%, 174/636), France (10%, 64/636), Germany (10%, 62/636), Japan (9%, 59/636), and UK (9%, 57/636). The most common primary endpoints were PFS (32%, 220/694), OS (31%, 215/694), and DFS (11%, 79/694); Forty-six percent of all trials (318/694) met their primary endpoint. Among superiority trials with “positive” results, 33% met ESMO-MCBS threshold for substantial clinical benefit. The median impact factor (IF) of journals which published the overall study cohort of trials was 21 (IQR 7-27); trials meeting their primary endpoint were published in higher profile journals (median IF 25 vs 18, p < 0.001). Conclusions: At the global level, oncology clinical trials are dominated by high-income countries and study diseases which do not necessarily reflect the global burden of cancer. The vast majority of trials are funded by industry and only one third of “positive” trials meet ESMO-MCBS threshold for substantial clinical benefit.
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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 | 0.495 | 0.730 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".