Randomised controlled trials evaluating anticancer therapies in haematological cancers: an overview of global research activity
Bibliographic record
Abstract
Background: Design, results, and interpretation of oncology randomised controlled trials (RCTs) have changed substantially over the past decade. In this study, we describe all RCTs evaluating anticancer therapies in haematological cancers published globally during 2014-2017 with comparisons with solid tumours RCTs. Methods: A PubMed literature search identified all phase 3 RCTs of anticancer therapy for haematological cancers and solid tumours published globally during 2014-2017. Descriptive statistics, chi-square tests and the Kruskal-Wallis test were used to compare RCT design results, and output between haematological cancers and solid tumours as well as for different haematological cancer subtypes. Results: < 0.001). Seventy-eight percent of haematologic trials were funded by industry as compared to 70% of solid tumour trials. Only 4% (5/124) of haematologicalcancer trials were led by investigators in upper-middle and lower-middle-income countries as compared to the 9% of solid tumour trials. Conclusion: The fact that only 12% of haematological cancer RCTs are designed to show improvements in OS is of grave concern for the field and the care of future patients. This is further compounded by the highly prevalent use of alternative primary endpoints that are rarely valid surrogates for OS in haematological cancers.
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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 | 0.670 | 0.478 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.001 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads 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".