Optimism bias in the design of phase III randomized control trials (RCTs) evaluating PD-1/PD-L1 targeting monoclonal antibodies (mAbs).
Bibliographic record
Abstract
e18616 Background: PD-1/PD-L1 targeting monoclonal antibodies (mAbs) improve outcomes in multiple cancer types. Multiple mAbs are in clinical development, and many randomized control trials (RCTs) have been completed or are in progress. These RCTs compete for limited clinical trials infrastructure, human resources and patients. Since the hypothesized benefit of an intervention is a critical determinant of the number of patients required for an RCT, it is crucial that the expected benefit be estimated appropriately. We examined the hypothesized hazard ratio (HHR) and the observed hazard ratio (OHR) in RCTs evaluating PD-1/PD-L1 targeting mAbs. Methods: Publications of RCTs evaluating at least one PD-1/PD-L1 targeting mAbs approved by the US Food and Drug Administration were identified through PubMed searches. The primary publication for each RCT and its associated protocol were retrieved. Two investigators independently extracted HHR, OHR for the primary endpoint among other data elements. The differences (∆HR) in HHR and OHR were analyzed statistically. Updated OHRs (uOHR) were extracted from reports with extended follow-ups. Results: 49 RCTs enrolling 36867 patients were included. 45/49 RCTs were in the palliative setting. HHR was met or exceeded in 22 (45%) RCTs. The mean HHR and OHR were 0.672 and 0.738, respectively. The mean ∆HR was 0.067 (range: -0.300 to 0.895, 95% confidence interval = 0.003 – 0.130). A lower magnitude of effect than hypothesized in 12/29 RCTs in non-small cell lung cancer, melanoma and renal cell carcinoma, but in 15/20 RCTs in other cancer types. OHR was ≥ 1.0 in 6 RCTs (12%). In the palliative setting, ∆HR was larger in more heavily pre-treated patients. PD-L1 expression was not associated with magnitude of effect. However, a higher magnitude of effect was observed for RCTs published in the New England Journal of Medicine. For 18 RCTs with extended follow-ups, uOHR was higher than OHR in 8. Conclusions: The majority of published RCTs evaluating PD-1/PD-L1 targeting mAbs did not achieve their hypothesized magnitude of effect. Investigators’ optimism regarding these agents should be combined with more realistic expectations. The optimism bias requires attention from the cancer clinical research community given the number of these agents in development and the intense interest in evaluating these agents in various disease settings.
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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 | 0.438 | 0.945 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".