Assessment of circulating tumor cell number as a transitional surrogate endpoint for survival in phase II trials for metastatic castration-resistant prostate cancer.
Bibliographic record
Abstract
143 Background: Short-term measures of response that reflect clinical benefit are a critical unmet need for clinical trials for mCRPC. Using data from 5 randomized mCRPC trials, we showed that a response endpoint (RE) based on a change in CTC number using the FDA cleared CellSearch® (Menarini) platform from any, (≥ 1, CTC any) to 0 (CTC0) per 7.5 ml of blood was associated strongly with overall survival (OS). Here we explored whether different CTC and PSA REs could serve as “transitional surrogates” defined as a biomarker validated in phase 2 but not in phase 3 trials for overall survival (OS), using the baseline and week 13 prostate-specific antigen (PSA) level and CTC counts. Methods: Four 13-week REs were studied: (i) PSA50 (≥ 50% PSA decline from baseline), (ii) CTC0 (≥ 1 CTC/7.5 ml of blood at baseline and 0 CTCs at week 13), (iii) both PSA50 and CTC0, and (iv) either PSA50 or CTC0. The relative effectiveness of these REs as transitional surrogates for OS was evaluated at the patient level by discrimination, the separation between responder and non-responder survival curves, and at the trial level using explained variation, the accuracy in predicting k-month survival in a trial with the response proportion. Results: A total of 6081 pts were enrolled of whom 5660 (93%) survived until week 13 and among these patients 3080 (54%) had a baseline CTC count ≥ 1 and baseline PSA ≥ 5 ng/ml. At the patient level, separation between responder and non-responder survival curves over time was greater using CTC0 than PSA50 (average difference in survival probability 0.35 vs. 0.29, respectively). At the trial level, explained variation in survival over time was also greater for CTC0 than PSA50 (average R-squared 0.67 vs. 0.58, respectively). CTC/PSA combination REs did not improve on CTC0 at either level. Conclusions: The CTC0 RE provides stronger discrimination than PSA50 at the patient level and greater observed explained variation at the trial level. The results suggest that for the individual patient, a decrease in CTCs to zero at week 13 is a stronger indicator of longer term OS than the more widely used PSA50 and serves as a reasonably likely surrogate for OS in clinical trials.
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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 | 0.021 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".