Plain Language Summary: Can Declines in Prostate-Specific Antigen Level Indicate How Long Patients with Advanced Prostate Cancer Will Live When Treated with Enzalutamide?
Bibliographic record
Abstract
WHAT IS THIS SUMMARY ABOUT?: . The PROSPER study involved men who had a type of advanced prostate cancer called non-metastatic castration-resistant prostate cancer (nmCRPC). In patients with nmCRPC, their prostate cancer keeps growing even after traditional hormone treatments. In these patients, rising prostate-specific antigen (PSA) levels suggest that cancer is active but CT and bone scans show that it has not spread to other parts of the body. Everyone in this study received androgen deprivation therapy (ADT) either with the medicine enzalutamide or a placebo. Enzalutamide is a medicine that can slow or stop androgens, such as testosterone, from making prostate cancer grow. The main results of the PROSPER study showed that patients with nmCRPC treated with enzalutamide and ADT lived longer than patients treated with placebo and ADT. In this study, researchers wanted to know if the findings were different depending on how much patients' PSA level declined after enzalutamide treatment. Researchers also wanted to know if this made a difference in how long patients lived without the cancer spreading to other parts of their body. WHAT WERE THE RESULTS?: Researchers found that patients with a large decline in PSA level after treatment were more likely to live longer and without their cancer spreading. WHAT DO THE RESULTS MEAN?: This study shows a link between PSA level changes and how long patients with nmCRPC live when treated with enzalutamide and ADT. These results may help health professionals monitor patients with different PSA level changes after enzalutamide treatment. Patients with a large decline in PSA level may not need to be monitored as closely as patients with a small decline in PSA level.
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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 | 0.007 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.099 | 0.053 |
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".