Enzalutamide with standard first-line therapy for metastatic hormone-sensitive prostate cancer: a plain language summary of the ENZAMET trial (ANZUP 1304)
Bibliographic record
Abstract
Plain Language SummaryWhat is this summary about?ENZAMET is a large international clinical trial involving people with metastatic hormone sensitive prostate cancer (mHSPC). Prior to the trial, standard treatment included testosterone suppression and sometimes, chemotherapy. However, the researchers thought enzalutamide, an anti-androgen (hormone) medicine, which helps to block the effects of testosterone, might be helpful if added to testosterone suppression.What are the key takeaways?ENZAMET showed that the addition of enzalutamide to standard testosterone suppression treatment for mHSPC improved survival, resulting in an increase in the percent of participants alive at 5 years from 57% to 67%. Enzalutamide extended the time until the cancer grew. Side effects were in keeping with what was already known about enzalutamide and these risks were outweighed by improved cancer control in the long-term.What are the main conclusions reported by the researchers?The combination of testosterone suppression plus enzalutamide is a very effective first-line treatment for mHSPC.This is an abstract of the Plain Language Summary of Publication article.View the full Plain Language Summary PDF of this article to read the full-text
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".