Androgen deprivation therapy for prostate cancer: not so simple
Bibliographic record
Abstract
P rostate cancer (PC) is the second most diagnosed visceral malignancy in men worldwide, with over 900 000 new diagnoses each year. 1 Approximately 50% of patients treated in industrialized nations will receive androgen deprivation therapy (ADT) at some point in their lifetimes.2 The use of ADT as a treatment approach is likely to increase as new drug developments have focused on intensifying the effect of reducing androgen receptor activation.While the benefits of ADT are well-recognized in select treatment groups, relatively little attention has been paid to its side effect profile until recently.Given the widespread use of ADT, detailed analyses of its potential harmful effects are critically important.Past research has shown that ADT can cause fatigue, loss of bone density, decreased sexual function and libido, as well as possible increases in diabetes and cardiovascular disease.3 Two new studies, by investigators from the University of Toronto add to our knowledge of the effects of ADT on physical and cognitive function in PC patients.They found that ADT had significant detrimental effects on both physical function and quality of life with a modest decrease in some areas of cognitive function.4,5 This study is the first prospective longitudinal study with a relatively large study population.They enrolled 87 patients with non-metastatic PC who were starting on ADT, and two matched control groups of 86 men each: one group with PC but not on ADT, and one group of healthy controls without a diagnosis of PC.They followed the groups for 1 year and measured multiple objective and subjective data points.Validated measures of future disability, mor-
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".