Serum testosterone changes in patients treated with radiation therapy alone for prostate cancer on NRG oncology RTOG 9408
Bibliographic record
Abstract
Objectives We reviewed testosterone changes for patients who were treated with radiation therapy (RT) alone on NRG oncology RTOG 9408. Methods and materials Patients (T1b-T2b, prostate-specific antigen <20 ng/mL) were randomized between RT alone and RT plus 4 months of androgen ablation. Serum testosterone (ST) levels were investigated at enrollment, RT completion, and the first follow-up 3 months after RT. The Wilcoxon signed rank test was used to compare pre- and post-treatment ST levels in patients who were randomized to the RT-alone arm. Results Of 2028 patients enrolled, 992 patients were randomized to receive RT alone and 917 (92.4%) had baseline ST values available and completed RT. Of these 917 patients, immediate and 3-month post-RT testosterone levels were available for 447 and 373 patients, respectively. Excluding 2 patients who received hormonal therapy off protocol after RT, 447 and 371 patients, respectively, were analyzed. For all patients, the median change in ST values at completion of RT and at 3-month follow-up were −30.0 ng/dL (p5-p95; −270.0 to 162.0; P < .001) and −34.0 ng/dL (p5-p95, −228.0 to 160.0; P < .01), respectively. Conclusion RT for prostate cancer was associated with a median 9.2% decline in ST at completion of RT and a median 9.3% decline 3 months after RT. These changes were statistically significant.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".