A comparison of the sarcopenic effect of androgen receptor-axis-targeted agents vs. androgen deprivation alone in patients with metastatic prostate cancer
Bibliographic record
Abstract
INTRODUCTION: Androgen deprivation therapy (ADT) with androgen receptor axis-targeted (ARAT) therapy is the standard of care provided to patients with metastatic prostate cancer. While effective, it results in sequelae, such as loss of skeletal muscle mass. In this study, we compared the sarcopenic effects of abiraterone and enzalutamide, two ARATs used to treat metastatic prostate cancer. METHODS: Our cohort was comprised of 55 patients diagnosed with metastatic hormonenaive prostate cancer from 2014-2019. Patients were divided into three treatment groups: gonadotropin-releasing hormone (GnRH ) agonist alone; GnRH agonist combined with abiraterone acetate; and GnRH agonist combined with enzalutamide. We then compared axial computed tomographic (CT) scans at the L3 level before and after the initiation of hormone therapy for each patient. A skeletal muscle index (SMI) was calculated for each patient, and alongside clinical data, was compared between the three groups. One-way analysis of variance (ANOVA) and Fisher's exact test were used to compare means and proportions, respectively. RESULTS: Baseline clinical characteristics were not significantly different between the three groups. The percent SMI change and number of newly sarcopenic patients were not found to be significantly different between the groups. The only variable that was significantly different across the three groups was time between CT scans. CONCLUSIONS: Although we found no significant difference in the sarcopenic effects of GnRH alone, GnRH with abiraterone, or GnRH with enzalutamide in our cohort of 55 hormone-naive metastatic prostate cancer patients, overall decreases in muscle mass were observed for all three groups. This highlights the importance of muscle-retaining strategies for patients undergoing ADT for metastatic prostate cancer, regardless of therapeutic regimen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".