Changes in blood glucose and cholesterol levels due to androgen deprivation therapy in men with non-metastatic prostate cancer
Bibliographic record
Abstract
OBJECTIVE: To investigate the effects of androgen deprivation therapy (ADT) on blood glucose and cholesterol over 12 months in a prospective matched cohort study. METHODS: English-speaking patients with non-metastatic prostate cancer attending the Princess Margaret Hospital were invited to participate in this study. Patients were divided into two cohorts: ADT users and controls. Androgen deprivation therapy users were frequency matched to controls on age, education and body mass index (BMI). The study consisted of two visits. Sociodemographic and clinical information, medication use, physical fitness, height and weight were collected before initiation of ADT. Twelve months later, fasting morning blood work was obtained to measure plasma glucose, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL) and triglycerides. Statistical analyses included univariate and multivariable linear regression. RESULTS: We recruited 75 patients (mean age 68.9), 38 of whom were undergoing ADT. Twelve patients with prior diabetes and 29 patients taking cholesterol-lowering medication at baseline were excluded from the glucose and cholesterol analysis, respectively. In adjusted analyses, ADT users had a significantly higher glucose level compared to controls (5.88 vs. 5.52 mmol/L, p = 0.024). Overall, ADT users had higher levels of total cholesterol, HDL, LDL, and triglycerides than controls, although none of the differences reached statistical significance. CONCLUSION: One year of ADT use is associated with elevated fasting glucose levels and may increase all lipid fractions in men with prostate cancer.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".