Incidence of periprostatic white adipose tissue inflammation in men with prostate cancer.
Bibliographic record
Abstract
63 Background: Obesity, a common cause of chronic inflammation, is associated with an increased risk of high grade, lethal prostate cancer (PC) and poor outcomes. The existence or clinical importance of periprostatic white adipose tissue inflammation (WATi) in patients (pts) with PC has not been previously described. We examined the relationships among periprostatic WATi and 1) tumor clinicopathologic features, and 2) host factors including age, body mass index (BMI), and circulating metabolic factors. Methods: Periprostatic WAT was collected prospectively from men with PC undergoing radical prostatectomy. WATi was defined by the presence of dead/dying adipocytes surrounded by macrophages forming crown-like structures (CLS). Tumor characteristics and host factors were measured. Wilcoxon rank-sum, Chi-square, or Fisher’s exact tests were used to examine the relationship between WATi and tumor and host characteristics. Results: From 11/2011-8/2015, periprostatic WAT was obtained from 169 pts (median age 62 years, range: 39 -77). Fasting blood samples were collected from 154 pts. CLS were present in 84 (49.7%) of pts. Presence of CLS was associated with higher median BMI (P = 0.02); 40/65 (61.5%) obese pts, 36/83 (43.4 %) overweight pts, and 8/21 (38.1 %) normal weight pts had CLS. Pts with CLS were more likely to have high grade prostate cancer (Gleason grade group IV/V, P = 0.02), larger adipocytes (P = 0.004), and positive surgical margins at the time of surgery (P = 0.04). WATi correlated with higher circulating levels of insulin, triglycerides, and leptin/adiponectin ratio, and lower high density lipoprotein cholesterol, compared to pts without WATi (P’s < 0.05). Conclusions: Periprostatic WATi is common in men with PC. It is associated with high grade PC and alterations in systemic factors that contribute to PC development and progression. Periprostatic WATi may represent a therapeutic target for improving PC risk and outcomes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".