Sex- and Age-Related Differences in the Distribution of Metastases in Patients With Upper Urinary Tract Urothelial Carcinoma
Bibliographic record
Abstract
BACKGROUND: The distribution of metastatic sites in upper tract urothelial carcinoma (UTUC) is not well-known. Consequently, the effects of sex and age on the location of metastases is also unknown. This study sought to investigate age- and sex-related differences in the distribution of metastases in patients with UTUC. MATERIALS AND METHODS: Within the Nationwide Inpatient Sample database (2000-2015), we identified 1,340 patients with metastatic UTUC. Sites of metastasis were assessed according to age (≤63, 64-72, 73-79, and ≥80 years) and sex. Comparison was performed with trend and chi-square tests. RESULTS: Of 1,340 patients with metastatic UTUC, 790 (59.0%) were men (median age, 71 years) and 550 (41.0%) were women (median age, 74 years). The lung was the most common site of metastases in men and women (28.2% and 26.4%, respectively), followed by bone in men (22.3% vs 18.0% of women) and liver in women (24.4% vs 20.5% of men). Increasing age was associated with decreasing rates of brain metastasis in men (from 6.5% to 2.9%; P=.03) and women (from 5.9% to 0.7%; P=.01). Moreover, increasing age in women, but not in men, was associated with decreasing rates of lung (from 33.3% to 24.3%; P=.02), lymph node (from 28.9% to 15.8%; P=.01), and bone metastases (from 22.2% to 10.5%; P=.02). Finally, rates of metastases in multiple organs did not vary with age or sex (65.2% in men vs 66.5% in women). CONCLUSIONS: Lung, bone, and liver metastases are the most common metastatic sites in both sexes. However, the distribution of metastases varies according to sex and age. These observations apply to everyday clinical practice and may be used, for example, to advocate for universal bone imaging in patients with UTUC. Moreover, our findings may also be used for design considerations of randomized trials.
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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 | 0.003 |
| 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 | 0.000 | 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".