Impact of Testicular Germ Cell Tumor Laterality on Recurrence-Free Survival in the Mexican Population
Bibliographic record
Abstract
BACKGROUND: To date, the prognostic value of laterality for testicular germ cell tumors remains unknown. Herein, we describe this prognostic factor in the Mexican population. METHODS: A retrospective single-center study that included 37 patients with primary testicular germ cell tumors was conducted. Primary outcome was recurrence-free survival (RFS) at 2 years. Secondary outcomes were RFS by histology, progression-free survival by laterality, and 2-year overall survival. RESULTS: Thirty-seven patients were included, of which five showed relapses. By laterality, the 2-year RFS rate was 100% for left tumors and 77.3% for right tumors, with a trend toward statistical significance (P = 0.058). By histology, the RFS rate was higher for seminomas than non-seminomas (89% vs. 83%, respectively) without this difference being statistically significant. Progression-free survival was higher for right tumors than left tumors (91% vs. 80%, respectively) but without reaching statistical significance. The overall survival rate for the entire cohort was 94.5%. CONCLUSIONS: Our study shows that patients with primary germ cell tumors of the right testicle have a higher risk of recurrence than those with primary germ cell tumors of the left testicle, with a trend toward statistical significance.
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 | 0.000 | 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) | 0.002 | 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".