Survival of Testicular Pure Embryonal Carcinoma vs. Mixed Germ Cell Tumor Patients across All Stages
Bibliographic record
Abstract
Background and Objectives: The impact of pure histological subtypes in testicular non-seminoma germ cell tumors on survival, specifically regarding pure embryonal carcinoma, is not well established. Therefore, this study aimed to test for differences between pure embryonal carcinoma and mixed germ cell tumor patients within stages I, II and III in a large population-based database. Materials and Methods: We relied on the Surveillance, Epidemiology and End Results (SEER) database (2004–2019) to identify testicular pure embryonal carcinoma vs. mixed germ cell tumor patients. Cumulative incidence plots depicted cancer-specific mortality that represented the main endpoint of interest. Multivariable competing risks regression models tested for differences between pure embryonal carcinoma and mixed germ cell tumor patients in analyses addressing cancer-specific mortality and adjusted for other-cause mortality. Results: Of 11,223 patients, 2473 (22%) had pure embryonal carcinoma. Pure embryonal carcinoma patients exhibited lower cancer-specific mortality relative to their mixed germ cell tumor counterparts for both stage III (13.9 vs. 19.4%; p < 0.01) and stage II (0.5 vs. 3.4%, p < 0.01), but not in stage I (0.9 vs. 1.6%, p = 0.1). In multivariable competing risks regression models, pure embryonal carcinoma exhibited more favorable cancer-specific mortality than mixed germ cell tumor in stage III (hazard ratio 0.71, p = 0.01) and stage II (hazard ratio 0.11, p < 0.01). Conclusions: Pure embryonal carcinoma exhibits a more favorable cancer-specific mortality profile relative to mixed germ cell tumor in stage II and III testicular cancers. Consequently, the presence of mixed germ cell tumor elements may be interpreted as a risk factor for cancer-specific survival.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".