Excellent outcomes in bilateral testicular germ cell tumors over four decades.
Bibliographic record
Abstract
523 Background: Bilateral testicular germ cell tumours (BTC) form a small minority of testicular cancer and detailed management data are sparse. Methods: Bilateral testicular cancer (BTC) patients managed at a single cancer centre were retrospectively analyzed. Synchronous BTC was defined as uni+contralateral presentation within 3 months. Patient characteristics, treatment and outcomes were collected. Kaplan-Meier method was used to calculate the overall survival (OS) and relapse-free survival (RFS). Results: Between Jan 1971 to Jun 2018, 118 pts were included. Nine patients (7.6%) had cryptorchidism. Twenty-two patients (18.6%) had synchronous BTC at median age of 30(21-54) years, 11 presented with concordant histology (10-seminoma). Median follow-up time was 96(1-220) months. Two of 14 patients (14%) with stage I disease on surveillance had retroperitoneal nodal recurrence, other 3 (21%) had testicular recurrence after partial orchiectomy alone. No recurrence occurred for 8 stage II/III patients (36%) who received stage-appropriate treatment. All patients were alive without disease at last follow-up. For metachronous BTC, the median age was 27(16-68) and 37(19-78) years for first and second diagnosis, respectively. The median time interval was 88 (8-352) months, with shorter interval when second primary was non-seminoma, median 69 vs. 92 months. Concordant histology was present in 58 (38-seminoma) patients and discordant in 38 patients. There were 66, 23, 7 and 84, 9, 3 patients with stage I, II, III disease for first and second testicular cancer (TC), respectively. For all stage I disease, 69% of non-seminoma (n = 33) and 79% of seminoma (n = 81) were on surveillance, of whom the crude relapse rate was 15%. The median follow-up time after second diagnosis was 87 months. In all, 35 patients (30%) with recurrence except 1 were successfully salvaged. The 10-year OS and RFS for whole cohort was 99% and 69.8%, respectively. Conclusions: In our series, seminoma was the more common pathology, and management based on pathology and stage yielded excellent outcomes regardless of prior therapy. Metachronous BTC may occur at extremely long time intervals such that longer follow-up is needed to capture the majority of contralateral primary TC.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".