Small Incidentally Discovered Testicular Masses in Infertile Men—Is Active Surveillance the New Standard of Care?
Bibliographic record
Abstract
PURPOSE: The management of small, incidental testicular masses found on scrotal ultrasound is controversial. Although these neoplasms are classically treated with surgical excision, ultrasound surveillance has been proposed as an alternative to surgery. MATERIALS AND METHODS: We reviewed our experience of ultrasound surveillance for small testicular masses at Mount Sinai Hospital Fertility Clinic from 2001 to 2008, offered to all patients with subcentimeter, incidentally discovered hypoechoic testicular lesions. Patient age, semen parameters, the size and growth of the lesion on serial ultrasounds, need for surgery and pathological diagnosis were collected in a database. RESULTS: Of 4,418 patients evaluated 46 (1%) met the study inclusion criteria. Mean age was 35 years, and 39 patients (85%) presented with infertility. Semen analysis revealed azoospermia, oligospermia and normospermia in 15, 18 and 7 patients, respectively, and was unavailable in 6. Mean ultrasound followup was 253 days and mean number of ultrasounds was 2.8. Mean lesion diameter was 4.3 mm (range 1 to 10). There were 38 patients with serial ultrasound followup only with a mean growth of 0.5 mm per year (95% CI -2.2-3.3). Three patients underwent immediate surgery and 5 underwent surgery following a period of ultrasound followup. Indications for surgery were interval growth in 2 patients and patient choice in 6. Larger size (p = 0.02) and presence of vascular flow (p <0.01) were associated with intervention. One patient underwent radical orchiectomy for pure seminoma identified due to interval growth from 3 to 6 mm at 3 months. The other 7 masses excised with partial orchiectomy were benign. CONCLUSIONS: Ultrasound surveillance of small (less than 1 cm) incidental testicular masses is a safe alternative to immediate surgical removal.
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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 | 0.001 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".