Treatment Options, Prognostic Factors and Selection of Treatment in Stage I Seminoma
Bibliographic record
Abstract
Treatment options in patients with stage I seminoma include radiotherapy (RT), surveillance, and adjuvant chemotherapy. This patient population has virtually a 100% cure rate whichever approach is taken. While adjuvant retroperitoneal RT has been the standard of care for the past 50-60 years, there is increasingly persuasive data that adjuvant RT in this setting is associated with a small but definite increased risk of second malignancy and cardiovascular death. The long-term data from surveillance series have documented the safety of this approach, and it is now accepted that a policy of surveillance is the optimal management approach. This gives a relapse rate of 15%, and most patients can be successfully salvaged with RT. Second relapse after salvage RT occurs in a small proportion of cases, and these patients are cured with chemotherapy. Adjuvant chemotherapy using carboplatin has been investigated as an alternative strategy but has not lived up to its initial promise. If used, then 2 courses of treatment should probably be given. It must be remembered that 80-85% of patients with testicular seminoma require no treatment after orchiectomy, and the long-term side effects of any adjuvant treatment approach must be carefully considered.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".