Evidence‐based guidelines for following stage 1 seminoma
Bibliographic record
Abstract
BACKGROUND: The authors developed evidence-based guidelines for a follow-up schedule after orchiectomy for stage 1 seminoma. Required investigations, frequency of assessment, overall duration of follow-up, and management strategies were identified. METHODS: A systematic review of the literature was performed of prospective studies in stage 1 seminoma. Studies published after 1980 were considered eligible for inclusion. Data extracted included relapse-free rates, number of patients at risk, and relapse locations. Five strategies were identified: Surveillance, Extended-Field Radiotherapy, Para-aortic Radiotherapy, and either 1 or 2 cycles of Carboplatin Chemotherapy. For each strategy, Kaplan-Meier relapse-free estimates were used to calculate weighted-mean cumulative hazards of relapse over time. These were used to calculate semiannual weighted-mean relapse hazards. RESULTS: Seventeen prospective studies with a total of 5561 patients were identified. Actuarial data on relapse was available in 5013 (90.1%) patients, and 92.9% of all relapses had location data reported. Annual hazard rates for relapse were determined. CONCLUSIONS: Evidence-based recommendations for follow-up frequency based on risk of relapse were formulated. The authors suggested 3 times per year when the risk is >5%, 2 times per year when the risk is 1% to 5%, and annually until the risk is <0.3%. Investigations should reflect location(s) at risk of relapse and include computed tomography of the abdomen and pelvis for surveillance and adjuvant carboplatin, whereas for para-aortic radiotherapy, pelvic computed tomography alone is required. These recommendations offer the possibility of maximal patient convenience and optimal healthcare resource allocation without compromising disease control.
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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 | 0.026 | 0.091 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.017 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.010 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".