Temporal trends in management and outcomes of testicular cancer: A population‐based study
Bibliographic record
Abstract
BACKGROUND: Treatment guidelines for early-stage testicular cancer have increasingly recommended de-escalation of therapy with surveillance strategies. This study was designed to describe temporal trends in routine clinical practice and to determine whether de-escalation of therapy is associated with inferior survival in the general population. METHODS: The Ontario Cancer Registry was linked to electronic records of treatment to identify all patients diagnosed with testicular cancer treated with orchiectomy in Ontario during 2000-2010. Treatment after orchiectomy was classified as radiotherapy (RT), retroperitoneal lymph node dissection (RPLND), chemotherapy, or none. Surveillance was defined as no identified treatment within 90 days of orchiectomy. Overall survival (OS) and cancer-specific survival (CSS) were measured from the date of orchiectomy. RESULTS: The study population included 1564 and 1086 cases of seminomas and nonseminoma germ cell tumors (NSGCTs), respectively. Among patients with seminomas, there was a significant increase in the proportion of patients with no treatment within 90 days of orchiectomy (from 56% to 84%; P < .001); the use of RT decreased over time (from 38% to 8%; P < .001); and the use of chemotherapy remained stable (from 6% to 9%; P = .289). Practice patterns 90 days after orchiectomy remained stable over time among patients with NSGCTs: from 51% to 57% for no treatment (P = .435), from 43% to 43% for chemotherapy (P = .336), and from 9% to 3% for RPLND (P = .476). The OS rates for the entire cohort at 5 and 10 years were 97% and 96%, respectively; the CSS rates were 98% and 98%, respectively. There was no significant change in OS or CSS for patients with seminomas or NSGCTs during the study period. CONCLUSIONS: There has been substantial de-escalation in the treatment of testicular cancer in routine practice since 2000. Long-term survival in routine practice is excellent and has not decreased with the uptake of surveillance strategies. Cancer 2018;124:2724-2732. © 2018 American Cancer Society.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".