Long-term side effects of testicular cancer and treatment (observational study of mortality and morbidity in testicular cancer survivors)
Bibliographic record
Abstract
PURPOSE: Testicular cancer (TC) is a rare cancer, but due to early age at diagnosis and excellent cure rates, there is a large cohort of survivors. Recent studies have highlighted the late side effects of treatments of TC, especially cisplatin-based chemotherapy. These complications make the survivorship care challenging with detrimental effects on health and prognosis of TC survivors (TCS). In this study, we provide a snapshot of common late side effects in TCS and a possible care pathway with a nurse-led specialised clinic. METHODS: We invited TCS to participate in the study at one of the cancer centres in Ireland for a comprehensive screening using questionnaires, examination and blood tests. Further investigations were performed as indicated. Mortality was assessed through retrospective chart reviews. RESULTS: We recruited 78 TCS to participate in the study with a median of 129 months since diagnosis (range 60 to 304 months) and 3 who died in survivorship. Second malignant neoplasms accounted for all three mortalities. Most common conditions after 5 years of diagnosis were hypertension (40%), dyslipidaemia (55.6%), hypogonadism (~ 45%), and high BMI (52%). The majority of conditions were diagnosed during screening, including two cases of coronary artery disease and one case of transient ischaemic attacks. TCS who received chemotherapy and were aged more than 30 years at the time of diagnosis had a higher prevalence of the late side effects. CONCLUSIONS: TC survivorship phase is marred by a range of late side effects. This remains a challenge for patients and healthcare workers as ambiguity surrounds the care pathways in the survivorship setting. We hope this nurse-led, specialised, screening clinic might improve the care and service provision for TC survivors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".