Utility of annual screening serum testosterone level in men on surveillance for clinical stage I testicular cancer.
Bibliographic record
Abstract
144 Background: Testicular cancer occurs in young men and is usually cured leaving survivors with many life years at risk from long term treatment effects. Risks increase with treatment intensity and include cardiovascular disease associated with the metabolic syndrome (Haugnes 2012, de Haas 2013). Testosterone deficiency (TD) is associated with metabolic syndrome & reduced QoL (Huddart 2005). Serum testosterone levels (STLs) are also influenced by underlying testicular dysgenesis & the effects of ageing (Skakkebaek 2001, Oldenburg 2016). We added annual screening STL to our surveillance protocols in 2013 & reviewed the value of this practice. Methods: Men followed in our Testicular Surveillance Clinic from 01 Jan 2006 to 31 Dec 2015 were identified electronically & data extracted retrospectively. Men eligible for this analysis had clinical stage I (CS I) testicular cancer treated with unilateral orchiectomy alone. Outcomes of interest were STLs, Endocrinology referral (Endo) & treatment with androgen replacement therapy (ART). TD was defined by 3 cutoffs of most recent screening STL: < 8.6 nmol/L [age 20-49] (or < 6.7 nmol/L [age > 50]) (local laboratory), < 10.1 nmol/L (Huddart 2005), or < 12.1 nmol/L (EAA & EAU). Results: 77 eligible men were identified: median age 34 years (range, 15-65), seminoma/nonseminoma/mixed/other (45/27/4/1). By the 3 STL cutoffs, TD was present in 13 (16.9% [95%CI, 9.3-27.1%), 22 (28.6% [18.8-40.0%] & 37 (48.1% [36.5-59.7%]); respectively. Nine men (11.4%) were referred to Endo, 1 had morning STL pending & 1 was using OTC ART. Of 8 men assessed by Endo, 5 (6.5%) were prescribed ART. Six men had no screening STL done (3 nonadherent, 1 prostate cancer & 2 unknown). Two men were discharged from clinic with unequivocal low STL. Conclusions: Annual screening STL appears to be useful and may be necessary. 15 CS I men (19.5%) in our clinic had unequivocal TD &/or were referred to an Endo. An additional 20 men (26%) had STLs in a range associated with reduced QoL. Almost half had STLs considered suitable for ART in the presence of symptoms. Two men (2.6%) were discharged with low STLs unaddressed. Guidelines for the optimal assessment and management of men with positive screening for TD are needed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".