Adverse health outcomes in relationship to hypogonadism (HG) after platinum-based chemotherapy: A multicenter study of North American testicular cancer survivors (TCS).
Bibliographic record
Abstract
LBA10012 Background: HG affects a substantial percentage of TCS and can contribute to significant morbidity, but few studies have examined the relationship between HG and adverse health outcomes (AHO), taking into account genetic variation. Methods: Eligible TCS were < 55 y at diagnosis and treated with only first line chemotherapy after 1990. TCS underwent physical exams and genotyping, and completed questionnaires regarding 16 AHO and health behaviors. HG was defined as serum testosterone ≤ 3.0 ng/mL or the use of testosterone replacement therapy. Results: We evaluated 491 TCS. Median age at evaluation was 38 y (range 19-68). 38.5% had HG. Two SNPs in the sex-hormone-binding globulin ( SHBG) locus previously implicated in increased HG risk in the general population (Ohlsson et al, PLOS Genetics 2011) displayed effect sizes consistent with prior reports (rs6258, OR = 1.3; rs12150660, OR = 0.79), but were not statistically significant. However, TCS with ≥ 2 risk alleles for the two SNPs in the SHBG locus vs no risk alleles had 2-fold increased risk for HG (OR = 2.2, P = .12). Multivariate analysis identified risk factors for HG including: age (OR = 1.4 per 10 year increase, P = .007), and BMI ≥ 25 kg/m2 (OR = 2.2, P = .003). Vigorous-intensity physical activity appeared protective (OR = 0.6, P = .06). Type of chemotherapy regimen and socioeconomic factors did not correlate with HG. Only 35% of TCS with HG vs 49% of those without HG reported none or 1 AHO ( P = .003). TCS with HG were more likely to take medications for dyslipidemia (20% vs 6%, P < .001), hypertension (19% vs 11%, P = .01), erectile dysfunction (ED) (20% vs 12%, P = .02), diabetes (6% vs 3%, P = .07), or anxiety/depression (15% vs 10%, P = 0.06) compared to TCS with normal levels, and also to have peripheral neuropathy (PN) (31% vs 23%, P = .04). HG status did not correlate with oto- or renal toxicity. Conclusions: Over a third of TCS have HG at a relatively young age. HG was associated with increased cardiovascular disease risk factors, ED, and PN. SHBG polymorphisms appear important in TCS, but our study was underpowered to confirm an association. Providers should screen TCS for HG and treat those who are symptomatic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".