Metabolic syndrome (MetS) after platinum-based chemotherapy (CHEM): A multicenter study of North American testicular cancer survivors (TCS).
Bibliographic record
Abstract
102 Background: Testicular cancer has an excellent prognosis since the introduction of platinum-based CHEM. However, several European studies report an excess of cardiovascular disease (CVD) in TCS. MetS is a cluster of cardiovascular risk factors that doubles CVD risk, with several European series noting a prevalence ranging from 13-39% in TCS. In the first large multi-center North American study of TCS, we examine the prevalence of and potential risk factors for MetS after modern CHEM (NCI R01 CA157823). Methods: Eligible TCS were <50 y at diagnosis and treated with only first line CHEM after 1990. TCS underwent physical exams, completed questionnaires regarding co-morbidities and health behaviors and had lipid panels, testosterone, and serum soluble cell adhesion molecule-1 (sICAM-1) measured. A single nucleotide polymorphism, rs523349 (V89L), in 5-α-reductase gene ( SRD5A2) previously suggested to associate with MetS in TCS was genotyped. MetS was defined as ≥3 of the following: hypertension (HTN), waist circumference ≥102 cm, triglycerides ≥150 mg/dL, HDL ≤40 mg/dL, and diabetes (Alberti et al, Circulation 2009). Controls (1:1) derived from the National Health and Nutrition Examination Survey were matched on age, race, and educational status. Results: We evaluated 486 consecutively enrolled TCS. Median age at evaluation was 38 y (range: 19-68). TCS had higher prevalence of HTN compared to controls (43% vs 31%, P < .01) but lower prevalence of low HDL (24% vs 35%, P < .01) and abdominal obesity (28% vs 40%, P < .01). Prevalence of MetS was comparable (21% TCS; 22% controls, P = .59). In multivariate analysis, age at evaluation (P < .01), serum testosterone <3.0 ng/mL (OR = 2.0, P = .005), and elevated sICAM-1 (OR for quartiles 2, 3, 4 vs lowest quartile: 2.7 (P = .01), 3.1 (P < .01), and 3.6 (P < .01), respectively) significantly correlated with MetS. The variant rs523349 (VL/LL) did not associate with MetS. Conclusions: One in 5 TCS treated with CHEM developed MetS. Providers should screen for MetS, adequately treat hypogonadism, HTN and hyperlipidemia, and encourage TCS to maintain a healthy lifestyle. Significant elevations in sICAM-1 underscore a role for inflammation in MetS.
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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 | 0.000 | 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 | 0.000 |
| 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".