Factors associated with longitudinal progression of the cumulative burden of morbidity and overall mortality after cisplatin-based chemotherapy for testicular cancer
Bibliographic record
Abstract
BACKGROUND: To comprehensively evaluate the longitudinal progression of cumulative burden of morbidity (CBM) in testicular cancer survivors (TCS) following standard-dose cisplatin-based chemotherapy and the impact of modifiable risk factors on morbidity and early mortality. METHODS: Participants completed first-line chemotherapy at or longer than 6 months before baseline assessments with comprehensive questionnaires and physical examinations. Based on follow-up assessments (median: 7 years later), longitudinal progression of adverse health outcomes (AHOs) and CBM score (encompassing AHO number and severity) were examined. Baseline health behaviors and AHOs were evaluated for associations with mortality using mixed-effects parametric proportional-hazards regression to identify modifiable risk factors. RESULTS: Among 616 TCS longitudinally assessed, 23% experienced worsening CBM postchemotherapy (median = 11 years, interquartile range = 7-15). Declines were driven by worsening treatment-related AHOs: tinnitus (29.7%), hearing loss (24.4%), Raynaud's disease (22.6%), neuropathy (18.5%), and neuropathic pain (10.7%). Baseline factors associated with worsening neuropathy included lack of aerobic physical activity (odds ratio [OR] = 1.98, 95% confidence interval [CI] = 1.06 to 3.72), and obesity (OR = 1.85, 95% CI = 1.17 to 2.92). These were also related to worsening neuropathic pain (OR = 2.82, P = .009 and OR = 2.29, P = .023). Twenty-nine deaths occurred among 1830 5-year TCS (4.2% cumulative hazard) (median age = 48 years, range = 22-74). Participants reporting neuropathic pain (hazard ratio [HR] = 3.64, 95% CI = 1.45 to 9.10), no aerobic (HR = 6.56, 95% CI = 2.73 to 15.8), or no low-impact physical activity (HR = 3.96, 95% CI = 1.40 to 11.2) had significantly higher mortality, as did TCS indicating fair (HR = 9.23, 95% CI = 3.08 to 27.8) or poor (HR = 18.5, 95% CI = 3.30 to 103) health. Relationships between pain and mortality were mediated through lowered physical activity (P = .036). CONCLUSIONS: Clinically actionable factors associated with early mortality identify high-risk TCS in need of closer monitoring and targeted interventions. The significant relationship between neuropathic pain and mortality, mediated by low physical activity, is the first to our knowledge in TCS.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".