Utilization of mental health services among survivors of testicular cancer: A population-based study.
Bibliographic record
Abstract
e16062 Background: Testicular cancer survivors may experience long-term psychological distress related to their diagnosis and treatment. Measurement of mental health service use (MHS) is an objective way to quantify the incurred burden of psychological distress. Here we describe patterns of MHS use among survivors of testicular cancer in a single-payer health system. Methods: The Ontario Cancer Registry was linked to electronic treatment records to identify all incident cases of testicular cancer treated with orchiectomy in the Canadian province of Ontario during 2004-2010. Mental health clinical visits were identified from records of hospital admission, emergency room visits and out-patient physician billing records. Results: The study cohort included 1877 patients; mean age was 35 and 61% had pure seminoma. Two thirds of patients (66%, 1230/1877) were initially treated with active surveillance. In the 2-year period prior to orchiectomy, 24% (443/1877) of patients had MHS use. Post-orchiectomy, the prevalence of MHS use was 18% (331/1877), 23% (431/1877) and 30% (572/1877) at 6, 12 and 24 months, respectively. The use of MHS was greatest in the peri-diagnostic/surgical period. Rates of MHS visits, 3 months before, 0-3 months after, 4-6 months after and 2 years after orchiectomy were 11%, 14%, 10%, and 6%, respectively. Post-orchiectomy MHS use was greatest among those with baseline MHS use. The prevalence of MHS use for patients with and without baseline MHS use was 40% (175/443) vs 11% (156/1434, p < 0.001) at 6 months; 51% (225/443) vs 14% (206/1434, p < 0.001) at 12 months; and 61% (271/443) vs 21% (301/1434, p < 0.001) at 24 months post-orchiectomy. Post-orchiectomy MHS use did not vary by initial treatment strategy (active surveillance vs upfront treatment, p = 0.435). Older patients were more likely to have MHS visits at all time periods than younger patients; MHS rates at 6 months were 15% (93/631) vs 18% (112/625) vs 20% (126/621) for ages 16-29, 30-39, and 40+ years respectively (p = 0.035). Conclusions: MHS use among survivors of testicular cancer is common, particularly in the peri-diagnostic and surgical period. The rate of MHS use is highest among those patients with a history of prior MHS use. Clinicians should screen for the presence of psychological distress among survivors of testicular cancer.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".