O-263 Sperm parameters in cancer patients: the role of cancer and cancer diagnoses
Bibliographic record
Abstract
Abstract Study question How do sperm parameters compare in various oncologic conditions when compared with controls? Is there an association between severity of the disease and sperm parameters? Summary answer Most cancer types appear to affect sperm parameters. Motility is reduced in all cancers, while sperm concentration is strongly diminished in testicular cancer. What is known already There is no actual consensus whether cancer is negatively associated with semen quality. Some studies have reported poorer sperm parameters in men with cancer, especially testicular cancer. Others have reported no differences in semen parameters of cancer patients when compared with patients with benign diseases. Furthermore, small studies have shown conflicting differences in sperm parameters when comparing across different cancer types. Study design, size, duration Academic single-centered, retrospective cohort study with men banking sperm for fertility preservation prior to undergoing chemotherapy. A total 965 patients with various cancer types, recently diagnosed, produced at least one sample for sperm cryopreservation between 2004 and 2020. Concentration and progressive motility were analyzed for each sample at the time of cryopreservation, before beginning the chemotherapy treatments. Participants/materials, setting, methods The first sample of each patient was kept for data analysis (n = 965). The control group were unselected homosexual male couples planning parenthood, without any known fertility impairment (n = 39). Cancers were grouped as: testis (n = 297), lymphoma (n = 285), leukemia (n = 79), sarcoma (n = 85), brain (n = 61), gastro-intestinal (GI) (n = 73), ear-nose-throat (ENT) (n = 24), and other (n = 52). The last group included cancers of such as kidney, prostate, melanoma, or lung cancer. T-test and Fisher-test were used for statistical analyses. Main results and the role of chance Patients with testicular cancer had significantly lower mean sperm concentration when compared to controls (30.5 vs 69.9 M/ml; p < 0.01). Other groups showed similar concentration values when compared to controls. Furthermore 47% testicular cancer patients had oligospermia (as determined by WHO criteria) compared with 10% unselected controls (p < 0.001) However, sperm from patients with almost all types of cancer showed lower motility rates when compared to controls (31.5 to 35.0% vs 49.0%; p < 0.001). The only group showing similar motility with controls was ENT cancers (41.1% vs 49%, p = 0.2). Similarly, sperm samples from all cancer groups showed higher proportions with asthenospermia (as determined by WHO criteria) when compared with controls (39.1%-54.7% vs 18%, p < 0.01) For individual cancer groups, comparing sperm parameters between patients who survived and those who died, there were no significant differences, suggesting the severity or stage does not modulate the effect of the cancer itself on the sperm. Patients in the testis, lymphoma, leukemia, sarcoma and brain cancer groups were significantly younger than controls (25.3-29.1 vs 37.3 years old), while GI and ENT groups were similar to controls (37.4 and 36.5 vs 37.3). In the “other cancers” group, patients were significantly older than controls (44.4 vs 37.3). Limitations, reasons for caution The interpretation of the findings of this study is limited by the retrospective nature of the analysis and the potential for unmeasured confounding variables. Wider implications of the findings There is an association between abnormal sperm parameters in samples for pre-chemotherapy cryopreservation and all cancer types. This may affect the future likelihood of pregnancy. Young men with cancer need to be counselled that ICSI may be recommended should they need or choose to use their cryopreserved sperm. Trial registration number Not applicable
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".