Effect of Malignancy on Semen Parameters
Bibliographic record
Abstract
Purpose: We aimed to examine how various types of cancer, classified histologically, affect semen quality. Methods: The study group included 313 patients who were diagnosed with cancer and reached for a sperm cryopreservation before a gonadotoxic treatment (PG-Tx group). Their semen parameters were compared to those of two control groups: (a) individuals who attended a fertility investigation and were found to be above the limit of the lower reference value of the WHO 2010 manual (ARL group), and (b) fertile men, whose semen parameters were obtained from the dataset of the WHO 2020 manual. Results: Semen quality was significantly poorer in the PG-Tx group than in the ARL group. Differences included a 65.6% decrease in concentration, a 12.1% decrease in volume, a 72.7% decrease in total count, and a 33.0%, 22.2%, and 24.7% decrease in total motility, rapid motility, and progressive motility, respectively. Linear regression models comparing the PG-Tx and ARL groups revealed that the maximum reduction in total motility and concentration was in men with germ-cell tumors, whereas the minimum reduction was in hematological tumors. Similarly, all sperm quality parameters were significantly lower in the PG-Tx group than in the fertile-men group (p < 0.0001). Conclusions: While the effect of malignancy on semen parameters is debatable, we found that all examined types of cancer significantly impaired sperm quality parameters. Although the median of most semen parameters of patients with cancer were still in the normal WHO range, their fifth percentile, represents men with a delayed time to pregnancy.
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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".