Systematic Review of the Gonadotoxicity and Risk of Infertility of Soft Tissue Sarcoma Chemotherapies in Pre- and Postpubertal Females and Males
Bibliographic record
Abstract
Increasing awareness of gonadotoxicity in cancer treatments and infertility risk is essential for counseling young cancer patients. While fertility preservation options are available in many countries, limited data on gonadotoxicity hinder recommendations, especially for soft tissue cancers. This review, part of the FertiTOX project (www.fertitox.com), organized by FertiPROTEKT (www.fertiprotekt.com), aims to address this knowledge gap to improve fertility preservation guidance. We performed a systematic literature search on gonadotoxicity in soft tissue sarcoma (STS) cancer treatments. Only patients without metastases or recurrent disease were considered. "Suspected infertility" was defined based on low ovarian reserve parameters, low inhibin B levels, high gonadotropin concentration, gonadal dysfunction, amenorrhea, oligomenorrhea, azoospermia, or oligozoospermia due to limited infertility data. The study quality was assessed using the Newcastle-Ottawa Scale. The search yielded 3309 abstracts, with 138 undergoing full-text analysis. Eight studies on STS were included. Suspected infertility was observed in 20 of 28 females (71.4%, range 0-100%) and 38 of 63 males (60.3%, range 34.8-100%) with STS. Six of the eight studies received high-quality scores on the NOS, while two received a fair score. Our data suggest a high risk of infertility from chemotherapy in pre- and postpubertal STS survivors. This underscores the importance of considering fertility preservation measures when counseling these patients.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".