Fertility-sparing management in cervical cancer: balancing oncologic outcomes with reproductive success
Bibliographic record
Abstract
BACKGROUND: Cervical cancer is the fourth most common cancer among women worldwide, many of who are still within their reproductive lifespan. Advances in screening and treatment have increased the 5-year survival for early stage disease to over 90 % in developed countries. The focus is now shifting to reducing morbidity and improving fertility outcomes for cervical cancer patients. Radical trachelectomy with lymph node assessment became the standard of care for selected women with lesions <2 cm who desire fertility preservation. However, several questions still remain regarding the degree of surgical radicality required for tumors <2 cm, and fertility-sparing options for women with early-stage disesase ≥2 cm, and those with more advanced disease. Here, we compile a narrative review of the evidence for oncologic and pregnancy outcomes following radical trachelectomy, non-radical fertility-sparing surgery, and the use of neoadjuvant chemotherapy prior to surgery for larger lesions. We also review the literature for assisted reproductive technologies in women with more advanced disease. FINDINGS: Available literature suggests that the crude recurrence and mortality rates after radical trachelectomy are <5 and <2 %, respectively (approx. 11 and 4 % for tumors ≥ 2 cm). Among 1238 patients who underwent fertility-sparing surgery for early cervical cancer there were 469 pregnancies with a 67 % live birth rate. Among 134 cases with lesions ≥ 2 cm, there were ten conceptions with a live birth rate of 70 %. Outcomes after non-radical surgery (simple trachelectomy or cervical conization) are similar, although only applicable among a highly selected patient population. For patients ineligible for fertility-preserving surgery or who require adjuvant radiation therapy, current options include ovarian transposition and cryopreservation of oocytes or embryos but other techniques are under investigation. CONCLUSION: Today, many cervical cancer survivors have successful pregnancies. For those with early-stage disease, minimally invasive and fertility sparing techniques have resulted in improved obstetrical outcomes without compromising oncologic safety. Results from three ongoing trials on non-radical surgery for low-risk tumors <2 cm will further inform the need for radical surgery in such patients. For those in whom natural childbearing is unachievable, advances in assisted reproductive technologies provide reproductive options. Despite our advances, the effects of cervical cancer survivorship on quality of life are not fully elucidated.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".