FRICOVA, Lenka, Stefan KOMMOSS, Giovanni SCAMBIA, Gwenael FERRON, Roman KOCIAN, Philipp HARTER, Luigi Pedone ANCHORA, Anne-Sophie BATS, Zoltan NOVAK, Christina Barbara WALTER, Francesco RASPAGLIESI, Eric LAMBAUDIE, Kiarash BAHREHMAND, Juergen ANDRESS, Jaroslav KLAT, Jana PASTERNAK, Olga MATYLEVICH, Nina SZETERLAK, Luboš MINÁŘ, Florian HEITZ, Mihai Emil CAPILNA, Ingo RUNNEBAUM, David CIBULA and Jiri SLAMA. Reproductive outcomes after fertility-sparing surgery for cervical cancer - results of the multicenter FERTISS study. Gynecologic oncology. SAN DIEGO: ACADEMIC PRESS INC ELSEVIER SCIENCE, 2024, vol. 190, November 2024, p. 179-185. ISSN 0090-8258. Available from: https://dx.doi.org/10.1016/j.ygyno.2024.08.020.
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Basic information
Original name Reproductive outcomes after fertility-sparing surgery for cervical cancer - results of the multicenter FERTISS study
Authors FRICOVA, Lenka (203 Czech Republic), Stefan KOMMOSS, Giovanni SCAMBIA, Gwenael FERRON, Roman KOCIAN (203 Czech Republic), Philipp HARTER, Luigi Pedone ANCHORA, Anne-Sophie BATS, Zoltan NOVAK, Christina Barbara WALTER, Francesco RASPAGLIESI, Eric LAMBAUDIE, Kiarash BAHREHMAND, Juergen ANDRESS, Jaroslav KLAT (203 Czech Republic), Jana PASTERNAK, Olga MATYLEVICH, Nina SZETERLAK, Luboš MINÁŘ (203 Czech Republic, belonging to the institution), Florian HEITZ, Mihai Emil CAPILNA, Ingo RUNNEBAUM, David CIBULA (203 Czech Republic) and Jiri SLAMA (203 Czech Republic).
Edition Gynecologic oncology, SAN DIEGO, ACADEMIC PRESS INC ELSEVIER SCIENCE, 2024, 0090-8258.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30214 Obstetrics and gynaecology
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 4.700 in 2022
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.1016/j.ygyno.2024.08.020
UT WoS 001312918200001
Keywords in English Fertility-sparing treatment; Conization; Trachelectomy; Cervical cancer; Pregnancy
Tags 14110240, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tereza Miškechová, učo 341652. Changed: 23/9/2024 08:13.
Abstract
Introduction. Fertility-sparing treatment (FST) for patients with cervical cancer intends to achieve oncologic outcomes comparable to those after radical treatment while maximizing reproductive outcomes, including the ability to conceive and minimizing the risk of prematurity. Methodology. International multicentre retrospective FERTISS study focused on patients treated with FST analysed timing of FST relative to pregnancy, conception attempts and methods, abortion rates, prophylactic procedures reducing the risk of severe prematurity, pregnancy duration, and delivery mode. Results. Of the 733 patients treated at 44 centres in 13 countries, 49.7% attempted to conceive during median follow-up of 72 months and 22.6% (166/733) patients achieved a successful pregnancy. Success rate was significantly higher after non-radical surgery (63.2%; 122/193) compared to radical trachelectomy (25.7%; 44/171, p < 0.001). Available perinatological data shows that 89.5% (111/124) of the patients became pregnant naturally. There was no significant difference in the abortion rate in the first pregnancy nor delivery success rates between non-radical and radical procedures patients. Preterm delivery (<38 weeks gestation) occurred more frequently after radical than non-radical procedures (76.5% vs. 57.7%, p = 0.15). Almost all patients (97.3%; 73/75) who underwent regular ultrasound cervicometry in pregnancy with subsequent prophylactic procedures delivered a live fetus, compared to 30.6% (15/49) women without such management, p < 0.001. Conclusion. Patients who underwent non-radical surgery had significantly higher pregnancy rates. Most pregnancies resulted in a viable fetus, but radical trachelectomy led to a higher rate of preterm births in the severe prematurity range. Half of the patients did not attempt pregnancy after FST. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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