In the past two decades, evidence-based knowledge on the prevalence and risk factors for fertility impairment, including infertility, following cancer and numerous cancer treatment regimens has significantly increased. However, data remains mostly insufficient for individualized prediction of (future) fertility potential, including success of artificial reproductive technologies (ART). Furthermore, therapies have become increasingly complex. Recent treatment regimens have continuously implemented novel treatment approaches (e.g. immune therapies such as checkpoint inhibitors) for which no comprehensive data regarding its impact on fertility and pregnancy outcomes is available, yet. It is crucial to carefully balance risk-benefit between fertility preservation (FP) procedures and potential of gonadal function/fertility impairment, to examine the efficiency and safety, as well as to assess patients' satisfaction regarding the FP procedures. Answering these questions is highly relevant as it has been shown that fertility capacity and post-treatment gonadal function may represent a significant part of the quality of life in young cancer survivors. The study therefore aim to set up a large-scale network structure of emerging data collection programmes to evaluate the gonadotoxic risks, including the prevalence and course of ovarian/testicular dysfunction and/or fertility impairment and premature ovarian insufficiency/oligo/azoospermia following specific treatments, identification of further risk factors and predictive markers to enhance precision survivorship research in this field. Additionally, data on the use of fertility preservation/fertility treatment and patients' satisfaction related to these procedures in Europe shall be analysed to support patient-centric care. Reproductive health counselling should not be restricted to evaluating the individual risk of gonadotoxicty and offering fertility preservation to those at risk. It also includes the sexual health, the use of post-cancer treatment contraception for those recommended to delay attempting pregnancy after a cancer diagnosis and the identification of potential obstetrical and neonatal risks to provide individualized, risk-adapted follow-up during pregnancy. An increased risk of obstetrical and neonatal complications has been reported for several conditions, including preterm delivery, pre-eclampsia, cardiac dysfunction, and gestational diabetes. Most available studies are based on population registry and lack of detailed information on critical factors such as the impact of the timing of pregnancy, method of conception or the type of cancer treatment received (e.g pelvic irradiation, anthracycline, targeted therapy, immunotherapy…), all of which may influence the outcomes. The main objectives of this retrospective analysis of European ongoing adolescent and young adult (AYA) cancer patient cohorts are: • To establish harmonized databases with clinical data on pre- and post-cancer therapy and reproductive outcomes in AYA patients followed longitudinally. • To evaluate the impact of cancer treatment on long-term fertility according to cancer type and individual patients' characteristics (pre- and post-treatment) in male and female AYA populations. • To evaluate effect of cancer therapies on ovarian function in female AYA patients • To evaluate long-term effect on the endocrine function of the testis in male AYA patients i.e., the frequency of hypogonadism. • To evaluate the obstetrical and neonatal outcomes according to the disease and treatment.
Fertility preservation (FP) and fertility counselling at the time of diagnosis and throughout follow-up are recommended to improve the quality of life of young patients diagnosed with cancer (Lambertini et al. 2020; Su et al.2025). Indeed, it has been shown that gonadal function, as well as fertility capacity after treatment are crucial aspects for AYA cancer survivors (Letourneau et al.2012). While natural conception can be possible after cancer treatment, cancer-treatment related risk factors for impaired fertility, including a drastically reduced reproductive window, have been identified. FP techniques are progressing rapidly and have demonstrated their effectiveness in terms of pregnancy chances and live-birth rates. However, it remains difficult to establish firm and evidence-based FP strategies according to a patient's individual factors and cancer treatment. In addition, it remains crucial to carefully balance the risk-benefit of FP procedures and the potential of ovarian/fertility impairment, to examine the efficiency and safety of FP procedures and pregnancies as well as to assess patients' satisfaction regarding FP procedures. Large scale prospective and systematic short- and long-term data on the impact of specific cancer therapies on fertility based on fertility parameters such as ovarian reserve markers, sperm quality and pregnancies hardly exist. Specialized centres and joint regional and national network initiatives have started collecting such data. However, even though these initiatives are of great value and are sufficient to generate data from common cancer diseases such as breast or testicular cancer, rare cancers as well as on novel therapeutics (e.g. anti VEGF or immune therapies) and more complex cancer treatment regimen require large scale data collection initiatives to gain in-depth robust data for appropriate individual fertility-related counselling of female and male AYA patients. In female cancer patients, it has been shown that serum AMH levels variations may be a direct and real-time indicator of follicular depletion and recovery during and after cancer treatment, as well as it is a non-invasive and reproducible marker (Anderson et al., 2022; Decanter et al., 2021). Systematic follow-up of AMH has been suggested in AYA patients with at least a measurement at baseline and within the 2 years following the end of gonadotoxic treatment (Su et al., 2025; Decanter et al., 2024; von Wolff et al. 2025). In parallel, menstrual function pattern should be regularly analysed as a relevant clinical surrogate and independent variable to determine prevalence of cancer treatment-induced amenorrhea, it's duration and hormonal and clinical signs of potential post treatment premature ovarian insufficiency (POI). In the FollowAYA study within the PredictAYA project, the investigators therefore aim to set up a large-scale network structure of previously established data collection programmes in specialized centres/networks to evaluate the ovarian toxicity, the prevalence of impaired ovarian function, it's course and/or fertility impairment and POI following specific treatments, identification of predictive markers. Additionally, data on the use of FP and/or subsequent use of artificial reproductive treatment (ART) as well as patients' satisfaction related to these procedures in Europe shall drive the understanding of patient-centric care. In male cancer patients, the long-term reproductive and endocrine effects of cancer treatment on testicular function remain poorly studied, with existing data based on small cohorts and incomplete clinical characterization. No validated pre-conceptional tests currently exist to guide patients in deciding between natural conception and the use of cryopreserved sperm. Because treatment regimens vary widely even within the same cancer type and incidence rates are relatively low, only a coordinated European effort can generate sufficiently robust data. PredictAYA addresses this need by establishing a harmonized data platform across large male AYA cohorts. Its goals are to develop personalized risk-prediction tools for reproductive and testicular endocrine outcomes, provide evidence-based counselling on FP and future options, and design standardized follow-up protocols enabling early diagnosis and treatment of hypogonadism and infertility. As only limited evidence on sperm DNA damage and epigenetic alterations exist, these aspects will be validated in selected sub-cohorts to assess the frequency and persistence of chemotherapy-induced dysfunction (Farnetani et al. 2023 and 2024, Chan et al. 2023). Safety of pregnancy should also be an issue in counselling. Information on potential obstetrical and neonatal risks should also be given to provide individualized, risk-adapted follow-up during pregnancy. There is evidence that pregnancy in cancer survivors does not increase the risk for recurrence in women who became pregnant compared to those who did not, particularly in breast cancer (Lambertini et al. 2020). However, data remain limited regarding the impact of pregnancy timing, method of conception and the influence of adjuvant therapy such as hormonotherapy and immunotherapy (Bussies et al. 2022) Counselling patients in this context is particularly complex due to the lack of comprehensive human data (Maggen et al. 2021; Borgers et al. 2021). Finally, approximately 25-27 in 100,000 pregnancies is complicated by cancer, leaving specialists and patients to deal with a complex oncologic-obstetric decision-making process (Boere et al., 2021). PredictAYA also aim to confront the cancer recurrence rates during the follow up in haematological patients who were pregnant while receiving treatment for cancer versus expected recurrence rates for those neoplasms. An increased risk of neonatal and obstetrical complications has been reported in several conditions, including preterm delivery, pre-eclampsia, cardiac dysfunction, and gestational diabetes (Shliakhtsitsava et al. 2018, van der Kooi et al. 2019, van der Kooi et al. 2021), although population-based studies are reassuring regarding the health-related quality of life and the risk of congenital anomalies in the offspring in cancer survivors (Balcerek et al., 2021, Winther et al., 2004). Most available studies are based on population registry and lack of detailed information on critical factors such as the impact of the timing of pregnancy, method of conception or the type of treatment (e.g. pelvic irradiation, anthracycline, targeted therapy), all of which may influence the outcomes (Hartnett et al., 2018, Sunguc et al., 2024). To provide evidence-based guidance of pregnancies in women with a history of cancer, the current body of research is insufficient and warrants further investigation. Moreover, previous population-based studies reported a significantly lower childbirth rate in patients with aggressive tumours, with an increasing number of patients who used ART (Entrop et al., 2023a, Entrop et al., 2023b). ART has been associated with specific maternal and neonatal outcomes in infertile patients, related to placentation and endocrine environment (Bosdou et al., 2020, Busnelli et al., 2024). However, the impact of the conception methods, including ART after treatment and use of cryopreserved materials, on obstetrical and neonatal outcomes in cancer survivors' population is almost unknown (Borgmann-Staudt et al., 2022). Finally, few studies reported similar rate of unplanned pregnancies after cancer treatment and revealed a lack of contraception counselling in this population (Quinn et al. 2014, Massarotti et al 2021).
Study Type
OBSERVATIONAL
Enrollment
4,000
Constitution of the RedCap database
Constitution of a centralized RedCap database based on the collected variables from 4000 individuals diagnosed with cancer at age 15-39.
Time frame: June 2030
Treatment impact on AMH (1)
Percentage of included patients in which AMH decreases to below detection limit and percentage of AMH decrease if AMH stays above detection limit.
Time frame: June 2030
Incidence of azoo/oligo/normozoospermia
Incidence of azoo/oligo/normozoospermia through the analysis of sperm parameters pre/post treatment
Time frame: June 2030
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of disease (1)
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of disease
Time frame: June 2030
Treatment impact on AMH (2)
Change of menses pattern pre/post treatment.
Time frame: June 2030
Treatment impact on AMH (3)
Prevalence of POI post treatment.
Time frame: June 2030
Treatment impact on AMH (4)
Role of individual genetic backgrounds in menstrual function abnormalities and ultra-low or undetectable AMH levels.
Time frame: June 2030
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of disease (2)
Influence of disease type and stage on the obstetrical outcomes.
Time frame: June 2030
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of disease (3)
Influence of disease type and stage on the neonatal outcomes.
Time frame: June 2030
Incidence and type of FP according to the type of cancer and treatments.
Time frame: June 2030
Safety of FP procedures (1).
Short-term clinical safety of FP procedures.
Time frame: June 2030
ART induced pregnancy (1)
Cumulative incidence of spontaneous or ART induced pregnancy.
Time frame: June 2030
Incidence of overt and compensated hypogonadism
Incidence of overt and compensated hypogonadism pre/post treatment according to the type of cancer treatment .
Time frame: June 2030
Correlation between hormonal values/routine sperm parameters and clinical characteristics
Correlate hormonal values/routine sperm parameters and clinical characteristics (testis volume, andrological history) at baseline with the development of azoo/oligozoospermia and/or hypogonadism post-therapy.
Time frame: June 2030
Measurement of sperm DNA damage and epigenetic alterations pre and post-therapy
Time frame: June 2030
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of treatment and patient characteristic (1)
Obstetrical and neonatal outcomes according to the timing of pregnancy (at diagnosis or time from remission/end of treatment to conception)
Time frame: June 2030
Recurrence risk and survival after pregnancy
Recurrence (type and location) and survival rates after pregnancy according to the type of and stage of cancer disease, the cancer treatment (chemotherapy/radiotherapy/special attention to immunotherapy and targeted therapy), and the methods of conception (spontaneous versus ART).
Time frame: June 2030
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Prevalence of pregnancy, obstetrical and neonatal outcomes according to the method of conception
Obstetrical/neonatal outcomes in cancer survivors according to the method of conception (spontaneous or ART - type of ART and use of frozen materials).
Time frame: June 2030
Prevalence of unplanned pregnancies after treatment according to the disease and patients' characteristics
Occurrence of unplanned pregnancy and associated risk (type of treatment and disease, use of contraception, patient's characteristics, time from remission/end of treatment to conception)
Time frame: M60
Contraceptives use, type of contraception according to the disease, patient's characteristics and demographics
Use of contraception and associated factors (type of treatment and disease, use of contraception, patient's characteristics, time from remission/end of treatment to conception).
Time frame: June 2030
Safety of FP procedures (2).
Oncologic safety of FP procedures.
Time frame: June 2030
Safety of FP procedures (3).
Incidence of FP serious adverse events: OHSS, thrombosis, bleeding, infection etc.
Time frame: June 2030
ART induced pregnancy (2)
Method of conception according to the type of cancer and treatments.
Time frame: June 2030
ART induced pregnancy (3)
Re-use rates: ratio between number of clinical pregnancies and number of patients who asked for re-utilization.
Time frame: June 2030
ART induced pregnancy (4)
Pregnancy rate after reuse of cryopreserved gametes and/or ovarian tissue defined by the ratio between the number of clinical pregnancies and number of ART attempts.
Time frame: June 2030
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of treatment and patient characteristic (2)
Obstetrical and neonatal outcomes according to the type of treatment (chemotherapy/radiotherapy/special attention to immunotherapy and targeted therapy)
Time frame: June 2030
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of treatment and patient characteristic (3)
Obstetrical and neonatal outcomes according to the mothers condition (previous disease, age, co-morbidities)
Time frame: June 2030
Prevalence of pregnancy, obstetrical and neonatal outcomes according to the type of treatment and patient characteristics (4)
Obstetrical and neonatal outcomes according to the presence of cancer genetic predisposition (Lynch, P53 mutation, BRCA and others).
Time frame: June 2030