[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"male-fertility\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:male-fertility":29},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,5,0,[8,47,85,111,139],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":14,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":31,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":36,"lastUpdatePostDateStruct":37,"startDateStruct":40,"completionDateStruct":42,"leadSponsor":44,"locationsCount":4},"100638517","late-effects-of-cancer-therapies-on-gonadal-function-fertility-efficiency-of-fertility-preservation-procedures-and-pregnancy-outcomes-100638517",false,"NCT07622537","Late Effects of Cancer Therapies on Gonadal Function, Fertility, Efficiency of Fertility Preservation Procedures and Pregnancy Outcomes","Follow-AYA","Inclusion Criteria:\n\n* Female and male cancer patients aged between 15 and 39 years at diagnosis.\n* First diagnosed with any cancer disease between 01\u002F01\u002F2000 and 31\u002F12\u002F2025\n* Treated with chemotherapy and\u002For targeted therapy\u002Fimmunotherapy and\u002For radiotherapy\u002F radioactive iodine therapy and\u002For testis\u002Fscrotal or gynaecological surgery.\n* Information on treatment received available.\n\nExclusion Criteria:\n\n* Pre-existing known POI at cancer diagnosis\n* Cancer treated by surgery alone (except gynaecological\u002Ftesticular surgery)\n* Data from second malignant neoplasm diagnose and treatment\n* Adult subject of a measure of legal protection and\u002For patients with serious mental disorders","ALL","15 Years","39 Years",{"count":20,"type":21},4000,"ESTIMATED","OBSERVATIONAL","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.\n\nIt is crucial to carefully balance risk-benefit between fertility preservation (FP) procedures and potential of gonadal function\u002Ffertility 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.\n\nThe 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\u002Ftesticular dysfunction and\u002For fertility impairment and premature ovarian insufficiency\u002Foligo\u002Fazoospermia 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\u002Ffertility treatment and patients' satisfaction related to these procedures in Europe shall be analysed to support patient-centric care.\n\nReproductive 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.\n\nThe main objectives of this retrospective analysis of European ongoing adolescent and young adult (AYA) cancer patient cohorts are:\n\n• To establish harmonized databases with clinical data on pre- and post-cancer therapy and reproductive outcomes in AYA patients followed longitudinally.\n\n• 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.\n\n• To evaluate effect of cancer therapies on ovarian function in female AYA patients\n\n• To evaluate long-term effect on the endocrine function of the testis in male AYA patients i.e., the frequency of hypogonadism.\n\n• To evaluate the obstetrical and neonatal outcomes according to the disease and treatment.",[25,26,27,28,29,30],"Cancer","Infertility","Late Effects","Female Fertility","Male Fertility","AYA Cancer Survivors",[32,33,34],"cancer treatment induced late effects","infertility after cancer","AYA cancer survivours","NOT_YET_RECRUITING","2026-05-27",{"date":38,"type":39},"2026-06-03","ACTUAL",{"date":41,"type":21},"2026-06-01",{"date":43,"type":21},"2035-07-31",{"name":45,"class":46},"Karolinska Institutet","OTHER",{"id":48,"slug":49,"hasResults":11,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":53,"eligibilityCriteria":54,"healthyVolunteers":11,"sex":55,"minAge":56,"maxAge":57,"enrollmentInfo":58,"targetDuration":4,"studyType":60,"phases":61,"briefSummary":63,"conditions":64,"keywords":67,"overallStatus":74,"whyStopped":4,"lastUpdateSubmitDate":75,"lastUpdatePostDateStruct":76,"startDateStruct":78,"completionDateStruct":80,"leadSponsor":82,"locationsCount":84},"100579976","the-effects-of-diet-on-small-non-coding-rna-i-sperm-cells-and-the-possible-effects-on-reproductive-success-diet-intervention-effects-on-sperm-100579976","NCT06831292","The Effects of Diet on Small Non-coding RNA i Sperm Cells and the Possible Effects on Reproductive Success: Diet Intervention Effects on Sperm","Molecular Mechanisms for Male Fertility: Can Diet Change Sperm sncRNA and the Reproductive Potential?","DIET-IS","Inclusion Criteria:\n\n* Male (biological) partner in infertile couple, scheduled for first IVF treatment\n* Mature sperm cells in semen\n* Able to speak and read Swedish\n* Omnivore\n* Will refrain from nicotine and alcohol during intervention\n* Sperm sampled provided no more than 3 weeks before intervention start\n\nExclusion Criteria:\n\n* Former or present malignant disease\n* Former radiotherapy in pelvic area\n* Former chemotherapy\n* Known genetic\u002Fchromosomal disorder\n* Food allergy","MALE","23 Years","56 Years",{"count":59,"type":21},100,"INTERVENTIONAL",[62],"NA","In this study, patients with infertility treated with IVF at the Center of Reproductive Medicine in Linköping, Sweden, will receive recipes and food according to Nordic dietary guidelines. The purpose is to investigate whether a short diet intervention is sufficient to improve sperm quality and shift the small non-coding RNA profile. In our previous study sperm showed rapid response to diet.",[65,29,66],"Changes in sncRNA in Sperm","RNA Profile",[68,69,70,71,72,73],"male fertility","small non-coding RNA","diet","infertility","reproduction","diet intervention","RECRUITING","2026-05-04",{"date":77,"type":39},"2026-05-05",{"date":79,"type":39},"2024-12-26",{"date":81,"type":21},"2027-12",{"name":83,"class":46},"Ostergotland County Council, Sweden",1,{"id":86,"slug":87,"hasResults":11,"nctId":88,"briefTitle":89,"officialTitle":89,"acronym":4,"eligibilityCriteria":90,"healthyVolunteers":11,"sex":55,"minAge":91,"maxAge":92,"enrollmentInfo":93,"targetDuration":4,"studyType":60,"phases":95,"briefSummary":96,"conditions":97,"keywords":4,"overallStatus":74,"whyStopped":4,"lastUpdateSubmitDate":102,"lastUpdatePostDateStruct":103,"startDateStruct":105,"completionDateStruct":107,"leadSponsor":109,"locationsCount":84},"100542205","the-impact-of-lifestyle-intervention-on-weight-and-fertility-in-obese-males-100542205","NCT06339840","The Impact of Lifestyle Intervention on Weight and Fertility in Obese Males","Inclusion Criteria:\n\n1. Male, aged 22-40 years.\n2. BMI≥30 kg\u002Fm² (defined as obesity according to WHO standards).\n3. Patients who are willing and able to provide informed consent and follow all study procedures, including ongoing visits to the Reproductive Center of the Third Affiliated Hospital of Zhengzhou University and undergoing relevant tests\n4. Spouse aged 20-40 years, with menstrual regularity (menstrual cycle length of 21-35days, duration of 2-7days), with a BMI of 18.5≤BMI \\< 25 kg\u002Fm², planning for ART treatment at our center due to male factor infertility.\n5. Not participating in any other research projects currently or in the preceding three months.\n6. Willing to allow offspring conceived through the study to participate in follow-up research.\n\nExclusion Criteria:\n\n1. Male reproductive urinary system abnormalities: active urinary reproductive system infections; hypogonadism; hyperprolactinemia; excessive estrogen; cryptorchidism, etc.;\n2. Acute and chronic diseases that may affect fertility: chronic systemic diseases; history of systemic cytotoxic therapy or pelvic radiotherapy; other acute diseases that may affect study results;\n3. Digestive system and metabolic abnormalities: acute and chronic digestive system diseases affecting digestive absorption function; history of or current eating disorders; allergies to ingredients in meal replacement products; gout, kidney stones, or gallstones; history of weight loss surgery;\n4. Unhealthy lifestyle habits: meeting at least one of the following conditions: heavy alcohol consumption, daily smoking, history of drug abuse, history of substance abuse;\n5. Personal factors affecting trial participation: impaired capacity to fully consent to participation in the study; major mental disorders; occupations requiring intense physical exercise; current diets that may interfere with the dietary plans of this study; exclusion of current or past use of hormones or anti-obesity drugs, or the use of other medications that affect hormone levels, carbohydrate metabolism, or appetite.","22 Years","40 Years",{"count":94,"type":21},98,[62],"Obesity, defined by WHO standards as having a body mass index (BMI) equal to or greater than 30 kg\u002Fm², affects approximately 800 million people worldwide. It is evident that obesity has become a serious public health issue, resulting in significant health burdens.\n\nPrevious systematic reviews have indicated an association between obesity and male factor infertility. In populations undergoing assisted reproductive technology (ART), some studies have shown a correlation between increased male BMI and adverse ART outcomes. Furthermore, the negative effects of obesity may also be transmitted to offspring through genetic and epigenetic changes in reproductive cell DNA, increasing their risk of obesity, metabolic diseases, or other chronic conditions.\n\nCurrently, there is a lack of data on the impact of weight loss in obese men on fertility, and it is unclear which nutritional pattern in lifestyle interventions can more effectively control weight, improve semen quality, and address related endocrine issues in obese men, thereby improving reproductive treatment outcomes.\n\nBased on previous literature, we hypothesize that lifestyle interventions, particularly strict low-carbohydrate diets combined with lifestyle guidance, may offer greater health benefits for obese men. These benefits include effective weight loss, improvement in semen parameters, reproductive metabolic health, quality of life related to reproductive health, and the impact on reproductive treatment outcomes. This provides a basis for non-pharmacological intervention strategies and methods for the health of obese men.",[98,99,29,100,101],"Obesity","Weight Loss","Artificial Insemination","IVF-ET","2026-04-06",{"date":104,"type":39},"2026-04-13",{"date":106,"type":39},"2024-06-20",{"date":108,"type":21},"2027-12-31",{"name":110,"class":46},"Third Affiliated Hospital of Zhengzhou University",{"id":112,"slug":113,"hasResults":11,"nctId":114,"briefTitle":115,"officialTitle":115,"acronym":4,"eligibilityCriteria":116,"healthyVolunteers":11,"sex":55,"minAge":117,"maxAge":118,"enrollmentInfo":119,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":121,"conditions":122,"keywords":125,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":130,"lastUpdatePostDateStruct":131,"startDateStruct":133,"completionDateStruct":135,"leadSponsor":137,"locationsCount":84},"100607240","functional-development-and-clinical-validation-of-a-diagnostic-tool-based-on-artificial-intelligence-for-the-assessment-of-sperm-quality-and-the-selection-of-the-optimal-in-vitro-fertilisation-ivf-treatment-100607240","NCT07185984","Functional Development and Clinical Validation of a Diagnostic Tool Based on Artificial Intelligence for the Assessment of Sperm Quality and the Selection of the Optimal In Vitro Fertilisation (IVF) Treatment","* Inclusion criteria:\n\n  * Men between the ages of 18 and 50 who come to the clinic to undergo an ICSI cycle.\n  * Men between the ages of 18 and 50 who come to the clinic to undergo an artificial insemination cycle.\n  * All embryos will be placed in a time-lapse incubator.\n  * All women over 18 years of age who have obtained a MII number greater than or equal to 2 in oocyte retrieval, without excluding couples from the oocyte donation programme.\n  * All men and women with a previously known normal karyotype.\n  * Informed consent (IC) provided and signed by patients.\n* Exclusion criteria:\n\n  * All women diagnosed with recurrent pregnancy loss.\n  * All semen samples obtained by testicular biopsy.\n  * All donor semen samples.","18 Years","50 Years",{"count":120,"type":21},200,"Infertility is a growing global health problem affecting millions of couples worldwide, with male infertility accounting for approximately half of all cases. In the physiological environment, sperm go through an exhaustive selection process in the female reproductive tract before reaching the oocyte. During this journey, progressive mobility and morphology are key parameters for achieving fertilisation. Therefore, before starting an assisted reproduction treatment, it is essential to analyse and process the semen sample to assess the fertile potential, select the most optimal sperm and determine the most appropriate treatment.\n\nConventional methods of semen processing, such as density gradient centrifugation (DGC) and Swim-up washing of motile sperm, have significant limitations. These include interobserver and interlaboratory subjectivity, as well as damage to sperm DNA caused by centrifugation. Alternatively, microfluidics, which simulates natural selection, allows higher counts of morphologically normal, progressive motile sperm to be obtained. On the other hand, the CASA (computer-assisted sperm analysis) system has improved the standardisation and quality of semen analysis. Furthermore, the incorporation of Artificial Intelligence (AI) into semen quality analysis represents a promising opportunity, as it improves efficiency, accuracy and standardisation, and has the potential to increase success rates in assisted reproduction treatments.\n\nThis project aims to develop an innovative AI-based diagnostic tool to address male infertility. The tool will integrate microfluidic technology and the CASA system to analyse semen quality, calculate fertilisation potential and recommend personalised treatments with an estimate of success. Trained with large volumes of biological and clinical data, it will provide a comprehensive and patient-specific diagnosis by identifying complex relationships between multiple variables. Finally, a comparative study will be conducted to evaluate laboratory indicators and clinical outcomes of cycles using this tool versus those using conventional methods.",[123,29,124],"Infertility (IVF Patients)","Sperm Selection",[126,127,128,129],"Male infertility","Microfluidics","Artificial intelligence","Sperm quality","2025-09-19",{"date":132,"type":39},"2025-09-22",{"date":134,"type":21},"2025-11",{"date":136,"type":21},"2027-11",{"name":138,"class":46},"Instituto Valenciano de Infertilidad, IVI VALENCIA",{"id":140,"slug":141,"hasResults":11,"nctId":142,"briefTitle":143,"officialTitle":144,"acronym":145,"eligibilityCriteria":146,"healthyVolunteers":11,"sex":16,"minAge":117,"maxAge":4,"enrollmentInfo":147,"targetDuration":4,"studyType":60,"phases":148,"briefSummary":149,"conditions":150,"keywords":153,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":159,"lastUpdatePostDateStruct":160,"startDateStruct":162,"completionDateStruct":164,"leadSponsor":166,"locationsCount":4},"100605533","use-of-the-sidtm-v20-algorithm-to-assist-embiyologists-in-sperm-selection-during-icsi-procedures-100605533","NCT07163754","Use of the SiDTM v2.0 Algorithm to Assist Embiyologists in Sperm Selection During ICSI Procedures","Use of the SiDTM v2.0 Algorithm to Assist Embryologists in Sperm Selection During ICSI Procedures: Impact in Biological and Clinical Outcomes","SID_3","Inclusion Criteria:\n\n* Patients with indication for ICSI.\n* Women of advanced maternal age (\\>35 years) in whom at least 4 oocytes in metaphase II stages are obtained in the follicular puncture, without excluding patients from the oocyte donation program.\n* Sperm obtained by masturbation with a concentration above 1 million spermatozoa\u002FmL after sperm capacitation.\n* Normal karyotype of both partners.\n* Informed Consent (IC).\n\nExclusion Criteria:\n\n* Patients diagnosed with recurrent gestational loss.\n* Semen extracted by testicular biopsy.\n* Semen samples with globozoospermia (sperm defect due to lack of acrosome) or azoospermia (absence of spermatozoa in the ejaculate).\n* Semen samples treated with pentoxifylline.\n* ICSI cycles with application of calcium ionophore. o ICSI cycles with application of calcium ionophore.",{"count":59,"type":21},[62],"Infertility is defined as a failure of a couple to achieve a pregnancy after 12 or more months of unprotected intercourse. Males are found to be solely responsible for 20-30% of infertility cases but contribute to 50% of cases overall. The selection of sperm to microinject is completely subjective and there is high intra- and inter- observer variability. SiDTM v2.0 is an algorithm which analyses real-time seminal samples located at ICSI dishes. Particularly, it assesses morphology and several motility parameters of each sperm, and it assigns a categorical and numerical score to each one. Categorical scores are represented by colours: green colour for optimal sperm, yellow for good sperm, orange for medium-quality sperm and red for low-quality sperm. Numerical scores ranged from 0 to 100, with higher scores for those best-quality sperm. SiDTM v2.0 can reduce subjectivity of the sperm selection process to the maximum, selecting the optimal sperm in real time. In addition, it could help junior embryologists to perform this complex and tedious procedure, which is the sperm selection for ICSI. To carry out the study, we will conduct a prospective cohort study in a total of 100 couples. Therefore, the aim of this study is to validate SiDTM v2.0 as an useful Artificial Intelligence-tool for sperm selection; that means achieving , at least, same clinical results as sperm selection performed by the embryologist.",[29,151,152,124],"Testicular","Sperm Parameters in Fertile and Infertile Men",[154,155,156,157,158],"Intracytoplasmatic Sperm injection","automated sperm selection","artificial intelligence","fertilization","embryo quality","2025-09-02",{"date":161,"type":39},"2025-09-09",{"date":163,"type":21},"2025-10",{"date":165,"type":21},"2027-10",{"name":138,"class":46}]