Ignite Creation Date:
2025-12-25 @ 1:28 AM
Ignite Modification Date:
2025-12-27 @ 12:17 PM
Study NCT ID:
NCT06358794
Status:
COMPLETED
Last Update Posted:
2024-04-11
First Post:
2024-04-07
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Machine Learning Based-Personalized Prediction of Sperm Retrieval Success Rate
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D007248', 'term': 'Infertility, Male'}, {'id': 'C564665', 'term': 'Azoospermia, Nonobstructive'}], 'ancestors': [{'id': 'D005832', 'term': 'Genital Diseases, Male'}, {'id': 'D000091662', 'term': 'Genital Diseases'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D007246', 'term': 'Infertility'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 2612}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2022-06-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-04', 'completionDateStruct': {'date': '2023-05-31', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-04-07', 'studyFirstSubmitDate': '2024-04-07', 'studyFirstSubmitQcDate': '2024-04-07', 'lastUpdatePostDateStruct': {'date': '2024-04-11', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-04-11', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-12-31', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'SRR of micro-TESE', 'timeFrame': 'At the time after microdissection testicular sperm extraction', 'description': 'the sperm retrieval success rate of microdissection testicular sperm extraction'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Machine learning', 'Predictive model', 'Sperm retrieval'], 'conditions': ['Infertility, Male', 'Azoospermia, Nonobstructive']}, 'descriptionModule': {'briefSummary': 'Non-obstructive azoospermia (NOA) stands as the most severe form of male infertility. However, due to the diverse nature of testis focal spermatogenesis in NOA patients, accurately assessing the sperm retrieval rate (SRR) becomes challenging. The current study aims to develop and validate a noninvasive evaluation system based on machine learning, which can effectively estimate the SRR for NOA patients. In single-center investigation, NOA patients who underwent microdissection testicular sperm extraction (micro-TESE) were enrolled: (1) 2,438 patients from January 2016 to December 2022, and (2) 174 patients from January 2023 to May 2023 (as an additional validation cohort). The clinical features of participants were used to train, test and validate the machine learning models. Various evaluation metrics including area under the ROC (AUC), accuracy, etc. were used to evaluate the predictive performance of 8 machine learning models.'}, 'eligibilityModule': {'sex': 'MALE', 'stdAges': ['ADULT'], 'maximumAge': '60 Years', 'minimumAge': '20 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Nonobstructive azoospermia patients who underwent microdissection testicular sperm extraction at the Reproductive Center of Peking University Third Hospital were respectively enrolled.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* diagnosed with nonobstructive azoospermia\n* underwent microdissection testicular sperm extraction\n\nExclusion Criteria:\n\n* without intact clinical information\n* low data quality'}, 'identificationModule': {'nctId': 'NCT06358794', 'briefTitle': 'Machine Learning Based-Personalized Prediction of Sperm Retrieval Success Rate', 'organization': {'class': 'OTHER', 'fullName': 'Peking University Third Hospital'}, 'officialTitle': 'SpermFinder: Machine Learning Based-Personalized Prediction of Sperm Retrieval in Patients With Nonobstructive Azoospermia Prior to Microdissection Testicular Sperm Extraction', 'orgStudyIdInfo': {'id': 'IRB00006761-M2022692'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Training cohort', 'description': '2,438 patients diagnosed with NOA were included for model training and validation', 'interventionNames': ['Diagnostic Test: Machine learning-based predictive model']}, {'label': 'External validation cohort', 'description': '174 participants from January 2023 to May 2023 were included as the external validation cohort for online platform'}], 'interventions': [{'name': 'Machine learning-based predictive model', 'type': 'DIAGNOSTIC_TEST', 'description': 'The clinical features of participants were used to train, test and validate the machine learning models. Various evaluation metrics including area under the ROC (AUC), accuracy, etc. were used to evaluate the predictive performance of 8 machine learning models.', 'armGroupLabels': ['Training cohort']}]}, 'contactsLocationsModule': {'locations': [{'zip': '100191', 'city': 'Beijing', 'state': 'Beijing Municipality', 'country': 'China', 'facility': 'Peking University Third Hospital', 'geoPoint': {'lat': 39.9075, 'lon': 116.39723}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'The raw clinical data are not publicly available. Processed nonsensitive data and analysis code are available from the corresponding author on reasonable request.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Peking University Third Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}