Infertility, MaleNCT06358794
Machine Learning Based-Personalized Prediction of Sperm Retrieval Success Rate
An observational study of Infertility, Male and Azoospermia, Nonobstructive, run by Peking University Third Hospital at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 20 to 60 years, men only
- Conditions the study is for
- Infertility, Male, Azoospermia, Nonobstructive
- What is being tested?
- Machine learning-based predictive model
- How many people
- 2,612 participants
- Where
- 1 siteChina
- Study dates
- 1 Jun 2022to 31 May 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 60 years
- Men only
- No healthy volunteers
- Adult
Study population: Nonobstructive azoospermia patients who underwent microdissection testicular sperm extraction at the Reproductive Center of Peking University Third Hospital were respectively enrolled.
Who may be able to join
- diagnosed with nonobstructive azoospermia
- underwent microdissection testicular sperm extraction
Who cannot join
- without intact clinical information
- low data quality
Trial locations and contacts
1 site in 1 country.
China1 site
Peking University Third Hospital
Beijing, Beijing Municipality, 100191
About this study
Official title: SpermFinder: Machine Learning Based-Personalized Prediction of Sperm Retrieval in Patients With Nonobstructive Azoospermia Prior to Microdissection Testicular Sperm Extraction
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.
- Conditions
- Infertility, Male, Azoospermia, Nonobstructive
- Being tested
- Machine learning-based predictive model
- Keywords
- Machine learning, Predictive model, Sperm retrieval
- Medical subject headings
- Infertility, Male, Azoospermia, Nonobstructive
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Machine learning-based predictive modelDiagnostic test
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.
| Study group | Role | What they receive |
|---|---|---|
| Training cohort | 2,438 patients diagnosed with NOA were included for model training and validation Receives: Diagnostic Test: Machine learning-based predictive model | |
| External validation cohort | 174 participants from January 2023 to May 2023 were included as the external validation cohort for online platform |
What is being measured
The primary outcome is the main question the study is designed to answer.
SRR of micro-TESE
the sperm retrieval success rate of microdissection testicular sperm extraction
Measured: At the time after microdissection testicular sperm extraction
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Apr 2024
- Study start1 Jun 2022
- Primary completion31 Dec 2022
- Study completion31 May 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Infertility, MaleStudies of the same condition, open and under way.
- More trials run by Peking University Third HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 2,612 participants (actual)
Sponsor and investigators
- Lead sponsor
- Peking University Third Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06358794
- Sponsor's protocol ID
- IRB00006761-M2022692
- Status last verified
- Apr 2024
- First submitted
- 7 Apr 2024
- Last updated
- 11 Apr 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The raw clinical data are not publicly available. Processed nonsensitive data and analysis code are available from the corresponding author on reasonable request.
Study at a glance
From the registry record, last updated by the sponsor on 11 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- SpermFinder: Machine Learning Based-Personalized Prediction of Sperm Retrieval in Patients With Nonobstructive Azoospermia Prior to Microdissection Testicular Sperm Extraction
- ClinicalTrials.gov ID
- NCT06358794
- Acronym / sponsor ID
- IRB00006761-M2022692
- Conditions
- Infertility, Male, Azoospermia, Nonobstructive
- Keywords
- Machine learning, Predictive model, Sperm retrieval
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 2,612 participants (actual)
- Lead sponsor
- Peking University Third HospitalUniversity, hospital or other
- Study start
- 1 Jun 2022 (actual)
- Primary completion
- 31 Dec 2022 (actual)
- Study completion
- 31 May 2023 (actual)
- First posted
- 11 Apr 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Training cohort | – | Diagnostic Test: Machine learning-based predictive model2,438 patients diagnosed with NOA were included for model training and validation |
| External validation cohort | – | –174 participants from January 2023 to May 2023 were included as the external validation cohort for online platform |
Who may qualify
- Ages
- 20 to 60 years
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Adult
- Study population
- Nonobstructive azoospermia patients who underwent microdissection testicular sperm extraction at the Reproductive Center of Peking University Third Hospital were respectively enrolled.
Key inclusion criteria (2 listed)
- diagnosed with nonobstructive azoospermia
- underwent microdissection testicular sperm extraction
Key exclusion criteria (2 listed)
- without intact clinical information
- low data quality
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Machine learning-based predictive modelThe 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. | Diagnostic test | Training cohort |
Primary outcome
SRR of micro-TESE
Time frame: At the time after microdissection testicular sperm extraction
the sperm retrieval success rate of microdissection testicular sperm extraction
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Apr 2024.
- Individual participant dataSharing planned: No. The raw clinical data are not publicly available. Processed nonsensitive data and analysis code are available from the corresponding author on reasonable request.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Infertility, Male and Azoospermia, Nonobstructive, run by Peking University Third Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 11 Apr 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
SRR of micro-TESE (time frame: At the time after microdissection testicular sperm extraction). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 Apr 2024.