Development a Predictive Nomogram for Primary Ovarian Insufficiency
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|ClinicalTrials.gov Identifier: NCT02795000|
Recruitment Status : Unknown
Verified June 2016 by Guangzhou University of Traditional Chinese Medicine.
Recruitment status was: Active, not recruiting
First Posted : June 9, 2016
Last Update Posted : April 10, 2018
|Condition or disease|
|Primary Ovarian Insufficiency|
Many researches show primary ovarian insufficiency(POI) etiology is related with gene,immunization,iatrogenic, infection factors and social factors etc. In fact, approximate 70-90% POI have no definite cause, so a lot of patients don't know what will happen when they in occult stage of POI. In this research, researchers will investigate all possible factors in POI patients and normal women and select the valuable risk factor by integrated by statistical method to establish the reasonable predictive model.
This study consists two stages.The fist stage is the model establishment, the second stage is the certificate and evaluate the model.
|Study Type :||Observational|
|Estimated Enrollment :||260 participants|
|Official Title:||Development a Predictive Nomogram for Primary Ovarian Insufficiency|
|Study Start Date :||October 2016|
|Estimated Primary Completion Date :||May 2018|
|Estimated Study Completion Date :||July 2018|
Primary Ovarian insufficiency group
The normal group
- Draw the Primary Ovarian insufficiency normogram [ Time Frame: 1years ]Retrospective Investigation on inclusion criteria populations through multivariate cox proportional hazards regression analysis of independent risk factors can enter the predictive model using R software based on regression coefficient related variables draw the corresponding nomogram (nomogram) .
- Verify and evaluate the evaluation of Primary Ovarian insufficiency normogram [ Time Frame: 2years ]using the bootstrap method nomogram for internal verification to reduce overfitting bias, the evaluation of the model to predict the risk of premature menopause conformity. In the study population data, select postmenopausal cases, the use of prediction of survival analysis model initial assessment model; select Not menopause an independent risk factor for the population were followed ovarian anti-Mullerian hormone (AMH) decreased the extent of menopause Age as a standard curve prediction, evaluation nomogram model predictive accuracy and clinical value of premature menopause, and finally provide the first Chinese people have the physical characteristics of premature menopause prediction model
Biospecimen Retention: Samples With DNA
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02795000
|Guangdong provicial hospital of Chinese Medicine|
|GuangZhou, Guangdong, China, 510000|
|Study Chair:||hongyan Yang, professor||Guangzhou University of Traditional Chinese Medicine|