Development a Predictive Nomogram for Primary Ovarian Insufficiency

• Conditions: Primary Ovarian Insufficiency

• Registration Number: NCT02795000
• Lead Sponsor: Guangzhou University of Traditional Chinese Medicine

Brief Summary

The purpose of this research is to develop a predictive nomogram for primary ovarian insufficiency.

Detailed Description

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 Timeline

• Study First Submitted: 2016-03-19
• Status Verified: 2016-06
• Study First Submitted QC: 2016-06-08
• Study First Posted: 2016-06-09
• Study Start: 2016-10
• Last Update Submitted: 2018-04-09
• Last Update Posted: 2018-04-10
• Primary Completion: 2018-05
• Study Completion: 2018-07

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: Female
• Target Recruitment: 260

Inclusion Criteria

• Age18--42
• Definite spontaneous last menstrual period
• Informed consent for participating this research and could answer the questionnaires faithfully.

Exclusion Criteria

• Congenital gonadal dysgenesis and non organic diseases lead to menstrual disorders.
• Endocrine diseases such Polycystic ovary syndrome, hyperprolactinemia, dysfunctional uterine bleeding, low gonadotropin menstrual disorders and hyperthyreosis
• Reproductive toxicity of drugs used
• Release of chemotherapeutic drugs
• Accept sex hormone medicine in recent 3 months
• Pregnant and lactating women
• With serious heart, liver, kidney and other diseases
• With severe psychiatric disorders

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Draw the Primary Ovarian insufficiency normogram	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) .

Secondary Outcome Measures

Name	Time	Method
Verify and evaluate the evaluation of Primary Ovarian insufficiency normogram	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

Trial Locations

Locations (1)

Guangdong provicial hospital of Chinese Medicine; 🇨🇳 GuangZhou, Guangdong, China