Development a Predictive Nomogram for Primary Ovarian Insufficiency

Guangzhou University of Traditional Chinese Medicine260 enrolled

Overview

The purpose of this research is to develop a predictive nomogram for 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

Enrollment

260

Conditions

Primary Ovarian Insufficiency

Eligibility

Sex: FEMALEMin age: 18 YearsMax age: 42 YearsHealthy volunteers:

Medical Language ↔ Plain English

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

Locations (1)

Guangdong provicial hospital of Chinese Medicine

Guangzhou, Guangdong, China

Outcomes

Primary Outcomes

Draw the Primary Ovarian insufficiency normogram

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) .

Time frame: 1years

Secondary Outcomes

Verify and evaluate the evaluation of Primary Ovarian insufficiency normogram

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

Time frame: 2years

Data from ClinicalTrials.gov

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