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Development a Predictive Nomogram for Primary Ovarian Insufficiency

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. 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
Information provided by (Responsible Party):
Guangzhou University of Traditional Chinese Medicine

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

Condition or disease
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.

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Study Type : Observational
Estimated Enrollment : 260 participants
Observational Model: Case-Control
Time Perspective: Cross-Sectional
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

Resource links provided by the National Library of Medicine

Primary Ovarian insufficiency group
  1. amenorrhea one year or more than one year
  2. amenorrhea more than 4 months and FSH≥40IU/L
  3. ≤42 years old and AMH≤0.071
The normal group
  1. normal regular menorrhea
  2. ≤42 years old
  3. normal FSH and AMH level

Primary Outcome Measures :
  1. 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) .

Secondary Outcome Measures :
  1. 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
Whole blood to be retained

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years to 42 Years   (Adult)
Sexes Eligible for Study:   Female
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
The study population will be recruted from gynaecology department clinic of GuangDong provincial hospital of Chinese Medicine and web advertisement from April 2016 and December 2018.

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

Information from the National Library of Medicine

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 identifier (NCT number): NCT02795000

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China, Guangdong
Guangdong provicial hospital of Chinese Medicine
GuangZhou, Guangdong, China, 510000
Sponsors and Collaborators
Guangzhou University of Traditional Chinese Medicine
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Study Chair: hongyan Yang, professor Guangzhou University of Traditional Chinese Medicine
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Responsible Party: Guangzhou University of Traditional Chinese Medicine Identifier: NCT02795000    
Other Study ID Numbers: 2014KT1165
First Posted: June 9, 2016    Key Record Dates
Last Update Posted: April 10, 2018
Last Verified: June 2016
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Undecided
Keywords provided by Guangzhou University of Traditional Chinese Medicine:
Primary Ovarian Insufficiency
Additional relevant MeSH terms:
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Primary Ovarian Insufficiency
Menopause, Premature
Ovarian Diseases
Adnexal Diseases
Gonadal Disorders
Endocrine System Diseases