A model for predicting age at menopause in white women
To develop a model to predict the age at natural menopause and the risk for premenopausal hysterectomy. Cross-sectional study. Multicenter study. A total of 1,345 white women. Ten single nucleotide polymorphisms (SNPs) of seven estrogen (E)-metabolizing genes (i.e., catechol- O-methyltransferase, 17...
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| Veröffentlicht in: | Fertility and sterility 2006-02, Vol.85 (2), p.451-454 |
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| container_title | Fertility and sterility |
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| creator | Hefler, Lukas A. Grimm, Christoph Bentz, Eva-Katrin Reinthaller, Alexander Heinze, Georg Tempfer, Clemens B. |
| description | To develop a model to predict the age at natural menopause and the risk for premenopausal hysterectomy.
Cross-sectional study.
Multicenter study.
A total of 1,345 white women.
Ten single nucleotide polymorphisms (SNPs) of seven estrogen (E)-metabolizing genes (i.e., catechol-
O-methyltransferase, 17-β-hydroxysteroid dehydrogenase type 1, cytochrome P-450 [CYP] 17, CYP1A1, CYP1B1, CYP19, and E receptor [ER] α) were analyzed by sequencing-on-chip-technology.
Patients’ reproductive and medical histories were ascertained and correlated to genotypes.
The model incorporates the number of full term pregnancies, the body mass index (BMI), a history of breast surgery, and the presence of
CYP17 and
CYP1B1-4 polymorphisms as well as the BMI to predict age at natural menopause and the risk for undergoing premenopausal hysterectomy.
We present the first model to date, which can predict age at natural menopause and the risk for undergoing premenopausal hysterectomy based on genotype information and personal history. |
| doi_str_mv | 10.1016/j.fertnstert.2005.07.1300 |
| format | Article |
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Cross-sectional study.
Multicenter study.
A total of 1,345 white women.
Ten single nucleotide polymorphisms (SNPs) of seven estrogen (E)-metabolizing genes (i.e., catechol-
O-methyltransferase, 17-β-hydroxysteroid dehydrogenase type 1, cytochrome P-450 [CYP] 17, CYP1A1, CYP1B1, CYP19, and E receptor [ER] α) were analyzed by sequencing-on-chip-technology.
Patients’ reproductive and medical histories were ascertained and correlated to genotypes.
The model incorporates the number of full term pregnancies, the body mass index (BMI), a history of breast surgery, and the presence of
CYP17 and
CYP1B1-4 polymorphisms as well as the BMI to predict age at natural menopause and the risk for undergoing premenopausal hysterectomy.
We present the first model to date, which can predict age at natural menopause and the risk for undergoing premenopausal hysterectomy based on genotype information and personal history.</description><identifier>ISSN: 0015-0282</identifier><identifier>EISSN: 1556-5653</identifier><identifier>DOI: 10.1016/j.fertnstert.2005.07.1300</identifier><identifier>PMID: 16595226</identifier><identifier>CODEN: FESTAS</identifier><language>eng</language><publisher>New York, NY: Elsevier Inc</publisher><subject>age ; Aging - physiology ; Aryl Hydrocarbon Hydroxylases ; Biological and medical sciences ; Body Mass Index ; Breast - surgery ; Cross-Sectional Studies ; Cytochrome P-450 CYP1B1 ; Cytochrome P-450 Enzyme System - genetics ; estrogen ; Female ; gene ; Genotype ; Gynecology. Andrology. Obstetrics ; Humans ; Hysterectomy ; Linear Models ; Medical Records ; Medical sciences ; Menopause ; Models, Biological ; Parity ; polymorphism ; Polymorphism, Genetic ; Pregnancy ; Premenopause ; Risk Assessment ; Steroid 17-alpha-Hydroxylase - genetics ; timing</subject><ispartof>Fertility and sterility, 2006-02, Vol.85 (2), p.451-454</ispartof><rights>2006 American Society for Reproductive Medicine</rights><rights>2006 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c456t-1124126245af70c8b6550939b66b65da9095f5e49c993b1f29cc2a5952f56fb93</citedby><cites>FETCH-LOGICAL-c456t-1124126245af70c8b6550939b66b65da9095f5e49c993b1f29cc2a5952f56fb93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.fertnstert.2005.07.1300$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17495895$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16595226$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hefler, Lukas A.</creatorcontrib><creatorcontrib>Grimm, Christoph</creatorcontrib><creatorcontrib>Bentz, Eva-Katrin</creatorcontrib><creatorcontrib>Reinthaller, Alexander</creatorcontrib><creatorcontrib>Heinze, Georg</creatorcontrib><creatorcontrib>Tempfer, Clemens B.</creatorcontrib><title>A model for predicting age at menopause in white women</title><title>Fertility and sterility</title><addtitle>Fertil Steril</addtitle><description>To develop a model to predict the age at natural menopause and the risk for premenopausal hysterectomy.
Cross-sectional study.
Multicenter study.
A total of 1,345 white women.
Ten single nucleotide polymorphisms (SNPs) of seven estrogen (E)-metabolizing genes (i.e., catechol-
O-methyltransferase, 17-β-hydroxysteroid dehydrogenase type 1, cytochrome P-450 [CYP] 17, CYP1A1, CYP1B1, CYP19, and E receptor [ER] α) were analyzed by sequencing-on-chip-technology.
Patients’ reproductive and medical histories were ascertained and correlated to genotypes.
The model incorporates the number of full term pregnancies, the body mass index (BMI), a history of breast surgery, and the presence of
CYP17 and
CYP1B1-4 polymorphisms as well as the BMI to predict age at natural menopause and the risk for undergoing premenopausal hysterectomy.
We present the first model to date, which can predict age at natural menopause and the risk for undergoing premenopausal hysterectomy based on genotype information and personal history.</description><subject>age</subject><subject>Aging - physiology</subject><subject>Aryl Hydrocarbon Hydroxylases</subject><subject>Biological and medical sciences</subject><subject>Body Mass Index</subject><subject>Breast - surgery</subject><subject>Cross-Sectional Studies</subject><subject>Cytochrome P-450 CYP1B1</subject><subject>Cytochrome P-450 Enzyme System - genetics</subject><subject>estrogen</subject><subject>Female</subject><subject>gene</subject><subject>Genotype</subject><subject>Gynecology. Andrology. Obstetrics</subject><subject>Humans</subject><subject>Hysterectomy</subject><subject>Linear Models</subject><subject>Medical Records</subject><subject>Medical sciences</subject><subject>Menopause</subject><subject>Models, Biological</subject><subject>Parity</subject><subject>polymorphism</subject><subject>Polymorphism, Genetic</subject><subject>Pregnancy</subject><subject>Premenopause</subject><subject>Risk Assessment</subject><subject>Steroid 17-alpha-Hydroxylase - genetics</subject><subject>timing</subject><issn>0015-0282</issn><issn>1556-5653</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkE1v2zAMhoViRZum_QuDdlhvdinZlKNjEGxdgQC7rGdBlqlWgT8yyVnQf18bCZDrLiQhPKRePIx9E5ALEOppl3uKY5_GqeYSAHOoclEAXLGFQFQZKiy-sAWAwAzkSt6yu5R2AKBEJW_YrVCoUUq1YGrNu6Ghlvsh8n2kJrgx9G_cvhG3I--oH_b2kIiHnh_fw0j8OEyP9-za2zbRw7kv2evPH382v7Lt7-eXzXqbuRLVmAkhSyGVLNH6CtyqVoigC10rNY2N1aDRI5XaaV3UwkvtnLRzNo_K17pYssfT3X0c_h4ojaYLyVHb2p6GQzKqWkktASdQn0AXh5QiebOPobPxwwgwszSzMxdpZpZmoDKztGn36_mTQ91Rc9k8W5qA72fAJmdbH23vQrpwValxpecQmxNHk5J_gaJJLlDvJquR3GiaIfxHnE8IPo6B</recordid><startdate>20060201</startdate><enddate>20060201</enddate><creator>Hefler, Lukas A.</creator><creator>Grimm, Christoph</creator><creator>Bentz, Eva-Katrin</creator><creator>Reinthaller, Alexander</creator><creator>Heinze, Georg</creator><creator>Tempfer, Clemens B.</creator><general>Elsevier Inc</general><general>Elsevier Science</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20060201</creationdate><title>A model for predicting age at menopause in white women</title><author>Hefler, Lukas A. ; Grimm, Christoph ; Bentz, Eva-Katrin ; Reinthaller, Alexander ; Heinze, Georg ; Tempfer, Clemens B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c456t-1124126245af70c8b6550939b66b65da9095f5e49c993b1f29cc2a5952f56fb93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>age</topic><topic>Aging - physiology</topic><topic>Aryl Hydrocarbon Hydroxylases</topic><topic>Biological and medical sciences</topic><topic>Body Mass Index</topic><topic>Breast - surgery</topic><topic>Cross-Sectional Studies</topic><topic>Cytochrome P-450 CYP1B1</topic><topic>Cytochrome P-450 Enzyme System - genetics</topic><topic>estrogen</topic><topic>Female</topic><topic>gene</topic><topic>Genotype</topic><topic>Gynecology. Andrology. Obstetrics</topic><topic>Humans</topic><topic>Hysterectomy</topic><topic>Linear Models</topic><topic>Medical Records</topic><topic>Medical sciences</topic><topic>Menopause</topic><topic>Models, Biological</topic><topic>Parity</topic><topic>polymorphism</topic><topic>Polymorphism, Genetic</topic><topic>Pregnancy</topic><topic>Premenopause</topic><topic>Risk Assessment</topic><topic>Steroid 17-alpha-Hydroxylase - genetics</topic><topic>timing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hefler, Lukas A.</creatorcontrib><creatorcontrib>Grimm, Christoph</creatorcontrib><creatorcontrib>Bentz, Eva-Katrin</creatorcontrib><creatorcontrib>Reinthaller, Alexander</creatorcontrib><creatorcontrib>Heinze, Georg</creatorcontrib><creatorcontrib>Tempfer, Clemens B.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Fertility and sterility</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hefler, Lukas A.</au><au>Grimm, Christoph</au><au>Bentz, Eva-Katrin</au><au>Reinthaller, Alexander</au><au>Heinze, Georg</au><au>Tempfer, Clemens B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A model for predicting age at menopause in white women</atitle><jtitle>Fertility and sterility</jtitle><addtitle>Fertil Steril</addtitle><date>2006-02-01</date><risdate>2006</risdate><volume>85</volume><issue>2</issue><spage>451</spage><epage>454</epage><pages>451-454</pages><issn>0015-0282</issn><eissn>1556-5653</eissn><coden>FESTAS</coden><abstract>To develop a model to predict the age at natural menopause and the risk for premenopausal hysterectomy.
Cross-sectional study.
Multicenter study.
A total of 1,345 white women.
Ten single nucleotide polymorphisms (SNPs) of seven estrogen (E)-metabolizing genes (i.e., catechol-
O-methyltransferase, 17-β-hydroxysteroid dehydrogenase type 1, cytochrome P-450 [CYP] 17, CYP1A1, CYP1B1, CYP19, and E receptor [ER] α) were analyzed by sequencing-on-chip-technology.
Patients’ reproductive and medical histories were ascertained and correlated to genotypes.
The model incorporates the number of full term pregnancies, the body mass index (BMI), a history of breast surgery, and the presence of
CYP17 and
CYP1B1-4 polymorphisms as well as the BMI to predict age at natural menopause and the risk for undergoing premenopausal hysterectomy.
We present the first model to date, which can predict age at natural menopause and the risk for undergoing premenopausal hysterectomy based on genotype information and personal history.</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><pmid>16595226</pmid><doi>10.1016/j.fertnstert.2005.07.1300</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; Access via ScienceDirect (Elsevier); EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | age Aging - physiology Aryl Hydrocarbon Hydroxylases Biological and medical sciences Body Mass Index Breast - surgery Cross-Sectional Studies Cytochrome P-450 CYP1B1 Cytochrome P-450 Enzyme System - genetics estrogen Female gene Genotype Gynecology. Andrology. Obstetrics Humans Hysterectomy Linear Models Medical Records Medical sciences Menopause Models, Biological Parity polymorphism Polymorphism, Genetic Pregnancy Premenopause Risk Assessment Steroid 17-alpha-Hydroxylase - genetics timing |
| title | A model for predicting age at menopause in white women |
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