Genetic and Clinical Predictors for Breast Cancer Risk Assessment and Stratification Among Chinese Women
Background Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population. Me...
Saved in:
| Published in | JNCI : Journal of the National Cancer Institute Vol. 102; no. 13; pp. 972 - 981 |
|---|---|
| Main Authors | , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Cary, NC
Oxford University Press
07.07.2010
Oxford Publishing Limited (England) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0027-8874 1460-2105 1460-2105 |
| DOI | 10.1093/jnci/djq170 |
Cover
| Abstract | Background Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population. Methods We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided. Results Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose–response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, Ptrend = 2.5 × 10−15). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population. Conclusion A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs. |
|---|---|
| AbstractList | Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population. A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs. Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population. We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided. Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose-response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, P(trend) = 2.5 x 10(-15)). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population. A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs. Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population.BACKGROUNDMost of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population.We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided.METHODSWe analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided.Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose-response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, P(trend) = 2.5 x 10(-15)). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population.RESULTSEight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose-response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, P(trend) = 2.5 x 10(-15)). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population.A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs.CONCLUSIONA risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs. Background Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population. Methods We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided. Results Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose–response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, Ptrend = 2.5 × 10−15). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population. Conclusion A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs. Background Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population. Methods We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided. Results Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose-response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, P sub(trend) = 2.5 10 super(-15)). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population. Conclusion A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs. |
| Author | Shyr, Yu Li, Chun Cai, Qiuyin Lu, Wei Zheng, Wei Shu, Xiao-Ou Wen, Wanqing Long, Jirong Zheng, Ying Li, Guoliang Gu, Kai Gao, Yu-Tang |
| AuthorAffiliation | Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) |
| AuthorAffiliation_xml | – name: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) |
| Author_xml | – sequence: 1 givenname: Wei surname: Zheng fullname: Zheng, Wei email: wei.zheng@vanderbilt.edu organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 2 givenname: Wanqing surname: Wen fullname: Wen, Wanqing organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 3 givenname: Yu-Tang surname: Gao fullname: Gao, Yu-Tang organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 4 givenname: Yu surname: Shyr fullname: Shyr, Yu organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 5 givenname: Ying surname: Zheng fullname: Zheng, Ying email: wei.zheng@vanderbilt.edu organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 6 givenname: Jirong surname: Long fullname: Long, Jirong organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 7 givenname: Guoliang surname: Li fullname: Li, Guoliang organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 8 givenname: Chun surname: Li fullname: Li, Chun organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 9 givenname: Kai surname: Gu fullname: Gu, Kai organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 10 givenname: Qiuyin surname: Cai fullname: Cai, Qiuyin organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 11 givenname: Xiao-Ou surname: Shu fullname: Shu, Xiao-Ou organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) – sequence: 12 givenname: Wei surname: Lu fullname: Lu, Wei organization: Affiliations of authors: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center (WZ, WW, JL, GL, QC, X-OS) and Department of Biostatistics (YS, CL), Vanderbilt University School of Medicine, Nashville, TN; Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China (Y-TG); Shanghai Center for Disease Prevention and Control, Shanghai Institute of Preventive Medicine, Shanghai, China (YZ, KG, WL) |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23151398$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/20484103$$D View this record in MEDLINE/PubMed |
| BookMark | eNqFkV1vFCEYhYmpsdvqlfeGmBgvdCwMzMDcmKyjbk02avyIjTeEYd9p2c7CFli1_172w1abmJIQLnjOgfecA7TnvAOEHlLygpKGHc2dsUez-QUV5A4aUV6ToqSk2kMjQkpRSCn4PjqIcU7yakp-D-2XhEtOCRuhswk4SNZg7Wa4HayzRg_4Y4CZNcmHiHsf8KsAOibcamcg4E82nuNxjBDjAlzaKD-noJPtszhZ7_B44d0pbs-sgwj4m8_cfXS310OEB7vzEH19--ZLe1xMP0zeteNpYSrBUgENCC2qjna8YlLnDb3oOpB1rynIxggumwY6WYtKVpL3glNZ9qaXwCqqOTtEz7e-K7fUlz_1MKhlsAsdLhUlah2YWgemtoFl_OUWX666BcxMHijoa4nXVv174-yZOvU_VCkbIUWdDZ7uDIK_WEFMamGjgWHQDvwqKlHlQTgXze0kYzVngspMPr5Bzv0quBybyuPSksqN3aO_f3715T_dZuDJDtAxl9qHXJ-N1xyjFWXN-rVnW84EH2OA_pbA6A3a2LRpPcdjh_9oiq3GxgS_rux1OFe1YKJSxyff1et20pxM3zPF2W_No-S8 |
| CODEN | JNCIEQ |
| CitedBy_id | crossref_primary_10_1038_s41467_020_17680_w crossref_primary_10_1016_j_cgh_2012_09_010 crossref_primary_10_1266_ggs_17_00053 crossref_primary_10_1371_journal_pone_0136650 crossref_primary_10_3322_caac_20135 crossref_primary_10_1007_s12011_024_04215_3 crossref_primary_10_1093_jncics_pkaa021 crossref_primary_10_1109_TCSS_2019_2912629 crossref_primary_10_1371_journal_pone_0069056 crossref_primary_10_1007_s10549_010_1327_8 crossref_primary_10_18632_oncotarget_10874 crossref_primary_10_1007_s11033_022_07195_6 crossref_primary_10_1097_CM9_0000000000002891 crossref_primary_10_1371_journal_pone_0066979 crossref_primary_10_1016_j_jgg_2014_03_006 crossref_primary_10_1038_s44276_024_00100_7 crossref_primary_10_1016_j_clbc_2017_07_014 crossref_primary_10_1371_journal_pone_0052445 crossref_primary_10_1371_journal_pone_0056128 crossref_primary_10_2139_ssrn_4022247 crossref_primary_10_1042_BSR20202794 crossref_primary_10_1371_journal_pgen_1002532 crossref_primary_10_1007_s12041_019_1174_2 crossref_primary_10_2188_jea_JE20120043 crossref_primary_10_18632_oncotarget_20182 crossref_primary_10_1093_jncics_pkab060 crossref_primary_10_1097_CM9_0000000000001502 crossref_primary_10_1016_j_gene_2018_06_035 crossref_primary_10_7314_APJCP_2015_16_6_2231 crossref_primary_10_1158_1055_9965_EPI_10_0054 crossref_primary_10_1002_cam4_6198 crossref_primary_10_1186_s40001_018_0345_6 crossref_primary_10_1093_aje_kws238 crossref_primary_10_1007_s10549_011_1389_2 crossref_primary_10_2196_17364 crossref_primary_10_1093_hmg_ddr405 crossref_primary_10_1002_ijc_33176 crossref_primary_10_1371_journal_pone_0073611 crossref_primary_10_1371_journal_pone_0090771 crossref_primary_10_1186_s13058_016_0786_1 crossref_primary_10_1186_s13058_021_01439_2 crossref_primary_10_1002_jcla_21488 crossref_primary_10_3390_ijms15022130 crossref_primary_10_1007_s10549_017_4144_5 crossref_primary_10_1038_ejhg_2013_38 crossref_primary_10_1158_0008_5472_CAN_12_0748 crossref_primary_10_7314_APJCP_2015_16_7_2857 crossref_primary_10_1093_hmg_ddw164 crossref_primary_10_18632_oncotarget_24374 crossref_primary_10_1007_s10549_012_2234_y crossref_primary_10_1158_1055_9965_EPI_18_0810 crossref_primary_10_1155_2016_3065493 crossref_primary_10_1155_2015_626948 crossref_primary_10_1186_s12885_024_12370_y crossref_primary_10_18632_oncotarget_13402 crossref_primary_10_1158_0008_5472_CAN_11_2561 crossref_primary_10_1186_bcr3678 crossref_primary_10_1371_journal_pone_0072154 crossref_primary_10_1186_s12885_022_09425_3 crossref_primary_10_1002_cncr_35095 crossref_primary_10_1093_hmg_ddt089 crossref_primary_10_1038_s41588_024_01736_4 crossref_primary_10_1093_hmg_dds159 crossref_primary_10_1007_s10549_011_1904_5 crossref_primary_10_1016_j_knosys_2023_110745 crossref_primary_10_1158_1055_9965_EPI_23_0064 crossref_primary_10_1007_s10549_012_2202_6 crossref_primary_10_1007_s10549_020_05643_0 crossref_primary_10_1007_s12291_013_0414_0 crossref_primary_10_1007_s13277_016_4795_6 crossref_primary_10_1007_s12282_015_0609_8 crossref_primary_10_1186_1471_2350_13_118 crossref_primary_10_1186_bcr3101 crossref_primary_10_1515_tjb_2021_0161 crossref_primary_10_1109_TII_2018_2825345 crossref_primary_10_1001_jamanetworkopen_2021_49030 crossref_primary_10_3103_S0095452722040065 crossref_primary_10_1038_srep12773 crossref_primary_10_18632_oncotarget_10403 crossref_primary_10_3390_cancers15225380 crossref_primary_10_1016_j_jclinepi_2013_10_006 crossref_primary_10_1038_ng_2505 crossref_primary_10_1158_1055_9965_EPI_10_1282 crossref_primary_10_1158_0008_5472_CAN_10_2733 crossref_primary_10_3390_jpm9010015 |
| Cites_doi | 10.1001/jama.295.12.1379 10.1038/ng2064 10.1093/jnci/81.24.1879 10.1093/jnci/djn215 10.1093/jnci/djp130 10.1038/ng1107 10.7326/0003-4819-150-11-200906020-00007 10.1093/jnci/djn305 10.1016/S0895-4356(01)00341-9 10.3346/jkms.2002.17.1.1 10.1093/jnci/91.18.1541 10.1002/ijc.11661 10.1002/sim.2929 10.1038/ng2075 10.1093/jnci/djm223 10.1093/jnci/djn292 10.1056/NEJMsa0708739 10.2307/2533324 10.1002/ijc.20561 10.1038/ng.131 10.1038/87876 10.1002/1097-0215(20000715)87:2<295::AID-IJC23>3.0.CO;2-7 10.1016/j.breast.2006.08.005 10.1093/jnci/88.6.359 10.1093/aje/kwi322 10.1093/jnci/djn180 10.1038/nature05887 10.1093/jnci/djm224 10.1093/jnci/djj331 10.1093/jnci/djj332 10.2307/2531595 10.1093/ije/25.1.40 10.1038/ng.318 10.1073/pnas.0800441105 10.7326/0003-4819-148-5-200803040-00004 10.1038/ng853 |
| ContentType | Journal Article |
| Copyright | 2015 INIST-CNRS Copyright Oxford Publishing Limited(England) Jul 7, 2010 The Author 2010. Published by Oxford University Press. 2010 |
| Copyright_xml | – notice: 2015 INIST-CNRS – notice: Copyright Oxford Publishing Limited(England) Jul 7, 2010 – notice: The Author 2010. Published by Oxford University Press. 2010 |
| DBID | BSCLL AAYXX CITATION IQODW CGR CUY CVF ECM EIF NPM 7TO 7U7 7U9 C1K H94 K9. NAPCQ 7X8 7U1 5PM ADTOC UNPAY |
| DOI | 10.1093/jnci/djq170 |
| DatabaseName | Istex CrossRef Pascal-Francis Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Oncogenes and Growth Factors Abstracts Toxicology Abstracts Virology and AIDS Abstracts Environmental Sciences and Pollution Management AIDS and Cancer Research Abstracts ProQuest Health & Medical Complete (Alumni) Nursing & Allied Health Premium MEDLINE - Academic Risk Abstracts PubMed Central (Full Participant titles) Unpaywall for CDI: Periodical Content Unpaywall |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Nursing & Allied Health Premium Virology and AIDS Abstracts Oncogenes and Growth Factors Abstracts Toxicology Abstracts AIDS and Cancer Research Abstracts ProQuest Health & Medical Complete (Alumni) Environmental Sciences and Pollution Management MEDLINE - Academic Risk Abstracts |
| DatabaseTitleList | Nursing & Allied Health Premium MEDLINE MEDLINE - Academic Risk Abstracts |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1460-2105 |
| EndPage | 981 |
| ExternalDocumentID | oai:pubmedcentral.nih.gov:2897876 PMC2897876 2105844921 20484103 23151398 10_1093_jnci_djq170 ark_67375_HXZ_DCG9XLN3_4 |
| Genre | Journal Article Research Support, N.I.H., Extramural Feature |
| GeographicLocations | China China, People's Rep., Shanghai |
| GeographicLocations_xml | – name: China – name: China, People's Rep., Shanghai |
| GrantInformation_xml | – fundername: NCI NIH HHS grantid: P30 CA068485 – fundername: NCI NIH HHS grantid: R01CA124558 – fundername: NCI NIH HHS grantid: R01CA64277 – fundername: NCI NIH HHS grantid: R01CA90899 – fundername: NCI NIH HHS grantid: R37CA70867 |
| GroupedDBID | --- -E4 -~X .2P .I3 .XZ .ZR 08P 0R~ 1TH 29L 2WC 354 4.4 482 48X 53G 5GY 5RE 5VS 5WD 70D 96U AABZA AACZT AAHTB AAJKP AAJQQ AAKAS AAMVS AAOGV AAPNW AAPQZ AAPXW AARHZ AAUAY AAUQX AAVAP AAWTL ABCQX ABDFA ABEJV ABEUO ABGNP ABIXL ABJNI ABKDP ABNGD ABNHQ ABNKS ABOCM ABPEJ ABPMR ABPPZ ABPTD ABQLI ABQNK ABVGC ABXVV ABZBJ ACBMB ACGFO ACGFS ACGOD ACKOT ACNCT ACPRK ACUFI ACUKT ACUTJ ACUTO ACYHN ADBBV ADEYI ADEZT ADGZP ADHKW ADHZD ADIPN ADNBA ADOCK ADQBN ADRTK ADVEK ADYVW ADZCM AEGPL AEJOX AEKSI AEMDU AEMQT AENZO AEPUE AETBJ AEWNT AFAZI AFCHL AFFNX AFFZL AFIYH AFOFC AFRAH AFXAL AFYAG AGINJ AGKEF AGORE AGQPQ AGSYK AGUTN AHMBA AHMMS AHXPO AIAGR AIJHB AJBYB AJEEA AJNCP ALMA_UNASSIGNED_HOLDINGS ALUQC ALXQX APIBT APWMN ASPBG ATGXG AVWKF AZFZN BAWUL BAYMD BCRHZ BEYMZ BSCLL BTRTY BVRKM C45 CAG CDBKE COF CS3 CZ4 DAKXR DIK DILTD DU5 D~K E3Z EBS EE~ EJD EMOBN ENERS F5P F8P F9B FECEO FEDTE FLUFQ FOEOM FOTVD FQBLK GAUVT GJXCC GX1 H13 H5~ HAR HVGLF HW0 HZ~ IH2 IOX J21 JXSIZ KAQDR KBUDW KOP KQ8 KSI KSN L7B M-Z MHKGH ML0 N9A NGC NOMLY NOYVH NU- NVLIB O0~ OAUYM OAWHX OBH OCB OCZFY ODMLO ODZKP OGEVE OHH OJQWA OJZSN OK1 OPAEJ OVD OWPYF P2P PAFKI PB- PEELM PQQKQ Q.- Q1. Q5Y R44 RD5 RNS ROL ROX ROZ RUSNO RW1 RXO TCURE TEORI TJX TMA TR2 TWZ UDS UPT VVN W8F WH7 WOQ X7H YAYTL YKOAZ YQT YXANX ZKX ZRR ZY1 ~91 ~H1 AAYXX CITATION -DD .55 .GJ 186 2QL 3O- 8WZ A6W AAGKA AAPGJ AAQQT AAWDT ABEFU ABSMQ ACFRR ACPQN ACVCV ACZBC ADMTO ADXHL AEHUL AEKPW AETEA AFFQV AFSHK AGKRT AGMDO AGNAY AHGBF AI. AJDVS APJGH AQDSO AQKUS ATTQO AVNTJ BKOMP BZKNY EIHJH FA8 GOZPB GRPMH IQODW J5H LXL LXN LXY MBLQV MVM NTWIH OBFPC O~Y QBD RNI RZF RZO VH1 X7M XJT Y6R YHZ YR5 ~X8 ABQTQ ADJQC ADRIX ADZXQ CGR CUY CVF ECM EIF M49 NPM RHF VXZ 7TO 7U7 7U9 C1K H94 K9. NAPCQ 7X8 7U1 5PM ADTOC UNPAY |
| ID | FETCH-LOGICAL-c573t-e9e7a75b1b4538a538ef7bbe86fa1e89c74899eb86758584f74182fcf8e351a43 |
| ISSN | 0027-8874 1460-2105 |
| IngestDate | Wed Aug 20 00:12:38 EDT 2025 Tue Sep 30 16:20:32 EDT 2025 Sun Sep 28 12:03:28 EDT 2025 Sat Sep 27 22:44:20 EDT 2025 Mon Jun 30 08:41:21 EDT 2025 Wed Feb 19 01:47:13 EST 2025 Mon Jul 21 09:16:35 EDT 2025 Wed Oct 01 02:25:12 EDT 2025 Thu Apr 24 23:01:29 EDT 2025 Sat Sep 20 11:01:55 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 13 |
| Keywords | Human Breast disease Asiatic Genotype Breast cancer Malignant tumor Epidemiology Mammary gland diseases Cancerology Statistical model Risk factor Genetics Adult Chinese Female Single nucleotide polymorphism Public health Cancer |
| Language | English |
| License | CC BY 4.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c573t-e9e7a75b1b4538a538ef7bbe86fa1e89c74899eb86758584f74182fcf8e351a43 |
| Notes | istex:84FA1539F0D357968454FC9C64DEC1FECEA06971 ark:/67375/HXZ-DCG9XLN3-4 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/2897876 |
| PMID | 20484103 |
| PQID | 741121879 |
| PQPubID | 41605 |
| PageCount | 10 |
| ParticipantIDs | unpaywall_primary_10_1093_jnci_djq170 pubmedcentral_primary_oai_pubmedcentral_nih_gov_2897876 proquest_miscellaneous_754534479 proquest_miscellaneous_733643718 proquest_journals_741121879 pubmed_primary_20484103 pascalfrancis_primary_23151398 crossref_primary_10_1093_jnci_djq170 crossref_citationtrail_10_1093_jnci_djq170 istex_primary_ark_67375_HXZ_DCG9XLN3_4 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2010-07-07 |
| PublicationDateYYYYMMDD | 2010-07-07 |
| PublicationDate_xml | – month: 07 year: 2010 text: 2010-07-07 day: 07 |
| PublicationDecade | 2010 |
| PublicationPlace | Cary, NC |
| PublicationPlace_xml | – name: Cary, NC – name: United States – name: Oxford |
| PublicationTitle | JNCI : Journal of the National Cancer Institute |
| PublicationTitleAlternate | J Natl Cancer Inst |
| PublicationYear | 2010 |
| Publisher | Oxford University Press Oxford Publishing Limited (England) |
| Publisher_xml | – name: Oxford University Press – name: Oxford Publishing Limited (England) |
| References | Zheng ( key 20170521010218_bib9) 2009; 41 Chlebowski ( key 20170521010218_bib16) 2007; 99 Pharoah ( key 20170521010218_bib11) 2008; 358 Gail ( key 20170521010218_bib12) 1989; 81 Pharoah ( key 20170521010218_bib30) 2002; 31 Efron ( key 20170521010218_bib25) 1997; 92 Gail ( key 20170521010218_bib15) 2007; 99 Tan ( key 20170521010218_bib38) 2007; 16 Benichou ( key 20170521010218_bib28) 1995; 51 Nathanson ( key 20170521010218_bib1) 2001; 7 Harrell ( key 20170521010218_bib23) 2001 DeLong ( key 20170521010218_bib26) 1988; 44 Rosner ( key 20170521010218_bib13) 1996; 88 Pencina ( key 20170521010218_bib27) 2008; 27 Gail ( key 20170521010218_bib10) 2008; 100 Gao ( key 20170521010218_bib22) 2000; 87 Gail ( key 20170521010218_bib32) 2009; 101 Easton ( key 20170521010218_bib4) 2007; 447 Costantino ( key 20170521010218_bib14) 1999; 91 Chen ( key 20170521010218_bib19) 2006; 98 Steyerberg ( key 20170521010218_bib24) 2001; 54 Stacey ( key 20170521010218_bib6) 2007; 39 Parkin ( key 20170521010218_bib20) 2005 Balmain ( key 20170521010218_bib2) 2003; 33 Cook ( key 20170521010218_bib29) 2009; 150 Walsh ( key 20170521010218_bib3) 2006; 295 Pepe ( key 20170521010218_bib31) 2008; 100 Linos ( key 20170521010218_bib21) 2008; 100 Yoo ( key 20170521010218_bib35) 2002; 17 Hunter ( key 20170521010218_bib5) 2007; 39 Tice ( key 20170521010218_bib18) 2008; 148 Chia ( key 20170521010218_bib37) 2005; 113 Gold ( key 20170521010218_bib8) 2008; 105 Minami ( key 20170521010218_bib34) 2004; 108 Seow ( key 20170521010218_bib36) 1996; 25 Zheng ( key 20170521010218_bib33) 2005; 162 Okonkwo ( key 20170521010218_bib39) 2008; 100 Stacey ( key 20170521010218_bib7) 2008; 40 Barlow ( key 20170521010218_bib17) 2006; 98 18042936 - J Natl Cancer Inst. 2007 Dec 5;99(23):1782-92 10861490 - Int J Cancer. 2000 Jul 15;87(2):295-300 3203132 - Biometrics. 1988 Sep;44(3):837-45 17529974 - Nat Genet. 2007 Jul;39(7):865-9 18780864 - J Natl Cancer Inst. 2008 Sep 17;100(18):1290-300 16954473 - J Natl Cancer Inst. 2006 Sep 6;98(17):1204-14 8609645 - J Natl Cancer Inst. 1996 Mar 20;88(6):359-64 11984562 - Nat Genet. 2002 May;31(1):33-6 12610533 - Nat Genet. 2003 Mar;33 Suppl:238-44 16954474 - J Natl Cancer Inst. 2006 Sep 6;98(17):1215-26 15386413 - Int J Cancer. 2005 Jan 10;113(2):302-6 17081753 - Breast. 2007 Apr;16(2):113-9 11329055 - Nat Med. 2001 May;7(5):552-6 18579814 - N Engl J Med. 2008 Jun 26;358(26):2796-803 10491430 - J Natl Cancer Inst. 1999 Sep 15;91(18):1541-8 2593165 - J Natl Cancer Inst. 1989 Dec 20;81(24):1879-86 16236996 - Am J Epidemiol. 2005 Dec 1;162(11):1123-31 17569110 - Stat Med. 2008 Jan 30;27(2):157-72; discussion 207-12 18316752 - Ann Intern Med. 2008 Mar 4;148(5):337-47 8666502 - Int J Epidemiol. 1996 Feb;25(1):40-5 18612128 - J Natl Cancer Inst. 2008 Jul 16;100(14):978-9 19535781 - J Natl Cancer Inst. 2009 Jul 1;101(13):959-63 11470385 - J Clin Epidemiol. 2001 Aug;54(8):774-81 17529967 - Nature. 2007 Jun 28;447(7148):1087-93 18000216 - J Natl Cancer Inst. 2007 Nov 21;99(22):1695-705 19219042 - Nat Genet. 2009 Mar;41(3):324-8 19487714 - Ann Intern Med. 2009 Jun 2;150(11):795-802 14712495 - Int J Cancer. 2004 Mar 1;108(6):901-6 18612136 - J Natl Cancer Inst. 2008 Jul 16;100(14):1037-41 16551709 - JAMA. 2006 Mar 22;295(12):1379-88 18438407 - Nat Genet. 2008 Jun;40(6):703-6 11850580 - J Korean Med Sci. 2002 Feb;17(1):1-6 7766773 - Biometrics. 1995 Mar;51(1):182-94 17529973 - Nat Genet. 2007 Jul;39(7):870-4 18812552 - J Natl Cancer Inst. 2008 Oct 1;100(19):1352-60 18326623 - Proc Natl Acad Sci U S A. 2008 Mar 18;105(11):4340-5 |
| References_xml | – volume: 295 start-page: 1379 issue: 12 year: 2006 ident: key 20170521010218_bib3 article-title: Spectrum of mutations in BRCA1, BRCA2, CHEK2, and TP53 in families at high risk of breast cancer publication-title: JAMA doi: 10.1001/jama.295.12.1379 – volume: 39 start-page: 865 issue: 7 year: 2007 ident: key 20170521010218_bib6 article-title: Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer publication-title: Nat Genet. doi: 10.1038/ng2064 – volume: 81 start-page: 1879 issue: 24 year: 1989 ident: key 20170521010218_bib12 article-title: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually publication-title: J Natl Cancer Inst doi: 10.1093/jnci/81.24.1879 – volume: 100 start-page: 978 issue: 14 year: 2008 ident: key 20170521010218_bib31 article-title: Gauging the performance of SNPs, biomarkers, and clinical factors for predicting risk of breast cancer publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djn215 – volume: 101 start-page: 959 issue: 13 year: 2009 ident: key 20170521010218_bib32 article-title: Value of adding single-nucleotide polymorphism genotypes to a breast cancer risk model publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djp130 – volume: 33 start-page: 238 issue: suppl year: 2003 ident: key 20170521010218_bib2 article-title: The genetics and genomics of cancer publication-title: Nat Genet. doi: 10.1038/ng1107 – volume: 150 start-page: 795 issue: 11 year: 2009 ident: key 20170521010218_bib29 article-title: Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures publication-title: Ann Intern Med doi: 10.7326/0003-4819-150-11-200906020-00007 – volume: 100 start-page: 1352 issue: 19 year: 2008 ident: key 20170521010218_bib21 article-title: Effects of reproductive and demographic changes on breast cancer incidence in China: a modeling analysis publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djn305 – volume: 54 start-page: 774 issue: 8 year: 2001 ident: key 20170521010218_bib24 article-title: Internal validation of predictive models: efficiency of some procedures for logistic regression analysis publication-title: J Clin Epidemiol doi: 10.1016/S0895-4356(01)00341-9 – volume: 17 start-page: 1 issue: 1 year: 2002 ident: key 20170521010218_bib35 article-title: Epidemiology of breast cancer in Korea: occurrence, high-risk groups, and prevention publication-title: J Korean Med Sci. doi: 10.3346/jkms.2002.17.1.1 – volume: 91 start-page: 1541 issue: 18 year: 1999 ident: key 20170521010218_bib14 article-title: Validation studies for models projecting the risk of invasive and total breast cancer incidence publication-title: J Natl Cancer Inst doi: 10.1093/jnci/91.18.1541 – volume: 108 start-page: 901 issue: 6 year: 2004 ident: key 20170521010218_bib34 article-title: The increase of female breast cancer incidence in Japan: emergence of birth cohort effect publication-title: Int J Cancer doi: 10.1002/ijc.11661 – volume: 27 start-page: 157 issue: 2 year: 2008 ident: key 20170521010218_bib27 article-title: Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond publication-title: Stat Med doi: 10.1002/sim.2929 – volume: 39 start-page: 870 issue: 7 year: 2007 ident: key 20170521010218_bib5 article-title: A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer publication-title: Nat Genet. doi: 10.1038/ng2075 – volume: 99 start-page: 1782 issue: 23 year: 2007 ident: key 20170521010218_bib15 article-title: Projecting individualized absolute invasive breast cancer risk in African American women publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djm223 – volume: 100 start-page: 1290 issue: 18 year: 2008 ident: key 20170521010218_bib39 article-title: Breast cancer screening policies in developing countries: a cost-effectiveness analysis for India publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djn292 – volume: 358 start-page: 2796 issue: 26 year: 2008 ident: key 20170521010218_bib11 article-title: Polygenes, risk prediction, and targeted prevention of breast cancer publication-title: N Engl J Med doi: 10.1056/NEJMsa0708739 – volume: 51 start-page: 182 issue: 1 year: 1995 ident: key 20170521010218_bib28 article-title: Methods of inference for estimates of absolute risk derived from population-based case-control studies publication-title: Biometrics doi: 10.2307/2533324 – volume: 113 start-page: 302 issue: 2 year: 2005 ident: key 20170521010218_bib37 article-title: Profound changes in breast cancer incidence may reflect changes into a Westernized lifestyle: a comparative population-based study in Singapore and Sweden publication-title: Int J Cancer doi: 10.1002/ijc.20561 – volume: 40 start-page: 703 issue: 6 year: 2008 ident: key 20170521010218_bib7 article-title: Common variants on chromosome 5p12 confer susceptibility to estrogen receptor-positive breast cancer publication-title: Nat Genet. doi: 10.1038/ng.131 – volume: 7 start-page: 552 issue: 5 year: 2001 ident: key 20170521010218_bib1 article-title: Breast cancer genetics: what we know and what we need publication-title: Nat Med doi: 10.1038/87876 – volume: 87 start-page: 295 issue: 2 year: 2000 ident: key 20170521010218_bib22 article-title: Association of menstrual and reproductive factors with breast cancer risk: results from the Shanghai Breast Cancer Study publication-title: Int J Cancer doi: 10.1002/1097-0215(20000715)87:2<295::AID-IJC23>3.0.CO;2-7 – volume: 16 start-page: 113 issue: 2 year: 2007 ident: key 20170521010218_bib38 article-title: How relevant is breast cancer screening in the Asia/Pacific region? publication-title: Breast doi: 10.1016/j.breast.2006.08.005 – volume: 88 start-page: 359 issue: 6 year: 1996 ident: key 20170521010218_bib13 article-title: Nurses’ health study: log-incidence mathematical model of breast cancer incidence publication-title: J Natl Cancer Inst doi: 10.1093/jnci/88.6.359 – year: 2001 ident: key 20170521010218_bib23 article-title: Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis publication-title: Springer – volume: 162 start-page: 1123 issue: 11 year: 2005 ident: key 20170521010218_bib33 article-title: The Shanghai Women's Health Study: rationale, study design, and baseline characteristics publication-title: Am J Epidemiol doi: 10.1093/aje/kwi322 – volume: 100 start-page: 1037 issue: 14 year: 2008 ident: key 20170521010218_bib10 article-title: Discriminatory accuracy from single-nucleotide polymorphisms in models to predict breast cancer risk publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djn180 – volume: 447 start-page: 1087 issue: 7148 year: 2007 ident: key 20170521010218_bib4 article-title: Genome-wide association study identifies novel breast cancer susceptibility loci publication-title: Nature doi: 10.1038/nature05887 – volume: 99 start-page: 1695 issue: 22 year: 2007 ident: key 20170521010218_bib16 article-title: Predicting risk of breast cancer in postmenopausal women by hormone receptor status publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djm224 – volume-title: Cancer Incidence in Five Continents year: 2005 ident: key 20170521010218_bib20 – volume: 92 start-page: 548 issue: 438 year: 1997 ident: key 20170521010218_bib25 article-title: Improvements on cross-validation: The .632+ bootstrap method publication-title: J Amer Statist Assoc – volume: 98 start-page: 1204 issue: 17 year: 2006 ident: key 20170521010218_bib17 article-title: Prospective breast cancer risk prediction model for women undergoing screening mammography publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djj331 – volume: 98 start-page: 1215 issue: 17 year: 2006 ident: key 20170521010218_bib19 article-title: Projecting absolute invasive breast cancer risk in white women with a model that includes mammographic density publication-title: J Natl Cancer Inst doi: 10.1093/jnci/djj332 – volume: 44 start-page: 837 issue: 3 year: 1988 ident: key 20170521010218_bib26 article-title: Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach publication-title: Biometrics doi: 10.2307/2531595 – volume: 25 start-page: 40 issue: 1 year: 1996 ident: key 20170521010218_bib36 article-title: Breast cancer in Singapore: trends in incidence 19681992 publication-title: Int J Epidemiol doi: 10.1093/ije/25.1.40 – volume: 41 start-page: 324 issue: 3 year: 2009 ident: key 20170521010218_bib9 article-title: Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1 publication-title: Nat Genet. doi: 10.1038/ng.318 – volume: 105 start-page: 4340 issue: 11 year: 2008 ident: key 20170521010218_bib8 article-title: Genome-wide association study provides evidence for a breast cancer risk locus at 6q22.33 publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.0800441105 – volume: 148 start-page: 337 issue: 5 year: 2008 ident: key 20170521010218_bib18 article-title: Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model publication-title: Ann Intern Med doi: 10.7326/0003-4819-148-5-200803040-00004 – volume: 31 start-page: 33 issue: 1 year: 2002 ident: key 20170521010218_bib30 article-title: Polygenic susceptibility to breast cancer and implications for prevention publication-title: Nat Genet. doi: 10.1038/ng853 – reference: 18780864 - J Natl Cancer Inst. 2008 Sep 17;100(18):1290-300 – reference: 15386413 - Int J Cancer. 2005 Jan 10;113(2):302-6 – reference: 16954474 - J Natl Cancer Inst. 2006 Sep 6;98(17):1215-26 – reference: 11470385 - J Clin Epidemiol. 2001 Aug;54(8):774-81 – reference: 16954473 - J Natl Cancer Inst. 2006 Sep 6;98(17):1204-14 – reference: 12610533 - Nat Genet. 2003 Mar;33 Suppl:238-44 – reference: 16551709 - JAMA. 2006 Mar 22;295(12):1379-88 – reference: 18579814 - N Engl J Med. 2008 Jun 26;358(26):2796-803 – reference: 18000216 - J Natl Cancer Inst. 2007 Nov 21;99(22):1695-705 – reference: 11984562 - Nat Genet. 2002 May;31(1):33-6 – reference: 19219042 - Nat Genet. 2009 Mar;41(3):324-8 – reference: 10491430 - J Natl Cancer Inst. 1999 Sep 15;91(18):1541-8 – reference: 11850580 - J Korean Med Sci. 2002 Feb;17(1):1-6 – reference: 18438407 - Nat Genet. 2008 Jun;40(6):703-6 – reference: 14712495 - Int J Cancer. 2004 Mar 1;108(6):901-6 – reference: 18812552 - J Natl Cancer Inst. 2008 Oct 1;100(19):1352-60 – reference: 11329055 - Nat Med. 2001 May;7(5):552-6 – reference: 2593165 - J Natl Cancer Inst. 1989 Dec 20;81(24):1879-86 – reference: 16236996 - Am J Epidemiol. 2005 Dec 1;162(11):1123-31 – reference: 17569110 - Stat Med. 2008 Jan 30;27(2):157-72; discussion 207-12 – reference: 19487714 - Ann Intern Med. 2009 Jun 2;150(11):795-802 – reference: 18612136 - J Natl Cancer Inst. 2008 Jul 16;100(14):1037-41 – reference: 17081753 - Breast. 2007 Apr;16(2):113-9 – reference: 8666502 - Int J Epidemiol. 1996 Feb;25(1):40-5 – reference: 10861490 - Int J Cancer. 2000 Jul 15;87(2):295-300 – reference: 18612128 - J Natl Cancer Inst. 2008 Jul 16;100(14):978-9 – reference: 17529974 - Nat Genet. 2007 Jul;39(7):865-9 – reference: 17529967 - Nature. 2007 Jun 28;447(7148):1087-93 – reference: 18326623 - Proc Natl Acad Sci U S A. 2008 Mar 18;105(11):4340-5 – reference: 7766773 - Biometrics. 1995 Mar;51(1):182-94 – reference: 8609645 - J Natl Cancer Inst. 1996 Mar 20;88(6):359-64 – reference: 18316752 - Ann Intern Med. 2008 Mar 4;148(5):337-47 – reference: 19535781 - J Natl Cancer Inst. 2009 Jul 1;101(13):959-63 – reference: 3203132 - Biometrics. 1988 Sep;44(3):837-45 – reference: 18042936 - J Natl Cancer Inst. 2007 Dec 5;99(23):1782-92 – reference: 17529973 - Nat Genet. 2007 Jul;39(7):870-4 |
| SSID | ssj0000924 |
| Score | 2.3359747 |
| Snippet | Background Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk... Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model... |
| SourceID | unpaywall pubmedcentral proquest pubmed pascalfrancis crossref istex |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 972 |
| SubjectTerms | Adult Age of Onset Asian Continental Ancestry Group - genetics Asian Continental Ancestry Group - statistics & numerical data Asian people Biological and medical sciences Breast cancer Breast Neoplasms - epidemiology Breast Neoplasms - etiology Breast Neoplasms - genetics Case-Control Studies China - epidemiology European Continental Ancestry Group - genetics Female Genetic diversity Genetic Predisposition to Disease Genome-Wide Association Study Genomics Genotype Gynecology. Andrology. Obstetrics Health risk assessment Humans Live Birth Mammary gland diseases Medical sciences Menarche Middle Aged Models, Statistical Polymorphism, Single Nucleotide Predictive Value of Tests Risk Assessment Risk Factors Tumors Waist-Hip Ratio Women |
| Title | Genetic and Clinical Predictors for Breast Cancer Risk Assessment and Stratification Among Chinese Women |
| URI | https://api.istex.fr/ark:/67375/HXZ-DCG9XLN3-4/fulltext.pdf https://www.ncbi.nlm.nih.gov/pubmed/20484103 https://www.proquest.com/docview/741121879 https://www.proquest.com/docview/733643718 https://www.proquest.com/docview/754534479 https://pubmed.ncbi.nlm.nih.gov/PMC2897876 https://www.ncbi.nlm.nih.gov/pmc/articles/2897876 |
| UnpaywallVersion | submittedVersion |
| Volume | 102 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAFT databaseName: Open Access Digital Library customDbUrl: eissn: 1460-2105 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0000924 issn: 0027-8874 databaseCode: KQ8 dateStart: 19960101 isFulltext: true titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html providerName: Colorado Alliance of Research Libraries – providerCode: PRVBFR databaseName: Free Medical Journals customDbUrl: eissn: 1460-2105 dateEnd: 20241001 omitProxy: true ssIdentifier: ssj0000924 issn: 0027-8874 databaseCode: DIK dateStart: 19960101 isFulltext: true titleUrlDefault: http://www.freemedicaljournals.com providerName: Flying Publisher – providerCode: PRVFQY databaseName: GFMER Free Medical Journals customDbUrl: eissn: 1460-2105 dateEnd: 20241001 omitProxy: true ssIdentifier: ssj0000924 issn: 0027-8874 databaseCode: GX1 dateStart: 19960101 isFulltext: true titleUrlDefault: http://www.gfmer.ch/Medical_journals/Free_medical.php providerName: Geneva Foundation for Medical Education and Research |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LbxMxELZCKwEXxJtQqHwoHIi2zb7tYwjQgCBC0Kqhl5V3YystYdvmISh_jz_GjO190VAVDllFXu9zvp3xjD_PELIVCx-jS2OH-SpyAq64I8aedFQWSBm5Yzcda4LsMBrsB-9G4ajV-lVjLS0X6Xb2c-W6kv-RKrSBXHGV7D9ItjwpNMB_kC9sQcKwvZKMMWd0kXC1Xyxx_DjDuRddRAcphC-Rdb7o9FG6s84nZJL3ymychripM-cqG7zr9HT5IayrLedItvlmF4sVI9hh_62OI9SGspooWUQV7ZVKFkIVmpZGrxzIo2o-SCu9A5GfFSYUuUBCx2-_LJ09UbV-npzPTHM9UoGT7BgFrfza1Ssg69rZA4vJTNWebWkUchB1HXBLw4bG7np1aPo1BcxNISBry7kpB3PBTJgUWsd5hiIeH5-5pnhJMx33H2ayJC-K2Vdkw8VhMhgdJq_6u3z0fugnwTWy7sVRhGU0dkcVz6jLPZsK3DycXSQKt7CDN7BjLt8YFq3jF_4DabpiDsBRpsTKKh_oIpX3xjI_FeffxXRaGyft3Sa3LCpoz6D1DmnJ_C65_sFSOO6RiQUtBejRArS0Ai0F8VEDWmqgRBG0tAKtPrIJWqpBSy1oqQbtfbL_5vVef-DYch9OFsb-wpFcxiIOUzcNwAoL-EkVp6lkkRKuZDzDRElcpkz7uCxQmHjJU5li0g9dEfgPyFp-kstHhIJ40ixU3ZCpMEhZyEUWuB4SThgcyaI2eVG87SSzufCxJMs0MZwMP0HRJEY0bbJVdj41KWBWd3uuxVb2-RtO2mSzIdfyAHC1QnDIWJtsFIJOrLaZJ_CwLgzHY94mtNwLpgDn90QuT5bQxfdxGt5ll3QBhwlzfMJZHhrgVFcHWx64Xb9N4gakyg6YiL65Jz-a6IT0HuNg9-GtPivBd9mbenzVN7VBblZ65AlZW8yW8in4AIt0U39jvwFHcg3Z |
| linkProvider | Geneva Foundation for Medical Education and Research |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Genetic+and+Clinical+Predictors+for+Breast+Cancer+Risk+Assessment+and+Stratification+Among+Chinese+Women&rft.jtitle=JNCI+%3A+Journal+of+the+National+Cancer+Institute&rft.au=Zheng%2C+Wei&rft.au=Wen%2C+Wanqing&rft.au=Gao%2C+Yu-Tang&rft.au=Shyr%2C+Yu&rft.date=2010-07-07&rft.pub=Oxford+University+Press&rft.issn=0027-8874&rft.eissn=1460-2105&rft.volume=102&rft.issue=13&rft.spage=972&rft.epage=981&rft_id=info:doi/10.1093%2Fjnci%2Fdjq170&rft.externalDBID=n%2Fa&rft.externalDocID=ark_67375_HXZ_DCG9XLN3_4 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0027-8874&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0027-8874&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0027-8874&client=summon |