18 research outputs found
Schematic diagrams of the location of the seven SNPs in IGF1R and strength of the pairwise-linkage disequilibrium (LD) between SNPs.
<p>Strengths of the LD between SNPs were indicated by the color scheme, measured using a combination of the statistic D’ and the LOD score.</p
Analysis of the association between IGF1R gene under additive model and the risk of breast cancer.
<p>OR (CI 95%)<sup>1</sup>: Multivariate logistic regression model. Adjusted for age at diagnosis, BMI, age at menarche, and age at first parturition.</p><p><sup>2</sup> Tests for trend were conducted by coding for the number of variant alleles and reporting the <i>p</i>-value from models based on logistic regression analyses.</p
Haplotype analysis of the association between IGF1R under three genetic models and the risk of breast cancer.
<p>Percentage of genotype among group.</p><p>OR (CI95%)<sup>1</sup>: Univariate logistic regression model.</p><p>OR (CI95%)<sup>2</sup>: Multivariate logistic regression model. Adjusted for age at diagnosis, BMI, age at menarche, and age at first parturition.</p><p><sup>a</sup> Breast cancer risk for heterozygotes (AB) and homozygotes (BB), each compared with major allele homozygotes (AA) in model adjusted genotyping.</p><p><sup>b</sup> Breast cancer risk for minor allele carriers (AB/BB) compared with major allele homozygotes (AA) in model adjusted for genotyping.</p><p><sup>c</sup> Breast cancer risk for minor allele homozygotes (BB) compared with major allele carriers (AA/AB) in model adjusted for genotyping.</p><p>SNPs’ location on chromosome number.</p
IGF1R allele frequencies and genotype distribution in breast cancer controls and cases.
<p>Frequency of alleles among total genotyped subjects.</p
Correlation between the tumour roundness and recurrence score.
<p>The correlation plot shows a positive relationship between the tumour roundness and recurrence score (r = 0.349).</p
Receiver-operating characteristic curve determined by multivariate logistic regression analysis for distinguishing high recurrence scores from low or intermediate recurrence scores: parallel orientation, tumour roundness, lymphovascular invasion, PR negativity, and high Ki-67 are predictors of recurrence.
<p>Data in parentheses indicate the A<sub>z</sub> values for the each variables.</p
Multivariate analysis of factors associated with high recurrence scores.
<p>Multivariate analysis of factors associated with high recurrence scores.</p
Receiver-operating characteristic curve determined by multivariate logistic regression analysis for distinguishing low recurrence scores from high or intermediate recurrence scores: tumour roundness, absence of calcification in the mass, lymphovascular invasion, PR positivity, nuclear grade, and p53 are predictors of recurrence.
<p>Data in parentheses indicate the A<sub>z</sub> values for the each variables.</p
Multivariate analysis of factors associated with low recurrence scores.
<p>Multivariate analysis of factors associated with low recurrence scores.</p
Association between US features and recurrence scores by univariate analysis.
<p>Association between US features and recurrence scores by univariate analysis.</p