Effects of violations of assumptions on likelihood methods for estimating the penetrance of an autosomal dominant mutation from kin-cohort studies
Effects of violations of assumptions on likelihood methods for estimating the penetrance of an autosomal dominant mutation from kin-cohort studies
复制标题
DOI：
10.1016/s0378-3758(00)00333-5
复制
发表时间：
2001-06-01
影响因子：
0.9
通讯作者：
Carroll, R
中科院分区：
文献类型：
--
作者：
Gail, MH;Pee, D;Carroll, R
Struewing et al（1997）使用亲属队列设计估计BRCA 1和BRCA 2基因常染色体显性突变女性的乳腺癌风险。在这种设计中，先证者自愿接受基因分型，然后报告他或她的一级亲属的病史（表型）。call等人（1999）利用亲属队列设计开发了常染色体显性基因参数的最大似然估计。在本文中，我们研究的影响，违反了关键假设的似然推理。如果有患病亲属的人比没有患病亲属的人更容易自愿成为先证者，则会导致严重高估疾病风险和等位基因频率。如果先证者没有报告其亲属中存在的所有疾病，则外显率将被低估，如果先证者给出疾病的假阳性报告，则可能导致外显率和等位基因频率的严重高估。研究中的基因以外的家族性疾病聚集性来源导致突变携带者的等位基因频率被高估，非携带者的等位基因频率被低估，等位基因频率被高估。除非样本量非常大，否则基于Wald程序的置信区间可能具有次标称覆盖率;有限的数值研究表明基于似然比的置信区间表现更好。出版社：Elsevier Science B. V.
Struewing et al, (1997) used the kin-cohort design to estimate the risk of breast cancer in women with autosomal dominant mutations in the genes BRCA1 and BRCA2. In this design, a proband volunteers to be genotyped and then reports the disease history (phenotype) of his or her first-degree relatives. call et al. (1999) developed maximum likelihood estimation of parameters for autosomal dominant genes with the kin-cohort design. In this paper we examine the effects of violations of key assumptions on likelihood-based inference. Serious overestimates of disease risk (penetrance) and allele frequency result if people with affected relatives tend to volunteer to be probands more readily than people without affected relatives. Penetrance will be underestimated if probands fail to report all the disease present among their relatives, and serious overestimates of penetrance and allele frequency can result if probands give false positive reports of disease. Sources of familial disease aggregation other than the gene under study result in overestimates of the penetrance in mutation carriers, underestimates of penetrance in noncarriers, and overestimates of allele frequency. Unless sample sizes are quite large, confidence intervals based on the Wald procedure can have subnominal coverage; limited numerical studies indicate that likelihood ratio-based confidence intervals perform better. Published by Elsevier Science B.V.