Niendorf K B, Goggins W, Yang G, Tsai K Y, Shennan M, Bell D W, Sober A J, Hogg D, Tsao H
Center for Cancer Risk Analysis, Massachusetts General Hospital, Boston, MA 02114, USA.
J Med Genet. 2006 Jun;43(6):501-6. doi: 10.1136/jmg.2005.032441. Epub 2005 Sep 16.
Heritable alterations in CDKN2A account for a subset of familial melanoma cases although no robust method exists to identify those at risk of being a mutation carrier.
We set out to construct a model for estimating CDKN2A mutation carrier probability using a cohort of 116 consecutive familial cutaneous melanoma patients evaluated at Massachusetts General Hospital Pigmented Lesion Center between April 2001 and September 2004. Germline CDKN2A and CDK4 status on the familial melanoma cases and clinical features associated with mutational status were then used to build a multiple logistic regression model to predict carrier probability and performance of model on external validation.
From the 116 kindreds prone to melanoma in the Boston area, 13 CDKN2A mutation carriers were identified and 12 were subsequently used in the modeling. Proband age at diagnosis, number of proband primaries, and number of additional family primaries were most closely associated with germline mutations. The estimated probability of the proband being a mutation carrier based on the logistic regression model (MELPREDICT) is given by e(L)/(1 + e(L) where L = 1.99+[0.92x(no. of proband primaries)]+[0.74x(no. of additional family primaries)]-[2.11xln(age)]. The mean estimated probabilities for subjects in the Boston dataset were 55.4% and 5.1% for the mutation carriers and non-carriers respectively. In a receiver operator characteristic analysis, the area under the curve was 0.881 (95% confidence interval 0.739 to 1.000) for the Boston model set (n = 116) and 0.803 (0.729 to 0.877) for an external Toronto hereditary melanoma cohort (n = 143).
These results represent the first-iteration logistic regression model to approximate CDKN2A carrier probability. Validation of this model with an external dataset revealed relatively robust performance.
CDKN2A基因的遗传性改变占家族性黑色素瘤病例的一部分，尽管目前尚无可靠方法来识别那些有成为突变携带者风险的个体。
我们着手构建一个模型，以估计CDKN2A突变携带者概率。该模型使用了2001年4月至2004年9月间在马萨诸塞州总医院色素病变中心接受评估的116例连续的家族性皮肤黑色素瘤患者队列。然后，利用家族性黑色素瘤病例的种系CDKN2A和CDK4状态以及与突变状态相关的临床特征，建立多元逻辑回归模型，以预测携带者概率，并在外部验证中评估模型性能。
在波士顿地区的116个易患黑色素瘤的家族中，鉴定出13例CDKN2A突变携带者，其中12例随后用于建模。先证者诊断时的年龄、先证者原发肿瘤数量以及家族中其他原发肿瘤数量与种系突变关系最为密切。基于逻辑回归模型（MELPREDICT）的先证者为突变携带者的估计概率由e(L)/(1 + e(L)给出，其中L = 1.99 + [0.92×(先证者原发肿瘤数量)] + [0.74×(家族中其他原发肿瘤数量)] - [2.11×ln(年龄)]。波士顿数据集中突变携带者和非携带者的平均估计概率分别为55.4%和5.1%。在受试者工作特征分析中，波士顿模型集（n = 116）的曲线下面积为0.881（95%置信区间0.739至1.000），外部多伦多遗传性黑色素瘤队列（n = 143）的曲线下面积为0.803（0.729至0.877）。
这些结果代表了第一个用于估算CDKN2A携带者概率的迭代逻辑回归模型。用外部数据集对该模型进行验证显示其性能相对稳健。
