The effect of sample size on polygenic hazard models for prostate cancer.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69–1.77] to 2.41 [2.40–2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93–1.18] to 2.19 [2.16–2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70–1.85] and 1.73 [1.71–1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

我们确定了样本量对前列腺癌多基因风险评分（PHS）模型性能的影响。从PRACTICAL联盟获取了40861名男性的年龄和基因型。该数据集包含每个受试者201590个单核苷酸多态性（SNP），并被分为训练集和测试集。已确定SNP模型考虑了65个先前与前列腺癌相关的SNP。发现SNP模型采用逐步选择法来识别新的SNP。针对训练集的随机大小计算了每个PHS模型的性能。针对测试集的随机大小估计了一个代表性已确定SNP模型的性能。当训练样本数量从1000增加到30000时，已确定SNP模型的平均HR98/50（测试集中前2%与平均值的风险比）从1.73[95%置信区间：1.69 - 1.77]增加到2.41[2.40 - 2.43]。发现SNP模型相应的HR98/50从1.05[0.93 - 1.18]增加到2.19[2.16 - 2.23]。使用测试集样本量分别为600和6000个观测值的一个代表性已确定SNP模型的HR98/50分别为1.78[1.70 - 1.85]和1.73[1.71 - 1.76]。我们估计开发发现SNP PHS模型需要20000名男性的研究人群，而对于已确定SNP模型，10000名男性应该就足够了。