Background: Subsequent thyroid cancer (STC) is one of the most common malignancies in childhood cancer survivors. We aimed to evaluate the polygenic contributions to STC risk and potential utility in improving risk prediction. Methods: A polygenic risk score (PRS) was calculated from 12 independent SNPs associated with thyroid cancer risk in the general population. Associations between PRS and STC risk were evaluated among survivors from St. Jude Lifetime Cohort (SJLIFE) and were replicated in survivors from Childhood Cancer Survivor Study (CCSS). A risk prediction model integrating the PRS and clinical factors, initially developed in SJLIFE, and its performance were validated in CCSS. Results: Among 2,370 SJLIFE survivors with a median follow-up of 28.8 [interquartile range (IQR) = 21.9–36.1] years, 65 (2.7%) developed STC. Among them, the standardized PRS was associated with an increased rate of STC [relative rate (RR) = 1.57; 95% confidence interval (CI) = 1.24–1.98; P < 0.001]. Similar associations were replicated in 6,416 CCSS survivors, among whom 121 (1.9%) developed STC during median follow-up of 28.9 (IQR = 22.6–34.6) years (RR = 1.52; 95% CI = 1.25–1.83; P < 0.001). A risk prediction model integrating the PRS with clinical factors showed better performance than the model considering only clinical factors in SJLIFE ( P = 0.004, AUC = 83.2% vs. 82.1%, at age 40), which was further validated in CCSS ( P = 0.010, AUC = 72.9% vs. 70.6%). Conclusions: Integration of the PRS with clinical factors provided a statistically significant improvement in risk prediction of STC, although the magnitude of improvement was modest. Impact: PRS improves risk stratification and prediction of STC, suggesting its potential utility for optimizing screening strategies in survivorship care.

中文翻译：

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多基因风险评分改善儿童癌症后继发甲状腺癌的风险分层和预测

背景：继发性甲状腺癌（STC）是儿童癌症幸存者最常见的恶性肿瘤之一。我们旨在评估多基因对 STC 风险的贡献以及在改进风险预测方面的潜在效用。方法：从 12 个与普通人群甲状腺癌风险相关的独立 SNP 计算多基因风险评分 (PRS)。在 St. Jude Lifetime Cohort (SJLIFE) 的幸存者中评估了 PRS 和 STC 风险之间的关联，并在儿童癌症幸存者研究 (CCSS) 的幸存者中进行了复制。最初在 SJLIFE 开发的整合 PRS 和临床因素的风险预测模型，其性能在 CCSS 中得到验证。结果：在中位随访时间为 28.8 [四分位距 (IQR) = 21.9–36.1] 年的 2,370 名 SJLIFE 幸存者中，65 名 (2.7%) 患上了 STC。其中，标准化 PRS 与 STC 率增加相关 [相对率 (RR) = 1.57；95% 置信区间 (CI) = 1.24–1.98；P < 0.001]。在 6,416 名 CCSS 幸存者中复制了类似的关联，其中 121 名 (1.9%) 在中位随访 28.9 (IQR = 22.6-34.6) 年期间发展为 STC (RR = 1.52; 95% CI = 1.25-1.83; P < 0.001) . 在 SJLIFE 中，将 PRS 与临床因素相结合的风险预测模型比仅考虑临床因素的模型表现出更好的性能（P = 0.004，AUC = 83.2% vs. 82.1%，在 40 岁时），这在 CCSS 中得到了进一步验证（P = 0.010，AUC = 72.9% 对 70.6%）。结论：PRS 与临床因素的整合提供了 STC 风险预测的统计学显着改善，尽管改善幅度不大。影响：