Prediction Model: Breast Cancer in Women Irradiated for a Pediatric Malignancy

描述（由申请人提供）：儿童恶性肿瘤的幸存者存在与治疗相关的严重长期发病率和过早死亡的风险。接受过胸部放射治疗的儿童癌症患者在年轻时患乳腺癌的风险增加。我们使用术语胸部放射是指包括以下领域的放射：地幔、纵隔、肺、全身照射或脊柱。预测乳腺癌绝对风险的模型，如著名的盖尔模型，已被广泛用于向患者提供患乳腺癌的个人风险建议，并设计预防试验。这些风险计算器中的大多数不能立即适用于既往恶性肿瘤的幸存者，他们的风险因既往治疗而改变。此外，关于各种非治疗相关因素，包括传统的乳腺癌风险因素，是否与这些妇女患乳腺癌的风险有关，证据相互矛盾。传统的危险因素包括年龄、初潮年龄、第一个活产儿出生年龄、患乳腺癌的一级亲属人数、既往乳腺活检次数和非典型增生史。我们建议利用北美儿童癌症幸存者研究（CCSS）和荷兰晚期效应登记（LATER）队列的独特资源。我们的第一个目标是建立一个风险预测模型，该模型综合了胸部辐射剂量和体积、治疗相关暴露、传统风险因素以及其他可能的风险因素，如绝经年龄、体重指数、放疗后卵巢功能完好的年数，以及使用激素替代或口服避孕药治疗。为了估计因儿童癌症而接受胸部放射治疗的女性患乳腺癌的个体化绝对风险。该模型将使用最初的CCSS队列来开发，其中有1,677名接受胸部放射治疗的女性参与者，并将被纳入本分析。在这1677名女性中，187名女性在申请时已经患上了乳腺癌。我们的第二个目标是在独立数据上验证预测模型。验证队列将包括扩大CCSS队列中的1225名女性参与者和荷兰late队列中的1087名女性参与者。我们估计这些女性中大约有100人会患乳腺癌。第三个目标是创建和传播一种提供计算机辅助风险预测的风险计算器。我们的目标是提供一种易于使用的工具，并传播给医生和患者临床使用。该项目的长期目标是提供一种手段，促进医生和患者之间就适当的筛查和预防策略进行对话，并帮助完善针对这一人群的筛查建议。

DESCRIPTION (provided by applicant): Survivors of a pediatric malignancy are at risk for serious long-term morbidity and premature mortality related to their treatment. Women who were treated with chest radiation for their childhood cancer have an increased risk of developing breast cancer at a young age. We use the term chest radiation to refer to radiation that includes the following fields: mantle, mediastinal, lung, total body irradiation, or spinal. Models for predicting the absolute risk of breast cancer, such as the well-known Gail model, have been used extensively to advise patients on their individual risk of developing breast cancer and to design prevention trials. The majority of these risk calculators are not immediately applicable to survivors of a previous malignancy who have a risk that is modified by previous treatments. Moreover, there is conflicting evidence as to whether various non-treatment related factors, including the traditional breast cancer risk factors, are associated with the risk of breast cancer in these women. The traditional risk factors include age, age at menarche, age at birth of first live child, number of first-degree relatives with breast cancer, number of previous breast biopsies, and history of atypical hyperplasia. We propose to utilize the unique resources of the North American Childhood Cancer Survivor Study (CCSS) and the Dutch LATe Effect Registry (LATER) cohorts. Our first aim is to develop a risk prediction model that integrates chest radiation dose and volume, treatment-related exposures, the traditional risk factors, and other possible risk factors such as age at menopause, body mass index, the number of years with intact ovarian function after radiotherapy, and use of hormone replacement or oral contraceptive therapy, in order to estimate the individualized absolute risk of breast cancer for women who were treated with chest radiation for a childhood cancer. The model will be developed using the original CCSS cohort in which there are 1,677 female participants who were treated with chest radiation and would be included in this analysis. Of these 1,677 women, 187 women had developed breast cancer by the time of this application. Our second aim is to validate the prediction model on independent data. The validation cohort will consist of about 1225 female participants in the expanded CCSS cohort and 1087 female participants in the Dutch LATER cohort. We estimate that approximately 100 of these women will have breast cancer. The third aim is to create and disseminate a risk calculator that provides computer-assisted risk prediction. Our objective is to present a tool in an easily accessible format and disseminate it for clinical use by physicians and patients. The long-term goals of this project are to provide a means for facilitating conversations between physicians and their patients about appropriate screening and preventive strategies and to help refine screening recommendations for this population. PUBLIC HEALTH RELEVANCE: Women who were treated with chest radiation for a childhood cancer are at risk of developing breast cancer at a young age. We aim to quantify a woman's individualized risk of breast cancer as a function of the dose of radiation to the chest, other treatment-related factors, the traditional breast cancer risk factors such as family and reproductive histories, and other non-treatment related risk factors. This risk prediction model has the potential to facilitate conversations between physicians and patients and to help refine current screening recommendations for female survivors of a pediatric cancer.