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

描述（由申请方提供）：儿童恶性肿瘤的存活者存在与其治疗相关的严重长期发病率和过早死亡率风险。因儿童癌症接受胸部放射治疗的妇女在年轻时患乳腺癌的风险增加。我们使用术语胸部辐射来指包括以下领域的辐射：地幔，纵膈，肺，全身照射或脊柱。 预测乳腺癌绝对风险的模型，如众所周知的盖尔模型，已被广泛用于向患者提供关于其患乳腺癌的个体风险的建议，并设计预防试验。这些风险计算器中的大多数并不立即适用于先前恶性肿瘤的幸存者，他们的风险被先前的治疗所改变。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相关，存在相互矛盾的证据。传统的危险因素包括年龄、初潮年龄、第一个活产婴儿出生时的年龄、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病史。 我们建议利用北美儿童癌症幸存者研究（CCSS）和荷兰LATE效应登记（LATER）队列的独特资源。我们的第一个目标是开发一个风险预测模型，该模型整合了胸部辐射剂量和体积，治疗相关暴露，传统风险因素和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，以及激素替代或口服避孕药治疗的使用，以估计因儿童癌症接受胸部放疗的女性患乳腺癌的个体化绝对风险。该模型将使用原始CCSS队列开发，其中有1，677名接受胸部放射治疗的女性受试者将被纳入本分析。在这1，677名女性中，187名女性在本申请时已患乳腺癌。我们的第二个目标是在独立数据上验证预测模型。验证队列将包括扩展CCSS队列中的约1225名女性受试者和荷兰LATER队列中的1087名女性受试者。我们估计，这些妇女中约有100人将患乳腺癌。第三个目标是建立和传播一个风险计算器，提供计算机辅助风险预测。我们的目标是以一种易于访问的格式提供一种工具，并将其传播给医生和患者用于临床。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。 公共卫生相关性：因儿童癌症接受胸部放射治疗的妇女在年轻时有患乳腺癌的风险。我们的目标是量化女性乳腺癌的个体化风险，作为胸部辐射剂量的函数，其他治疗相关因素，传统的乳腺癌风险因素，如家族和生育史，以及其他非治疗相关的风险因素。这种风险预测模型有可能促进医生和患者之间的对话，并帮助完善目前对儿童癌症女性幸存者的筛查建议。

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.