A Model for Individualized Risk Prediction of Contralateral Breast Cancer

对侧乳腺癌个体化风险预测模型

• 批准号: 8692361
• 负责人: Swati Biswas
• 金额: $ 23.71万
• 依托单位: UNIVERSITY OF TEXAS DALLAS
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8692361
• 关键词: Abate; Adjuvant Therapy; Age; Benefits and Risks; Breast; Breast Cancer Risk Assessment Tool; Cancer Center; Cancer Patient; Characteristics; Clinical; Communities; Computer software; Contralateral; Counseling; Data; Databases; Diagnosis; Drops; Education; Emotional; Family; Future; General Population; Hospitals; Institution; Licensing; Literature; Malignant Neoplasms; Mastectomy; Measures; Medical; Medical center; Meta-Analysis; Modeling; Nature; Noninfiltrating Intraductal Carcinoma; Patient Education; Patients; Perception; Physicians; Population; Preventive; Recording of previous events; Risk; Risk Assessment; Risk Estimate; Risk Factors; Rosa; SEER Program; Site; Statistical Models; Texas; Time; Trauma; Universities; Variant; Woman; base; cancer risk; design; fighting; foot; malignant breast neoplasm; medical schools; medically necessary care; non-genetic; population based; prophylactic; prospective; public health relevance; sound; stem; tool; trend; tumor; user-friendly

Project Summary Patients diagnosed with invasive breast cancer or ductal carcinoma in situ are increasingly choosing to undergo contralateral prophylactic mastectomy (CPM) to reduce their risk of contralateral breast cancer (CBC). This is a particularly disturbing trend as a large number of these CPMs are believed to be medically unnecessary. This is because the risk of CBC has dropped markedly for most patients in the last two decades due to availability of effective adjuvant therapies. Despite this fact, patients diagnosed with first primary breast cancer tend to substantially overestimate their CBC risk. At the same time, they underestimate the complications, risks, and negative effects associated with CPM. These incorrect perceptions partly explain the rising CPM rates in the U.S. Morever, there is little evidence that CPM helps in prolonging survival. Thus, the benefits of CPM need to be weighed properly with its drawbacks. Given the invasive and irreversible nature of CPM, it behooves us to provide sound and effective education to breast cancer patients, who are going through an emotionally challenging period. Physicians do try to educate their patients; however, they lack tools that can help them in this endeavor. In particular, they need a CBC risk prediction model that can provide individualized risk estimates for sporadic (non-genetic) breast cancer patients. This project aims to fill this need by developing such a model, validating it, and implementing it in a freely available software package for immediate clinical use. To build the model, we will use data from Surveillance, Epidemiology, and End Results (SEER) Program and meta-analysis of risk estimates from literature. The proposed model will be in the style of the Gail model - a popular tool for counseling women on the risk of developing breast cancer - but one that is exclusively designed for counseling women with unilateral breast cancer on the risk of developing CBC. After building the model, we will validate it on prospectively collected data on breast cancer patients from four institutions - University of Texas at Southwestern Medical Center, Parkland Memorial Hospital in Dallas, M D Anderson Cancer Center, and Dartmouth Medical School. Once the model is validated, we will create a user- friendly package in statistical software R for implementing the model. Then we will integrate the package into CancerGene, a widely used and freely available clinical software for counseling patients on the risk of breast cancer. CancerGene is licensed to more than 4000 sites worldwide and therefore will be a perfect gateway to make the new model available to a large number of practitioners. We believe our proposed model will greatly facilitate patients' education and will help stem the increasing trend of medically unnecessary CPMs.

项目概要 诊断患有浸润性乳腺癌或导管原位癌的患者越来越多地选择 接受对侧预防性乳房切除术 (CPM)，以降低患对侧乳腺癌 (CBC) 的风险。 这是一个特别令人不安的趋势，因为据信这些 CPM 中有大量是医学上的问题。 不必要。这是因为在过去二十年中，大多数患者的 CBC 风险显着下降 由于有效的辅助疗法的可用性。尽管如此，诊断出患有第一原发性乳房的患者 癌症往往会大大高估他们的 CBC 风险。与此同时，他们也低估了 与 CPM 相关的并发症、风险和负面影响。这些不正确的认识部分解释了 美国 CPM 率不断上升 此外，几乎没有证据表明 CPM 有助于延长生存期。因此， 需要正确权衡 CPM 的优点和缺点。鉴于其侵入性和不可逆性 CPM，我们有必要为即将到来的乳腺癌患者提供健全有效的教育 度过一段情感上充满挑战的时期。医生确实尽力教育他们的病人；然而，他们缺乏工具 这可以帮助他们实现这一目标。特别是，他们需要一个 CBC 风险预测模型，可以提供 散发性（非遗传性）乳腺癌患者的个体化风险评估。该项目旨在满足这一需求 通过开发这样的模型，验证它，并在免费可用的软件包中实现它 立即临床使用。为了构建模型，我们将使用来自监测、流行病学和最终结果的数据 (SEER) 对文献风险估计的程序和荟萃分析。拟议的模型将采用以下风格 盖尔模型——一种为女性提供有关患乳腺癌风险咨询的流行工具——但该模型 专门为患有单侧乳腺癌的女性提供关于患 CBC 风险的咨询。后 构建模型后，我们将根据前瞻性收集的来自四个乳腺癌患者的数据对其进行验证 机构 - 德克萨斯大学西南医学中心、位于马里兰州达拉斯的帕克兰纪念医院 安德森癌症中心和达特茅斯医学院。一旦模型被验证，我们将创建一个用户- 统计软件 R 中用于实现模型的友好包。然后我们将这个包集成到 CancerGene，一种广泛使用且免费提供的临床软件，用于为患者提供有关乳腺癌风险的咨询 癌症。 CancerGene 已授权给全球 4000 多个站点，因此将成为 使新模式可供广大从业者使用。我们相信我们提出的模型将极大地 促进患者教育，并将有助于遏制医疗上不必要的 CPM 日益增长的趋势。