Abstract PR07: Comparison of risk model recommendations for women at high-risk of breast cancer based on clinical thresholds using the Prospective Family Study Cohort (ProF-SC)
M. Terry, K. Phillips, Y. Liao, R. MacInnis, G. Dite, M. Daly, E. John, I. Andrulis, S. Buys, R. Buchsbaum, J. Hopper
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Methods: We prospectively followed 16,285 women without breast cancer at baseline for an average of 10.2 years to compare the RLR and 10-year risk assigned by two commonly used risk estimation models for high risk women: 1) The International Breast Cancer Intervention Study tool (IBIS); and 2) the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). We compared the model-assigned 10-year risks with subsequent incidence of breast cancer in the cohort. We used chi-square statistics to assess calibration and the area under the receiver operating characteristic curve (AUC) to assess discrimination. Results: We observed differences between risk models in terms of the proportion of women classified as high-risk based on 20% or more RLR (IBIS=56% vs BOADICEA=23%). Only 21% of women were classified as high risk by both models, 35% of women were classified as high risk by IBIS only and 2% of women were classified as high risk by BOADICEA only. The difference was not evident (IBIS=52% vs BOADICEA=51%) when using a 10-year risk threshold of 3.34%. Using this 10-year threshold, 43% of women were classified as high risk by both models, 9% of women were classified as high risk by IBIS only and 8% of women were classified as high risk by BOADICEA only. IBIS risk predictions (mean=4.9%) were better calibrated to observed breast cancer incidence (5.8%, 95% confidence interval (CI)=5.4% to 6.2%) than were those based on BOADICEA (mean=4.2%). When we compared the magnitude of the discordancy between IBIS and BOADICEA by age, race/ethnicity, and number of relatives affected, we observed the extent of discordancy (e.g. one model resulted in a woman being above the clinical threshold when the other did not) depended on age. Specifically, for women under the age of 40 years, only 3.1% of women were high risk with IBIS but not BOADICEA compared with 7.5% classified as high risk by BOADICEA but not IBIS. Both models gave similar predictions of high risk with same proportion discordant for women over 50, and the same proportion discordant by race/ethnicity. When we compared the discordancy by those unaffected and affected with breast cancer after ten years of follow-up, 51% of unaffected women were high risk by IBIS using the 10-year threshold and 50% by BOADICEA with only 8% discordant (high risk on only one model). For women who were diagnosed with breast cancer prospectively after baseline, 75% were classified as high risk at baseline by IBIS and 72% were classified by BOADICEA with 8% high risk by IBIS only and 5% high risk by BOADICEA only. Conclusion: These results suggest that there is a considerable discordancy between two commonly used risk models to determine high risk classification for MRI and chemoprevention. There is a greater concordancy between the two models when using a shorter time-horizon, especially for women over the age of 50 years. However, as MRI and chemoprevention for high-risk women often needs to start before the age of 50 years, there is a great need to enhance risk assessment for these younger high risk women. Citation Format: Mary Beth Terry, Kelly-Anne Phillips, Yuyan Liao, Robert J. MacInnis, Gillian S. Dite, Mary B. Daly, Esther M. John, Irene L. Andrulis, Saundra S. Buys, Richard Buchsbaum, John L. Hopper. Comparison of risk model recommendations for women at high-risk of breast cancer based on clinical thresholds using the Prospective Family Study Cohort (ProF-SC). [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR07.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":"113 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Epidemiology and Prevention Biomarkers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1158/1538-7755.CARISK16-PR07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Clinical guidelines for classifying women as high-risk for breast cancer when considering chemoprevention and/or MRI screening options include thresholds of remaining lifetime risk (RLR) of 20% or more and/or a fixed time interval (e.g., 5-year risk of 1.67 or higher, 10-year risk of 3.34 or higher). Although clinicians have noted differences in risk estimates from the existing risk models, there have been few prospective validations using large cohorts to describe the magnitude of the discordancies between these models. Methods: We prospectively followed 16,285 women without breast cancer at baseline for an average of 10.2 years to compare the RLR and 10-year risk assigned by two commonly used risk estimation models for high risk women: 1) The International Breast Cancer Intervention Study tool (IBIS); and 2) the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). We compared the model-assigned 10-year risks with subsequent incidence of breast cancer in the cohort. We used chi-square statistics to assess calibration and the area under the receiver operating characteristic curve (AUC) to assess discrimination. Results: We observed differences between risk models in terms of the proportion of women classified as high-risk based on 20% or more RLR (IBIS=56% vs BOADICEA=23%). Only 21% of women were classified as high risk by both models, 35% of women were classified as high risk by IBIS only and 2% of women were classified as high risk by BOADICEA only. The difference was not evident (IBIS=52% vs BOADICEA=51%) when using a 10-year risk threshold of 3.34%. Using this 10-year threshold, 43% of women were classified as high risk by both models, 9% of women were classified as high risk by IBIS only and 8% of women were classified as high risk by BOADICEA only. IBIS risk predictions (mean=4.9%) were better calibrated to observed breast cancer incidence (5.8%, 95% confidence interval (CI)=5.4% to 6.2%) than were those based on BOADICEA (mean=4.2%). When we compared the magnitude of the discordancy between IBIS and BOADICEA by age, race/ethnicity, and number of relatives affected, we observed the extent of discordancy (e.g. one model resulted in a woman being above the clinical threshold when the other did not) depended on age. Specifically, for women under the age of 40 years, only 3.1% of women were high risk with IBIS but not BOADICEA compared with 7.5% classified as high risk by BOADICEA but not IBIS. Both models gave similar predictions of high risk with same proportion discordant for women over 50, and the same proportion discordant by race/ethnicity. When we compared the discordancy by those unaffected and affected with breast cancer after ten years of follow-up, 51% of unaffected women were high risk by IBIS using the 10-year threshold and 50% by BOADICEA with only 8% discordant (high risk on only one model). For women who were diagnosed with breast cancer prospectively after baseline, 75% were classified as high risk at baseline by IBIS and 72% were classified by BOADICEA with 8% high risk by IBIS only and 5% high risk by BOADICEA only. Conclusion: These results suggest that there is a considerable discordancy between two commonly used risk models to determine high risk classification for MRI and chemoprevention. There is a greater concordancy between the two models when using a shorter time-horizon, especially for women over the age of 50 years. However, as MRI and chemoprevention for high-risk women often needs to start before the age of 50 years, there is a great need to enhance risk assessment for these younger high risk women. Citation Format: Mary Beth Terry, Kelly-Anne Phillips, Yuyan Liao, Robert J. MacInnis, Gillian S. Dite, Mary B. Daly, Esther M. John, Irene L. Andrulis, Saundra S. Buys, Richard Buchsbaum, John L. Hopper. Comparison of risk model recommendations for women at high-risk of breast cancer based on clinical thresholds using the Prospective Family Study Cohort (ProF-SC). [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR07.
背景:在考虑化学预防和/或MRI筛查选择时,将女性划分为乳腺癌高危人群的临床指南包括剩余终生风险阈值(RLR)为20%或以上和/或固定时间间隔(例如,5年风险为1.67或更高,10年风险为3.34或更高)。尽管临床医生已经注意到风险估计与现有风险模型之间的差异,但很少有使用大型队列来描述这些模型之间不一致程度的前瞻性验证。方法:前瞻性随访16,285名基线时无乳腺癌的女性,平均随访10.2年,比较两种常用的高风险女性风险估计模型的RLR和10年风险:1)国际乳腺癌干预研究工具(IBIS);2)乳腺卵巢疾病发病率分析及载体估计算法(BOADICEA)。我们将模型分配的10年风险与队列中随后的乳腺癌发病率进行了比较。我们用卡方统计来评估校准,用受试者工作特征曲线下面积(AUC)来评估鉴别。结果:我们观察到基于20%或以上RLR的高风险女性比例在不同风险模型之间存在差异(IBIS=56% vs BOADICEA=23%)。只有21%的妇女被两种模型归为高风险,35%的妇女仅被IBIS归为高风险,2%的妇女仅被BOADICEA归为高风险。当使用3.34%的10年风险阈值时,差异不明显(IBIS=52% vs BOADICEA=51%)。使用这个10年阈值,43%的妇女被两种模型归为高风险,9%的妇女仅被IBIS归为高风险,8%的妇女仅被BOADICEA归为高风险。IBIS风险预测(平均=4.9%)比基于BOADICEA的预测(平均=4.2%)更好地校准到观察到的乳腺癌发病率(5.8%,95%置信区间(CI)=5.4%至6.2%)。当我们比较IBIS和BOADICEA在年龄、种族/民族和受影响亲属数量上的不一致程度时,我们观察到不一致的程度(例如,一个模型导致女性高于临床阈值,而另一个模型没有)取决于年龄。具体来说,对于40岁以下的女性,只有3.1%的女性患有IBIS而不是BOADICEA,而7.5%的女性被BOADICEA列为高风险,而不是IBIS。两种模型都给出了类似的高风险预测,对50岁以上的女性有相同比例的不一致,对种族/民族也有相同比例的不一致。当我们比较未受影响和受影响的乳腺癌患者在10年随访后的不一致性时,51%的未受影响的女性在IBIS使用10年阈值时为高风险,50%的BOADICEA为高风险,只有8%的不一致性(只有一种模型的高风险)。基线后被诊断为乳腺癌的女性,75%在基线时被IBIS分类为高风险,72%被BOADICEA分类为高风险,仅IBIS分类为8%高风险,仅BOADICEA分类为5%高风险。结论:这些结果表明,在确定MRI和化学预防的高危分类时,两种常用的风险模型之间存在相当大的不一致性。在较短的时间范围内,特别是50岁以上的妇女,这两种模式之间的一致性更大。然而,由于高风险女性的MRI和化学预防通常需要在50岁之前开始,因此非常需要加强对这些年轻高风险女性的风险评估。引文格式:Mary Beth Terry, Kelly-Anne Phillips, Yuyan Liao, Robert J. MacInnis, Gillian S. Dite, Mary B. Daly, Esther M. John, Irene L. Andrulis, Saundra S. Buys, Richard Buchsbaum, John L. Hopper。使用前瞻性家庭研究队列(profo - sc)比较基于临床阈值的高危女性乳腺癌风险模型建议[摘要]。摘自:AACR特别会议论文集:改进癌症风险预测以预防和早期发现;2016年11月16日至19日;费城(PA): AACR;癌症流行病学生物标志物pre2017;26(5增刊):摘要nr PR07。