A clinical calculator to predict disease outcomes in women with hormone receptor-positive advanced breast cancer treated with first-line endocrine therapy

用于预测接受一线内分泌治疗的激素受体阳性晚期乳腺癌女性患者疾病预后的临床计算器

阅读:1

Abstract

PURPOSE: Endocrine therapy (ET) is an effective strategy to treat hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) advanced breast cancer (ABC) but nearly all patients eventually progress. Our goal was to develop and validate a web-based clinical calculator for predicting disease outcomes in women with HR+ABC who are candidates for receiving first-line single-agent ET. METHODS: The meta-database comprises 891 patient-level data from the control arms of five contemporary clinical trials where patients received first-line single-agent ET (either aromatase inhibitor or fulvestrant) for ABC. Risk models were constructed for predicting 24-months progression-free survival (PFS-24) and 24-months overall survival (OS-24). Final models were internally validated for calibration and discrimination using ten-fold cross-validation. RESULTS: Higher number of sites of metastases, measurable disease, younger age, lower body mass index, negative PR status, and prior endocrine therapy were associated with worse PFS. Final PFS and OS models were well-calibrated and associated with cross-validated time-dependent area under the curve (AUC) of 0.61 and 0.62, respectively. CONCLUSIONS: The proposed ABC calculator is internally valid and can accurately predict disease outcomes. It may be used to predict patient prognosis, aid planning of first-line treatment strategies, and facilitate risk stratification for future clinical trials in patients with HR+ABC. Future validation of the proposed models in independent patient cohorts is warranted.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。