Development and Validation of a Prognostic Nomogram for HR+ HER- Breast Cancer

IF 2.5 4区 医学 Q3 ONCOLOGY Cancer Management and Research Pub Date : 2024-05-21 DOI:10.2147/cmar.s459714
Jie-Yu Zhou, Cheng-Geng Pan, Yang Ye, Zhi-Wei Li, Wei-Da Fu, Bin-Hao Jiang
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Abstract

Purpose: We aimed to develop a nomogram to predict prognosis of HR+ HER2- breast cancer patients and guide the application of postoperative adjuvant chemotherapy.
Methods: We identified 310 eligible HR+ HER- breast cancer patients and randomly divided the database into a training group and a validation group. The endpoint was disease free survival (DFS). Concordance index (C-index), area under the curve (AUC) and calibration curves were used to evaluate predictive accuracy and discriminative ability of the nomogram. We also compared the predictive accuracy and discriminative ability of our nomogram with the eighth AJCC staging system using overall data.
Results: According to the training group, platelet-to-lymphocyte ratio (PLR), tumor size, positive lymph nodes and Ki-67 index were used to construct the nomogram of DFS. The C-index of DFS was 0.708 (95% CI: 0.623– 0.793) in the training group and 0.67 (95% CI: 0.544– 0.796) in the validation group. The calibration curves revealed great consistencies in both groups.
Conclusion: We have developed and validated a novel and practical nomogram that can provide individual prediction of DFS for patients with HR+ HER- breast cancer. This nomogram may help clinicians in risk consulting and guiding the application of postoperative adjuvant chemotherapy.

Keywords: nomograms, prognosis, prediction, HR+ HER- breast cancer, chemotherapy
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HR+ HER- 乳腺癌预后提名图的开发与验证
目的:我们旨在开发一种预测HR+ HER2-乳腺癌患者预后的提名图,并指导术后辅助化疗的应用:我们确定了 310 名符合条件的 HR+ HER- 乳腺癌患者,并将数据库随机分为训练组和验证组。终点为无病生存期(DFS)。采用一致性指数(C-index)、曲线下面积(AUC)和校准曲线来评估提名图的预测准确性和判别能力。我们还利用总体数据比较了我们的提名图与 AJCC 第八分期系统的预测准确性和鉴别能力:结果:根据训练组的数据,血小板淋巴细胞比值(PLR)、肿瘤大小、阳性淋巴结和 Ki-67 指数被用于构建 DFS 的提名图。训练组 DFS 的 C 指数为 0.708(95% CI:0.623- 0.793),验证组为 0.67(95% CI:0.544- 0.796)。两组的校准曲线显示出极大的一致性:我们开发并验证了一种新颖实用的提名图,它可以对 HR+ HER- 乳腺癌患者的 DFS 进行个体预测。该提名图可帮助临床医生进行风险咨询并指导术后辅助化疗的应用。关键词:提名图、预后、预测、HR+ HER- 乳腺癌、化疗
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来源期刊
Cancer Management and Research
Cancer Management and Research Medicine-Oncology
CiteScore
7.40
自引率
0.00%
发文量
448
审稿时长
16 weeks
期刊介绍: Cancer Management and Research is an international, peer reviewed, open access journal focusing on cancer research and the optimal use of preventative and integrated treatment interventions to achieve improved outcomes, enhanced survival, and quality of life for cancer patients. Specific topics covered in the journal include: ◦Epidemiology, detection and screening ◦Cellular research and biomarkers ◦Identification of biotargets and agents with novel mechanisms of action ◦Optimal clinical use of existing anticancer agents, including combination therapies ◦Radiation and surgery ◦Palliative care ◦Patient adherence, quality of life, satisfaction The journal welcomes submitted papers covering original research, basic science, clinical & epidemiological studies, reviews & evaluations, guidelines, expert opinion and commentary, and case series that shed novel insights on a disease or disease subtype.
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