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系统评价用于预测早期乳腺癌病理完全缓解的列线图。

Systematic Review of Nomograms Used for Predicting Pathological Complete Response in Early Breast Cancer.

机构信息

Mastology Department, Hospital do Servidor Público Estadual, Francisco Morato de Oliveira, São Paulo 04029-000, Brazil.

Mastology Department, Women's Health Hospital, São Paulo 01206-001, Brazil.

出版信息

Curr Oncol. 2023 Oct 16;30(10):9168-9180. doi: 10.3390/curroncol30100662.

Abstract

Pathological complete response (pCR) is an important surrogate outcome to assess the effects of neoadjuvant chemotherapy (NAC). Nomograms to predict pCR have been developed with local data to better select patients who are likely to benefit from NAC; however, they were never critically reviewed regarding their internal and external validity. The purpose of this systematic review was to critically appraise nomograms published in the last 20 years (2010-2022). Articles about nomograms were searched in databases, such as PubMed/MEDLINE, Embase and Cochrane. A total of 1120 hits were found, and seven studies were included for analyses. No meta-analysis could be performed due to heterogeneous reports on outcomes, including the definition of pCR and subtypes. Most nomograms were developed in Asian centers, and nonrandomized retrospective cohorts were the most common sources of data. The most common subtype included in the studies was triple negative (50%). There were articles that included HER2+ (>80%). In one study, scholars performed additional validation of the nomogram using DFS and OS as outcomes; however, there was a lack of clarity on how such endpoints were measured. Nomograms to predict pCR cannot be extrapolated to other settings due to local preferences/availability of NAC. The main gaps identified in this review are also opportunities for future nomogram research and development.

摘要

病理完全缓解 (pCR) 是评估新辅助化疗 (NAC) 效果的重要替代终点。已经使用局部数据开发了预测 pCR 的列线图,以更好地选择可能从 NAC 中获益的患者;然而,它们从未在内部和外部有效性方面受到严格审查。本系统评价的目的是批判性地评估过去 20 年(2010-2022 年)发表的列线图。在 PubMed/MEDLINE、Embase 和 Cochrane 等数据库中搜索关于列线图的文章。共发现 1120 个靶点,纳入了 7 项研究进行分析。由于结局报告存在异质性,包括 pCR 和亚型的定义,无法进行荟萃分析。大多数列线图是在亚洲中心开发的,非随机回顾性队列是数据的最常见来源。研究中最常见的亚型是三阴性(50%)。也有文章包含 HER2+ (>80%)。在一项研究中,学者们使用 DFS 和 OS 作为结局进一步验证了列线图;然而,对于如何测量这些终点,尚不清楚。由于局部对 NAC 的偏好/可用性,预测 pCR 的列线图不能外推到其他环境。本综述中确定的主要差距也是未来列线图研究和开发的机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f38/10605609/0173fe53cfaa/curroncol-30-00662-g001.jpg

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