Early Tumor Shrinkage and Depth of Response as Predictive Markers of Treatment Response and Prognosis in Solid Tumors

IF 3.1 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2025-09-17 DOI:10.1002/cam4.71251

Peng Cao, Xiaojuan Yang

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引用次数: 0

Abstract

Background

Evaluation of tumor efficacy is central to cancer care. Progression-free survival (PFS) is widely used as an early surrogate for treatment effectiveness, but more timely and reliable biomarkers are needed. Early tumor shrinkage (ETS) and depth of response (DpR) have emerged as promising predictors: ETS reflects early treatment sensitivity at first radiologic assessment, whereas DpR quantifies the maximum tumor reduction and may capture the durability of benefit.

Methods

We conducted a narrative synthesis of clinical studies assessing ETS and/or DpR across solid tumors, focusing on their definitions, measurement under RECIST, and associations with PFS and overall suvival (OS). We also summarized advances in imaging and multidimensional assessment framworks that could improve the accuracy and clinical utility of these indicators, and highlighted sources of heterogeneity and current gaps.

Results

Across multiple retrospective and post-hoc analyses, ETS provides an early signal that identifies patients more likely to benefit from therapy and can inform treatment adaptation. DpR shows consisten correlations with long-term outcomes and complements PFS by reflecting the magnitude of tumor control. Both ETS and DpR demonstrate predictive value for PFS and OS; however, variability in cut-offs (e.g., ETS 20%–30%), timing of assessments, tumor types, and treatment modalities limits comparability. Emerging imaging technologies and composite response frameworks offer opportunities to enhance measurement precision and reproducibility.

Conclusions

ETS and DpR are promising, clinically interpretable markers for monitoring treatment effcacy and prognosis. Standardized definitons, prospective validation, and integration with molecular and imaging biomarkers (e.g., ctDNA, radiomics, and machine—learning—enhanced imaging) are needed to refine their application and solidify their role in routine cancer therapy monitoring.

Abstract Image

查看原文本刊更多论文

早期肿瘤缩小和反应深度作为实体瘤治疗反应和预后的预测指标。

背景：肿瘤疗效评价是肿瘤治疗的核心。无进展生存期（PFS）被广泛用作治疗有效性的早期替代指标，但需要更及时、更可靠的生物标志物。早期肿瘤缩小（ETS）和反应深度（DpR）已成为有希望的预测指标：ETS反映了首次放射学评估时的早期治疗敏感性，而DpR量化了最大肿瘤缩小并可能捕获获益的持久性。方法：我们对实体肿瘤中评估ETS和/或DpR的临床研究进行了叙叙性综合，重点关注它们的定义、RECIST下的测量以及与PFS和总生存期（OS）的关联。我们还总结了成像和多维评估框架的进展，这些框架可以提高这些指标的准确性和临床实用性，并强调了异质性的来源和当前的差距。结果：通过多项回顾性和事后分析，ETS提供了一个早期信号，可以识别更有可能从治疗中受益的患者，并可以为治疗适应提供信息。DpR与长期预后具有一致的相关性，并通过反映肿瘤控制的程度来补充PFS。ETS和DpR对PFS和OS均具有预测价值；然而，截止值（如ETS 20%-30%）、评估时间、肿瘤类型和治疗方式的可变性限制了可比性。新兴的成像技术和复合响应框架提供了提高测量精度和可重复性的机会。结论：ETS和DpR是一种有前景的、临床可解释的监测治疗效果和预后的指标。标准化的定义、前瞻性验证以及与分子和成像生物标志物（如ctDNA、放射组学和机器学习增强成像）的整合需要完善它们的应用并巩固它们在常规癌症治疗监测中的作用。

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.