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Prosigna 检测对淋巴结阴性早期乳腺癌辅助治疗决策的影响——一项前瞻性全国多中心研究(EMIT-1)。

Impact of Prosigna test on adjuvant treatment decision in lymph node-negative early breast cancer-a prospective national multicentre study (EMIT-1).

机构信息

Department of Oncology, Division of Cancer Medicine, Oslo University Hospital, Oslo.

Department of Oncology, University of North Norway, Tromsø; Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø.

出版信息

ESMO Open. 2024 Jun;9(6):103475. doi: 10.1016/j.esmoop.2024.103475. Epub 2024 Jun 4.

DOI:10.1016/j.esmoop.2024.103475
PMID:38838499
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11190479/
Abstract

BACKGROUND

EMIT-1 is a national, observational, single-arm trial designed to assess the value of the Prosigna, Prediction Analysis of Microarray using the 50 gene classifier (PAM50)/Risk of Recurrence (ROR), test as a routine diagnostic tool, examining its impact on adjuvant treatment decisions, clinical outcomes, side-effects and cost-effectiveness. Here we present the impact on treatment decisions.

PATIENTS AND METHODS

Patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative pT1-pT2 lymph node-negative early breast cancer (EBC) were included. The Prosigna test and standard histopathology assessments were carried out. Clinicians' treatment decisions were recorded before (pre-Prosigna) and after (post-Prosigna) the Prosigna test results were disclosed.

RESULTS

Of 2217 patients included, 2178 had conclusive Prosigna results. The pre-Prosigna treatment decisions were: no systemic treatment (NT) in 27% of patients, endocrine treatment alone (ET) in 38% and chemotherapy (CT) followed by ET (CT + ET) in 35%. Post-Prosigna treatment decisions were 25% NT, 51% ET and 24% CT + ET, respectively. Adjuvant treatment changed in 28% of patients, including 21% change in CT use. Among patients assigned to CT + ET pre-Prosigna, 45% were de-escalated to ET post-Prosigna. Of patients assigned to ET, 12% were escalated to CT + ET and 8% were de-escalated to NT; of those assigned to NT, 18% were escalated to ET/CT + ET. CT was more frequently recommended for patients aged ≤50 years. In the subgroup with pT1c-pT2 G2 and intermediate Ki67 (0.5-1.5× local laboratory median Ki67 score), the pre-Prosigna CT treatment decision varied widely across hospitals (3%-51%). Post-Prosigna, the variability of CT use was markedly reduced (8%-24%). The correlation between Ki67 and ROR score within this subgroup was poor (r = 0.25-0.39). The median ROR score increased by increasing histological grade, but the ROR score ranges were wide (for G1 0-79, G2 0-90, G3 16-94).

CONCLUSION

The Prosigna test result changed adjuvant treatment decisions in all EBC clinical risk groups, markedly decreased the CT use for patients categorized as higher clinical risk pre-Prosigna and reduced treatment decision discrepancies between hospitals.

摘要

背景

EMIT-1 是一项全国性的、观察性的、单臂试验,旨在评估 Prosigna、使用 50 基因分类器的微阵列预测分析(PAM50)/复发风险(ROR)的预测分析作为常规诊断工具的价值,检查其对辅助治疗决策、临床结果、副作用和成本效益的影响。这里我们介绍对治疗决策的影响。

患者和方法

纳入激素受体阳性、人表皮生长因子受体 2 阴性 pT1-pT2 淋巴结阴性早期乳腺癌(EBC)患者。进行了 Prosigna 检测和标准组织病理学评估。记录了临床医生在 Prosigna 检测结果公布之前(预 Prosigna)和之后(后 Prosigna)的治疗决策。

结果

2217 例患者中,2178 例有明确的 Prosigna 检测结果。预 Prosigna 的治疗决策为:27%的患者不进行全身治疗(NT),38%的患者单独进行内分泌治疗(ET),35%的患者进行化疗(CT)后再进行 ET(CT+ET)。后 Prosigna 的治疗决策分别为 25%的 NT、51%的 ET 和 24%的 CT+ET。28%的患者接受了辅助治疗的改变,其中 21%的 CT 使用率发生了改变。在前 Prosigna 被分配到 CT+ET 的患者中,45%的患者在后 Prosigna 时被降级为 ET。在被分配到 ET 的患者中,12%的患者被升级为 CT+ET,8%的患者被降级为 NT;在被分配到 NT 的患者中,18%的患者被升级为 ET/CT+ET。CT 更常被推荐用于年龄≤50 岁的患者。在 pT1c-pT2 G2 和中间 Ki67(0.5-1.5×局部实验室 Ki67 评分中位数)的亚组中,预 Prosigna 的 CT 治疗决策在各医院之间差异很大(3%-51%)。在后 Prosigna,CT 的使用变化明显减少(8%-24%)。在这个亚组中,Ki67 和 ROR 评分之间的相关性较差(r=0.25-0.39)。随着组织学分级的增加,中位 ROR 评分增加,但 ROR 评分范围很宽(G1 0-79、G2 0-90、G3 16-94)。

结论

Prosigna 检测结果改变了所有 EBC 临床风险组的辅助治疗决策,显著降低了在前 Prosigna 被归类为高临床风险的患者中 CT 的使用率,并减少了医院之间治疗决策的差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/44c70157b61e/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/4a10317f36be/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/8ce0f7d92b26/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/07b4eaa12300/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/44c70157b61e/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/4a10317f36be/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/8ce0f7d92b26/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/07b4eaa12300/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/987e/11190479/44c70157b61e/gr4.jpg

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