Amir Alishahi Tabriz, Matthew J Boyer, Adelaide M Gordon, David J Carpenter, Jeffrey R Gingrich, Sudha R Raman, Deepika Sirohi, Alexis Rompre-Brodeur, Joseph Lunyera, Fahmin Basher, Rhonda L Bitting, Andrzej S Kosinski, Sarah Cantrell, Belinda Ear, Jennifer M Gierisch, Morgan Jacobs, Karen M Goldstein
{"title":"基因组分类对局限性前列腺癌患者风险分层和治疗强度的影响：一项系统综述。","authors":"Amir Alishahi Tabriz, Matthew J Boyer, Adelaide M Gordon, David J Carpenter, Jeffrey R Gingrich, Sudha R Raman, Deepika Sirohi, Alexis Rompre-Brodeur, Joseph Lunyera, Fahmin Basher, Rhonda L Bitting, Andrzej S Kosinski, Sarah Cantrell, Belinda Ear, Jennifer M Gierisch, Morgan Jacobs, Karen M Goldstein","doi":"10.7326/ANNALS-24-00700","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.</p><p><strong>Purpose: </strong>To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment.</p><p><strong>Data sources: </strong>MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.</p><p><strong>Study selection: </strong>Two investigators independently identified studies on risk classification and treatment choice after GC testing for patients with localized PCa considering first-line treatment.</p><p><strong>Data extraction: </strong>Relevant data extracted by 1 researcher and overread by a second. Risk of bias (ROB) was assessed in duplicate.</p><p><strong>Data synthesis: </strong>Ten studies reported risk reclassification after GC testing. In low ROB observational studies, very low- or low-risk patients with PCa were more likely to have their risk levels classified as the same or lower (GPS, 100% to 88.1%; Decipher, 87.2% to 82.9%; Prolaris, 76.9%). However, 1 randomized trial found that GC testing with GPS reclassified 34.5% of very low-risk and 29.4% of low-risk patients to a higher risk category. Twelve observational studies indicated that treatment decisions after GC testing either remained unchanged or slightly favored active surveillance. In contrast, analyses from a single randomized trial found fewer choices for active surveillance after GPS testing.</p><p><strong>Limitations: </strong>Heterogeneity in screening patterns, risk-determination cutoffs, pathology, and clinical practices. Studies on treatment choice were moderate to high ROB.</p><p><strong>Conclusion: </strong>Although GC tests do not consistently influence risk classification or treatment decisions, the differences observed between observational and randomized studies highlight a need for well-designed trials to explore the role of GC tests in patients with newly diagnosed PCa considering first-line treatment.</p><p><strong>Primary funding source: </strong>U.S. Department of Veterans Affairs. 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Risk of bias (ROB) was assessed in duplicate.</p><p><strong>Data synthesis: </strong>Ten studies reported risk reclassification after GC testing. In low ROB observational studies, very low- or low-risk patients with PCa were more likely to have their risk levels classified as the same or lower (GPS, 100% to 88.1%; Decipher, 87.2% to 82.9%; Prolaris, 76.9%). However, 1 randomized trial found that GC testing with GPS reclassified 34.5% of very low-risk and 29.4% of low-risk patients to a higher risk category. Twelve observational studies indicated that treatment decisions after GC testing either remained unchanged or slightly favored active surveillance. In contrast, analyses from a single randomized trial found fewer choices for active surveillance after GPS testing.</p><p><strong>Limitations: </strong>Heterogeneity in screening patterns, risk-determination cutoffs, pathology, and clinical practices. Studies on treatment choice were moderate to high ROB.</p><p><strong>Conclusion: </strong>Although GC tests do not consistently influence risk classification or treatment decisions, the differences observed between observational and randomized studies highlight a need for well-designed trials to explore the role of GC tests in patients with newly diagnosed PCa considering first-line treatment.</p><p><strong>Primary funding source: </strong>U.S. Department of Veterans Affairs. 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引用次数: 0
摘要
背景：基于组织的基因组分类器（GCs）已被开发用于改善前列腺癌（PCa）的风险评估和治疗建议。目的：总结在考虑一线治疗的局限性前列腺癌患者中，Decipher、Oncotype DX基因组前列腺评分（GPS）和Prolaris基因评分对风险分层和患者-临床决定治疗选择的影响。数据来源：2010年1月至2024年8月出版的MEDLINE、EMBASE和Web of Science。研究选择：两名研究者独立确定了考虑一线治疗的局限性PCa患者GC检测后的风险分类和治疗选择的研究。数据提取：相关数据由1名研究者提取，1秒过读。偏倚风险（ROB）一式两份评估。数据综合：10项研究报告了GC检测后的风险重新分类。在低ROB观察性研究中，非常低风险或低风险的PCa患者更有可能将其风险水平分类为相同或更低(GPS， 100%至88.1%；破译，87.2%至82.9%；Prolaris, 76.9%)。然而，一项随机试验发现，GPS的GC检测将34.5%的极低风险患者和29.4%的低风险患者重新分类为高风险类别。12项观察性研究表明，GC检测后的治疗决定要么保持不变，要么略微倾向于主动监测。相比之下，一项随机试验的分析发现，在GPS测试后，主动监测的选择更少。局限性：筛查模式、风险确定临界值、病理和临床实践的异质性。治疗选择的研究为中高ROB。结论：虽然GC检测并不总是影响风险分类或治疗决策，但观察性研究和随机研究之间的差异突出了需要精心设计的试验来探索GC检测在考虑一线治疗的新诊断PCa患者中的作用。主要资金来源：美国退伍军人事务部。(普洛斯彼罗:CRD42022347950)。
Impact of Genomic Classifiers on Risk Stratification and Treatment Intensity in Patients With Localized Prostate Cancer : A Systematic Review.
Background: Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.
Purpose: To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment.
Data sources: MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.
Study selection: Two investigators independently identified studies on risk classification and treatment choice after GC testing for patients with localized PCa considering first-line treatment.
Data extraction: Relevant data extracted by 1 researcher and overread by a second. Risk of bias (ROB) was assessed in duplicate.
Data synthesis: Ten studies reported risk reclassification after GC testing. In low ROB observational studies, very low- or low-risk patients with PCa were more likely to have their risk levels classified as the same or lower (GPS, 100% to 88.1%; Decipher, 87.2% to 82.9%; Prolaris, 76.9%). However, 1 randomized trial found that GC testing with GPS reclassified 34.5% of very low-risk and 29.4% of low-risk patients to a higher risk category. Twelve observational studies indicated that treatment decisions after GC testing either remained unchanged or slightly favored active surveillance. In contrast, analyses from a single randomized trial found fewer choices for active surveillance after GPS testing.
Limitations: Heterogeneity in screening patterns, risk-determination cutoffs, pathology, and clinical practices. Studies on treatment choice were moderate to high ROB.
Conclusion: Although GC tests do not consistently influence risk classification or treatment decisions, the differences observed between observational and randomized studies highlight a need for well-designed trials to explore the role of GC tests in patients with newly diagnosed PCa considering first-line treatment.
Primary funding source: U.S. Department of Veterans Affairs. (PROSPERO: CRD42022347950).
期刊介绍：
Established in 1927 by the American College of Physicians (ACP), Annals of Internal Medicine is the premier internal medicine journal. Annals of Internal Medicine’s mission is to promote excellence in medicine, enable physicians and other health care professionals to be well informed members of the medical community and society, advance standards in the conduct and reporting of medical research, and contribute to improving the health of people worldwide. To achieve this mission, the journal publishes a wide variety of original research, review articles, practice guidelines, and commentary relevant to clinical practice, health care delivery, public health, health care policy, medical education, ethics, and research methodology. In addition, the journal publishes personal narratives that convey the feeling and the art of medicine.
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