化学免疫疗法
滤泡性淋巴瘤
医学
正电子发射断层摄影术
标准摄取值
淋巴瘤
无进展生存期
前瞻性队列研究
弥漫性大B细胞淋巴瘤
核医学
肿瘤科
内科学
美罗华
放射治疗
作者
Judith Trotman,Andrew R. Pettitt
出处
期刊:Blood
[American Society of Hematology]
日期:2022-03-17
标识
DOI:10.1182/blood.2020008243
摘要
18F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) is now established as the gold-standard imaging modality for both staging and response assessment in follicular lymphoma (FL). In this Perspective, we propose where PET can, and cannot, guide clinicians in their therapeutic approach. PET at diagnosis and pretreatment is important for staging, with greater sensitivity compared with standard CT, and consequent improved outcomes in truly limited-stage FL. Small data sets suggesting that a high baseline standardized uptake value (SUVmax) identifies de novo histologic transformation (HT) have not been corroborated by data from GALLIUM, the largest prospective study to examine modern therapies for FL. Nonetheless, the role of baseline quantitative PET measures requires further clarification. The median survival of patients with newly diagnosed FL is now potentially >20 years. Treatment of symptomatic FL aims to achieve remission and optimize quality of life for as long as possible, with many patients achieving a "functional cure" at the cost of unwanted treatment effects. Several studies have identified end-of-induction (EOI) PET after initial chemoimmunotherapy in patients with a high tumor burden as strongly predictive of both progression-free and overall survival, and EOI PET is being evaluated as a platform for response-adapted treatment. Unmet needs remain: improving the inferior survival for patients remaining PET positive and quantifying the progression-free survival and time to next treatment advantage, and additional toxicity of anti-CD20 maintenance in patients who achieve complete metabolic remission. In the absence of an overall survival advantage for frontline antibody maintenance, the question of using PET to guide the therapeutic approach is more important than ever in the context of the COVID-19 pandemic.
科研通智能强力驱动
Strongly Powered by AbleSci AI