Improved diagnostic accuracy for polymyalgia rheumatica using FDG-PET/CT with clinical diagnosis or 2012 ACR/EULAR classification criteria.

IF 4.4 2区 医学 Q1 RHEUMATOLOGY Rheumatology Pub Date : 2025-04-01 DOI:10.1093/rheumatology/keae377
Andreas Wiggers Nielsen, Kornelis S M van der Geest, Ib Tønder Hansen, Berit Dalsgaard Nielsen, Søren Geill Kjær, Jesper Blegvad-Nissen, Pieter H Nienhuis, Maria Sandovici, Kate Rewers, Christian Møller Sørensen, Riemer H J A Slart, Lars Christian Gormsen, Elisabeth Brouwer, Ellen-Margrethe Hauge, Kresten Krarup Keller
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Abstract

Objective: In routine care, clinicians may employ 2-[18F]fluoro-2-deoxy-D-glucose (FDG)-PET/CT to validate their initial clinical diagnosis of PMR. Nevertheless, the diagnostic utility of combining FDG-PET/CT findings with clinical presentation has not been explored. Therefore, this study aimed to investigate whether the diagnostic accuracy for PMR could be enhanced by combining FDG-PET/CT findings with the clinical baseline diagnosis or the 2012 ACR/EULAR clinical classification criteria for PMR.

Methods: An investigation and a validation cohort were included from two countries, encompassing 66/27 and 36/21 PMR/non-PMR patients, respectively. The cohorts comprised treatment-naïve patients suspected of PMR, who initially received a clinical baseline diagnosis and underwent FDG-PET/CT scans. The FDG-PET/CT Leuven score was applied to classify patients as either PMR or non-PMR and combined with the clinical baseline diagnosis. Final diagnoses were established through clinical follow-up after 12 or six months in the investigation and validation cohorts, respectively.

Results: In the investigation cohort, a clinical baseline diagnosis yielded a sensitivity/specificity of 94%/82%, compared with 78%/70% using the ACR/EULAR criteria. Combining the clinical baseline diagnosis with a positive Leuven score showed a sensitivity/specificity of 80%/93%, compared with 80%/82% for an ACR/EULAR-Leuven score. In the validation cohort, the baseline diagnosis revealed a sensitivity/specificity of 100%/91%, compared with 92%/76% using the ACR/EULAR criteria. Combining FDG-PET/CT with the baseline diagnosis demonstrated a sensitivity/specificity of 83%/95% compared with 89%/81% for the ACR/EULAR-Leuven score.

Conclusion: Combining FDG-PET/CT findings with the clinical baseline diagnosis or ACR/EULAR clinical classification criteria can improve the diagnostic specificity for PMR.

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利用FDG-PET/CT与临床诊断或2012 ACR/EULAR分类标准提高多发性风湿肌痛的诊断准确性。
目的:在常规治疗中,临床医生可能会采用 2-[18F]fluoro-2-deoxy-D-glucose (FDG) 正电子发射计算机断层扫描(PET)来验证多发性风湿痛(PMR)的初步临床诊断。然而,将 FDG-PET/CT 结果与临床表现相结合的诊断效用尚未得到探讨。因此,本研究旨在探讨将FDG-PET/CT检查结果与临床基线诊断或2012年ACR/EULAR风湿病临床分类标准相结合能否提高风湿病诊断的准确性:来自两个国家的调查组和验证组分别包括66/27和36/21名PMR/非PMR患者。这两个队列由未经治疗的疑似 PMR 患者组成,他们最初都得到了临床基线诊断,并接受了 FDG-PET/CT 扫描。FDG-PET/CT鲁汶评分用于将患者划分为PMR或非PMR,并与临床基线诊断相结合。调查组和验证组分别在 12 个月或 6 个月后通过临床随访确定最终诊断:在调查组中,临床基线诊断的敏感性/特异性分别为94%/82%,而采用ACR/EULAR标准的敏感性/特异性分别为78%/70%。将临床基线诊断与鲁汶评分阳性相结合的灵敏度/特异性为80%/93%,而ACR/EULAR-鲁汶评分的灵敏度/特异性为80%/82%。在验证队列中,基线诊断的灵敏度/特异性为100%/91%,而使用ACR/EULAR标准的灵敏度/特异性为92%/76%。将FDG-PET/CT与基线诊断相结合的灵敏度/特异性为83%/95%,而ACR/EULAR-Leuven-score的灵敏度/特异性为89%/81%:结论:将FDG-PET/CT结果与临床基线诊断或ACR/EULAR临床分类标准相结合可提高PMR的诊断特异性。
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来源期刊
Rheumatology
Rheumatology 医学-风湿病学
CiteScore
9.40
自引率
7.30%
发文量
1091
审稿时长
2 months
期刊介绍: Rheumatology strives to support research and discovery by publishing the highest quality original scientific papers with a focus on basic, clinical and translational research. The journal’s subject areas cover a wide range of paediatric and adult rheumatological conditions from an international perspective. It is an official journal of the British Society for Rheumatology, published by Oxford University Press. Rheumatology publishes original articles, reviews, editorials, guidelines, concise reports, meta-analyses, original case reports, clinical vignettes, letters and matters arising from published material. The journal takes pride in serving the global rheumatology community, with a focus on high societal impact in the form of podcasts, videos and extended social media presence, and utilizing metrics such as Altmetric. Keep up to date by following the journal on Twitter @RheumJnl.
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