Diagnostic models for fever of unknown origin based on 18F-FDG PET/CT: a prospective study in China

Jia Chen; MingYou Xing; Dong Xu; NaNa Xie; WenCong Zhang; QiuRong Ruan; JianXin Song

doi:10.1186/s13550-022-00937-4

Diagnostic models for fever of unknown origin based on ¹⁸F-FDG PET/CT: a prospective study in China

EJNMMI Res. 2022 Oct 28;12(1):69. doi: 10.1186/s13550-022-00937-4.

Authors

Jia Chen¹, MingYou Xing¹, Dong Xu¹, NaNa Xie¹, WenCong Zhang¹, QiuRong Ruan², JianXin Song³

Affiliations

¹ Department of Infectious Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, China.
² Institute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, China.
³ Department of Infectious Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, China. songsingsjx@sina.com.

Abstract

Background: This study aims to analyze the ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) characteristics of different causes of fever of unknown origin (FUO) and identify independent predictors to develop a suitable diagnostic model for distinguishing between these causes. A total of 524 patients with classical FUO who underwent standard diagnostic procedures and PET/CT were prospectively studied. The diagnostic performance of PET/CT imaging was analyzed, and relevant clinical parameters that could improve diagnostic efficacy were identified. The model was established using the data of 369 patients and the other 155 patients comprised the validation cohort for verifying the diagnostic performance of the model.

Results: The metabolic characteristics of the "hottest" lesion, the spleen, bone marrow, and lymph nodes varied for various causes. PET/CT combined with clinical parameters achieved better discrimination in the differential diagnosis of FUO. The etiological diagnostic models included the following factors: multisite metabolic characteristics, blood cell counts, inflammatory indicators (erythrocyte sedimentation rate, C-reactive protein, serum ferritin, and lactate dehydrogenase), immunological indicators (interferon gamma release assay, antinuclear antibody, and anti-neutrophil cytoplasm antibody), specific signs (weight loss, rash, and splenomegaly), and age. In the testing cohort, the AUCs of the infection prediction model, the malignancy diagnostic model, and the noninfectious inflammatory disease prediction model were 0.89 (95% CI 0.86-0.92), 0.94 (95% CI 0.92-0.97), and 0.95 (95% CI 0.93-0.97), respectively. The corresponding AUCs for the validation cohort were 0.88 (95% CI 0.82-0.93), 0.93 (95% CI 0.89-0.98), and 0.95 (95% CI 0.92-0.99), respectively.

Conclusions: ¹⁸F-FDG PET/CT has a certain level of sensitivity and accuracy in diagnosing FUO, which can be further improved by combining it with clinical parameters. Diagnostic models based on PET/CT show excellent performance and can be used as reliable tools to discriminate the cause of FUO. Trial registration This study (a two-step method apparently improved the physicians' level of diagnosis decision-making for adult patients with FUO) was registered on the website http://www.clinical-trials.gov on January 14, 2014, with registration number NCT02035670.

Keywords: 18F-FDG PET/CT; Clinical parameters; Diagnostic model; FUO.

Associated data

ClinicalTrials.gov/NCT02035670