Diagnostic Predictive Model for Distinguishing Intravascular Large B-Cell Lymphoma Among Patients with Fever of...

Background/Objectives: Intravascular large B-cell lymphoma (IVLBCL) is a rare and diagnostically challenging disease, often presenting as fever of unknown origin (FUO). This study aimed to develop and validate diagnostic predictive models and scoring systems to distinguish IVLBCL from other causes of FUO in hospitalized patients. Methods: A retrospective analysis was conducted in patients with IVLBCL or other causes of FUO who were treated between February 2015 and October 2023. Two multivariable logistic regression models and corresponding integer-based scoring systems were developed in a training cohort comprising 42 patients with IVLBCL and 45 FUO controls. Internal validation was performed using leave-one-out cross-validation and bootstrap resampling, followed by temporal validation in an independent cohort of 18 patients with IVLBCL and 21 FUO controls. Model 1 was additionally evaluated for sensitivity in an external case-only cohort comprising 40 patients with IVLBCL from eight hospitals. Results: Model 1 incorporated peripheral edema, hypoxemia, neurological symptoms, hemophagocytic lymphohistiocytosis, and interstitial lung abnormalities on computed tomography and achieved an area under the receiver operating characteristic curve (AUC) of 0.916 in the training cohort. Model 2 combined the interleukin-10/interleukin-6 (IL-10/IL-6) ratio with peripheral edema, hypoxemia, and neurological symptoms and demonstrated significantly improved discrimination (AUC = 0.982, p = 0.021 vs. Model 1). In the temporal validation cohort, the AUCs of Models 1 and 2 were 0.975 and 0.997, respectively. The corresponding integer-based scoring systems achieved AUCs of 0.903 and 0.952 in the training cohort and 0.926 and 0.992 in the temporal validation cohort. In the external case-only cohort, both Model 1 and its integer-based score identified 32 of 40 patients, yielding a sensitivity of 80.0%. Random skin biopsy provided the histological diagnosis in 58% of cases, with a positivity rate of 79.5%. Conclusions: Two diagnostic models and their simplified scoring systems were developed and internally and temporally validated to aid the diagnosis of IVLBCL in hospitalized patients with FUO. These models may assist in the diagnostic workup of hospitalized FUO patients, especially when IL-10/IL-6 testing is unavailable. Their performance in outpatient or community settings remains uncertain, and prospective multicenter validation with appropriate FUO controls is warranted.