ReviewCancer management and research2026
Precision Management of Tumor-Associated Fever: From Classification to Targeted Intervention.
Review in Cancer management and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor-associated fever (TAF) is a common clinical complication in patients with malignant tumors, encompassing neoplastic fever directly attributable to the malignancy itself and secondary fever induced by anticancer treatments. Its pathogenesis is complex, clinical differentiation remains challenging, and it exerts a dual impact on tumor progression and therapeutic response. In the context of advancing precision medicine, a conceptual framework integrating "differential classification-mechanism orientation-targeted intervention" has been proposed to guide the future management of TAF, shifting from the traditional empirical approach. This review systematically outlines the evolution of TAF definitions, epidemiological heterogeneity, multidimensional differential diagnosis strategies, and a three-dimensional subtyping framework integrating etiological mechanisms, molecular characteristics, and clinical phenotypes. We focus on elucidating the pyrogenic mechanisms centered on the IL-6/JAK/STAT3 axis and the subtype-specific molecular underpinnings, and comprehensively summarize the refined application of traditional non-steroidal anti-inflammatory drugs, targeted therapies (including cytokine antagonists, JAK inhibitors, and HSP inhibitors), and emerging interventions (natural bioactive compounds and intravascular temperature control), along with their levels of evidence. This review also addresses key bottlenecks hindering clinical translation-namely, the lack of highly specific diagnostic biomarkers, the scarcity of high-level evidence for targeted interventions, and the absence of a stratified decision-making framework for the "double-edged sword" effects of antipyretic therapy-and proposes corresponding solutions. Finally, we discuss the potential of integrating artificial intelligence and multi-omics technologies into personalized, whole-process TAF management, emphasizing that future efforts should rely on prospective disease-specific cohorts and randomized controlled trials to facilitate the transition from empirical symptomatic management to data-driven precision intervention.
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