The Accuracy and Sensitivity of Delta Neutrophil Index in Malignancy: Diagnostic Study of Different Types

中性粒细胞δ指数在恶性肿瘤诊断中的准确性和敏感性:不同类型肿瘤的诊断研究

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Abstract

Background/Objectives: The delta neutrophil index (DNI)-a hematology analyzer-derived measure of circulating immature granulocytes-may assist pre-biopsy decision-making, yet its behavior across tumor types is incompletely defined. We examined whether pre-biopsy DNI differs by pathology category, tumor class, and definitive histology, and evaluated diagnostic performance. Methods: In this retrospective, single-center cohort, consecutive inpatients with malignancy were screened (n = 2009). Exclusions included positive blood cultures, prior chemotherapy/radiotherapy before index labs, and lack of definitive pathology, yielding 1313 analyzable cases. All laboratories, including DNI, were obtained before diagnostic biopsy. DNI was assessed as a continuous variable and categorized (Zero = 0; High > 0.6). Groupwise differences used Kruskal-Wallis and χ(2) tests with FDR control; discrimination used ROC analyses (one-versus-rest/pairwise). Results: DNI distributions differed across pathology, tumor class, and definitive diagnoses (all p < 0.001). High DNI (>0.6) and Zero DNI (=0) proportions also varied significantly by grouping. Hematologic malignancies showed the highest DNI (median ~1.0) compared with sarcoma and carcinoma (medians ~0.4). Using DNI alone, one-versus-rest AUCs were 0.735 (hematologic), 0.692 (melanoma), 0.672 (sarcoma), and 0.652 (carcinoma); the strongest pairwise separation was hematologic versus sarcoma (AUC 0.780). For specific solid tumors, including breast and renal cell carcinoma, single-marker discrimination was modest; no clinically actionable RCC cutoff emerged. Sensitivity analyses restricted to culture-negative cases yielded consistent findings. Conclusions: Pre-biopsy DNI exhibits tumor-type-dependent variation and provides adjunct diagnostic signal-the strongest for hematologic malignancy-yet is insufficient alone for solid tumor subtyping. Integration with clinical assessment and routine biomarkers, and multi-center validation with device harmonization are warranted.

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