ArticleJournal of inflammation research2024
A Nomogram Model Based on the Inflammation-Immunity-Nutrition Score (IINS) and Classic Clinical Indicators for Predicting Prognosis in Extranodal Natural Killer/T-Cell Lymphoma.
Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic value of inflammation-immunity-nutrition score in cancer patients: a meta-analysis.Annals of medicine · 2026Pooled it
- Prognostic value of inflammation-immunity-nutrition score in patients with cancers.Discover oncology · 2026Article
- Ferritin as a novel predictive index for nasopharyngeal carcinoma survival and therapeutic efficacy of different chemotherapy regimens.World journal of clinical oncology · 2026Article
- A low-cost bedside nomogram integrating TSF and pain for predicting severe malnutrition in nasopharyngeal carcinoma: a prospective cohort study.Frontiers in nutrition · 2026Article
- Combined fibrinogen concentration and neutrophil-to-lymphocyte ratio, an integrative model of the inflammatory response and coagulation cascades, for predicting prognosis in patients with upper tract urothelial carcinoma.Biomolecules & biomedicine · 2025Article
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7 authors.
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Abstract
Background: Systemic inflammation, immunity, and nutritional status are closely related to patients' outcomes in several kinds of cancers. This study aimed to establish a new nomogram based on inflammation-immunity-nutrition score (IINS) to predict the prognosis of extranodal natural killer/T-cell lymphoma (ENKTL) patients. Methods: The clinical data of 435 patients with ENTKL were retrospectively reviewed and randomly assigned to training cohort (n=305) and validation cohort (n=131) at a ratio of 7:3. Cox regression analysis was employed to identify independent prognostic factors and develop a nomogram in the training cohort. Harrell's concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) curve were employed to assess the performance of the nomogram and compare it with traditional prognostic systems (PINK, IPI, KPI). Internal validation was performed using 1000 bootstrap resamples in the validation cohort. Kaplan-Meier survival analyses were conducted to compare the overall survival (OS) of patients in different risk groups. Results: In the training cohort, in addition to several classic parameters, IINS was identified as an independent prognostic factor significantly associated with the OS of patients. The nomogram established based on the independent prognostic indicators showed superior survival prediction efficacy, with C-index of 0.733 in the training cohort and 0.759 in the validation cohort compared to the PINK (0.636 and 0.737), IPI (0.81 and 0.707), and KPI (0.693 and 0.639) systems. Furthermore, compared with PINK, IPI, and IPI systems, the nomogram showed relatively superior calibration curves and more powerful prognostic discrimination ability in predicting the OS of patients. DCA curves revealed some advantages in terms of clinical applicability of the nomogram compared to the PINK, IPI, and IPI systems. Conclusion: Compared with traditional prognostic systems, the nomogram showed promising prospects for risk stratification in ENKTL patient prognosis, providing new insights into the personalized treatment.
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