A Scoring System Based on Nutritional and Inflammatory Parameters to Predict the Efficacy of First-Line Chemotherapy and Survival Outcomes for De Novo Metastatic Nasopharyngeal Carcinoma

Li, Wang‐Zhong; Hua, Xin; Lv, Shu‐Hui; Hu, Liang; Li, Guoying; Lu, Nian; Bei, Wei-Xin; Xia, Wei‐Xiong; Xiang, Yan‐Qun

doi:10.2147/jir.s296710

Cited by 11 publications

(15 citation statements)

References 44 publications

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“…Compared with one or few markers, the integration of multiple markers into a single model improves prognostic value substantially. 14 , 48–51 Our results were in line with the reported literature. In this study, we developed a CISIG based on a panel of inflammatory biomarkers, which was more potent than traditional models for the estimation of DFS in patients with NPC.…”

Section: Discussionsupporting

confidence: 92%

“…Compared with one or few markers, the integration of multiple markers into a single model improves prognostic value substantially. 14,[48][49][50][51] Our results were in line with the reported literature. In this study, we developed a CISIG based on a panel of…”

supporting

confidence: 91%

“…These selected circulating inflammatory biomarkers have been extensively investigated in NPC or other types of cancers and are highly correlated with survival outcomes. [14][15][16][17][18][19][20][21][22][27][28][29][30][31] These candidate biomarkers were costeffective and easily measured.…”

Section: Laboratory Measurementsmentioning

confidence: 99%

“…[10][11][12][13] In addition to plasma Epstein Barr virus (EBV) DNA, many circulating inflammatory biomarkers have been identified as significant prognostic factors, independent of current clinicopathological NPC characteristics, such as lactic dehydrogenase (LDH), the C-reactive protein (CRP)/albumin (ALB) ratio, and the neutrophil-to-lymphocyte ratio (NLR). [14][15][16][17][18][19][20][21][22] These biomarkers are commonly used to predict prognosis and improve the performance of predictive NPC models. The limitation of these studies was that they typically investigated only one or a few biomarkers at a time.…”

Section: Introductionmentioning

confidence: 99%

“…The association between cancer-related inflammation markers and poor survival outcomes has been wellstudied in previous studies. [14][15][16][17][18][19][20][21][22]46 Published biomarkerrelated studies have been designed specifically for the assessment of one or a few markers. However, estimates of the risk associated with specific inflammatory markers are not always equal.…”

mentioning

confidence: 99%

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Prognostic and Predictive Value of Circulating Inflammation Signature in Non-Metastatic Nasopharyngeal Carcinoma: Potential Role for Individualized Induction Chemotherapy

et al. 2021

JIR

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We sought to assess the prognostic and predictive value of a circulating inflammation signature (CISIG) and develop CISIG-based tools for predicting prognosis and guiding individualized induction chemotherapy (ICT) in non-metastatic nasopharyngeal carcinoma (NPC). Patients and Methods: We retrospectively collected a candidate inflammatory biomarker panel from patients with NPC treated with definitive radiotherapy between 2012 and 2017. We developed the CISIG using candidate biomarkers identified by a least absolute shrinkage and selection operator (LASSO) Cox regression model. The Cox regression analyses were used to evaluate the CISIG prognostic value. A CISIG-based prediction model was constructed, validated, and assessed. Potential stratified ICT treatment effects were examined. Results: A total of 1149 patients were analyzed. Nine biomarkers selected by LASSO regression in the training cohort were used to construct the CISIG, including hyaluronidase, laminin, procollagen III, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, high-density lipoprotein, lactate dehydrogenase, and C-reactive protein-to-albumin ratio. CISIG was an independent prognostic factor for disease-free survival (DFS; hazard ratio: 2.65, 95% confidence interval: 1.93-3.64; P < 0.001). High CISIG group (>−0.2) was associated with worse 3-year DFS than low CISIG group in both the training (67.5% vs 88.3%, P < 0.001) and validation cohorts (72.3% vs 85.1%, P < 0.001). We constructed and validated a CISIG-based nomogram, which showed better performance than the clinical stage and Epstein-Barr virus DNA classification methods. A significant interaction between CISIG and the ICT treatment effect was observed (P for interaction = 0.036). Patients with high CISIG values did not benefit from ICT, whereas patients with low CISIG values significantly benefited from ICT. Conclusion:The developed CISIG, based on a circulating inflammatory biomarker panel, adds prognostic information for patients with NPC. The proposed CISIG-based tools offer individualized risk estimation to facilitate suitable ICT candidate identification.

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Section: Discussionsupporting

confidence: 92%

supporting

confidence: 91%

Section: Laboratory Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Prognostic and Predictive Value of Circulating Inflammation Signature in Non-Metastatic Nasopharyngeal Carcinoma: Potential Role for Individualized Induction Chemotherapy

et al. 2021

JIR

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Prognostic value of the nutritional risk index in patients with newly diagnosed multiple myeloma

et al. 2022

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The nutritional risk index (NRI), which is based on weight and albumin levels, is closely associated with the prognosis of many cancers. However, its prognostic value has not been investigated in patients with newly diagnosed multiple myeloma (NDMM). We aimed to assess the association between the NRI and survival outcomes in patients with NDMM. We retrospectively collected and analyzed clinical and laboratory data from patients with NDMM between 2005 and 2019 at our center. Patients were stratified into the high NRI (> 89) and low NRI (≤ 89) groups for prognostic analysis. The NRI and other variables were also explored to evaluate their prognostic value for overall survival (OS). A total of 638 patients diagnosed with NDMM were retrospectively included. Patients in the high NRI group had a significantly better median OS than those in the low NRI group (64 months vs 43 months, p < 0.001). In the multivariate analysis, a high NRI was shown to be an independent prognostic factor for OS (hazard ratio, 0.758; 95% confidence interval, 0.587–0.977; p = 0.033). Age, performance status, transplant status, and lactate dehydrogenase level were also independent prognostic factors for OS. In conclusion, our study demonstrates that the NRI is a simple and useful predictor of survival outcomes in patients with NDMM.

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New scoring system combining computed tomography body composition analysis and inflammatory–nutritional indicators to predict postoperative complications in stage II–III colon cancer

Liu

et al. 2023

J of Gastro and Hepatol

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Background and AimPostoperative complications are important clinical outcomes for colon cancer patients. This study aimed to investigate the predictive value of inflammatory–nutritional indicators combined with computed tomography body composition on postoperative complications in patients with stage II–III colon cancer.MethodsWe retrospectively collected data from patients with stage II–III colon cancer admitted to our hospital from 2017 to 2021, including 198 patients in the training cohort and 50 patients in the validation cohort. Inflammatory–nutritional indicators and body composition were included in the univariate and multivariate analyses. Binary regression was used to develop a nomogram and evaluate its predictive value.ResultsIn the multivariate analysis, the monocyte–lymphocyte ratio (MLR), systemic immune‐inflammation index (SII), nutritional risk score (NRS), skeletal muscle index (SMI), and visceral fat index (VFI) were independent risk factors for postoperative complications of stage II–III colon cancer. In the training cohort, the area under the receiver operating characteristic curve of the predictive model was 0.825 (95% confidence interval [CI] 0.764–0.886). In the validation cohort, it was 0.901 (95% CI 0.816–0.986). The calibration curve showed that the prediction results were in good agreement with the observational results. Decision curve analysis showed that colon cancer patients could benefit from the predictive model.ConclusionsA nomogram combining MLR, SII, NRS, SMI, and VFI with good accuracy and reliability in predicting postoperative complications in patients with stage II–III colon cancer was established, which can help guide treatment decisions.

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A Scoring System Based on Nutritional and Inflammatory Parameters to Predict the Efficacy of First-Line Chemotherapy and Survival Outcomes for De Novo Metastatic Nasopharyngeal Carcinoma

Cited by 11 publications

References 44 publications

Prognostic and Predictive Value of Circulating Inflammation Signature in Non-Metastatic Nasopharyngeal Carcinoma: Potential Role for Individualized Induction Chemotherapy

Prognostic and Predictive Value of Circulating Inflammation Signature in Non-Metastatic Nasopharyngeal Carcinoma: Potential Role for Individualized Induction Chemotherapy

Prognostic value of the nutritional risk index in patients with newly diagnosed multiple myeloma

New scoring system combining computed tomography body composition analysis and inflammatory–nutritional indicators to predict postoperative complications in stage II–III colon cancer

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