Prognostic nutritional index predicts the prognosis of patients with advanced esophageal cancer treated with immune checkpoint inhibitors: a retrospective cohort study

Wu, Mengjing; Zhu, Yunyun; Chen, Xiancheng; Wang, Xinpeng; Lin, Xinyue; Yan, Xue; Mo, Peng; Ye, Ying; Zeng, Yanjing; Yang, Yue; Fu, Zhichao

doi:10.21037/jgo-23-48

Cited by 4 publications

(1 citation statement)

References 27 publications

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“…p < 0.05 was considered statistically significant. the eligibility criteria, resulting in a total of 2883 patients (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34). The PRISMA flowchart in Figure 1 depicts the study selection process.…”

Section: Methodsmentioning

confidence: 99%

Prognostic nutritional index as a prognostic biomarker for gastrointestinal cancer patients treated with immune checkpoint inhibitors

Zhang

Qiu

et al. 2023

Front. Immunol.

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ObjectiveOur study represents the first meta-analysis conducted to evaluate the prognostic utility of the baseline prognostic nutritional index (PNI) in patients with gastrointestinal cancer (GIC) who received immune checkpoint inhibitor (ICI) therapy.MethodsWe searched PubMed, the Cochrane Library, EMBASE, and Google Scholar until April 23, 2023, to obtain relevant articles for this study. Our analysis examined several clinical outcomes, including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR).ResultsIn this analysis, a total of 17 articles with 2883 patients were included. Our pooled results indicated that patients with high PNI levels had longer OS (HR: 0.530, 95% CI: 0.456-0.616, p < 0.001) and PFS (HR: 0.740, 95% CI: 0.649-0.844, p < 0.001), as well as higher ORR (OR: 1.622, 95% CI: 1.251-2.103, p < 0.004) and DCR (OR: 1.846, 95% CI: 1.428-2.388, p < 0.001). Subgroup analysis showed that PNI cutoff values of 40 to 45 showed greater predictive potential. Subgroup analysis also confirmed that the above findings still hold true in patients with esophageal cancer, gastric cancer, and hepatocellular carcinomas.ConclusionThe PNI were reliable predictors of outcomes in GIC patients treated with ICIs.

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Section: Methodsmentioning

confidence: 99%

Prognostic nutritional index as a prognostic biomarker for gastrointestinal cancer patients treated with immune checkpoint inhibitors

Zhang

Qiu

et al. 2023

Front. Immunol.

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Combining dynamics of serum inflammatory and nutritional indicators as novel biomarkers in immune checkpoint inhibitor treatment of non-small-cell lung cancer with bone metastases

Asano,

Hayashi,

Takeuchi

et al. 2024

International Immunopharmacology

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Multiparametric radiomics and prognostic nutritional index for predicting postoperative survival in esophageal carcinoma

Luo,

Dong,

Deng

et al. 2024

Preprint

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Background Surgery can lead to radical cure and long-term survival for individuals with esophageal squamous cell carcinoma (ESCC). Nevertheless, the survival rates markedly vary among patients. Accurately predicting surgical efficacy remains a pressing issue. This investigation sought to examine the predictive value of preoperative radiomics and the prognostic nutritional index for individuals with ESCC and to construct a comprehensive model for estimating the postoperative overall survival (OS) of individuals with ESCC. Methods This research conducted a retrospective examination of 466 individuals with ESCC from two medical centers. The data were arbitrarily categorized into a training cohort (TC, hospital 1, 246 cases), an internal validation cohort (IVC, hospital 1, 106 cases), and an external validation cohort (EVC, hospital 2, 114 cases). Upon demarcation of the area of interest, radiological features were extracted. The least absolute shrinkage and selection operator (LASSO) regression was utilized to identify the optimal radiomics features and calculate the radiomics score (RS). After the delineation of region of interest, radiological features were procured. Subsequently, the LASSO regression was employed to ascertain the optimal features and calculate the RS. The independent influencing factors acquired through Cox analyses were incorporated with the RS to establish a combined nomogram. The predictive capability of the model was examined utilizing the concordance index, time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis. Results In the predictive model integrating preoperative radiomics with prognostic nutritional index and tumor–node–metastasis (TNM) stage for forecasting the 3-year OS rate, the area under the time-dependent ROC curve (AUC) was 0.812, 0.748, and 0.810 in the TC, IVC, and EVCs, respectively, thereby demonstrating outstanding prognostic significance. This was superior to the AUC values of the TNM stage prediction model in the TC, IVC, and EVCs, which were 0.717, 0.612, and 0.699, respectively. The concordance indexes of the combined model in the TC, IVC, and EVCs were 0.780, 0.760, and 0.764, respectively. The calibration and decision curves illustrated the nomogram’s remarkable calibration performance and clinical application value. Conclusion In this investigation, a predictive model was developed by integrating radiomics and the prognostic nutritional index. This model can predict the OS rate of postoperative patients with ESCC and could be employed as a tool for preoperative risk stratification.

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Prognostic nutritional index predicts the prognosis of patients with advanced esophageal cancer treated with immune checkpoint inhibitors: a retrospective cohort study

Cited by 4 publications

References 27 publications

Prognostic nutritional index as a prognostic biomarker for gastrointestinal cancer patients treated with immune checkpoint inhibitors

Prognostic nutritional index as a prognostic biomarker for gastrointestinal cancer patients treated with immune checkpoint inhibitors

Combining dynamics of serum inflammatory and nutritional indicators as novel biomarkers in immune checkpoint inhibitor treatment of non-small-cell lung cancer with bone metastases

Multiparametric radiomics and prognostic nutritional index for predicting postoperative survival in esophageal carcinoma

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