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

Zhang, Lilong; Ma, Wangbin; Qiu, Zhendong; Kuang, Tianrui; Wang, Kunpeng; Hu, Bo; Wang, Weixing

doi:10.3389/fimmu.2023.1219929

Cited by 18 publications

(8 citation statements)

References 54 publications

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“…The results demonstrated that the PNI exhibited higher prognostic value in all subgroup analyses [ 26 ]. Zhang and his colleagues’ meta-analysis further corroborated these findings, integrating data and results from 17 studies, revealing that the PNI is a reliable predictive factor for gastric cancer patients receiving ICIs [ 27 ]. Meanwhile, Wan and colleagues have extensively studied inflammatory markers and found that the NLR was associated with the benefits of immunotherapy [ 28 ].…”

Section: Discussionmentioning

confidence: 81%

The Gastric Cancer Immune Prognostic Score (GCIPS) Shows Potential in Predicting an Unfavorable Prognosis for Gastric Cancer Patients Undergoing Immune Checkpoint Inhibitor Treatment

Zuo,

Sun,

Pan

et al. 2024

Biomedicines

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(1) Background: This study aims to explore the predictive capability of the Gastric Cancer Immune Prognostic Score (GCIPS) for an unfavorable prognosis in gastric cancer patients undergoing immune checkpoint inhibitor (ICI) treatment. (2) Methods: This study included 302 gastric cancer patients who underwent treatment with ICIs at our institution from January 2017 to December 2022. The patients were randomly divided into a test set (201 cases) and a validation set (101 cases) using a random number table. Kaplan–Meier survival analysis and the log-rank test were used to investigate survival differences. Cox regression analysis and Lasso regression analysis were employed to establish the GCIPS and identify independent prognostic indicators. ROC curves, time–ROC curves, and nomograms were utilized to further explore the predictive performance of GCIPS. (3) Results: The test set and validation set showed no statistical differences in clinical and pathological features, as well as blood parameters (all p > 0.05). Cox regression analysis revealed that white blood cells (WBC), lymphocytes (LYM), and the international normalized ratio (INR) emerged as independent prognostic blood indicators after eliminating collinearity through Lasso analysis. The GCIPS was established using β coefficients with the following formula: GCIPS = WBC (109/L) × 0.071 − LYM (109/L) × 0.375 + INR × 2.986. ROC curves based on death and time–ROC curves demonstrated that the GCIPS had higher AUCs than other classical markers at most time points. Survival analyses of all subgroups also revealed a significant correlation between the GCIPS and patients’ progression-free survival (PFS) and overall survival (OS) (all p < 0.05). Furthermore, the GCIPS was identified as an independent prognostic factor for both PFS and OS. Analyses in the validation set further confirmed the reliability and stability of the GCIPS in predicting patient prognosis. Finally, nomograms incorporating the GCIPS exhibited high accuracy in both the test and validation sets. Additionally, the nomograms revealed that the GCIPS had a higher prognostic value than any other factor, including the TNM stage. (4) Conclusions: The GCIPS demonstrated its ability to predict adverse outcomes in gastric cancer patients undergoing ICIs treatment and had a high prognostic value. As a readily accessible and simple novel biomarker, it effectively identified high-risk patients.

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Section: Discussionmentioning

confidence: 81%

The Gastric Cancer Immune Prognostic Score (GCIPS) Shows Potential in Predicting an Unfavorable Prognosis for Gastric Cancer Patients Undergoing Immune Checkpoint Inhibitor Treatment

Zuo,

Sun,

Pan

et al. 2024

Biomedicines

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“…p < 0.1 and I 2 > 50% were defined as high heterogeneity and a random effect model would be applied when it occurred. Otherwise, the fixed effect model was used [20]. The tests of Egger [21] and Begg [22] were employed to evaluate publication bias.…”

Section: Discussionmentioning

confidence: 99%

The predictive value of sarcopenia and myosteatosis in trans-arterial (chemo)-embolization treated HCC patients

Long,

Zhang,

et al. 2024

Aging

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Background: We conducted a meta-analysis to provide evidence-based results for the predictive values of sarcopenia, skeletal muscle index, psoas muscle index and the myosteatosis regarding the impact of survival outcomes and tumor response in patients treated by trans-arterial (chemo)-embolization (TAE/TACE), thereby optimizing therapeutic strategies and maximizing clinical benefits for hepatocellular carcinoma patients. Methods: Qualified studies were retrieved from PubMed, the Cochrane Library, EMBASE, and Google Scholar before June 19, 2023. We investigated the relationships between sarcopenia, SMI, PMI, myosteatosis, and the overall survival of TAE/TACE-treated hepatocellular carcinoma patients with pooling data. Results: A total of 167 studies were collected and 12 studies were finally included for analysis. The metaanalysis assisted that the sarcopenia (HR: 1.46, 95% CI: 1.30-1.64, p < 0.001), skeletal muscle index (HR: 1.48, 95% CI: 1.29-1.69, p < 0.001), and psoas muscle index (HR: 1.45, 95% CI: 1.19-1.77, p < 0.001) were significantly related to a shorter OS of hepatocellular carcinoma patients who treated by TAE/TACE. Sarcopenia significantly contributed to a lower objective response rate of TAE/TACE treated hepatocellular carcinoma patients (OR: 0.80, 95% CI: 0.65-0.98, p = 0.032). But there was no significant association between the myosteatosis and the overall survival (HR: 1.29, 95% CI: 0.74-2.25, p = 0.366). Sensitivity analysis supported the stability and dependability of above analyses conclusions. Conclusion: Sarcopenia, skeletal muscle index and psoas muscle index, are significant prognostic predictors for TAE/TACE treated hepatocellular carcinoma patients. While myosteasis does not demonstrate a prognostic impact on the overall survival of TAE/TACE treated hepatocellular carcinoma patients.

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“…Heterogeneity was estimated using Cochran’s Q test and I 2 statistics. A fixed-effect model with the Inverse Variance method was utilized when p > 0.1 and I 2 <50% indicated non-significant heterogeneity; otherwise, the random-effect model with the DerSimonian-Laird method was applied [ 17 , 18 ]. To investigate publication bias, the funnel plot, Egger tests, and Begg tests were utilized [ 19 , 20 ].…”

Section: Methodsmentioning

confidence: 99%

Cancer cachexia reduces the efficacy of immune checkpoint inhibitors in cancer patients

Yu,

Yan,

Huang

et al. 2024

Aging

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Objective: Cachexia, a multifactorial syndrome, is frequently noticed in cancer patients. A recent study has shown inconsistent findings about the relationship between cachexia and the efficiency of immune checkpoint inhibitors (ICIs). To analyze this disparity, we did a meta-analysis. Methods: From the beginning of each database to July 2023, literature describing the association between cachexia and prognosis of ICI-treated patients with solid malignancies was systematically searched in three online databases. Estimates were pooled, and 95% confidence intervals (CIs) were generated. Results: We analyzed a total of 12 articles, which included data from 1407 patients. The combined results of our analysis showed that cancer patients with cachexia had significantly worse overall survival (HR = 1.88, 95% CI: 1.59–2.22, p < 0.001), progression-free survival (HR = 1.84, 95% CI: 1.59–2.12, p < 0.001), and time to treatment failure (HR = 2.15, 95% CI: 1.32–3.50, p = 0.002). These findings were consistent in both univariate and multivariate analyses. Additionally, while not statistically significant, we observed a trend towards a lower objective response rate in cancer patients with cachexia compared to those without cachexia (OR = 0.59, 95% CI: 0.32–1.09, p = 0.093). Conclusion: Poor survival in cachexia patients suggests a negative relationship between cachexia and ICI efficacy. In clinical practice, the existence of cachexia should be estimated to choose individuals who may benefit from ICIs.

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

Cited by 18 publications

References 54 publications

The Gastric Cancer Immune Prognostic Score (GCIPS) Shows Potential in Predicting an Unfavorable Prognosis for Gastric Cancer Patients Undergoing Immune Checkpoint Inhibitor Treatment

The Gastric Cancer Immune Prognostic Score (GCIPS) Shows Potential in Predicting an Unfavorable Prognosis for Gastric Cancer Patients Undergoing Immune Checkpoint Inhibitor Treatment

The predictive value of sarcopenia and myosteatosis in trans-arterial (chemo)-embolization treated HCC patients

Cancer cachexia reduces the efficacy of immune checkpoint inhibitors in cancer patients

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