The Effect of the Prognostic Nutritional Index on the Toxic Side Effects of Radiochemotherapy and Prognosis After Radical Surgery for Gastric Cancer

Body composition change indices combined with Prognostic Nutritional Index predicts the clinical outcomes of patients with gastric cancer treated with immune checkpoint inhibitor

OBJECTIVE

This study aimed to investigate the prognostic significance of the Prognostic Nutritional Index (PNI) in conjunction with body composition change indices, namely subcutaneous fat area (SFA) and skeletal muscle index (SMI), with regard to clinical outcomes in patients with gastric cancer (GC) undergoing immune checkpoint inhibitors (ICIs) treatment.

METHODS

This retrospective investigation encompassed patients with comprehensive clinical and pathological data, inclusive of portal phase enhanced CT images. Continuous variables underwent analysis utilizing the Student t-test or Mann-Whitney U-test, while categorical variables were assessed employing the Pearson chi-squared test or Fisher test. Survival outcomes were evaluated using Kaplan-Meier survival curves and the Log-rank test. Independent prognostic indicators were determined through Cox regression analysis, and a nomogram predicting survival probability for progression-free survival (PFS) and overall survival (OS) was constructed.

RESULTS

Within the PNI-SFA groups, patients in Group 1 exhibited inferior PFS and OS compared to the other two groups. Similarly, among the PNI-SMI groups, Group 1 patients demonstrated poorer PFS and OS. PNI-SMI and Eosi were identified as independent prognostic factors through Cox regression analysis. Furthermore, positive associations with patient prognosis were observed for BMI, SAF, SMI, and PNI.

CONCLUSION

The comprehensive consideration of PNI-SFA and PNI-SMI proved to be a superior prognostic predictor for GC patients undergoing ICI treatment.

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

Objective

Our 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.

Methods

We 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).

Results

In 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.

Conclusion

The PNI were reliable predictors of outcomes in GIC patients treated with ICIs.

CD19 (+) B Cell Combined with Prognostic Nutritional Index Predicts the Clinical Outcomes of Patients with Gastric Cancer Who Underwent Surgery

(1) Background: The aim of this study was to explore the predictive ability of lymphocyte subsets for the prognosis of gastric cancer patients who underwent surgery and the prognostic value of CD19 (+) B cell combined with the Prognostic Nutritional Index (PNI). (2) Methods: This study involved 291 patients with gastric cancer who underwent surgery at our institution between January 2016 and December 2017. All patients had complete clinical data and peripheral lymphocyte subsets. Differences in clinical and pathological characteristics were examined using the Chi-square test or independent sample t-tests. The difference in survival was evaluated using Kaplan-Meier survival curves and the Log-rank test. Cox's regression analysis was performed to identify independent prognostic indicators, and nomograms were used to predict survival probabilities. (3) Results: Patients were categorized into three groups based on their CD19 (+) B cell and PNI levels, with 56 cases in group one, 190 cases in group two, and 45 cases in group three. Patients in group one had a shorter progression-free survival (PFS) (HR = 0.444, p < 0.001) and overall survival (OS) (HR = 0.435, p < 0.001). CD19 (+) B cell-PNI had the highest area under the curve (AUC) compared with other indicators, and it was also identified as an independent prognostic factor. Moreover, CD3 (+) T cell, CD3 (+) CD8 (+) T cell, and CD3 (+) CD16 (+) CD56 (+) NK T cell were all negatively correlated with the prognosis, while CD19 (+) B cell was positively associated with the prognosis. The C-index and 95% confidence interval (CI) of nomograms for PFS and OS were 0.772 (0.752-0.833) and 0.773 (0.752-0.835), respectively. (4) Conclusions: Lymphocyte subsets including CD3 (+) T cell, CD3 (+) CD8 (+) T cell, CD3 (+) CD16 (+) CD56 (+) NK T cell, and CD19 (+) B cell were related to the clinical outcomes of patients with gastric cancer who underwent surgery. Additionally, PNI combined with CD19 (+) B cell had higher prognostic value and could be used to identify patients with a high risk of metastasis and recurrence after surgery.

Prognostic nutritional index for predicting the clinical outcomes of patients with gastric cancer who received immune checkpoint inhibitors

OBJECTIVE

Although the application of immunotherapy in gastric cancer has achieved satisfactory clinical effects, many patients have no response. The aim of this retrospective study is to investigate the predictive ability of the prognostic nutrition index (PNI) to the prognosis of patients with gastric cancer who received immune checkpoint inhibitors (ICIs).

MATERIALS AND METHODS

Participants were 146 gastric cancer patients with ICIs (PD-1/PD-L1 inhibitors) or chemotherapy. All patients were divided into a low PNI group and a high PNI group based on the cut-off evaluated by the receiver operating characteristic (ROC) curve. We contrasted the difference in progression-free survival (PFS) and overall survival (OS) in two groups while calculating the prognosis factors for PFS and OS by univariate and multivariate analyses. Moreover, the nomogram based on the results of the multivariate analysis was constructed to estimate the 1- and 3-year survival probabilities.

RESULTS

There were 41 (28.1%) cases in the low PNI group and 105 (71.9%) cases in the high PNI group. The median survival time for PFS in the low PNI group and high PNI group was 12.30 months vs. 33.07 months, and 18.57 months vs. not reached in the two groups for OS. Patients in low PNI group were associated with shorter PFS and OS in all patients [Hazard ratio (HR) = 1.913, p = 0.013 and HR = 2.332, p = 0.001]. Additionally, in subgroup analysis, low PNI group cases also had poorer PFS and OS, especially in patients with ICIs. In addition, the multivariate analysis found that carbohydrate antigen 724 (CA724) and TNM stage were independent prognostic factors for PFS. At the same time, indirect bilirubin (IDBIL), CA724, PNI, and TNM stage were independent prognostic factors for OS.

CONCLUSION

Prognostic nutrition index was an accurate inflammatory and nutritional marker, which could predict the prognosis of patients with gastric cancer who received ICIs. PNI could be used as a biomarker for ICIs to identify patients with gastric cancer who might be sensitive to ICIs.

Prognostic Value of Combination of Controlling Nutritional Status and Tumor Marker in Patients with Radical Non-Small-Cell Lung Cancer

Background

Controlling nutritional status (CONUT) and tumor markers are associated with prognosis in patients with non-small-cell lung cancer (NSCLC). This study is aimed at exploring the potential usefulness of T-CONUT, constructed by combining CONUT and tumor markers, for NSCLC patients undergoing radical surgery.

Methods

A total of 483 patients with NSCLC underwent radical surgical resection. The receiver characteristic operating curve (ROC) was used to select the tumor marker with the highest predictive performance, and CONUT was combined with this marker to construct the T-CONUT. The Kaplan–Meier method and log-rank test were used to analyze the overall survival (OS), and chi-square analysis was used to analyze the association between T-CONUT and clinicopathological characteristics. The independent risk factors were analyzed by Cox regression. A nomogram was constructed by R studio. Calibration plots, the c-index, and decision curves were evaluated for the performance of the nomogram.

Results

ROC analysis showed that the predictive performance of CYFRA21–1 was better than that of CEA, NSE, and SCC. CYFRA21–1 was selected for combining with CONUT to construct T-CONUT. Elevated T-CONUT indicates poor prognosis of patients. Histological type, pTNM, and T-CONUT are independent risk factors associated with patient prognosis. The areas under the curve of the nomogram for predicting 3- and 5-year OS were 0.760 and 0.761, respectively.

Conclusion

T-CONUT comprising CYFRA21–1 and CONUT can effectively predict the prognosis of NSCLC patients.

Prognostic impact of prognostic nutritional index on renal cell carcinoma: A meta-analysis of 7,629 patients

Background

Prognostic nutritional index (PNI) is a parameter which reflects nutritional and inflammatory status. The prognostic value of PNI in renal cell carcinoma (RCC) remains in debate. The aim of this study is to evaluate the prognostic value and clinicopathological features of PNI in RCC.

Methods

A literature search was performed in the databases of PubMed, Embase, Web of Science, and Cochrane Library. Hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) were extracted for meta-analysis. The association between PNI and overall survival (OS), cancer-specific survival (CSS), disease-free survival (DFS), progression-free survival (PFS), recurrence-free survival (RFS), and clinicopathological factors were evaluated.

Results

Eleven studies involving 7,629 patients were included for meta-analysis. A decreased PNI was shown to be a significant predictor of worse OS (HR = 2.00, 95%CI = 1.64–2.42, p<0.001), CSS (HR = 2.54, 95%CI = 1.61–4.00, p<0.001), and DFS/PFS/RFS (HR = 2.12, 95%CI = 1.82–2.46, p<0.001) in RCC. Furthermore, a low PNI was correlated with Fuhrman grade III-IV (OR = 1.96, 95%CI = 1.27–3.02, p = 0.002), T stage T3-T4 (OR = 2.21, 95%CI = 1.27–3.87, p = 0.005), presence of sarcomatoid differentiation (OR = 5.00, 95%CI = 2.52–9.92, p<0.001), and presence of tumor necrosis (OR = 3.63, 95%CI = 2.54–5.19, p<0.001).

Conclusion

PNI is an independent prognostic indicator of survival and associated with Fuhrman grade, T stage, sarcomatoid differentiation, and tumor necrosis in patients with RCC.

Preoperative Prognostic Nutritional Index and Neutrophil-to-Lymphocyte Ratio Predict Survival Outcomes of Patients With Hepatocellular Carcinoma After Curative Resection

Increasing evidence indicates that preoperative prognostic indices can serve as independent predictors of survival in patients with cancer. However, the applicability of these indices in patients with hepatocellular carcinoma (HCC) is controversial. This study aims to investigate the prognostic value of these indices in patients with HCC after curative hepatectomy. We retrospectively analyzed the data of 215 patients who underwent curative resection for HCC. Prognostic indices including prognostic nutritional index (PNI) and neutrophil-to-lymphocyte ratio (NLR) were evaluated by comparing by the area under the curve (AUC). Univariate analysis and multivariate analysis were performed to identify independent prognostic factors. Additionally, risk factors were combined to predict the survival of patients. We found that serum albumin concentration, tumor diameter, tumor stage, degree of differentiation, PNI, and NLR were independent prognostic factors for overall survival (OS). Vascular invasion, tumor stage, degree of differentiation, and PNI were independent prognostic factors for recurrence-free survival (RFS). The cutoff value of the PNI and NLR was 43.75 and 3.29, respectively. Patients with low NLR and high PNI had the best outcomes, potentially indicative of the intensive antitumor effects of the immune system. Moreover, patients with at least three risk factors had a significantly lower OS and RFS compared with those with two or fewer risk factors. This new nomogram based on PNI and NLR may provide an accessible and individualized prediction of survival and recurrence for HCC patients.

Emerging strategies based on nanomaterials for ionizing radiation-optimized drug treatment of cancer

Drug-radiotherapy is a common and effective combinational treatment for cancer. This study aimed to explore the ionizing radiation-optimized drug treatment based on nanomaterials so as to improve the synergistic efficacy of drug-radiotherapy against cancer and limit the adverse effect on healthy organs. In this review, these emerging strategies were divided into four parts. First, the delivery of the drug-loaded nanoparticles was optimized owing to the strengthened passive targeting process, active targeting process, and cell targeting process of nanoparticles after ionizing radiation exposure. Second, nanomaterials were designed to respond to the ionizing radiation, thus leading to the release of the loading drugs controllably. Third, radiation-activated pro-drugs were loaded onto nanoparticles for radiation-triggered drug therapy. In particular, nontoxic nanoparticles with radiosensitization capability and innocuous radio-dynamic contrast agents can be considered as radiation-activated drugs, which were discussed in this review. Fourth, according to the various synergetic mechanisms, radiotherapy could improve the drug response of cancer, obtaining optimized drug-radiotherapy. Finally, relative suggestions were provided to further optimize these aforementioned strategies. Therefore, a novel topic was selected and the emerging strategies in this region were discussed, aiming to stimulate the inspiration for the development of ionizing radiation-optimized drug treatment based on nanomaterials.