BACKGROUND: This study explores the significance of computed tomography (CT) radiomic features, along with inflammation and nutrition biomarkers, in the prognosis of postoperative patients with T3N0M0 esophageal squamous cell carcinoma (ESCC). The study aims to construct a related nomogram.
METHODS: A total of 114 patients were enrolled and randomly assigned to training and validation cohorts in a 7:3 ratio. Radiomic features were extracted from their preoperative chest-enhanced CT arterial images of the primary tumor, and inflammatory and nutritional indices, including neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI), were calculated based on laboratory data from the 3 days before surgery. Intra-class correlations coefficient (ICC) and least absolute shrinkage and selection operator (Lasso) were applied to screen valuable radiomics features predicting overall survival (OS), and the Rad-score was calculated. In the training cohort, univariate and multivariate Cox regression analyses identified independent prognostic factors, which were adopted to establish the nomogram.
RESULTS: Eight radiomic features were selected for Rad-score calculation. Multivariate Cox regression revealed Rad-score, PNI, NLR, and PLR as independent prognostic factors for ESCC patients (p < 0.05). A nomogram was constructed based on these variables. The concordance index (C-index) for the nomogram was 0.797 (95% CI: 0.726-0.868) in the training cohort and 0.796 (95% CI: 0.702-0.890) in the validation cohort. Calibration curves indicated good calibration ability, and the receiver operating characteristic (ROC) analysis demonstrated superior discriminative ability for the nomogram in comparison to the Rad-score alone. Decision curve analysis (DCA) confirmed the clinical utility of the nomogram.
CONCLUSIONS: We developed and validated a nomogram for predicting the OS of postoperative T3N0M0 ESCC patients, integrating nutritional, inflammatory markers, and radiomic signature. The combined nomogram can serve as a robust tool for risk stratification and clinical management.

Background: The objective was to examine the predictive value of malnutrition, assessed via the Controlling Nutritional status (CONUT) and Prognostic Nutrition Index (PNI) scores, in the development of contrast-associated acute kidney injury (CA-AKI) following peripheral vascular intervention (PVI).Methods: This retrospective cross-sectional observational study included the enrollment of 243 consecutive patients who underwent PVI. Patients were categorized into two groups based on the occurrence of CA-AKI.Results: Patients with CA-AKI had lower PNI scores and the PNI score was an independent predictor of CA-AKI development (Odds Ratio: 0.518, 95% CI: 2.295-0.908, p = 0.021). Nomogram had higher discriminative ability than both PNI and CONUT scores and discriminative abilities were similar for PNI and CONUT scores.Conclusion: Malnutrition, as identified by the CONUT and PNI, was found to be associated with a high risk of CA-AKI development following PVI.
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UNASSIGNED: To assess the impact of perioperative prognostic nutritional index (PNI) changes on prognosis and recurrence after colorectal cancer surgery.
UNASSIGNED: A total of 475 patients who underwent curative resection for primary colorectal adenocarcinoma and were diagnosed with pathological stage (pStage) II/III were retrospectively reviewed. The patients were divided into two groups: the high group (preoperative PNI ≤ postoperative PNI, n = 290) and the low group (preoperative PNI > postoperative PNI, n = 185).
UNASSIGNED: The low group exhibited significantly higher recurrence and mortality rates (all p < 0.001). Kaplan-Meier analysis showed worse overall and recurrence-free survival in the low group (all p < 0.001). Perioperative PNI changes predicted prognosis and recurrence independent of preoperative nutritional conditions. Subgroup analyses showed better overall survival and recurrence-free survival in the high group across various parameters, such as patient background, surgical outcomes, adjuvant chemotherapy, and pathological characteristics. Multivariate analysis revealed that the low group based on perioperative PNI changes (hazard ratio [HR]: 5.809, 95% confidence interval [CI]: 3.451-9.779, p < 0.001), pathological T stage (HR: 1.962, 95% CI: 1.184-3.253, p = 0.009), and pathological N stage (HR: 3.434, 95% CI: 1.964-6.004, p < 0.001) were identified as independent predictors of worse overall survival.
UNASSIGNED: Patients with pStage II/III colorectal cancer who demonstrate a lower postoperative PNI levels compared to preoperative had poorer overall survival and recurrence-free survival. Perioperative PNI changes can serve as useful biomarkers for predicting survival and recurrence.

UNASSIGNED: Prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) are two novel markers that have emerged as potential candidates as an early indication of the severity of the disease in coronavirus disease 2019 (COVID-19) patients.
UNASSIGNED: The objective of the study is to assess the utility of the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) as markers of severity among patients with COVID-19 infection.
UNASSIGNED: This is a retrospective study conducted in a tertiary care centre in South India. A total of 80 patients diagnosed with COVID-19 were included in the study. The patients were divided into mild, moderate, and severe groups based on the clinical parameters as per Indian Council of Medical Research guidelines. Lab values taken at admission were obtained from patient records, using which the PNI and SII were calculated using standard formulae. These markers were correlated with the severity of the COVID-19 illness.
UNASSIGNED: PNI and SII were significantly elevated in the patients with severe COVID-19 illness as compared with mild COVID-19 illness. The mean PNI among subjects with mild COVID-19 and severe COVID-19 being 46.62 ± 6.51 and 34.09 ± 5.81, respectively. The mean SII among subjects with mild COVID-19 was 9,52,287.2 ± 1,42,113, and among subjects with severe COVID-19 was 15,39,461 ± 8,04,285. The cut-off value for PNI and SII for predicting severity of COVID-19 illness was 35.93 and 5,82,400, respectively. The sensitivity for PNI was 87.5, and the SII was 95.
UNASSIGNED: The present study showed a significant correlation between the SII and PNI as markers used to determine the severity of COVID-19. Based on these findings, it can be effectively used independently of other markers to predict critical illness among COVID-19 patients.

BACKGROUND: Hip fractures in older people result in increased mortality.
OBJECTIVE: We developed and validated an accurate and simple prognostic scoring system for hip fractures that can be used preoperatively.
METHODS: Retrospective study.
METHODS: Multicenter.
METHODS: Patients aged ≥65 years with hip fractures who underwent surgery between 2011 and 2021 were enrolled.
METHODS: The significant factors were determined with logistic regression analysis, and a scoring system was developed. The patients were classified into three groups, and a log-rank test was performed to evaluate 1-year survival rates. The model was internally and externally validated using the 5-fold cross-validation and data from another hospital, respectively.
RESULTS: We included 1026 patients. The analysis revealed eight significant prognostic factors: sex, body mass index, history of chronic heart failure and malignancy, activities of daily living (ADLs) before injury, hemoglobin and the prognostic nutritional index (PNI) at injury, and the American Society of Anesthesiologists Physical Status. The area under the receiver operating characteristic curve (AUC) after internal validation was 0.853. The external validation data consisted of 110 patients. The AUC of the model for the validation data was 0.905, showing outstanding discrimination. Sensitivity and specificity were 88.7% vs. 100% and 93.3% vs. 95.2% for the development and validation data, respectively.
CONCLUSIONS: We developed and validated an accurate and simple prognostic scoring system for hip fractures using only preoperative factors. Our findings highlight PNI as an important predictor of prognosis in hip fracture patients.

BACKGROUND: Several research have indicated the significant potential of the Prognostic Nutritional Index (PNI) as a prognostic biomarker in lymphoma patients. However, there is some inconsistency in the findings of a few studies. Hence, to offer a thorough evaluation of the predictive significance of PNI in lymphoma patients, we performed a meta-analysis to examine the prognostic value of PNI for survival outcomes in lymphoma patients.
METHODS: We conducted a comprehensive search for pertinent works published up until December 2023 in databases such as PubMed, EMBASE, Cochrane Library, and Web of Science. We obtained hazard ratio (HR) data related to survival outcomes and computed aggregated HRs with their corresponding 95% confidence intervals (CIs) to evaluate the correlation between PNI and both overall survival (OS) and progression-free survival (PFS) in lymphoma patients.
RESULTS: By analyzing data from 1260 patients in 28 studies, we found that PNI levels were associated with prognosis in lymphoma patients. High PNI levels predicted that patients had longer OS (HR: 0.46, 95% CI 0.37-0.58, P < 0.05) and better PFS (HR: 0.56, 95% CI 0.45-0.70, P < 0.05). Subgroup analyses showed that the predictive ability of PNI for patient prognosis may differ depending on the type of lymphoma. In addition, we found that the critical PNI value had greater predictive potential at 40-45 and above 45.
CONCLUSIONS: Our study suggests a strong association between PNI and prognostic outcomes in lymphoma patients, indicating that PNI holds substantial prognostic value in this population.

OBJECTIVE: Prognostic inflammation-based parameters have been reported as useful tools in various oncologic diseases. Pancreatic ductal adenocarcinoma (PDAC) is characterized by a high mortality rate, making reliable prognostic markers highly desirable. However, there is still inconsistency in the literature regarding the efficacy of the different available scores.
METHODS: A total of 207 patients, who underwent primary resection of PDAC from January 2000 to December 2018 at the University Hospital of Erlangen, were included in this retrospective single-center study. Different biomarkers, including the preoperative neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), the c-reactive protein (CRP)-albumin ratio (CAR), the lymphocyte-CRP ratio (LCR), the prognostic nutritional index (PNI) and the modified Glasgow prognostic score (mGPS) were analyzed for their ability to predict overall survival (OS).
RESULTS: In our cohort, the median overall survival was 20.7 months. Among the investigated biomarkers, NLR and PNI were identified as independent prognostic markers (Hazard Ratio (HR) 1.6 (1.0-2.5), p = 0.048 and HR 0.6 (0.4-0.9), p = 0.018), whereas PLR, CAR, LCR and mGPS did not reach significance in the multivariate analysis. Subgroup analysis revealed that the prognostic value of NLR and PNI is particularly evident in locally advanced tumor stages (pT3/4 and pN+).
CONCLUSIONS: The NLR and PNI could serve as valuable tools for estimating prognosis in patients with PDAC undergoing pancreatic resection in curative intention, especially in locally advanced tumor stages. However, conflicting results in the current literature highlight the need for further prospective studies to validate these findings.

OBJECTIVE: An increasing number of patients with complicated systemic comorbidity can undergo colorectal cancer (CRC) surgery. Such patients have a high risk of developing poor postoperative outcomes. This study aimed to identify preoperative factors, including nutritional and sarcopenia statuses, leading to poor postoperative outcomes in patients with severe systemic comorbidities.
METHODS: This study included 114 patients who underwent radical CRC resections and had American Society of Anesthesiologists Physical Statuses ≥3. We retrospectively analyzed the relationships between clinical factors, postoperative complications (within 28 days postoperatively and Clavien-Dindo classification grade ≥2), length of hospital stay, discharge destination, and overall survival (OS).
RESULTS: The median patient age was 74.5 years (range=41.0-93.0 years). Thirty-six patients had postoperative complications (31.6%), and the risk factors in the multivariate analyses were rectal cancer and preoperative nutritional disorders with Prognostic Nutritional Index ≤40. In patients with nutritional disorders, the postoperative hospital stay was longer, and a higher (but not statistically significant) percentage were not discharged home. Moreover, the independent factors for OS identified in the multivariate analyses were body mass index (BMI) and hemodialysis.
CONCLUSIONS: In patients with CRC and severe systemic comorbidities, those with Prognostic Nutritional Index ≤40 have a high risk of developing postoperative complications, leading to a prolonged postoperative hospital stay and possibly preventing discharge home. Additionally, among these patients, OS was poor in those with low BMI or preoperative hemodialysis.

OBJECTIVE: Immune checkpoint inhibitors (ICIs) are the standard treatment for advanced head and neck squamous cell carcinoma (HNSCC). Programmed death-ligand 1 (PD-L1) is clinically assessed before initiating ICIs; however, there are no established biomarkers for predicting the response to immunotherapy. In this study, inflammatory and nutritional parameters were examined to determine the therapeutic outcomes of ICIs for HNSCC.
METHODS: Sixty-five patients with metastatic or recurrent HNSCC who received programmed death-1 (PD-1) blockade were enrolled. Inflammatory and nutritional indices were correlated with patient outcomes, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI).
RESULTS: Patients aged <70 years were significantly associated with a high NLR, whereas those with a performance status of 2 or 3 were closely related to a high NLR, high SII, and low PNI. Although all patients achieved an objective response rate of 24.6% and a disease control rate of 36.9%, the NLR, PLR, SII, and PNI values were not significantly different between responders and non-responders. Univariate analysis showed that the NLR, PLR, SII, and PNI were significant predictors of progression-free survival (PFS) and overall survival (OS). Multivariate analysis identified PNI as an independent predictor of PFS and OS.
CONCLUSIONS: PNI, as a nutritional marker, was identified as a significant predictor of outcomes following PD-1 blockade administration in patients with advanced HNSCC, compared to inflammatory markers, such as NLR, PLR, and SII.

UNASSIGNED: The management of nutritional risk has garnered significant attention in individuals diagnosed with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) due to the high prevalence of malnutrition and its correlation with unfavorable outcomes. While numerous rating scales exist to assist in assessment for both clinical and research purposes, there is considerable variability in the selection of scales based on the characteristics of the study participants and the study design. The objective of this study was to examine the efficacy of the Geriatric Nutritional Risk Index (GNRI) and Prognostic Nutritional Index (PNI) in identifying malnutrition and predicting prognosis in elderly AECOPD patients.
UNASSIGNED: From January 2022 to December 2022, a consecutive inclusion of elderly AECOPD patients admitted to the First Affiliated Hospital of Zhengzhou University was conducted. Diagnosing malnutrition in patients using PNI and GNRI, comparing the results with the diagnostic outcomes based on the Global Leadership Initiative on Malnutrition (GLIM) criteria through Receiver Operating Characteristic curves. Logistic regression analysis was employed to assess the risks associated with length of stay (LOS), hospitalization costs, and Charlson Comorbidity Index (CCI) based on GLIM, GNRI, or PNI.
UNASSIGNED: A total of 839 elderly AECOPD patients were investigated in the study. The GNRI and PNI demonstrated a sensitivity of 89.5 and 74.1%, specificity of 77.2 and 66.4%, and an area under the curve of 0.834 and 0.702, respectively. The identification of high malnutrition-risk cases using the GLIM, GNRI and PNI were associated with a significant increase in the risk of LOS over 7 days [odds ratio (95% CI) for GLIM, GNRI, PNI: 1.376 (1.033-1.833); 1.405 (1.070-1.846); 1.875 (1.425-2.468)] and higher hospitalization expenses [OR (95% CI) for GLIM, GNRI: 1.498 (1.080-2.080); 1.510 (1.097-2.079)], but not with the CCI.
UNASSIGNED: According to our study, it is possible to use GNRI and PNI as alternatives to GLIM in the context of AECOPD, which makes it easier to identify malnutrition. The utilization of GNRI and PNI as alternatives to GLIM in the context of AECOPD enables the identification of malnutrition. The presence of malnourished individuals experiencing AECOPD is correlated with higher probabilities of extended hospital stays and escalated in-hospital expenses.