Can maternal inflammatory and nutritional status, evaluated by the hemoglobin, albumin, lymphocyte, and platelet (HALP) score and the prognostic nutritional index (PNI) in the first trimester, predict late-onset fetal growth restriction?

OBJECTIVE: The aim of this study was to evaluate the potential of immunonutritional markers, specifically the hemoglobin, albumin, lymphocyte, and platelet (HALP) score and the prognostic nutritional index (PNI), in predicting late-onset fetal growth restriction (LO-FGR) during the first trimester. MATERIALS AND METHODS: This retrospective study was conducted at a tertiary care center between October 2022 and August 2023. The study included a total of 213 singleton pregnancies, with 99 women in the LO-FGR group and 114 in the healthy control group, matched by maternal age and gestational age at delivery. All blood samples were collected between 11 and 14 weeks of gestation (during the first-trimester screening test). We analyzed first-trimester laboratory parameters, specifically focusing on hemoglobin levels, white blood cells (WBCs), lymphocytes, platelets, and albumin levels. Afterwards, we calculated the HALP score and PNI, and then compared the values of both groups. RESULTS: Both HALP score (3.58 ± 1.31 vs. 4.19 ± 1.8, p = 0.012) and PNI (36.75 ± 2.9 vs. 39.37 ± 3.96, p < 0.001) were significantly lower in the FGR group than in the control group. The HALP score cut-off value of < 3.43 in predicting FGR had a sensitivity of 62.3% and specificity of 54.5% (AUC = 0.600, 95% CI: 0.528-0.672, p = 0.012). The PNI cut-off value of < 37.9 in predicting FGR had a sensitivity of 65.8% and specificity of 62.9% (AUC = 0.707, 95% CI: 0.632-0.778, p < 0.001). While the HALP score was not a significant predictor of composite adverse neonatal outcomes in the FGR group, PNI showed a cut-off value of < 37.7 with a sensitivity of 60.9% and specificity of 59.7% (AUC = 0.657, 95% CI: 0.581-0.733, p < 0.001). CONCLUSION: The HALP score and PNI are valuable prognostic tools for predicting the risk of FGR in the first trimester. Low PNI values are also associated with composite adverse neonatal outcomes in pregnancies complicated by FGR.

Prognostic Nutritional Index is Related to All-Cause Mortality in Patients With Stage IV Colorectal Cancer Treated With Capecitabine: Single-Center 24-Month Observational Study in Vietnam.

AIM: To determine the mortality rate and the predictive value of the prognostic nutritional index (PNI) for all-cause mortality during the 24 months in patients with stage IV colorectal cancer treated with capecitabine. METHODS: We conducted a study on 87 stage IV colorectal cancer patients treated with capecitabine. Before the day of treatment, all patients were measured CEA and CRP-hs levels and calculated neutrophil/lympho ratio (NLR) and PNI. Patients were monitored and collected drug side effects and mortality for 24 months. RESULTS: The mortality rate of study subjects was 60.9%. CRP-hs, NLR, and PNI were independent factors associated with 24-month mortality in patients with stage IV colorectal cancer (p < 0.05 to p < 0.01). At a cut-off value of 38.51, PNI was a predictor for mortality, with the area under the curve (AUC) of 0.88 and p < 0.001. CONCLUSIONS: PNI was a good predictor of all-cause mortality in patients with stage IV colorectal cancer treated with capecitabine for 24 months.

Prognostic Nutritional Index as a New Prediction Tool for All-Cause Mortality in Patients with Chronic Limb-Threatening Ischemia Undergoing Endovascular Therapy.

Objectives: Chronic Limb-Threatening Ischemia (CLTI) represents a complex manifestation of peripheral artery disease distinguished by symptoms such as ischemic rest pain, non-healing ulcers on the lower limb or foot, and the development of gangrene. CLTI is associated with a high risk of limb amputation, decreased quality of life, and substantial morbidity and mortality. The Prognostic Nutritional Index (PNI), which is calculated using albumin and lymphocyte levels, reflects the immunological and nutritional status. The objective of this study was to investigate the correlation between PNI levels and mortality among patients diagnosed with CLTI who underwent endovascular therapy. Methods: Individuals diagnosed with CLTI who received endovascular therapy below the knee in our tertiary care center were enrolled in this retrospective study. The patients were divided into two groups: survivors and non-survivors. Logistic regression analyses were performed to detect independent predictors of mortality and using Cox regression model, we assessed the relationship between PNI and mortality. Survival curves were estimated using the Kaplan-Meier method. Results: The study comprised 113 patients diagnosed with PAD who underwent EVT. The non-survivor group (42 patients) was older (62.9±10.9 vs. 67.7±9.9, p=0.045) and had a higher prevalence of chronic renal failure (22.5% vs. 42.9%, p=0.023) and congestive heart failure (8.5% vs. 21.4%, p:0.049) than the survivor group (71 patients). The median PNI value was lower in the non-survivor group than in the survivor group (35.9±5 vs 38.2±4.4, p=0.012). Cox regression analyses showed that Low PNI was associated with increased mortality (HR=0.931, CI=0.872-0.995, p=0.035). PNI cut-off of 37.009 showed 64.3% sensitivity, 64.8% specificity, and AUC of 0.642 for predicting all-cause mortality. Kaplan-Meier analysis supported higher PNI correlating with better survival. Conclusion: The Prognostic Nutritional Index was independently associated with mortality among individuals diagnosed with Chronic Limb-Threatening Ischemia.

Predicting monotherapy resistance risk in patients with low-risk gestational trophoblastic neoplasia: integration of the systemic immune-inflammation index and the prognostic nutritional index.

Purpose: Currently, there are no reliable indicators for the early identification of patients with low-risk gestational trophoblastic neoplasia (GTN) who develop resistance to monotherapy. This study aimed to evaluate the effectiveness of combining the Systemic Immune-Inflammation Index (SII) and Prognostic Nutritional Index (PNI) in detecting early resistance to monotherapy in patients with low-risk GTN. Methods: This retrospective study included 91 patients with low-risk GTN who received initial monotherapy at Fujian Maternal and Child Health Hospital between 2013 and 2021. The SII and PNI before chemotherapy were calculated from prechemotherapy peripheral blood samples, with cut-off values determined by receiver operating characteristic (ROC) curves. The SII-PNI score ranged from 0 to 2 points and was categorized as follows: a score of 2 points indicated a high SII (≥467.02) and a low PNI (≤51.35); a score of 1 point indicated either a high SII or a low PNI; and a score of 0 points indicated neither a high SII nor a low PNI. Results: Ninety-one patients with low-risk GTN underwent monotherapy, 19 of whom developed resistance, whereas the remaining 72 did not. The SII was significantly greater in chemotherapy-resistant patients than in non-resistant patients (P=0.04), whereas the PNI was markedly lower in chemotherapy-resistant patients (P=0.002). Univariate analysis revealed that cut-off values of 467.02 for the SII (P=0.04) and 51.35 for the PNI (P=0.024) were associated with chemotherapy resistance in patients with low-risk GTN. As the SII-PNI score increased, the proportion of chemotherapy-resistant patients increased (P<0.001), and the time for human chorionic gonadotropin (hCG) normalization correspondingly increased (P<0.001). Multivariate logistic regression analysis indicated that a high SII-PNI score is an independent risk factor for chemotherapy resistance in patients with low-risk GTN (P=0.001). Conclusion: A high SII and low PNI are linked to chemotherapy resistance in patients with low-risk GTN. The pretreatment SII-PNI score is a key indicator for predicting the sensitivity of patients with low-risk GTN to single-agent chemotherapy, aiding in the early identification of individuals at high risk of resistance.

Development and validation of a prognostic scoring system for 1-year mortality in older patients with hip fractures.

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. DESIGN: Retrospective study. SETTING: Multicenter. PARTICIPANTS: 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.

Predictors of Length of Stay after Transcatheter Aortic Valve Implantation: Impact of Prognostic Nutritional Index.

Background: Pre-transcatheter aortic valve replacement (TAVR) nutritional status can potentially affect the length of hospital stay (LoS) after TAVR. The Prognostic Nutritional Index (PNI) is a widely recognised nutritional index. We aimed to determine the effect of PNI on LoS in patients undergoing TAVR. Methods: The study population (158 patients) was divided into two groups: early discharge (LoS ≤ 3 days) and late discharge (LoS > 3 days). PNI was calculated before TAVR. Results: In the LoS > 3 days group, the median age, creatinine level, rate of surgical access site closure and rate of major complications were higher, whereas estimated glomerular filtration rate, albumin, haemoglobin, lymphocyte count and PNI were significantly lower. Receiver operating characteristic curve analysis revealed a PNI cutoff of 39 (area under the curve = 0.778, p < 0.001) with 86.8% sensitivity and 55.2% specificity for predicting extended LoS. The 30-day endpoint analysis revealed significantly higher rates of death and hospitalisation with LoS > 3 days and PNI ≤ 39. Multivariate binary logistic regression analysis identified several independent predictors of extended LoS: severe renal insufficiency [odds ratio: 3.951 (95% confidence interval: 1.281-12.191); p = 0.017], surgical access site closure [4.353 (1.701-11.141); p = 0.002), complications [7.448 (1.305-42.518); p = 0.024] and PNI < 39 [5.906 (2.375-14.684); p < 0.005]. Conclusions: Decreased PNI may be associated with LoS > 3 days after TAVR. Nutritional status assessed using PNI may be a useful independent predictor of LoS after TAVR.

A prognostic nomogram for T3N0M0 esophageal squamous cell carcinoma patients undergoing radical surgery based on computed tomography radiomics and inflammatory nutritional biomarkers.

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. CONCLUSION: 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.

Prognostic value of nutrition for contrast-induced nephropathy in patients undergoing peripheral vascular intervention.

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.

[Box: see text].

Prognostic Nutritional Index (PNI) and Systemic Immune-Inflammatory Index (SII) as markers of severity among patients having COVID-19 infection.

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusion: 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.

Impact of perioperative prognostic nutritional index changes on the survival of patients with stage II/III colorectal cancer.

Aim: To assess the impact of perioperative prognostic nutritional index (PNI) changes on prognosis and recurrence after colorectal cancer surgery. Methods: 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). Results: 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. Conclusions: 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.

Predictive value of prognostic nutritional index as prognostic biomarkers in patients with lymphoma: a systematic review and meta-analysis.

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. CONCLUSION: Our study suggests a strong association between PNI and prognostic outcomes in lymphoma patients, indicating that PNI holds substantial prognostic value in this population.

Associations of prognostic nutritional index with risk of all-cause and cardiovascular disease mortalities in persons with gestational diabetes mellitus: A NHANES-based analysis.

OBJECTIVE: To investigate relationships between prognostic nutritional index (PNI) during pregnancy and risk of all-cause mortality (ACM) and cardiovascular disease (CVD) mortality in persons with gestational diabetes mellitus (GDM). METHODS: A cross-sectional study was conducted using NHANES data from 2007 to 2018, and weighted Cox regression models were established. Restricted cubic spline analysis was used to unveil associations of PNI with risk of ACM and CVD mortalities in individuals with GDM. Receiver operating characteristic curve was employed for determination of threshold value for association of PNI with mortality. Sensitivity analysis was performed to verify the stability of the results. RESULTS: 734 GDM individuals and 7987 non-GDM individuals were included in this study. In GDM population, after adjusting for different categorical variables, PNI was significantly negatively correlated with ACM risk. Subgroup analysis showed that among GDM populations with no physical activity, moderate physical activity, parity of 1 or 2, negative correlation between PNI and risk of ACM was stronger than other subgroups. Sensitivity analysis results showed stable negative correlations between PNI and ACM and CVD mortality of total population, and between PNI and ACM of GDM. CONCLUSION: In individuals with GDM, PNI was negatively correlated with ACM risk, especially in populations with no physical activity, moderate physical activity, and parity of 1 or 2. PNI = 50.75 may be an effective threshold affecting ACM risk in GDM, which may help in risk assessment and timely intervention for individuals with GDM.

PNI is useful for predicting the prognosis of patients with soft tissue sarcoma: A retrospective study.

BACKGROUND: It is known that preoperative Prognostic Nutritional Index (PNI) is useful in predicting prognosis in gastrointestinal diseases and that preoperative improvement of nutritional status improves prognosis. However, there have been few large-scale reports examining the prognostic value of PNI in soft tissue sarcomas. Therefore, the aim of this study is to investigate whether the PNI can be useful for predicting overall survival in soft tissue sarcoma. METHODS: Between January 2006 and March 2022 at our hospital, 111 patients with pathologically diagnosed soft tissue sarcoma were included, retrospectively. Several nutritional or inflammatory biomarkers such as PNI were calculated from the pretreatment blood sample results. The patients were classified into two groups (low and high groups) based on the median value of each parameter. Overall survival was analyzed by the Kaplan‒Meier method and log-rank test. Univariate and multivariate analyses using the Cox proportional hazards model were used to investigate prognostic factors for overall survival. RESULTS: The median overall survival was 24.3 months (mean 37.3 months), and the high PNI group had a significantly longer overall survival than the low PNI group (p < 0.0001). PNI was the most significant univariate factor for overall survival among other nutritional and inflammatory parameters (HR: 5.64, 95% CI: 2.26-14.12, p = 0.0002). The multivariate proportional hazards model was built using variables with prognostic potential as suggested by previous analysis with respect to patient characteristics and PNI. As potential confounding factors, we included PNI, stage, age, and tumor location. PNI was also an independent prognostic factor in multivariate analysis (HR: 7.02, CI: 2.52-19.40, p = 0.0002). CONCLUSION: PNI is a useful prognostic factor among various parameters for overall survival in patients with soft tissue sarcoma.

Comment on, "Creactive protein levels, the prognostic nutritional index, and the lactate dehydrogenasetolymphocyte ratio are important prognostic factors in primary central nervous system lymphoma: a singlecenter study of 223 patients".

This study by Zuo et al. (2024) investigates the prognostic significance of C-reactive protein (CRP) levels, the prognostic nutritional index (PNI), and the lactate dehydrogenase-to-lymphocyte ratio (LLR) in primary central nervous system lymphoma (PCNSL) using data from 223 patients. The research demonstrates that these markers are critical in predicting patient outcomes, offering novel insights beyond traditional prognostic models like the MSKCC and IELSG scores. Despite its strengths, the study's retrospective design and lack of validation cohort limit its generalizability. Future research should focus on validating these findings in diverse, multicenter settings and integrating these markers with existing prognostic models to improve clinical decision-making. Longitudinal studies and advanced statistical methods are recommended to further explore the interactions between these factors and their impact on patient outcomes, potentially leading to the development of targeted therapies for PCNSL.

Prognostic Nutritional Index and the Survival of Patients with Endometrial cancer: A Meta-analysis.

The prognostic nutritional index (PNI) has emerged as a potential predictor of clinical outcomes in various cancers. However, a quantativetily analysis of its role in endometrial cancer (EC) remains lacking. This meta-analysis aims to evaluate the prognostic value of PNI on the survival outcomes of patients with EC. A comprehensive literature search was conducted in PubMed, EMBASE, Web of Science, Wanfang, and CNKI to identify relevant cohort studies. Studies were included if they provided sufficient data to calculate hazard ratios (HRs) for overall survival (OS) and progression-free survival (PFS) based on PNI levels. Data extraction and quality assessment were performed independently by two reviewers. Pooled HRs with 95% confidence intervals (CIs) were calculated using a random-effects model to account for heterogeneity. A total of 10 studies, encompassing 3656 patients, met the inclusion criteria. The meta-analysis revealed that a low PNI was significantly associated with poorer OS (HR = 2.01, 95% CI = 1.62-2.49, p < 0.05; I2 = 54%) and PFS (HR = 2.75, 95% CI = 1.74-4.33, p < 0.05; I2 = 78%) in patients with EC. Subgroup analyses indicated that the prognostic impact of PNI was consistent in studies from Asian and non-Asian countries, and across studies with different ages of the patients, cutoff values of PNI, and follow-up duration (p for subgroup difference all > 0.05). In conclusion, the PNI is a prognostic marker for survival in patients with EC.

Systemic immunoinflammatory index and prognostic nutrition index for predicting pathologic responses of patients with advanced gastric cancer after neoadjuvant therapy for advanced gastric cancer.

To investigate the value of prognostic nutrition index (PNI) and systemic immunoinflammatory index (SII) for predicting pathological responses of patients with advanced gastric cancer (GC) after neo-adjuvant chemotherapy (NACT). The clinicopathological data of 326 patients with advanced GC who received NACT in Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City) from January 2017 to December 2021 were retrospectively collected. The SII and PNI of patients were calculated. The receiver operating characteristics (ROC) curve was leveraged for getting the optimal cutoff values of SII and PNI. The pathological response of patients after NACT, as obtained from their postoperative pathological examinations, was evaluated based on the tumor regression grade (TRG) criteria. Multivariate regression analysis was employed for identifying factors that led to various pathological responses after NACT in advanced GC patients. The log-rank test was utilized for between-group comparison of patients' survival curves. The SII and PNI were 507.45 and 48.48 respectively, and their levels were divided into high and low groups. Pathological response (TRG 0-1) was observed in 66 cases (20.25%), while non-pathological response (TRG 2-3) was observed in 260 cases (79.75%). The results of multivariate logistic regression analysis showed that tumor diameter < 5 cm, ypT T0-T2, ypN N0, chemotherapy regimen XELOX (capecitabine combined with oxaliplatin), SII < 507.45 (P=0.002), PNI > 48.48 were all independent factors affecting the pathological responses of advanced GC patients after NACT (all P < 0.05). With SII and PNI being included, the AUC was 0.821 (95% CI: 0.765-0.876), and the specificity was 87.90% and the sensitivity was 64.20%. The Kaplan-Meier survival curve analysis showed that NACT patients with tumor diameter < 5 cm, ypT T0-T2, ypN N0, XELOX chemotherapy regimen, SII < 507.45 and SII ≥ 507.45 had a higher survival rate. (P < 0.001). Before treatment, tumor diameter < 5 cm, ypT T0-T2, ypN N0, chemotherapy regimen XELOX, SII < 507.45, PNI > 48.48 were all independent factors affecting the pathological response of advanced GC patients after NACT. Moreover, the inclusion of SII and PNI increased the accuracy of predicting the pathological response of patients after NACT.

Prognostic value of anthropometric- and biochemistry-based nutrition status indices on blood chemistry panel levels during cancer treatment.

Body weight, body mass index (BMI), Nutrition Risk Screening 2002 (NRS2002), and prognostic nutritional index (PNI) are among vital nutrition status indices employed during cancer treatment. These have also been associated with levels of blood chemistry panels (BCPs), which are touted as significant indicators of disease prognosis. However, it remains unclear which nutrition status index better predicts future trends in specific BCPs. Using the records of 407 cancer patients, we retrospectively examined the potential of nutritional status indices at baseline for predicting changes in specific BCPs over a 6-week period. Generally, both serum biochemical parameters and nutrition status indices fluctuated over the study period among study participants. PNI was often linearly associated with blood cell counts (white blood cells [WBCs] and hemoglobin) compared with anthropometric-based nutrition status indices. Increase in body weight was protective against having abnormal lymphocyte levels at 6 weeks (odds ratio [OR]: 0.960-0.974; CI: 0.935-0.997; P < 0.05), while increase in baseline PNI was associated with 0.865-0.941 and 0.675-0.915 odds of having future abnormal WBC and lymphocyte levels, respectively. Increases in PNI were also protective against having future abnormal albumin levels (OR: 0.734-0.886) and 8.5-12.5% decreases in the odds of having an abnormal C-reactive protein level in subsequent visits. Changes in NRS2002 tended to be associated with the odds of having future abnormal blood glucose levels. In conclusion, the serum biochemistry-derived nutrition status index, PNI, is a more consistent measure as an early indicator to track the trends of future changes in the BCPs of cancer patients. This implies that PNI could be targeted as an early-warning measure with relevant preventive interventions for patients at risk of malnutrition.

Association Apo B/Apo a-1 Ratio and Prognostic Nutritional Index with 90-Day Outcomes of Acute Ischemic Stroke.

Background: The relationship between insulin resistance-related indices and the outcomes of acute ischemic stroke (AIS) is still unclear. This study aimed to explore the association between the Apo B/Apo A-1 ratio and the Prognostic Nutritional Index (PNI) with the 90-day outcomes of AIS. Methods: A total of 2011 AIS patients with a 3-month follow-up were enrolled in the present study from January 2017 to July 2021. Multivariate logistic regression modeling was performed to analyze the relationship between Apo B/Apo A-1 ratio, PNI, and AIS poor outcomes. The mediating effect between the three was analyzed using the Bootstrap method with PNI as the mediating variable. Results: Among the 2011 included AIS patients, 20.3% had a poor outcome. Patients were categorized according to quartiles of Apo B/Apo A-1 ratio and PNI. Multivariate logistic regression revealed that the fourth Apo B/Apo A-1 ratio quartile had poorer outcomes than the first quartile (OR 1.75,95%CL 1.21-2.53, P=0.003), and the fourth PNI quartile exhibited a lower risk of poor outcomes than the first quartile (OR 0.40, 95%CL 0.27-0.61, P<0.001). PNI displayed a significant partially mediating effect (21.4%) between the Apo B/Apo A-1 ratio and poor AIS outcomes. Conclusion: The Apo B/Apo A-1 ratio is a risk factor for poor AIS outcomes, whereas PNI acts as a protective factor. The association between the ApoB/ApoA-1 ratio and poor AIS outcomes was partially mediated by PNI.

The malnutrition in AECOPD and its association with unfavorable outcomes by comparing PNI, GNRI with the GLIM criteria: a retrospective cohort study.

Introduction: 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. Methods: 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. Results: 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. Conclusion: 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.

Pancreatic cancer - epidemiology, risk factors, nutritional and infl ammatory prognostic and predictive factors.

BACKGROUND: Pancreatic cancer remains one of the most challenging malignancies to treat, with consistently low survival rates despite advances in medical research. The identification and validation of effective prognostic biomarkers are crucial for improving diagnostic accuracy and treatment outcomes. OBJECTIVE: The aim of the work is to analyze the latest data of the pancreatic cancer incidence and mortality, comparing them with global epidemiological data. The narrative review also aims to summarize current knowledge about various prognostic biomarkers in the pancreatic cancer treatment, including indicators of performance status, nutritional and inflammatory markers. METHODS: The most recently available national epidemiological data on pancreatic cancer are analyzed. The literature review is focused on markers that evaluate the general condition of patients, such as performance status, body mass index, prognostic nutritional index and markers of the inflammatory response, such as Glasgow prognostic score, C-reactive protein, neutrophil to lymphocyte ratio, systemic inflammatory response index and systemic immune inflammation index. These biomarkers are analyzed for their role in predicting prognosis and response to systemic therapy for pancreatic cancer. RESULTS: Both the Slovak Republic and the Czech Republic are globally ranked in the leading places in terms of pancreatic cancer incidence and mortality, both in estimates and real data. Indicators of nutritional and performance status play a critical role in patient assessment and influence treatment decisions, with potential impact on treatment outcomes. Inflammatory markers have shown significant prognostic value, correlating with the patient's immune response to the tumor and inflammatory processes that may promote disease progression. However, despite their promising predictive capabilities, these biomarkers are not routinely used in clinical practice due to the need for further validation. CONCLUSION: Integration of new biomarkers into clinical practice could lead to more personalized therapeutic decisions and improved treatment outcomes. Further research is needed for a more comprehensive assessment of the validity of these biomarkers and their use in common clinical conditions.