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.

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.

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.

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

To investigate the association between preoperative nutritional scores and moderate-to-severe acute kidney injury (AKI) after coronary artery bypass graft (CABG) surgery and the predictive significance of nutritional indices for moderate to severe AKI.

This study retrospectively included older patients underwent CABG surgery from the Medical Information Mart for Intensive Care (MIMIC) database. Nutritional scores were calculated by the Geriatric Nutritional Risk Index (GNRI) and the Prognostic Nutritional Index (PNI), respectively. Moderate-to-severe injury was determined by KDIGO criteria. Logistic regression, subgroup analysis, and restricted cubic splines were utilized to investigate the association. The predictive value was also assessed by the area under the curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI).

A total of 1,007 patients were retrospectively included, of which 100 (9.9%) and 380 (37.7%) had malnutrition calculated by GNRI and PNI scores. The incidence of moderate-to-severe AKI was 524 (52.0%). After adjustment for selected risk factors, worse nutritional scores were associated with a higher incidence of moderate-to-severe AKI (PGNRI<0.001; PPNI=0.001). Integrating these indices into different base models improves their performance, as manifested by significant improvements in AUCs and NRIs (p < 0.05).

Worse preoperative nutritional status was associated with an elevated risk of postoperative moderate-to-severe AKI. Integrating these indices into base models improve their predictive performance. These results highlight the importance of assessing nutritional status among older patients had CABG surgery.

This study aimed to assess the predictive value of baseline 18F-FDG PET radiomics features, metabolic parameters, and clinical factors for PFS and OS in elderly DLBCL patients. Using LASSO COX regression, we derived Radscore from PET radiomics features. We constructed and externally validated prognostic models, evaluating their performance through various metrics. From 341 training set patients and 83 external validation set patients revealed significant correlations between PET radiomics features and survival outcomes. Multivariate COX analysis identified associations of radiomics features (Radscore), metabolic parameters (TMTV, Dmax), and clinical factors (ECOG PS, hemoglobin level) with PFS and OS. In external validation, the combined model incorporating radiomic features, metabolic parameters, and clinical factors showed superior predictive performance for PFS and OS compared to other models. The combined model had higher C-index values for both PFS and OS, and its td-ROC curves exhibited significantly higher AUCs. Calibration curves demonstrated good consistency, and DCA revealed a higher net benefit for the combined model. In conclusion, the combined model that incorporated 18F-FDG PET radiomics features, metabolic parameters, and clinical factors demonstrated superior prognostic predictive ability, providing a useful tool for personalized treatment decisions in elderly DLBCL patients.

To find the independent factors affecting the prognosis of AITL patients, establish a novel predictive model, and stratify the prognosis of AITL patients. We retrospectively analyzed the clinical data of 86 patients diagnosed with AITL in the First Affiliated Hospital of Wenzhou Medical University from December 2010 to March 2022. The clinical features, recurrence time, and death time of patients were collected and analyzed statistically. The median age of our patients was 68 years old, and the male-to-female ratio was 2.2: 1. There are differences between males and females in ECOG PS score (p = 0.037), β2 microglobulin levels (p = 0.018) and IgM (p = 0.021). Multivariate COX regression analysis showed that C-reactive protein > 39.3 mg/L (hazard ratio (HR), 5.41; p = 0.0001), Age > 66 years (hazard ratio (HR), 3.06; p = 0.0160), Ki67 positive (hazard ratio (HR), 4.86; p = 0.0010) and early progression of disease within 24 months (POD24) after diagnosis (hazard ratio (HR), 12.47; p = 0.0001) were independent factors affecting the prognosis of OS. KM analysis showed that the predictive model established by these four factors could effectively predict the prognosis of patients with AITL (p < 0.0001), and the ROC curve showed that the predictive ability of the new predictive model (AUC = 0.909) was significantly better than that of the traditional predictive models, such as IPI (AUC = 0.730), PIT (AUC = 0.720), PIAI (AUC = 0.715) and AITL score (AUC = 0.724). Age, C-reactive protein, Ki67, and POD24 were independent factors affecting the prognosis of OS. The prognostic model established by them combined clinical features, and serological and pathological indicators and could effectively predict the prognosis of AITL patients.

The online version contains supplementary material available at 10.1007/s12288-024-01767-1.

Malnutrition is linked to adverse outcomes in post-cardiac surgery patients. This study investigates the correlation between the Geriatric Nutritional Risk Index (GNRI) and adverse hospital outcomes in patients following cardiac surgery. This retrospective study included elderly patients with heart disease who were admitted to the Department of Cardiology, Fujian Medical University Union Hospital from January 2020 to December 2022. Patients were divided into two groups based on the cut-off value (98 g/dL). Data from 407 patients were assessed, with 278 (68.3%) classified as having nutritional risk and 129 (31.7%) as having no nutritional risk. Notable distinctions were observed in body weight, BMI, and left ventricular ejection fraction (P < 0.05). Laboratory indicators indicated lower levels of serum albumin, lymphocytes, red blood cells, hemoglobin, admission blood glucose, and admission triglyceride in the nutritional risk group (P < 0.05). Neutrophils and serum creatinine were higher in the nutritional risk group (P < 0.05). Poor prognosis was prevalent in the nutrition risk group (64.7%), with higher incidences of adverse outcomes (P < 0.05). Univariate and multivariate studies showed that GNRI < 98 g/dL was an independent predictor of postoperative cardiac surgery. Nutritional risk was an important predictor of adverse hospital outcomes after the surgery.

Aim: This multicenter retrospective study aimed to develop a novel prognostic system for extranodal natural killer/T-cell lymphoma (ENKTL) patients in the era of pegaspargase/L-asparaginase.Materials & methods: A total of 844 newly diagnosed ENKTL patients were included.Results: Multivariable analysis confirmed that Eastern Cooperative Oncology Group performance status, lactate dehydrogenase, Chinese Southwest Oncology Group and Asia Lymphoma Study Group ENKTL (CA) system, and albumin were independent prognostic factors. By rounding up the hazard ratios from four significant variables, a maximum of 7 points were assigned. The model of Huaihai Lymphoma Working Group-Natural killer/T-cell Lymphoma prognostic index (NPI) was identified with four risk groups and the 5-year overall survival was 88.2, 66.7, 54.3 and 30.5%, respectively.Conclusion: Huaihai Lymphoma Working Group-NPI provides a feasible stratification system for patients with ENKTL in the era of pegaspargase/L-asparaginase.

There have been no reports about the application of random survival forest (RSF) model to predict disease progression of HIV-associated B-cell lymphoma.

A total of 44 patients with HIV-associated B-cell lymphoma who were referred to Nanjing Second Hospital from 2012 to 2019 were included. The RSF model was used to find predictors of survival, and the results of the RSF model were compared with those of the Cox model. The data were analyzed using R software (version 4.1.1).

One-, 2-, and 3-year survival rates were 74.5%, 57.7%, and 48.6%, respectively, and the median survival was 59.0 months. The first 3 most important predictors of survival included lactate dehydrogenase (LDH), absolute monocyte count (AMC), and white blood cells (WBCs) count. The median survival of high-risk patients was only 4.0 months. Areas under the curve (AUCs) of the RSF model remained at more than 0.90 at 1, 2, and 3 years. The RSF model displayed a lower prediction error rate (21.9%) than the Cox model (25.4%).

Lactate dehydrogenase, AMC, and WBCs count are the most important prognostic predictors for patients with HIV-associated B-cell lymphoma. Much larger prospective and/or multicentre studies are required to validtae this RSF model.

This editorial contains comments on the article "Correlation between preoperative systemic immune inflammation index, nutritional risk index, and prognosis of radical resection of liver cancer" in a recent issue of the World Journal of Gastrointestinal Surgery. It pointed out the actuality and importance of the article and focused primarily on the underlying mechanisms making the systemic immune-inflammation index (SII) and geriatric nutritional risk index (GNRI) prediction features valuable. There are few publications on both SII and GNRI together in hepatocellular carcinoma (HCC) and patient prognosis after radical surgery. Neutrophils release cytokines, chemokines, and enzymes, degrade extracellular matrix, reduce cell adhesion, and create conditions for tumor cell invasion. Neutrophils promote the adhesion of tumor cells to endothelial cells, through physical anchoring. That results in the migration of tumor cells. Pro-angiogenic factors from platelets enhance tumor angiogenesis to meet tumor cell supply needs. Platelets can form a protective film on the surface of tumor cells. This allows avoiding blood flow damage as well as immune system attack. It also induces the epithelial-mesenchymal transformation of tumor cells that is critical for invasiveness. High SII is also associated with macro- and microvascular invasion and increased numbers of circulating tumor cells. A high GNRI was associated with significantly better progression-free and overall survival. HCC patients are a very special population that requires increased attention. SII and GNRI have significant survival prediction value in both palliative treatment and radical surgery settings. The underlying mechanisms of their possible predictive properties lie in the field of essential cancer features. Those features provide tumor nutrition, growth, and distribution throughout the body, such as vascular invasion. On the other hand, they are tied to the possibility of patients to resist tumor progression and development of complications in both postoperative and cancer-related settings. The article is of considerable interest. It would be helpful to continue the study follow-up to 2 years and longer. External validation of the data is needed.

The geriatric nutritional risk index (GNRI) has been wildly used to predict the prognosis of patients with solid cancer, but it's value in postoperative complications remains unclear. The aim of our study was to systematically explore the value of the GNRI in postoperative complications in patients with solid cancer.

The study conducted a systematic literature search using electronic databases to investigate the influence of the GNRI on postoperative complications in patients with solid cancer. The search covered articles published up until May 2023. The odds ratio (OR) with a 95% confidence interval (CI) was employed to assess the effect of GNRI on postoperative complications.

A total of 11 studies with 11,002 patients were enrolled in our meta-analysis. The results suggested that patients with a low GNRI have a higher risk of experiencing postoperative complications (OR=2.51, 95%CI 2.05-3.02, z=9.86, p<0.001), a higher risk of suffering Clavien-Dindo (CD) grades≥2 complications(OR=2.24, 95%CI 1.84-2.73, z=8.01, p<0.001), a higher risk of suffering infection (OR=1.85, 95%CI 1.18-2.88, z=2.70, p=0.007) and a higher risk of suffering respiratory complications(OR = 2.94, 95%CI: 1.56-5.55, z=3.31, p=0.001).

Based on existing evidence, the GNRI was a valuable predictor of postoperative complications in patients with solid cancer.

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=434299, identifier CRD42023434299.

This study aimed to examine the predictive ability of inflammatory and nutritional markers and further establish a novel inflammatory nutritional prognostic scoring (INPS) system.

We collected clinicopathological and baseline laboratory data of 352 patients with DLBCL between April 2010 and January 2023 at the First affiliated hospital of Ningbo University. Eligible patients were randomly divided into training and validation cohorts (n = 281 and 71, respectively) in an 8:2 ratio. We used the least absolute shrinkage and selection operator (LASSO) Cox regression model to determine the most important factors among the eight inflammatory-nutritional variables. The impact of INPS on OS was evaluated using the Kaplan-Meier curve and the Log rank test. A prognostic nomogram was developed based on the multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the nomogram.

Seven inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), prognostic nutritional index (PNI), body mass index (BMI), monocyte-lymphocyte ratio (MLR), prealbumin, C reactive protein, and D-dimer were selected using the LASSO Cox analysis to construct INPS, In the multivariate analysis, IPI-High-intermediate group, IPI-High group, high INPS were independently associated with OS, respectively. The prognostic nomogram for overall survival consisting of the above two indicators showed excellent discrimination. The C-index for the nomogram was 0.94 and 0.95 in the training and validation cohorts. The time-dependent ROC curves showed that the predictive accuracy of the nomogram for OS was better than that of the NCCN-IPI system.

The INPS based on seven inflammatory-nutritional indexes was a reliable and convenient predictor of outcomes in DLBCL patients.

Geriatric assessment can aid in optimizing treatment strategies and supportive interventions for older patients with diffuse large B-cell lymphoma (DLBCL). Fondazione Italiana Linformi has recently introduced novel geriatric assessment tools, simplified Geriatric Assessment (sGA) and Elderly Prognostic Index (EPI), aimed at tailoring the treatment and predicting the outcomes for older patients with DLBCL. The objectives of this study are the validation and possible modification of the sGA and EPI in China. In the study, both sGA and EPI demonstrated the predictive capabilities for overall survival (OS) and early mortality (both p < 0.05) in older individuals with DLBCL. Albumin, serving as an independent predictive biomarker for OS (p = 0.006), was utilized to adjust the measurements, resulting in the establishment of sGA-A and EPI-A. The sGA-A effectively addressed the shortcomings of the sGA and EPI in predicting PFS and surpassed them in predicting OS and early mortality. Nevertheless, there is insufficient evidence to support the use of sGA and EPI as treatment guidance tools. In conclusion, the modified sGA-A model proved to be a successful instrument for geriatric assessment of older patients with DLBCL.

Posterior cervical decompression with or without fusion (PCD/F) is used to manage degenerative spinal conditions. Malnutrition has been implicated for poor outcomes in spine surgery. The aim of this study was to assess the ability of the Geriatric Nutritional Risk Index (GNRI) as a risk calculator for postoperative complications in patients undergoing PCD/F.

The 2006 to 2018 American College of Surgeons National Surgery Quality Improvement Program Database was queried for patients undergoing PCD/F. Nutritional status was categorized as normal (GNRI greater than 98), moderately malnourished (GNRI 92-98), or severely malnourished (GNRI less than or equal to 92). Complications within 30 days of surgery were compared among the groups. Preoperative data that were statistically significant (P < 0.05) upon univariate χ2 analysis were included in the univariate then multivariate binary regression model to calculate adjusted ORs. All ORs were assessed at the 95% CI.

Of the 7597 PCD/F patients identified, 15.6% were severely malnourished and 19.1% were moderately malnourished. Severe and moderate malnourishment were independent risk factors for mortality (OR = 3.790, 95% CI 2.492-5.763, P < 0.001; OR = 2.150, 95% CI 1.351-3.421, P = 0.011). Severe malnourishment was an independent risk factor for sepsis/septic shock (OR = 3.448, 95% CI 2.402-4.948, P < 0.001).

In elderly patients undergoing PCD/F, severe malnutrition, as defined by the GNRI, was an independent risk factor for mortality and sepsis/septic shock.

The GNRI may be more useful than other indices for risk stratification in elderly patients because it accounts for confounding variables such as hydration status and paradoxical malnourishment in obese patients.

Radical surgery is the most commonly used treatment for hepatocellular carcinoma (HCC). However, the surgical effect remains not ideal, and prognostic evaluation is insufficient. Furthermore, clinical intervention is rife with uncertainty and not conducive to prolonging patient survival.

To explore correlations between the systemic immune inflammatory index (SII) and geriatric nutritional risk index (GNRI) and HCC operation prognosis.

This retrospective study included and collected follow up data from 100 HCC. Kaplan-Meier survival curves were used to analyze the correlation between SII and GNRI scores and survival. SII and GNRI were calculated as follows: SII = neutrophil count × platelet count/lymphocyte count; GNRI = [1.489 × albumin (g/L) + 41.7 × actual weight/ideal weight]. We analyzed the predictive efficacy of the SII and GNRI in HCC patients using receiver operating characteristic (ROC) curves, and the relationships between the SII, GNRI, and survival rate using Kaplan-Meier survival curves. Cox regression analysis was utilized to analyze independent risk factors influencing prognosis.

After 1 year of follow-up, 24 patients died and 76 survived. The area under the curve (AUC), sensitivity, specificity, and the optimal cutoff value of SII were 0.728 (95% confidence interval: 0.600-0.856), 79.2%, 63.2%, and 309.14, respectively. According to ROC curve analysis results for predicting postoperative death in HCC patients, the AUC of SII and GNRI combination was higher than that of SII or GNRI alone, and SII was higher than that of GNRI (P < 0.05). The proportion of advanced differentiated tumors, tumor maximum diameter (5-10 cm, > 10 cm), lymph node metastasis, and TNM stage III-IV in patients with SII > 309.14 was higher than that in patients with SII ≤ 309.14 (P < 0.05). The proportion of patients aged > 70 years was higher in patients with GNRI ≤ 98 than that in patients with GNRI > 98 (P < 0.05). The 1-year survival rate of the SII > 309.14 group (compared with the SII ≤ 309.14 group) and GNRI ≤ 98 group (compared with the GNRI > 98 group) was lower (P < 0.05).

The prognosis after radical resection of HCC is related to the SII and GNRI and poor in high SII or low GNRI patients.

The elderly comprises over one-third of hepatocellular carcinoma (HCC) patients, however, they are not adequately represented in prognostic studies. The study aims to determine the prognostic significance of the preoperative prognostic nutritional index (PNI) and develop nomograms for predicting their recurrence-free and overall survival (RFS and OS). The study consisted of 282 elderly patients (aged ≥ 65 years) with early-stage HCC (China Liver Cancer Staging System: I-IIA) after curative resection (R0). They were randomly divided into a training (n = 197) and a test cohort (n = 85). The patients were stratified into two groups: PNI-low (PNI ≤ 49.05) and PNI-high (PNI > 49.05) based on a cut-off value. Most patients' demographics and perioperative outcomes were comparable, while patients in the PNI-high group were younger (P = 0.002), heavier (P < 0.001), and had lower comorbidity rates (P = 0.003). Although the tumor stages were earlier in the PNI-low group (P < 0.001), patients' OS (5-year OS: 48.9% vs. 93.1%) and RFS (5-year RFS: 27.3% vs. 75.7%) were significantly worse compared to the PNI-high group (both P < 0.0001). Patients' OS and RFS nomograms were developed by incorporating independent survival predictors including chronic obstructive pulmonary disease (COPD), age ≥ 75 years, PNI-low, tumor presence of satellite nodules, capsule, and microvascular invasion. The nomograms showed good calibration and discrimination, with all C-indexes ≥ 0.75 and calibration plots essentially coinciding with the diagonal. In conclusion, for elderly HCC patients, COPD, age ≥ 75 years, PNI-low, and tumor presence of satellite nodules, capsule, and microvascular invasion were independent prognostic factors. The nomogram could accurately predict the prognosis of these patients.

To establish a nomogram for elderly patients with diffuse large B-cell lymphoma (DLBCL) based on nutritional and imaging features. The data of 221 elderly pretreatment DLBCL patients were retrospectively analyzed. All cases were randomly separated into the training group and validation group. A nomogram was built based on the results of multivariate analysis. A nomogram was established based on maximum standardized uptake value (SUVmax), geriatric nutritional risk index (GNRI), and lactate dehydrogenase. The concordance index (C-index) of the nomogram was 0.772 for the training group and 0.729 for the validation group, and similar results were found in the area under the curve (AUC). The calibration curve showed favorable consistency between prediction and real survival. The decision curve analysis (DCA) also showed that the nomogram had favorable clinical effectiveness. The new risk-stratification model divided patients into three groups with obvious survival. The C-index and AUCs for the new model were greater than those of IPI and NCCN-IPI. The DCA curve suggested that the new model had better clinical effectiveness than the IPI and NCCN-IPI. The nomogram prognostic model based on SUVmax and GNRI performed superior to NCCN-IPI and equal to IPI for risk stratification of elderly DLBCL patients.

Recent studies have reported inconsistent results regarding the association between geriatric nutritional risk index (GNRI) and clinical outcomes in patients with hematologic malignancies (HMs). We performed a meta-analysis to evaluate the effect of low GNRI on the overall survival (OS) and progression-free survival (PFS) in patients with HMs.

We conducted the research via PubMed, Embase, and Cochrane Library databases to identify trials. Exploring the association between GNRI and prognosis in patients with HMs. A meta-analysis of OS and PFS was performed. Quality In Prognostic Studies instrument and Newcastle-Ottawa quality assessment Scale were used to assess the quality of included trials.

Fourteen studies enrolling 3,524 patients with HMs were included. Low GNRI was associated with shorter OS (Hazard ratio (HR) = 1.77; 95% CI = 1.44-2.18, p < 0.01) and PFS (HR = 1.63; 95% CI = 1.17-2.27, p < 0.01) in patients with HMs. In the subgroup analysis, GNRI was not significantly associated with prognosis in Chinese patients with HMs (OS, HR =1.33; 95% CI = 0.89-1.98, p = 0.16; PFS, HR = 1.70; 95% CI = 0.72-4.01, p = 0.23). For the subgroup with a GNRI cutoff value less than 98, there was no significant difference in PFS (HR = 1.34; 95% CI = 0.98-1.83, p = 0.06).

Low GNRI negatively impacted on the prognosis in patients with HMs. Prospective studies to identify the best cut-off value for GNRI are required.

This study evaluated the value of PNI to predicting relapse-free survival (RFS) and overall survival (OS) in patients with resectable gastroesophageal junction adenocarcinoma (AGE).

Between 2016 and 2020, there were 236 resectable AGE patients underwent a retrospective review via propensity score matched (PSM) analysis. The PNI values were computed for each patient prior to surgery [PNI= 10×albumin (gr/dL) + 0.005×total lymphocyte count (mm3)]. By using disease progression and mortality as the end points, a receiver operating characteristic(ROC) curve was plotted to identify the PNI cut-off value. Kaplan-Meier curves and Cox proportional hazard models were used for survival analysis.

The ROC curve indicated that the ideal cutoff value was 45.60. After propensity score matching, there were 143 patients in our retrospective study, which included 58 patients in the low-PNI group and 85 patients in the high-PNI group. When compared to the low PNI group, the high PNI group substantially increased RFS and OS (p<0.001, p=0.003, respectively) according to the Kaplan-Meier analysis and Log rank test. Advanced pathological N stage (p=0.011) and poor PNI (p=0.004) were also significant risk factors for a shorter OS, according to a univariate analysis. Multivariate analysis revealed that the N0 plus N1 group had an endpoint mortality risk that was 0.39 times lower than the N2 plus N3 group's (p=0.008). In comparison to the high PNI group, the hazard of endpoint mortality was 2.442 times greater in the low PNI group (p = 0.003).

PNI is a simplistic and practical predictive predictor of the RFS and OS time in patients with resectable AGE.

Although the survival rate of patients who undergo surgery for gastric cancer has greatly improved, still many patients have a poor prognosis. This retrospective study aimed to investigate the predictive ability of the PNI-IgM score, a combined prognostic nutritional index (PNI), and immunoglobulin M (IgM), on the prognosis of patients undergoing surgery for gastric cancer.

340 patients with gastric cancer who underwent surgery from January 2016 to December 2017 were selected. The PNI-IgM score ranged from 1 to 3: score of 1, low PNI (< 48.45) and low IgM (< 0.87); score of 2, low PNI and high IgM, or high PNI and low IgM; score of 3, high PNI and high IgM. We compared the differences in disease-free survival (DFS) and overall survival (OS) among the three groups, while univariate and multivariate analyses calculated prognostic factors for DFS and OS. In addition, the nomograms were constructed based on the results of multivariate analysis to estimate the 1-, 3- and 5-year survival probability.

There were 67 cases in the PNI-IgM score 1 group, 160 cases in the PNI-IgM score 2 group, and 113 cases in the PNI-IgM score 3 group. The median survival times of DFS in the PNI-IgM score group 1, the PNI-IgM score group 2, and the PNI-IgM score group 3 were 62.20 months, not reached, and not reached, and 67.57 months vs. not reached vs. not reached in three groups for OS. Patients in the PNI-IgM score group 1 had a lower DFS than the PNI-IgM score group 2 (HR = 0.648, 95% CI: 0.418-1.006, P = 0.053) and the PNI-IgM score group 3 (HR = 0.337, 95% CI: 0.194-0.585, P < 0.001). In stratified analysis, PNI-IgM score 1 had a worse prognosis in the age < 60 years group and CA724 < 2.11 U/m group.

PNI-IgM score is a novel combination of nutritional and immunological markers that can be used as a sensitive biological marker for patients with gastric cancer who undergo surgery. The lower the PNI-IgM score, the worse the prognosis.

Controlling nutritional status (CONUT) score as an original nutritional assessment tool can be used to assess the prognosis of patients with a variety of malignancies. However, the predictive power of CONUT in extranodal natural killer/T cell lymphoma (ENKTL) patients has never been demonstrated. Our retrospective multicenter study aimed to explore the prognostic value of CONUT in newly diagnosed ENKTL. A total of 1085 newly diagnosed ENKTL patients between 2003 and 2021 were retrospectively retrieved. Cox proportional hazard model was used to explore the prognostic factors of overall survival (OS). The survival rate of ENKTL was evaluated using Kaplan-Meier analysis, and log-rank test was applied to the difference between groups. We investigated the prognostic performance of CONUT, the International Prognostic Index (IPI), the Korean Prognostic Index (KPI), and the Prognostic Index of Natural Killer Cell Lymphoma (PINK) using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA). The median age at diagnosis for the whole cohort was 47 years, and the male to female ratio was 2.2:1. The 5-year OS for all patients was 72.2%. Multivariable analysis showed that CONUT, age, bone marrow involvement, ECOG PS score, and Chinese Southwest Oncology Group and Asia Lymphoma Study Group ENKTL stage were identified as independent predictive factors for OS. Based on multivariable results, a prognostic nomogram was developed. Subgroup analysis demonstrated that patients with severe malnutrition had poorest clinical outcome. In addition, ROC curves and DCA analysis proved that compared with IPI, KPI, and PINK models, the CONUT score-based nomogram showed a better prognostic predictive efficiency of ENKTL. CONUT could effectively stratify the prognosis of ENKTL and the proposed nomogram based on CONUT was an effective prognostic model for prediction.

Malnutrition is associated with poor outcomes for geriatric patients in intensive care unit (ICU). It is important to identify patients at risk of malnutrition and provide individual nutrition support. The assessment of malnutrition risk is not easy for these patients due to their cognitive impairment. Geriatric nutrition risk index (GNRI) is a simple and objective scoring tool to evaluate the risk of malnutrition in elderly patients. In this study, we aimed to see whether GNRI score was appropriate to predict clinical outcomes among geriatric patients in the setting of ICU.

Elderly patients with age ≥ 65 years were extracted from Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Categories based on GNRI were classified as major risk (GNRI <82), moderate risk (GNRI 82 to <92), low risk (GNRI 92 to ≤98), and no risk (GNRI >98). The primary outcome was all-cause hospital mortality. Multivariable Cox proportional hazards regression models and restricted cubic spline were used to investigate associations of GNRI with hospital mortality, respectively. A two-piecewise linear regression model was applied to examine the inflection point of GNRI on hospital mortality. To reduce selection bias, propensity score matching (PSM) was used in a 1:1 ratio.

A total of 3,696 geriatric patients were finally included with median age 75 (69, 81) years. The prevalence of major risk was 28.6%. In the fully adjusted model, GNRI categories featured a negative trend with hospital mortality (p for trend = 0.037). Restricted cubic spline analysis demonstrated an L-shaped relationship between GNRI and hospital mortality before and after matching. The inflection point was 78.7. At the left side of inflection point, GNRI levels were significantly negatively associated with hospital mortality (HR = 0.96, 95% CI: 0.94-0.98; p < 0.001) and featured no significant relations at the right side. Multiple linear regression also showed that GNRI was negatively associated with length of stay in hospital.

The major risk of malnutrition defined by GNRI was able to predict poor prognosis for geriatric patients admitted to ICU.

Previous studies have explored the relationship between the geriatric nutritional risk index (GNRI) and survival outcomes of diffuse large B-cell lymphoma (DLBCL) cases, but the results were inconsistent. Consequently, the present meta-analysis was conducted to investigate how GNRI affects DLBCL and its function in terms of prognosis.

The Web of Science, PubMed, Embase, and Cochrane Library databases were thoroughly searched until January 18, 2023. We calculated combined hazard ratios (HRs) and 95% confidence intervals (CIs) to estimate the relationship between the GNRI and survival outcomes of patients with DLBCL.

This meta-analysis included seven articles involving 2,353 cases. A lower level of GNRI predicted dismal overall survival (HR=1.40, 95% CI=1.25-1.56, p<0.001) and inferior progression-free survival (HR=1.46, 95% CI=1.19-1.80, p<0.001) of DLBCL patients. Moreover, a low GNRI was significantly related to Eastern Cooperative Oncology Group Performance Status ≥2 (odds ratio [OR]=4.55, 95% CI=2.75-7.54, p<0.001), Ann Arbor stage III-IV (OR=2.91, 95% CI=2.38-3.57, p<0.001), B symptoms (OR=3.51, 95% CI=2.34-5.29, p<0.001), and extranodal disease (OR=2.90, 95% CI=2.32-3.63, p<0.001).

A lower GNRI level predicted poorer short- and long-term prognosis in patients with DLBCL. A low GNRI was correlated with clinical factors of disease progression in DLBCL patients.

Controlling nutritional status (CONUT) score, based on three indexes including serum albumin (ALB), total cholesterol (CHO), and absolute lymphocyte count (ALC), has been closely associated with the prognosis of cancer patients. Multiple studies revealed the significance of CONUT score in hematological malignancies, including diffuse large B-cell lymphoma (DLBCL), peripheral T-cell lymphoma (PTCL), multiple myeloma (MM), and leukemia.

This review aimed to explore the prognostic role of CONUT score in hematological malignancies.

We conducted this review through Pubmed to summarize the published studies on the CONUT score in hematological malignancies, using the terms: Controlling nutritional status, CONUT score, hematological malignancy, lymphoma, multiple myeloma, and leukemia.

CONUT score can reflect not only the nutritional status but also the inflammatory status of patients with hematological malignancies. It can assist in predicting the survival of patients with DLBCL, PTCL, MM, adult T-cell leukemia (ATL), myelodysplastic syndrome (MDS), and acute myeloid leukemia with myelodysplasia related changes (AML-MRC).

CONUT score plays an important role in predicting the prognosis of patients with hematological malignancies.

The purpose of study was to evaluate the association between prognostic nutritional index (PNI) and all-cause mortality of critically ill patients with stroke.

Clinical data derived from Multiparameter Intelligent Monitoring in Intensive Care were analyzed. The primary endpoint was 30-day all-cause mortality; secondary endpoints were 90-day mortality and one-year cause mortality. The potential prognostic roles of PNI were analyzed by Cox proportional hazard models. The independent prognostic roles of PNI in the cases were analyzed by smooth curve fitting.

Concerning 30-day mortality, the HR (95% CI) for a high PNI (≥39.7) was 0.700 (0.544, 0.900; P = 0.00539), compared to a low PNI (<39.7). After adjusting for multiple confounders, the HR (95% CI) for a high PNI (≥39.7) was 0.732 (0.547, 0.978; P = 0.03514), compared to a low PNI (<39.7). Regarding 90-day and one-year mortality, a similar trend was observed. In addition, a nonlinear association between PNI and 30-day mortality was found. Using recursive algorithm and two-piecewise linear regression model, inflection point (IP) was calculated, which was 49.4. On the right side of the IP, there was a positive relationship between PNI and 30-day mortality, and the effect size, 95% CI, and P value were 1.04 (1.01, 1.07), P = 0.0429, respectively. On the left of the IP, the effect size, 95% CI, and P value were 0.97 (0.96, 0.99) and 0.0011, respectively.

The PNI was an independent predicting factor of 30-day, 90-day, and 1-year mortality of the critically ill patients with stroke. In addition, there was a U-shaped relationship between PNI and all-cause mortality of stroke patients. PNI was a risk factor for the outcome of stroke when PNI was >49.4, while PNI was a protective factor for outcome of stroke when PNI was <49.4.

Purpose: To explore the prognostic role of the pretreatment geriatric nutritional risk index (GNRI) in patients with esophageal cancer. Methods: Several electronic databases were searched from inception to January 27, 2022, for relevant studies. Hazard ratios (HRs) and 95% confidence intervals (CIs) were combined to assess the association between pretreatment GNRI and the prognosis of patients with esophageal cancer. The primary and secondary outcomes were overall survival (OS) and progression-free survival (PFS), respectively. Statistical analyses were performed using STATA software (version 12.0). Results: Fourteen retrospective studies involving 3981 patients were enrolled. The pooled results demonstrated that lower pretreatment GNRI was an independent prognostic risk factor for poorer OS (HR = 1.47, 95% CI: 1.33-1.63, P < 0.001) and PFS (HR = 1.69, 95% CI: 1.24-2.31, P = 0.001). Subgroup analysis based on pathological type (squamous cell carcinoma vs. esophageal cancer) and treatment (non-surgery vs. surgery) showed similar results. Conclusion: Pretreatment GNRI was significantly associated with prognosis of patients with esophageal cancer, and lower pretreatment GNRI predicted worse survival. However, more prospective high-quality studies are needed to verify these findings.