Prognostic Nutritional Index as a Novel Biomarker for Predicting Prognosis in Sepsis‐Associated Encephalopathy: A Multicenter Retrospective Cohort Study

Hip fractures in super-elderly patients are associated with high short-term mortality. The Prognostic Nutritional Index (PNI) is a simple marker reflecting both nutritional and immune status, but its prognostic value in super-elderly hip fracture patients remains unclear. We retrospectively included 614 patients aged ≥80 years with traumatic hip fractures from a tertiary hospital (n = 457) and the MIMIC-IV database (n = 157). PNI was calculated from serum albumin and absolute lymphocyte count measured within 24 h of admission. The optimal PNI cut-off for predicting 90-day all-cause mortality was determined using X-tile and used to define low- and high-PNI groups. Least absolute shrinkage and selection operator (LASSO) regression, Cox proportional hazards models, and propensity score matching (PSM) were applied to evaluate the association between admission PNI and 90-day mortality. The optimal PNI cut-off was 37.2, yielding 231 patients (37.6%) in the low-PNI group (PNI ≤ 37.2) and 383 (62.4%) in the high-PNI group (PNI > 37.2). Before PSM, patients with low PNI were older and had worse laboratory profiles, including lower hemoglobin, albumin, and lymphocyte counts. The 90-day mortality rate was significantly higher in the low-PNI than in the high-PNI group (21.65% vs. 9.40%, p < 0.001). LASSO identified sex, race, chronic pulmonary disease, hemoglobin, creatinine, and PNI as variables associated with 90-day mortality. After 1:2 PSM, 398 patients were retained with most baseline imbalances effectively reduced. In robust Cox proportional hazards analyses for the matched cohort, high PNI was associated with lower 90-day mortality in univariate models (HR 0.34, 95% CI 0.18-0.63; p < 0.001); Race violated the proportional hazards assumption; this association remained robust in the fully adjusted robust Cox model with race treated as a stratified variable (HR 0.34, 95% CI 0.19-0.63; p < 0.001). A low admission PNI (≤37.2) is strongly and independently associated with higher 90-day mortality in super-elderly patients with hip fractures. PNI, derived from routine laboratory tests within 24 h of admission, provides a simple and inexpensive tool for early risk stratification in this vulnerable population.

BackgroundLong-term or high-dose glucocorticoid administration can markedly impair immune responses, mask clinical indicators of pulmonary infections, and increase the susceptibility to refractory pneumonia, leading to heightened mortality risk. The Prognostic nutritional index (PNI), derived from peripheral lymphocyte count and serum albumin (ALB) levels, serves as a reliable indicator for evaluating nutritional and immune statuses across various clinical populations, including oncology patients, individuals with cardiovascular disorders, and perioperative patients. However, the predictive value of PNI in pneumonia patients receiving glucocorticoids, especially within the Chinese population, has not been sufficiently investigated. This observational analysis aimed to explore the correlation between PNI levels and all-cause mortality (ACM) in patients undergoing prolonged glucocorticoid therapy for pneumonia.MethodsA retrospective cohort study was conducted utilizing data extracted from the Dryad database. Kaplan–Meier curves, multivariable Cox regression, restricted cubic splines (RCS), and subgroup analyses were used to assess the association between PNI and ACM in patients with pneumonia who received glucocorticoids.ResultsThe study incorporated a total of 639 pneumonia patients who received glucocorticoid therapy. The ACM rates were 22.5% at 30 days and rose to 26.0% at 90 days. Multivariable Cox regression showed that, after full adjustment for potential confounders, every 2-unit decrease in PNI was associated with a 10% higher 30-day mortality hazard (HR = 1.10, 95% CI = 1.05–1.15, p < 0.001) and a 9% higher 90-day mortality hazard (HR = 1.09, 95% CI = 1.04–1.14, p < 0.001). Compared with patients with PNI ≥ 43, patients with PNI < 43 had a 118% increased risk of 30-day mortality (HR = 2.18, 95% CI = 1.28–3.81, p = 0.005) and a 96% increased risk of 90-day mortality (HR = 1.96, 95% CI = 1.20–3.19, p = 0.008). Further validation using RCS analysis revealed a robust inverse relationship between PNI scores and ACM, and subgroup analyses revealed no significant interactions.ConclusionAmong pneumonia patients receiving glucocorticoid therapy, a decreased PNI was associated with an increased risk of 30-day and 90-day mortality, particularly in those with a PNI < 43.

Introduction: To investigate the impact of prognostic nutritional index (PNI) on short- and long-term outcomes of patients who underwent curative-intent resection for gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs). Methods: Patients with GET-NETs who underwent curative-intent resection were identified from a multi-center database. The prognostic impact of clinicopathological factors including PNI on post-operative outcomes were evaluated. A novel nomogram was developed and externally validated. Results: A total of 2,099 patients with GEP-NETs were included in the training cohort; 255 patients were in the external validation cohort. Median PNI (n = 973) was 47.4 (IQR 43.1–52.4). At the time of presentation, 1,299 (61.9%) patients presented with some type of clinical symptom. Low-PNI (≤42.2) was associated with gastrointestinal symptoms, as well as nodal metastasis and distant metastasis (all p < 0.05). Patients with a low PNI had a higher incidence of severe (≥Clavien-Dindo grade IIIa: low PNI 24.9% vs. high PNI 15.4%, p = 0.001) and multiple (≥3 types of complications: low PNI 14.5% vs. high PNI 9.2%, p = 0.024) complications, as well as a worse overall survival (OS)(5-year OS, low PNI 73.7% vs. high PNI 88.5%, p < 0.001), and RFS (5-year RFS, low PNI 68.5% vs. high PNI 79.8%, p = 0.008) versus patients with high PNI (>42.2). A nomogram based on PNI, tumor grade and metastatic disease demonstrated excellent discrimination and calibration to predict OS in both the training (C-index 0.748) and two external validation (C-index 0.827, 0.745) cohorts. Conclusions: Low PNI was common and associated with worse short- and long-term outcomes among patients with GEP-NETs.

BackgroundSepsis patients often have immune dysfunction and malnutrition, which is a high-risk disease for death in critically ill patients. Although various biomarkers can predict the prognosis of sepsis patients, they are cumbersome to implement clinically. This study evaluates the prognostic potential of the Prognostic Nutritional Index (PNI) to fill this gap.MethodsWe conducted a retrospective analysis of data from patients admitted to the Intensive Care Unit (ICU) of Beth Israel Deaconess Medical Center with sepsis between 2008 and 2022. The Prognostic Nutritional Index (PNI) was calculated using the first measurement within 24 h of admission. Kaplan–Meier analysis was used to compare mortality risks among three groups, and a multivariable Cox proportional hazards regression model assessed the link between PNI and mortality risk in sepsis patients. Restricted cubic splines (RCS) explored the potential dose—response relationship between PNI and mortality, and threshold analysis determined the critical threshold of PNI. Receiver operating characteristic (ROC) analysis evaluated the predictive ability, sensitivity, and specificity of LAR for all—cause mortality in patients with liver cirrhosis and sepsis, and calculated the area under the curve (AUC). Finally, subgroup analyses were performed to evaluate the relationship between PNI and prognosis in different populations.ResultsA total of 6,234 patients were included Kaplan—Meier analysis showed that patients with high PNI had lower 14, 28, and 90-day all—cause mortality risks (all log—rank P < 0.001). The multivariable Cox proportional hazards model indicated that high PNI was independently associated with 14, 28, and 90-day all—cause mortality, with HRs of 0.62, 0.56, and 0.59 (all P < 0.0001), before and after adjusting for confounders RCS analysis revealed a non-linear link between PNI and short—and medium—term all—cause mortality in sepsis patients. A two—segment Cox proportional hazards model identified inflection points at 11.6 for 14-day, 11.2 for 28-day, and 11.2 for 90-day all-cause mortality ROC analysis showed PNI has lower predictive value for sepsis prognosis than sequential organ failure assessment and acute physiology and chronic health evaluation, yet it can enhance their predictive power Subgroup analyses found no significant interaction between PNI and specific subgroups.ConclusionThere is a significant association between short-term and medium—term all—cause mortality in sepsis patients and PNI, indicating that PNI can be a valuable indicator for predicting in—hospital and ICU mortality risk.

Background The survival of critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT) is highly dependent on their nutritional status. Objectives The prognostic nutritional index (PNI) is an indicator used to assess nutritional status and is calculated as: PNI = (serum albumin in g/dL) × 10 + (total lymphocyte count in/mm3) × 0.005. In this retrospective study, we investigated the correlation between this index and clinical outcomes in critically ill patients with AKI receiving CRRT. Methods We analyzed data from 2076 critically ill patients admitted to the intensive care unit at Changhua Christian Hospital, a tertiary hospital in central Taiwan, between January 1, 2010, and April 30, 2021. All these patients met the inclusion criteria of the study. The relationship between PNI and renal replacement therapy-free survival (RRTFS) and mortality was examined using logistic regression models, Cox proportional hazard models, and propensity score matching. High utilization rate of parenteral nutrition (PN) was observed in our study. Subgroup analysis was performed to explore the interaction effect between PNI and PN on mortality. Results Patients with higher PNI levels exhibited a greater likelihood of achieving RRTFS, with an adjusted odds ratio of 2.43 (95% confidence interval [CI]: 1.98-2.97, p-value < 0.001). Additionally, these patients demonstrated higher survival rates, with an adjusted hazard ratio of 0.84 (95% CI: 0.72-0.98) for 28-day mortality and 0.80 (95% CI: 0.69-0.92) for 90-day mortality (all p-values < 0.05), compared to those in the low PNI group. While a high utilization rate of parenteral nutrition (PN) was observed, with 78.86% of CRRT patients receiving PN, subgroup analysis showed that high PNI had an independent protective effect on mortality outcomes in AKI patients receiving CRRT, regardless of their PN status. Conclusions PNI can serve as an easy, simple, and efficient measure of lymphocytes and albumin levels to predict RRTFS and mortality in AKI patients with require CRRT.

This study aims to explore the correlation between the prognostic nutritional index (PNI) and all-cause mortality in patients diagnosed with ischemic stroke (IS). A single-center retrospective cohort study was conducted at Dandong Central Hospital, enrolling 1,152 consecutive patients with IS who were discharged from January to December 2024. Multivariate Cox regression models, subgroup analysis, sensitivity analysis, receiver operating characteristic (ROC) curve, and Kaplan-Meier survival analysis were employed to investigate the association between the PNI and all-cause mortality. During a median follow-up period of 14.23 months, a total of 96 (8.3%) patients experienced all-cause mortality. Multivariate Cox regression analysis showed that after adjusting for multiple confounding factors, each 1-unit increase in PNI was associated with an 8.5% reduction in all-cause mortality risk (hazard ratio [HR] = 0.915, 95% confidence interval [CI]: 0.883-0.947, p < 0.001), each 1-standard deviation increase was associated with a 40.1% reduction in all-cause mortality risk (HR = 0.599, p < 0.001). Compared with the lowest PNI quartile (Q1, PNI ≤ 44.16), the Q2 (PNI: 44.16-44.75) had a 54.1% lower risk of all-cause mortality (HR = 0.459, p = 0.004), the Q3 (PNI: 44.75-51.30) had a 56.4% lower risk of all-cause mortality (HR = 0.436, p = 0.007), the Q4 (PNI > 51.30) had a 72.6% lower risk of all-cause mortality (HR = 0.274, p < 0.001). Multiple subgroup and sensitivity analyses further confirmed the robustness of these associations. Stratified analyses based on various cutoff values of PNI uniformly demonstrated that patients with higher PNI levels had a notably reduced risk of all-cause mortality compared to those with lower PNI levels. ROC curve analysis indicated that PNI had favorable predictive value for all-cause mortality (overall population, AUC = 0.710; male, AUC = 0.720; female, AUC = 0.703; all p < 0.001). Kaplan-Meier survival curve analysis revealed significant differences in cumulative all-cause mortality risk among different PNI groups, with higher PNI levels correlating with lower cumulative mortality risk (Log-rank p < 0.001). The PNI establishes itself as an independent prognostic biomarker in IS patients, with higher levels correlating with a lower all-cause mortality risk.

Preoperative prognostic nutritional index is an independent indicator for perioperative prognosis in coronary artery bypass grafting patients

To investigate the association between the Prognostic Nutritional Index (PNI) and mortality risk in intensive care unit (ICU) patients with pressure injuries (PIs) to provide a basis for early risk stratification and clinical decision-making. This retrospective cohort study used data from the Medical Information Mart for Intensive Care IV database, which included 972 ICU patients diagnosed with PI. Patients were stratified by median PNI levels, and Kaplan-Meier survival analysis, Cox regression, logistic regression, restricted cubic splines, and propensity score matching (PSM) were performed to assess the relationship between PNI and 28-day, 90-day, and ICU mortality. A higher PNI was significantly associated with lower 28-day (hazard ratio [HR] = 0.702, 95% confidence interval [CI] 0.551-0.895), 90-day (HR = 0.722, 95% CI: 0.576-0.905), and ICU mortality (odds ratio [OR] = 0.644, 95% CI: 0.474-0.872). An L-shaped relationship between the PNI and all-cause mortality was observed. This association remained robust after multivariate adjustment, subgroup analysis, and PSM. This study is the first to evaluate the prognostic significance of the PNI in ICU patients with PIs, addressing the gap in current research by identifying a simple and accessible marker associated with mortality risk in this vulnerable population. PNI can be calculated from routine laboratory results and may guide early nutritional or wound care interventions in ICU patients with PI. A PNI value below 19.02 is associated with an increased risk of mortality (i.e., PNI <19.02 = high risk) and serves as a critical threshold for identifying patients at elevated risk.

BackgroundThe prognostic nutritional index (PNI) is a nutritional indicator and predictor of various diseases. However it is unclear whether PNI can be a predictor of perioperative ischemic stroke. This study aims to evaluate the association of the preoperative PNI and ischemic stroke in patients undergoing non-cardiac surgery.MethodsThe retrospective cohort study included patients who underwent noncardiac surgery between January 2008 and August 2019. The patients were divided into PNI ≥ 38.8 and PNI < 38.8 groups according to the cut-off value of PNI. Univariate and multivariate logistic regression analyses were performed to explore the association between PNI and perioperative ischemic stroke. Subsequently, propensity score matching (PSM) analysis was performed to eliminate the confounding factors of covariates and further validate the results. Subgroup analyses were completed to assess the predictive utility of PNI for perioperative ischemic stroke in different groups.ResultsAmongst 221,542 hospitalized patients enrolled, 485 (0.22%) experienced an ischemic stroke within 30 days of the surgery, 22.1% of patients were malnourished according to PNI < 38.8, and the occurrence of perioperative ischemic stroke was 0.34% (169/49055) in the PNI < 38.8 group. PNI < 38.8 was significantly associated with an increased incidence of perioperative ischemic stroke whether in univariate logistic regression analysis (OR = 1.884, 95% CI: 1.559—2.267, P < 0.001) or multivariate logistic regression analysis (OR = 1.306, 95% CI: 1.061—1.602, P = 0.011). After PSM analysis, the ORs of PNI < 38.8 group were 1.250 (95% CI: 1.000–1.556, P = 0.050) and 1.357 (95% CI: 1.077–1.704, P = 0.009) in univariate logistic regression analysis and multivariate logistic regression analysis respectively. The subgroup analysis indicated that reduced PNI was significantly associated to an increased risk of perioperative ischemic stroke in patients over 65 years old, ASA II, not taking aspirin before surgery, without a history of stroke, who had neurosurgery, non-emergency surgery, and were admitted to ICU after surgery.ConclusionsOur study indicates that low preoperative PNI is significantly associated with a higher incidence of ischemic stroke in patients undergoing non-cardiac surgery. Preoperative PNI, as a preoperative nutritional status evaluation index, is an independent risk factor useful to predict perioperative ischemic stroke risk, which could be used as an intervenable preoperative clinical biochemical index to reduce the incidence of perioperative ischemic stroke.

Background The prognostic nutritional index (PNI) has been reported to significantly correlate with poor survival and postoperative complications in patients with various diseases, but its relationship with mortality in COVID-19 patients has not been addressed. Method A multicenter retrospective study involving patients with severe COVID-19 was conducted to investigate whether malnutrition and other clinical characteristics could be used to stratify the patients based on risk. Results A total of 395 patients were included in our study, with 236 patients in the training cohort, 59 patients in the internal validation cohort, and 100 patients in the external validation cohort. During hospitalization, 63/236 (26.69%) and 14/59 (23.73%) patients died in the training and validation cohorts, respectively. PNI had the strongest relationships with the neutrophil-lymphocyte ratio (NLR) and lactate dehydrogenase (LDH) level but was less strongly correlated with the CURB65, APACHE II, and SOFA scores. The baseline PNI score, platelet (PLT) count, LDH level, and PaO2/FiO2 (P/F) ratio were independent predictors of mortality in COVID-19 patients. A nomogram incorporating these four predictors showed good calibration and discrimination in the derivation and validation cohorts. A PNI score less than 33.405 was associated with a higher risk of mortality in severe COVID-19 patients in the Cox regression analysis. Conclusion These findings have implications for predicting the risk of mortality in COVID-19 patients at the time of admission and provide the first direct evidence that a lower PNI is related to a worse prognosis in severe COVID-19 patients.

ObjectiveThis study aimed to evaluate the prognostic value of the Prognostic Nutritional Index (PNI), derived from serum albumin and lymphocyte count, in predicting all-cause mortality among lung cancer patients, using both a hospital-based cohort and an external validation dataset.MethodsA hospital-based retrospective cohort study was conducted, supplemented with external validation using the NHANES database. Univariate and multivariate Cox proportional hazards regression analyses were performed to assess associations between PNI, its components, and mortality. Variance inflation factor (VIF) testing was used to evaluate multicollinearity. Kaplan–Meier (KM) curves and log-rank tests were employed to compare survival across PNI tertiles. Restricted cubic spline (RCS) models were applied to examine non-linear relationships between continuous variables and mortality risk.ResultsIn the hospital cohort, univariate Cox analysis revealed significant associations between PNI (HR = 0.89, 95% CI: 0.85–0.93, p < 0.01), albumin (HR = 0.88, 95% CI: 0.86–0.92, p < 0.01), lymphocyte count (HR = 0.60, 95% CI: 0.50–0.80, p < 0.01), and mortality. After multivariate adjustment and VIF testing (all VIF < 5), PNI remained an independent predictor of mortality. KM curves showed significant survival differences across PNI tertiles (log-rank p < 0.001). RCS analysis indicated a non-linear relationship between PNI and mortality risk (p for nonlinear = 0.007). External validation using NHANES data consistently supported the association between PNI and mortality, with significant survival differences in KM analysis (log-rank p = 0.011) and a non-linear trend in RCS.ConclusionPNI and its components—albumin and lymphocyte count—are significantly associated with all-cause mortality in lung cancer patients. PNI demonstrates promise as a practical and reproducible prognostic indicator, potentially aiding in risk stratification and clinical decision-making.

BackgroundThe prognostic nutritional index (PNI), reflecting the body’s immune-nutritional status, has been established as a correlate of prognosis across various diseases. However, its significance in community-acquired pneumonia (CAP) remains unclear. This study investigated the relationship between PNI and clinical outcomes in CAP patients.MethodsIn this retrospective cohort study, we aimed to evaluate the prognostic value of the PNI in adults with CAP admitted to the ICU. Participants were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and categorized into quartiles (Q1–Q4) according to their PNI values. We employed Kaplan-Meier survival analysis, multivariate Cox regression, and restricted cubic spline (RCS) models to explore the association between PNI and the clinical outcomes of these CAP patients.ResultsIn this study, we included 1,608 patients with CAP. The observed 30-day and 90-day mortality rates stood at 30.85% and 39.99%, respectively. Patients with higher PNI levels exhibited a reduced risk of both 30-day and 90-day mortality. Following adjustment for confounders, PNI showed a significant negative association with 30-day mortality [HR, 0.93 (0.91–0.94), P < 0.001] and 90-day mortality [HR, 0.94 (0.92–0.95), P < 0.001]. RCS analysis revealed a consistent trend of declining all-cause mortality risk corresponding to increasing PNI values. PNI demonstrated predictive value for 30-day and 90-day mortality in CAP patients, with AUCs of 0.71 and 0.68, respectively. Combining PNI with CURB-65 enhanced the predictive value of CURB-65.ConclusionOur investigation identified a significant negative association between the PNI and the risk of mortality in patients with CAP. Additionally, the PNI demonstrated superior predictive value for mortality risk in CAP patients when compared to the CURB-65 scoring system.

BackgroundHeart failure (HF) is the leading cause of morbidity and mortality among adults worldwide. Systemic chronic inflammatory, immune dysfunction and malnutrition are considered important characteristics of HF patients. The prognostic nutritional index (PNI) is an emerging indicator for evaluating an individual's immune-inflammatory and nutritional status. However, its relationship with the prevalence of HF is unclear. This study aimed to investigate the relationship between PNI and HF.MethodsThis study included 19,965 participants from 2011 to 2018 in the National Health and Nutrition Examination Survey (NHANES) database. Weighted multiple linear regression and logistic regression, adjusted for potential confounders, were used to analyze the association between PNI and HF. Generalized additive modeling (GAM), smoothing curves, and subgroup analyses were also conducted for a deeper understanding. The diagnostic ability of the PNI for HF was assessed by analyzing the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC).ResultsUnadjusted model 1 indicated a negative association between PNI and HF risk (odds ratio (OR) = 0.90, 95% CI: 0.89, 0.92), which persisted in the fully adjusted model 3 (OR = 0.97, 95% CI: 0.95, 0.99). This suggests that each unit increase in PNI reduces the likelihood of developing HF by 3%. When continuous variables were divided into quartiles, quartile 4 had a 52% lower PNI than quartile 1 (OR = 0.48, 95% CI: 0.39, 0.56). Subgroup analyses showed a significant interaction between age and the correlation between PNI and HF (interaction P < 0.05). Among those aged 20–59 years, the risk of developing HF was reduced by 9% for each 1-unit increase in PNI. The ROC curve showed that PNI had a high diagnostic value for HF with an AUC value of 0.642.ConclusionsThe higher PNI is significantly associated with a lower prevalence of HF, particularly in the nonelderly population (20–59 years). This suggests that PNI may serve as a valuable screening tool for HF risk, emphasizing the importance of nutritional and immune status in HF development.

Background Previous studies have reported that both inflammation and nutrition may affect breast cancer development, but there has been no comprehensive analysis of the influence of the immune nutritional indicator Prognostic Nutritional Index on breast cancer. The Prognostic Nutritional Index (PNI), integrating serum albumin and lymphocyte count, serves as a dual biomarker reflecting systemic nutritional status and antitumor immune competence. Mechanistically, hypoalbuminemia signifies malnutrition and cancer-associated chronic inflammation, while lymphocytopenia indicates impaired immune surveillance facilitating tumor evasion. Clinically validated across gastrointestinal and breast malignancies, low PNI correlates with therapeutic resistance and reduced survival, attributable to compromised tissue repair and antitumor immunity. Despite its cost-effectiveness and calculability from routine blood tests, PNI’s potential as an accessible risk stratification tool remains. Methods We selected 18,709 eligible participants from the National Health and Nutrition Examination Survey (NHANES) conducted from 2001–2018. Statistical methods such as weighted multivariate logistic regression and subgroup analysis were used to analyze the associations between the PNI and breast cancer incidence. In addition, the PNI thresholds for breast cancer incidence were determined via a two-stage linear regression model. Finally, a machine learning algorithm (XGBoost) was applied to verify the effect of the PNI on the incidence of breast cancer. The Prognostic Nutritional Index (PNI), derived from serum albumin (ALB, g/L) and peripheral blood lymphocyte count (×109/L) via the formula PNI = ALB + 5 × lymphocyte count, was evaluated using weighted multivariable logistic regression to assess its dose–response relationship with the outcome. To this end, PNI was modeled both as a continuous variable (per 1-unit increase) and using gender-specific tertiles (T1: <46.8; T2: 46.8–52.4; T3: >52.4). Results In this study, the Prognostic Nutritional Index (PNI) demonstrated a significant inverse association with breast cancer risk. The mean PNI value was 52.5 (±8.9) in the overall population, with significantly lower values observed in breast cancer patients compared to controls (p < 0.001). A consistent dose-response relationship was identified, wherein each unit increase in PNI corresponded to a 4% reduction in breast cancer risk (fully adjusted OR = 0.96; 95% CI: 0.94–0.98). This linear association was further confirmed by restricted cubic splines (RCS) analysis (P-overall <0.001; P-non-linear > 0.05). Moreover, when PNI was categorized into tertiles, the highest tertile was associated with a substantially lower risk of breast cancer compared to the lowest tertile (OR = 0.58; 95% CI: 0.41–0.81; p < 0.001). A two-stage linear regression model identified a PNI threshold of 58.0 for breast cancer incidence. Importantly, the relevance of PNI was corroborated by machine learning approaches; XGBoost algorithm identified PNI as one of the top five predictive variables for breast cancer. In conclusion, these findings indicate that lower PNI levels are significantly associated with increased breast cancer risk, highlighting its potential role as an auxiliary indicator for risk stratification. However, further prospective studies are warranted to validate its clinical utility. Conclusion Our study suggests that the PNI is negatively and linearly correlated with the incidence of breast cancer. A lower Prognostic Nutritional Index (PNI) is associated with an increased risk of breast cancer.

BackgroundPoor nutritional status is associated with progression and advanced disease in patients with cancer. The prognostic nutritional index (PNI) may represent a simple method of assessing host immunonutritional status. This study was designed to investigate the prognostic value of the PNI for distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma (NPC).MethodsA training cohort of 1,168 patients with non-metastatic NPC from two institutions was retrospectively analyzed. The optimal PNI cutoff value for DMFS was identified using the online tool “Cutoff Finder”. DMFS was analyzed using stratified and adjusted analysis. Propensity score-matched analysis was performed to balance baseline characteristics between the high and low PNI groups. Subsequently, the prognostic value of the PNI for DMFS was validated in an external validation cohort of 756 patients with NPC. The area under the receiver operating characteristics curve (AUC) was calculated to compare the discriminatory ability of different prognostic scores.ResultsThe optimal PNI cutoff value was determined to be 51. Low PNI was significantly associated with poorer DMFS than high PNI in univariate analysis (P<0.001) as well as multivariate analysis (P<0.001) before propensity score matching. In subgroup analyses, PNI could also stratify different risks of distant metastases. Propensity score-matched analyses confirmed the prognostic value of PNI, excluding other interpretations and selection bias. In the external validation cohort, patients with high PNI also had significantly lower risk of distant metastases than those with low PNI (Hazards Ratios, 0.487; P<0.001). The PNI consistently showed a higher AUC value at 1-year (0.780), 3-year (0.793) and 5-year (0.812) in comparison with other prognostic scores.ConclusionPNI, an inexpensive and easily assessable inflammatory index, could aid clinicians in developing individualized treatment and follow-up strategies for patients with non-metastatic NPC.