A Prognostic Model Based on Nutritional Risk Index in Operative Breast Cancer

Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients

BACKGROUND

This study aimed to construct a novel model and validate its predictive power in non-esophageal squamous cell carcinoma (NESCC) patients.

METHODS

This retrospective study included 151 patients between October 2006 and September 2016. The LASSO Cox and Random Survival Forest (RSF) models were developed with the help of hematological biomarkers and clinical characteristics. The concordance index (C-index) was used to assess the prognostic power of the LASSO Cox model, RSF model, and TNM staging. Based on the risk scores of the LASSO Cox and RSF models, we divided patients into low-risk and high-risk subgroups.

RESULTS

We constructed two models in NESCC patients according to LASSO Cox regression and RSF models. The RSF model reached a C-index of 0.841 (95% CI: 0.792-0.889) in the primary cohort and 0.880 (95% CI: 0.830-0.930) in the validation cohort, which was higher than the C-index of the LASSO Cox model 0.656 (95% CI: 0.580-0.732) and 0.632 (95% CI: 0.542-0.720) in the two cohorts. The integrated C/D area under the ROC curve (AUC) values for the LASSO Cox and RSF models were 0.701 and 0.861, respectively. In both two models, Kaplan-Meier survival analysis and the estimated restricted mean survival time (RMST) values indicated that the low-risk subgroup had a better prognostic outcome than the high-risk subgroup (p < 0.05).

CONCLUSIONS

The RSF model has better prediction power than the LASSO Cox and the TNM staging models. It has a guiding value for the choice of individualized treatment in patients with NESCC.

Prognostic value of the preoperative systemic immune-inflammation nutritional index in patients with gastric cancer

BACKGROUND

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related deaths in China. Many patients with GC frequently experience symptoms related to the disease, including anorexia, nausea, vomiting, and other discomforts, and often suffer from malnutrition, which in turn negatively affects perioperative safety, prognosis, and the effectiveness of adjuvant therapeutic measures. Consequently, some nutritional indicators such as nutritional risk index (NRI), prognostic nutritional index (PNI), and systemic immune-inflammatory-nutritional index (SIINI) can be used as predictors of the prognosis of GC patients.

AIM

To examine the prognostic significance of PNI, NRI, and SIINI in postoperative patients with GC.

METHODS

A retrospective analysis was conducted on the clinical data of patients with GC who underwent surgical treatment at the Guangxi Medical University Cancer Hospital between January 2010 and December 2018. The area under the receiver operating characteristic (ROC) curve was assessed using ROC curve analysis, and the optimal cutoff values for NRI, PNI, and SIINI were identified using the You-Review-HTMLden index. Survival analysis was performed using the Kaplan-Meier method. In addition, univariate and multivariate analyses were conducted using the Cox proportional hazards regression model.

RESULTS

This study included a total of 803 patients. ROC curves were used to evaluate the prognostic ability of NRI, PNI, and SIINI. The results revealed that SIINI had superior predictive accuracy. Survival analysis indicated that patients with GC in the low SIINI group had a significantly better survival rate than those in the high SIINI group (P < 0.05). Univariate analysis identified NRI [hazard ratio (HR) = 0.68, 95% confidence interval (CI): 0.52-0.89, P = 0.05], PNI (HR = 0.60, 95%CI: 0.46-0.79, P < 0.001), and SIINI (HR = 2.10, 95%CI: 1.64-2.69, P < 0.001) as prognostic risk factors for patients with GC. However, multifactorial analysis indicated that SIINI was an independent risk factor for the prognosis of patients with GC (HR = 1.65, 95%CI: 1.26-2.16, P < 0.001).

CONCLUSION

Analysis of clinical retrospective data revealed that SIINI is a valuable indicator for predicting the prognosis of patients with GC. Compared with NRI and PNI, SIINI may offer greater application for prognostic assessment.

The association between lower prognostic nutritional index and higher short- & long-term mortality in older adults (≥ 70 years) undergoing coronary artery bypass grafting: a retrospective study

BACKGROUND

The incidence of cardiovascular diseases among old individuals is on the rise with the growing trend of population aging. Coronary artery bypass grafting (CABG) is an important treatment modality for coronary heart diseases and is increasingly employed in older adults. However, concerns arise due to the poor prognosis following surgery in this population. The prognostic nutritional index (PNI) reflects the nutritional status and immune function of patients. It has been previously utilized in prognostic assessments for other surgical procedures and receives increasing attention in the field of cardiovascular surgery.

METHODS

This retrospective study examined a cohort of older adults (70 to 90 years) who underwent initial CABG-only surgery at five cardiac centers, excluding patients with coexisting neoplastic or immune disorders. The objective was to investigate the relationship between low PNI and both short- and long-term mortality in this population. PNI was calculated based on total lymphocyte count and serum albumin concentration measured before surgery, after surgery, and before discharge. The cut-off value of PNI was established through receiver's operating characteristic curve. Univariate and multivariate logistic and cox regression analyses were performed to identify the independent risk factors related to the occurrence of short- and long-term mortality. Smooth survival model and Kaplan-Meier analysis were employed to evaluate survival and relative risk.

RESULTS

Among the 1173 patients, 90 patients (7.7%) experienced short-term mortality and 131 (11.2%) patients had long-term mortality during follow-up and the survival probabilities at 1,3,5,10 years were 96.98%, 94.64%, 89.89%, 76.96%, respectively. In this population, lower preoperative PNI was independently and significantly correlated with short-term mortality (OR = 2.372, 95%CI: 1.394-4.035). Additionally, a low PNI before discharge was independently and significantly associated with increased long-term mortality risk in older adults who underwent CABG (HR = 1.451, 95%CI: 1.012-2.082). Long-term follow-up also showed that patients with a low PNI before discharge had significantly higher long-term mortality (log-rank: P = 0.004). Moreover, extended Kaplan-Meier analysis showed that women (log-rank: P = 0.005) and obese patients (log-rank: P = 0.073) appeared to have higher long-term survival rates.

CONCLUSION

The current investigation unveiled that PNI has emerged as an autonomous determinant for both short-and long-term mortality in older adults receiving CABG.

Nutritional Risk Index (NRI) predicts the clinical outcomes of patients with gastric cancer who received immune checkpoint inhibitors (PD-1/PD-L1)

Numerous studies have consistently indicated a connection between the clinical results of individuals who receive immunotherapy and their nutritional condition. This study aims to evaluate the predictive capacity of the Nutritional Risk Index (NRI) in gastric cancer patients who are undergoing treatment with immune checkpoint inhibitors (ICIs). This study included a total of 146 individuals diagnosed with gastric cancer and received a combination of chemotherapy and immunotherapy using PD-1/PD-L1 inhibitors. The threshold was established by utilizing the receiver operating characteristic (ROC) curve. To analyze the clinical and pathological characteristics of the 2 groups, we performed Chi-square test or Fisher exact test. Univariate and multivariate analyses were performed to assess the factors influencing progression-free survival (PFS) and overall survival (OS) rates. Additionally, we developed nomograms to accurately predict the probability of 1- year and 3-year survival in these patients. According to the threshold, there were 38 (26.0%) patients in the low NRI category and 108 (74.0%) patients in the high NRI category. In the high NRI group, the median survival PFS was 32.50 months, while it was 11.77 months in the low NRI group. Likewise, the average survival OS in the 2 categories was 18.57 months compared to an indefinite duration. Individuals classified in the low NRI category encountered reduced PFS and OS, with a hazard ratio (HR) of 2.015 and 2.093 respectively, along with corresponding P-values of .009 and .006. The analysis of multiple variables showed that the number of platelets and TNM stage were separate factors that predicted both PFS and OS. Additionally, NRI was further recognized as a separate predictive factor for overall survival. The analysis of a specific subgroup revealed that individuals in the low NRI category experienced worse PFS and OS, especially within the group receiving ICIs. The C-index and the respective 95% CI of the nomograms to forecast the likelihood of PFS and OS survival were 0.646 (0.583-0.709) and 0.693 (0.635-0.751). NRI has the capability to forecast the clinical results of individuals who were diagnosed with gastric cancer and have received ICIs. This makes it a feasible biomarker for identifying patients who could benefit from ICIs.

A review of enhanced recovery after surgery concept in perioperative radical prostatectomy for prostate cancer

Radical prostatectomy (RP) is the main treatment for early-stage localized prostate cancer. With the improvement of medical technology, radical prostatectomy is mainly performed under laparoscopy or robot assistance. With the continuous deepening of the Enhanced Recovery After Surgery (ERAS) concept in clinical practice, patients have increasingly high requirements for postoperative recovery. The ERAS concept is of great significance in the perioperative period and has been used in many surgical fields due to its ability to improve prognosis. ERAS has not yet been widely applied in urology and the research progress of other disciplines in ERAS has promoted its development in radical prostatectomy. This review summarizes the key elements of ERAS in the perioperative period of RP, aiming to demonstrate the superiority of ERAS and provide new references and inspirations for urologists.

Performance of nutritional and inflammatory markers in patients with pancreatic cancer

BACKGROUND

Systemic inflammation and nutrition play pivotal roles in cancer progression and can increase the risk of delayed recovery after surgical procedures.

AIM

To assess the significance of inflammatory and nutritional indicators for the prognosis and postoperative recovery of patients with pancreatic cancer (PC).

METHODS

Patients who were diagnosed with PC and underwent surgical resection at our hospital between January 1, 2019, and July 31, 2023, were enrolled in this retrospective observational cohort study. All the data were collected from the electronic medical record system. Seven biomarkers - the albumin-to-globulin ratio, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), nutritional risk index (NRI), and geriatric NRI were assessed.

RESULTS

A total of 446 patients with PC met the inclusion criteria and were subsequently enrolled. Patients with early postoperative discharge tended to have higher PNI values and lower SII, NLR, and PLR values (all P < 0.05). Through multivariable logistic regression analysis, the SII value emerged as an independent risk factor influencing early recovery after surgery. Additionally, both univariable and multivariable Cox regression analyses revealed that the PNI value was the strongest prognostic marker for overall survival (OS; P = 0.028) and recurrence-free survival (RFS; P < 0.001). The optimal cutoff PNI value was established at 47.30 using X-tile software. Patients in the PNI-high group had longer OS (P < 0.001) and RFS (P = 0.0028) times than those in the PNI-low group.

CONCLUSION

Preoperative systemic inflammatory-nutritional biomarkers may be capable of predicting short-term recovery after surgery as well as long-term patient outcomes.

Combined influence of nutritional and inflammatory status and breast cancer: findings from the NHANES

BACKGROUND

Previous studies have hinted at the benefits of following an anti-inflammatory diet for potentially reducing breast cancer prevalence. However, the combined influence of diet and inflammation on breast cancer remains unclear.

METHODS

The advanced lung cancer inflammation index (ALI) was used to assess inflammation and nutritional status. Statistical methods, such as multivariable logistic regression, eXtreme Gradient Boosting (XGBoost) model, and subgroup analysis, were employed to analyze the impact of ALI on prevalence of BC. Additionally, a two-piece-wise logistic regression model with smoothing was used to determine the ALI threshold for BC prevalence. The study aimed to understand the mechanistic association between ALI levels and BC development.

RESULTS

The mean (SD) age of the study population was 50.0 (17.7) years, with 40.0% of individuals classified as obese. Comparing ALI tertiles to the lowest tertile, the odds ratios (95% CI) for breast cancer (BC) were 0.78 (0.62, 0.98) and 0.68 (0.52, 0.87) for T2-T3. The XGBoost machine learning model was employed to assess the importance of selected factors, revealing ALI as one of the top five variables influencing BC. Subgroup analysis identified a correlation between ALI, alcohol consumption, and menopausal status. Additionally, ALI levels were associated with decreased estradiol (E2) levels, increased total testosterone (TT)/E2 ratio, and TT/sex hormone-binding globulin (SHBG) ratio.

CONCLUSION

This study indicates a potential protective effect of ALI levels against breast cancer, possibly related to sex hormone disruption. The findings support the use of optimal therapeutic strategies for preventing breast cancer.

A nomogram based on inflammation and nutritional biomarkers for predicting the survival of breast cancer patients

Background

We aim to develop a new prognostic model that incorporates inflammation, nutritional parameters and clinical-pathological features to predict overall survival (OS) and disease free survival (DFS) of breast cancer (BC) patients.

Methods

The study included clinicopathological and follow-up data from a total of 2857 BC patients between 2013 and 2021. Data were randomly divided into two cohorts: training (n=2001) and validation (n=856) cohorts. A nomogram was established based on the results of a multivariate Cox regression analysis from the training cohorts. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. Furthermore, decision curve analysis (DCA) was performed to assess the clinical value of the nomogram.

Results

A nomogram was developed for BC, incorporating lymphocyte, platelet count, hemoglobin levels, albumin-to-globulin ratio, prealbumin level and other key variables: subtype and TNM staging. In the prediction of OS and DFS, the concordance index (C-index) of the nomogram is statistically greater than the C-index values obtained using TNM staging alone. Moreover, the time-dependent AUC, exceeding the threshold of 0.7, demonstrated the nomogram's satisfactory discriminative performance over different periods. DCA revealed that the nomogram offered a greater overall net benefit than the TNM staging system.

Conclusion

The nomogram incorporating inflammation, nutritional and clinicopathological variables exhibited excellent discrimination. This nomogram is a promising instrument for predicting outcomes and defining personalized treatment strategies for patients with BC.

Phase Angle but Not Psoas Muscle Predicts Nutritional Risk and Prognosis in Males with Hepatocellular Carcinoma

Despite those with hepatocellular carcinoma (HCC) being at increased risk of malnutrition, there is a notable absence of practical approaches for nutritional assessment in clinical practice. We investigated the usefulness of phase angle (PhA) and Total Psoas Area Index (TPAI) for indicating nutritional risk and HCC prognosis. Weight, height, body mass index (BMI), adductor pollicis muscle thickness (APMT), and handgrip strength (HGS) were assessed. The Nutritional Risk Index (NRI) was calculated. Body composition was assessed using bioimpedance spectroscopy and magnetic resonance imaging. The Child-Turcotte-Pugh (CTP) score and Barcelona-Clinic Liver Cancer (BCLC) classification determined the prognosis. Fifty-one males with HCC were enrolled (CTP C = 11.8%). PhA showed a moderate positive correlation with APMT (r = 0.450; p < 0.001) and HGS (r = 0.418; p = 0.002) and a weak positive correlation with TPAI (r = 0.332; p = 0.021). PhA had a strong positive correlation with NRI (r = 0.614; p < 0.001). Mean PhA values were significantly different according to disease severity (CTP C p = 0.001, and BCLC D p = 0.053). TPAI had no significant correlation with HGS, CTP, or BCLC. PhA was a superior approach for predicting nutritional risk and prognosis in HCC than TPAI. Lower PhA is associated with disease progression, lower muscle mass and function, greater severity of nutritional risk, and increased mortality in HCC.

The Utility of the Cachexia Index and the Modified Glasgow Score in Young Patients With Breast Cancer

Background Breast cancer is the most common cancer in women. Body composition and inflammatory markers are increasingly important for predicting cancer prognosis. The Cancer Cachexia Index (CXI) and the modified Glasgow Prognostic Score (GPS) are two new markers evaluating prognosis in cancer. In this study, we evaluated the utility of the CXI and the modified GPS in young patients with breast cancer. Methods Eighty patients diagnosed between 2012 and 2023 were included in the study. The following information was recorded: patient features, pathological subtype, estrogen receptor and human epidermal growth factor receptor-2 (HER-2) status, disease stage, therapies, disease recurrence, and last control or death date. The CXI and the modified GPS were calculated using clinical data, including skeletal muscle index, albumin, C-reactive protein, and neutrophil-to-lymphocyte ratio. Results There were no differences in overall survival with respect to the CXI in the study population (p=0.96). Only stage 4 patients showed statistically significant survival differences according to the CXI (p=0.046). Although the median survival time was not reached for the modified GPS groups, there was a statistical overall survival difference favoring the negative group (p=0.017). No significant differences were observed in disease-free survival due to the CXI (p=0.128). In multivariate analysis, no factors, including the modified GPS and the CXI, influenced overall survival. There was a significant effect of the modified GPS and body mass index on recurrence (p=0.037; p=0.034). The CXI had a non-significant marginal p-value (p=0.074). Conclusion Our study showed that the modified GPS may be related to disease-free survival and overall survival, whereas the CXI has a more prominent prognostic effect on overall survival in advanced-stage breast cancers. In early-stage and young patients, optimization of risk scores is lacking.

Cost-effective prognostic evaluation of breast cancer: using a STAR nomogram model based on routine blood tests

Background

Breast cancer (BC) is the most common and prominent deadly disease among women. Predicting BC survival mainly relies on TNM staging, molecular profiling and imaging, hampered by subjectivity and expenses. This study aimed to establish an economical and reliable model using the most common preoperative routine blood tests (RT) data for survival and surveillance strategy management.

Methods

We examined 2863 BC patients, dividing them into training and validation cohorts (7:3). We collected demographic features, pathomics characteristics and preoperative 24-item RT data. BC risk factors were identified through Cox regression, and a predictive nomogram was established. Its performance was assessed using C-index, area under curves (AUC), calibration curve and decision curve analysis. Kaplan-Meier curves stratified patients into different risk groups. We further compared the STAR model (utilizing HE and RT methodologies) with alternative nomograms grounded in molecular profiling (employing second-generation short-read sequencing methodologies) and imaging (utilizing PET-CT methodologies).

Results

The STAR nomogram, incorporating subtype, TNM stage, age and preoperative RT data (LYM, LYM%, EOSO%, RDW-SD, P-LCR), achieved a C-index of 0.828 in the training cohort and impressive AUCs (0.847, 0.823 and 0.780) for 3-, 5- and 7-year OS rates, outperforming other nomograms. The validation cohort showed similar impressive results. The nomogram calculates a patient's total score by assigning values to each risk factor, higher scores indicating a poor prognosis. STAR promises potential cost savings by enabling less intensive surveillance in around 90% of BC patients. Compared to nomograms based on molecular profiling and imaging, STAR presents a more cost-effective, with potential savings of approximately $700-800 per breast cancer patient.

Conclusion

Combining appropriate RT parameters, STAR nomogram could help in the detection of patient anemia, coagulation function, inflammation and immune status. Practical implementation of the STAR nomogram in a clinical setting is feasible, and its potential clinical impact lies in its ability to provide an early, economical and reliable tool for survival prediction and surveillance strategy management. However, our model still has limitations and requires external data validation. In subsequent studies, we plan to mitigate the potential impact on model robustness by further updating and adjusting the data and model.

Development and Validation of Nomograms Based on Nutritional Risk Index for Predicting Extracapsular Extension and Seminal Vesicle Invasion in Patients Undergoing Radical Prostatectomy

BACKGROUND

The aim of the study was to investigate the predictive value of the nutritional risk index (NRI) for extracapsular extension (ECE) and seminal vesicle invasion (SVI) in prostate cancer (PCa) patients undergoing radical prostatectomy (RP), and further develop and validate predictive nomograms for ECE and SVI based on the NRI.

METHODS

We retrospectively analyzed 734 PCa patients who underwent RP between 2010 and 2020 in the Department of Urology at Peking University Third Hospital. The enrolled patients were randomly divided into a primary cohort (n = 489) and a validation cohort (n = 245) in a 2:1 manner. The baseline NRI of patients was calculated using serum albumin level and body mass index, and a malnutrition status was defined as NRI ≤ 98. Univariate and multivariate logistic regression analyses were conducted to identify predictors for ECE and SVI. Nomograms for predicting ECE and SVI were established based on the results of the multivariate logistic regression analysis. The performance of the nomograms was estimated using Harrell's concordance index (C-index), the area under curve (AUC) of receiver operating characteristic (ROC) curves and the calibration curves.

RESULTS

In the primary cohort, 70 (14.3%) patients with NRI ≤ 98 were classified as malnutrition, while the remaining 419 (85.7%) patients with NRI > 98 were considered to have normal nutrition. The nomograms for predicting ECE and SVI shared common factors including NRI, percentage of positive biopsy cores (PPC) and biopsy Gleason score, while prostate-specific antigen (PSA) levels and PSA density (PSAD) were only incorporated in ECE nomogram. The C-indexes of the nomograms for predicting ECE and SVI were 0.785 (95% confidence interval (CI): 0.745 - 0.826) and 0.852 (95% CI: 0.806 - 0.898), respectively. The calibration curves demonstrated excellent agreement between the predictions by the nomograms and the actual observations. The results remained reproducible when the nomograms were applied to the validation cohort.

CONCLUSIONS

The NRI is significantly associated with ECE and SVI in PCa patients. The nomogram established based on the NRI in our study can provide individualized risk estimation for ECE and SVI in PCa patients, and may be valuable for clinicians in making well-informed decisions regarding treatment strategies and patient management.

Nutritional risk index predicts the prognosis of gastric cancer patients with pyloric stenosis who received preoperative parenteral nutrition

Patients with gastric cancer with pyloric stenosis frequently have poor nutritional status and preoperative parenteral nutrition has been a common treatment strategy. The present study aimed to explore the predictive ability of the nutritional risk index (NRI) regarding the prognosis of patients with gastric cancer and pyloric stenosis who received preoperative parenteral nutrition. A total of 194 patients with gastric cancer with pyloric stenosis who received preoperative parenteral nutrition at Tthe Second People's Hospital of Neijiang (Neijiang, China) between January 2016 and December 2021 were included. At the same time, 221 patients with gastric cancer without pyloric stenosis who received surgery during the same period were also collected and the clinicopathological characteristics of the patients were compared. The optimal cut-off value of the NRI was determined from the receiver operating characteristic curve and prognostic factors were identified by survival analysis. Finally, a nomogram was constructed to predict the survival probability of patients with gastric cancer. The results indicated that patients with pyloric stenosis exhibited a wide range of unfavorable pathological characteristics and blood parameters. In addition, their overall survival (OS) was significantly worse (P<0.001). Among the patients with pyloric stenosis, there were 120 patients (61.9%) with an NRI <93.42 and 74 patients (38.1%) with NRI ≥93.42. Furthermore, patients with an NRI <93.42 had poorer OS (34.37 months vs. not reached, P=0.004). Of note, age, tumor size, radical resection, NRI and TNM stage were determined to be independent prognostic factors for OS. The C-index of the nomogram was 0.760 (95%CI: 0.688-0.832). In conclusion, the NRI was indicated to be an accurate score reflecting the nutritional status of patients, which was able to predict the clinical outcomes of patients with gastric cancer with pyloric stricture who received preoperative parenteral nutrition. Patients with a low NRI had shorter survival times.

Prognostic Utility of Nutritional Risk Index in Patients with Head and Neck Soft Tissue Sarcoma

BACKGROUND

The nutritional risk index (NRI) is an excellent indicator of nutritional status and a significant prognostic factor in several malignancies, but the relationship between NRI and the prognosis of head and neck soft tissue sarcoma (HNSTS) patients remains unclear. The aim of this study was to investigate the role of NRI in patients with HNSTS.

METHODS

We retrospectively reviewed patients with HNSTS between 1990 and 2021. In order to determine the optimal cut-off value of NRI, the Maximally selected log-rank statistic was performed. We evaluated the effect of NRI on overall survival (OS) and progression-free survival (PFS) by using the Kaplan-Meier method and Cox regression analysis. Then, OS and PFS nomograms based on NRI were constructed.

RESULTS

In total, 436 HNSTS patients were included in this study. The optimal cut-off value of NRI was 99.34. Patients with low-NRI showed significantly worse OS and PFS than patients with high-NRI, respectively (5-year OS rate of 43.0 vs. 70.8%, 5-year PFS rate of 29.0 vs. 45.0%, all p < 0.05). In the multivariate analysis, distant metastasis, deep tumor depth, tumor grade, and NRI were prognostic factors for both PFS and OS, and treatment modality was associated with OS but not PFS. The concordance indexes (C-indexes) of OS and PFS nomograms were 0.794 (95% CI, 0.759-0.829) and 0.663 (95% CI, 0.626-0.700), respectively, which also performed well in the validation set.

CONCLUSIONS

NRI is an independent predictor of OS and PFS in HNSTS patients. The validated nomograms based on NRI provide useful predictions of OS and PFS for patients with HNSTS.