Comparison of the Prognostic Value of Inflammatory and Nutritional Indices in Nonmetastatic Renal Cell Carcinoma

Association between Geriatric Nutritional Risk Index and survival outcomes in patients with urological cancers: an updated meta-analysis

OBJECTIVES

This meta-analysis aimed to evaluate the association between the Geriatric Nutritional Risk Index (GNRI) and survival outcomes in patients with urological cancer.

DESIGN

Systematic review and meta-analysis of observational studies.

DATA SOURCES

A comprehensive literature search was conducted in Medline, EMBASE, Google Scholar and the Cochrane Library from inception to 7 July 2024.

ELIGIBILITY CRITERIA

Studies were included if they examined the correlation between the GNRI and long-term survival outcomes in adult patients (≥18 years old) with urological cancers.

DATA EXTRACTION AND SYNTHESIS

Two researchers independently extracted data and assessed study quality using the Newcastle-Ottawa Scale and certainty of evidence using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) methodology. Publication bias was evaluated using funnel plots and Egger's test for outcomes with more than 10 studies. Pooled HRs and 95% CIs were calculated using a random-effects model. Subgroup analyses, meta-regression and sensitivity analyses were performed.

RESULTS

17 studies involving 8816 patients were included. Study quality assessment showed that 15 studies had a low risk of bias (scores 7-9) and two had a high risk (scores 5-6). Low GNRI was significantly associated with poor overall survival (OS) (HR: 2.6, 95% CI: 2.0 to 3.38, p<0.00001, I² = 64%, 13 studies), cancer-specific survival (CSS) (HR: 2.65, 95% CI: 1.76 to 3.98, p<0.00001, I² = 75%, 7 studies), recurrence-free survival (RFS) (HR: 1.47, 95% CI: 1.02 to 2.1, p=0.04, I² = 58%, four studies) and progression-free survival (PFS) (HR: 1.86, 95% CI: 1.54 to 2.23, p<0.00001, I² = 0%, five studies). Funnel plot and Egger's test (p=0.948) indicated a low risk of publication bias for OS. GRADE assessment showed low certainty of evidence for OS and PFS, and very low certainty for CSS and RFS. Meta-regression identified follow-up time and sample size as significant sources of heterogeneity.

CONCLUSIONS

A low GNRI is significantly associated with poor survival outcomes in patients with urological cancer. The GNRI may serve as a valuable prognostic tool in clinical practice. Further research is needed to validate these findings in diverse populations and to explore the underlying biological mechanisms.

PROSPERO REGISTRATION NUMBER

CRD42023476678.

Hematologic Inflammation Indices for Differentiating between Brucella, Pyogenic, and Tuberculous Spondylodiscitis

Infectious spondylodiscitis is a life-threatening disease and has some challenges in terms of diagnostic, differentiative, and therapeutic processes. Therefore, rapid and effective management of infectious spondylodiscitis is necessary. Hematological inflammation indices (HIIs) such as the neutrophil/lymphocyte ratio and aggregate index of systemic inflammation are derived from blood cells and used as diagnostic, prognostic, predictive, and treatment monitoring indicators. This study aimed to evaluate HIIs for discriminating between infectious spondylodiscitis pathogens. This retrospective comparative study included 116 patients with infectious spondylodiscitis. According to the responsible infectious pathogens, three types of infectious spondylodiscitis were defined: Brucella (n = 51), pyogenic (n = 43), and tuberculous (n = 22). The HIIs were derived from baseline complete blood counts. The three types of infectious spondylodiscitis were statistically compared for the HII scores. We found that the Brucella group had significantly lower HII scores than the pyogenic group (p < 0.05). Also, the Brucella group had significantly lower HII scores than the tuberculous group (p < 0.05). However, no significant differences were found between the pyogenic and tuberculous groups regarding HIIs (p > 0.05). In conclusion, the HIIs may be considered in the differentiation between Brucella spondylodiscitis and other types of infectious spondylodiscitis.

Outcomes of first-line treatment and their association with pretreatment neutrophil-to-lymphocyte ratio in patients with advanced renal cell carcinoma: Insights from a tertiary care institute in Pakistan

Background

Renal cell carcinomas (RCCs) are renal parenchymal neoplasms that contribute to <5% of cancer cases worldwide. Within the diverse group of renal tumours, clear cell carcinoma is the most common subtype. The recommended first-line treatment for metastatic disease is a tyrosine kinase inhibitor given either as monotherapy or in combination with an immune checkpoint inhibitor, based on improved survival outcomes. These endpoints are not only influenced by the initial risk stratification but also by certain variables such as the neutrophil-to-lymphocyte (NLR) ratio.

Methods

A retrospective review was conducted to evaluate the progression-free survival (PFS) with first-line treatment in patients with metastatic RCC treated at our institute from the year 2017-2021. We also investigated the association of PFS with both Memorial Sloan Kettering Cancer Center risk groups and the pretreatment NLR ratio.

Results

Overall, 35 patients were enrolled after fulfilling the eligibility criteria. Of these, 25 patients received Pazopanib, 5 patients were treated with Sunitinib and the remaining patients were administered Pembrolizumab with Axitinib. Two-thirds of the study population belonged to the intermediate-risk group. The median PFS for all participants was 16 months. Among the overall population, patients in the favourable-risk group demonstrated superior PFS. Patients with elevated pretreatment NLR experienced shorter PFS compared to the patients with low to normal NLR.

Conclusion

This review highlights the prognostic significance of initial risk stratification and pretreatment NLR in predicting the response to first-line treatment in metastatic RCC patients. As this is a comprehensive study emphasizing the outcomes of metastatic RCC in Pakistan, it fills a void in the literature by providing invaluable perspectives on the real-world outcomes of patients. This not only enhances our understanding of disease management in this region but also lays the foundation for future investigations.

Editorial for the Special Issue: Pathophysiology of Chronic Kidney Disease and Its Complications

Chronic kidney disease (CKD) is a risk factor for end-stage kidney disease, requiring renal replacement therapy [...].

Interpretable machine learning model based on the systemic inflammation response index and ultrasound features can predict central lymph node metastasis in cN0T1-T2 papillary thyroid carcinoma

Background

It is arguable whether individuals with T1-T2 papillary thyroid cancer (PTC) who have a clinically negative (cN0) diagnosis should undergo prophylactic central lymph node dissection (pCLND) on a routine basis. Many inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammatory index (SII), have been reported in PTC. However, the associations between the systemic inflammation response index (SIRI) and the risk of central lymph node metastasis (CLNM) remain unclear.

Methods

Retrospective research involving 1,394 individuals with cN0T1-T2 PTC was carried out, and the included patients were randomly allocated into training (70%) and testing (30%) subgroups. The preoperative inflammatory indices and ultrasound (US) features were used to train the models. To assess the forecasting factors as well as drawing nomograms, the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were utilized. Then eight interpretable models based on machine learning (ML) algorithms were constructed, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost). The performance of the models was evaluated by incorporating the area under the precision-recall curve (auPR) and the area under the receiver operating characteristic curve (auROC), as well as other conventional metrics. The interpretability of the optimum model was illustrated via the shapley additive explanations (SHAP) approach.

Results

Younger age, larger tumor size, capsular invasion, location (lower and isthmus), unclear margin, microcalcifications, color Doppler flow imaging (CDFI) blood flow, and higher SIRI (≥0.77) were independent positive predictors of CLNM, whereas female sex and Hashimoto thyroiditis were independent negative predictors, and nomograms were subsequently constructed. Taking into account both the auROC and auPR, the RF algorithm showed the best performance, and superiority to XGBoost, CatBoost and ANN. In addition, the role of key variables was visualized in the SHAP plot.

Conclusions

An interpretable ML model based on the SIRI and US features can be used to predict CLNM in individuals with cN0T1-T2 PTC.

A prognostic immune nutritional index can predict all-cause mortality in patients with antineutrophil cytoplasmic antibody-associated vasculitis

Background

Studies have proposed that nutritional and immune-related markers are relevant with patient outcomes of various medical conditions and could be a useful indicator of patient prognostication.

Objectives

This study investigated whether a prognostic immune nutritional index (PINI) at diagnosis could predict adverse clinical outcomes in patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV).

Design

A retrospective, single-centre observational cohort analysis of patients with AAV.

Methods

All-cause mortality and end-stage renal disease (ESRD) were investigated outcomes during the observation period. PINI was calculated by serum albumin (g/mL) × 0.9 - monocyte count (/mm3) × 0.0007, and the optimal cut-off of PINI was obtained using a Youden index-based bootstrapping method. Cox hazard analyses were performed to identify independent predictors of patient outcomes.

Results

Of the 250 eligible patients, the median age of patients was 60.0 years, and 34.0% were men. During the disease course, 33 (13.2%) died and 42 (16.8%) developed ESRD, respectively. The ideal PINI cut-offs for all-cause mortality and ESRD were set as ⩽2.47 and ⩽3.12 (sensitivity and specificity of 75.1% and 60.6% for mortality and 46.2% and 78.6% for ESRD). AAV patients with PINI ⩽2.47 and those with PINI ⩽3.12 exhibited significantly higher rates for all-cause mortality and ESRD compared to those with PINI >2.47 and >3.12. In the multivariable Cox analysis, PINI ⩽2.47 (hazard ratio [HR]: 3.173, 95% confidence interval [CI]: 1.129, 8.916, p = 0.029) was independently associated with all-cause patient mortality; however, PINI ⩽3.12 was not independently associated with ESRD (HR: 1.097, 95% CI: 0.419, 2.870, p = 0.850).

Conclusion

Findings from this study demonstrated PINI could predict all-cause patient mortality in AAV, and a higher clinical attention is warranted in those with PINI ⩽2.47 at initial diagnosis.

Combination of Sarcopenia and Hypoalbuminemia Is a Poor Prognostic Factor in Surgically Treated Nonmetastatic Renal Cell Carcinoma

PURPOSE

The purpose of this study is to observe how preoperative sarcopenia and hypoalbuminemia affect the oncological outcome of nonmetastatic renal cell carcinoma (RCC) after partial or radical nephrectomy.

METHODS

This study retrospectively analyzes 288 Japanese patients with nonmetastatic RCC who underwent radical treatment at Kanazawa University Hospital between October 2007 and December 2018. Relationships between sarcopenia as indicated by the psoas muscle mass index and hypoalbuminemia (albumin ≤ 3.5 g/dL) with overall survival (OS) and metastasis-free survival (MFS) were determined.

RESULTS

The study found that 110 (38.2%) of the 288 patients were sarcopenic and 29 (10.1%) had hypoalbuminemia. The combination of sarcopenia and hypoalbuminemia was associated with a shorter OS and MFS (p for trend = 0.0007 and <0.0001, respectively), according to Kaplan-Meier curves. The concurrent presence of sarcopenia and hypoalbuminemia were found to be significant and independent predictors of poor MFS (hazard ratio (HR), 2.96; 95% confidence interval (95% CI), 1.05-8.39; p = 0.041) and poor OS (HR, 6.87; 95% CI, 1.75-26.94; p = 0.006), respectively.

CONCLUSIONS

In Japanese patients with surgically treated nonmetastatic RCC, combined preoperative sarcopenia and hypoalbuminemia was a significant predictor of poor survival.