Association between albumin-to-globulin ratio and the risk of overall survival in advanced non-small cell lung cancer patients with anlotinib treatment: a retrospective cohort study

Relationship between albumin-globulin ratio and prostate-specific antigen: a cross-sectional study based on NHANES 2003-2010

PURPOSE

The albumin-globulin ratio (AGR) influences the development of prostate cancer; however, the relationship between AGR and prostate-specific antigen (PSA) has not been reported.

METHODS

This cross-sectional investigation used comprehensive AGR versus PSA data from men with 40 years of age and older, who participated in the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2010, spanning 4 investigation cycles, as only these cycles contained complete PSA data. To evaluate the nonlinear relationship between the ARG and PSA level, a regression utilizing smoothed curve fitting (penalized spline approach) and a generalized additive model (GAM) were employed. A two-segment linear regression model was used to conduct threshold effect evaluations. Lastly, subgroup analyses were carried out along with interaction tests.

RESULTS

This study included 5,376 subjects, whose total serum PSA (mean ± standard deviation) was 1.83 ± 3.34, and its level decreased roughly with increasing quartiles of AGR. In the fully-adjusted model, AGR was negatively correlated with the likelihood of PSA, and this relationship persisted across subgroups (trend > 0.05). The PSA was characterized by an "L"-shaped curve with an inflection point. On the left side of the inflection point (K = 1.32), there was a negative relationship between AGR and PSA.

CONCLUSION

In the United States, among men over 40 years of age without prostate diseases, AGR demonstrated a nonlinear relationship with PSA, negatively correlating when AGR was below 1.32.

CLINICAL TRIAL NUMBER

Not applicable.

A prognostic nomogram of non-small cell lung cancer based on tumor marker inflammatory nutrition score

Background

Patients diagnosed with non-small cell lung cancer (NSCLC) usually have a poor prognosis, so it is critical to identify effective biomarkers for prognosis prediction. The aim of this study is to establish a nomogram to evaluate the prognostic significance of blood markers in patients with NSCLC and provide reference for clinical work.

Methods

A total of 486 patients with NSCLC who were admitted to hospital from January 2009 to December 2019 were retrospectively analyzed. The cohort was divided into a training set (n=340) and a validation set (n=146). Eleven blood indicators were selected as prognostic parameters by the least absolute shrinkage and selection operator (LASSO) model to establish tumor marker inflammatory nutrition (TMIN) score. Univariate and multivariate regression analyses were performed to establish a TMIN-nomogram model for predicting overall survival (OS) and progression-free survival (PFS). Receiver operating characteristic (ROC) survival curve, calibration curve and clinical decision curve analysis (DCA) were used to evaluate the predictive performance of the TMIN-nomogram model.

Results

The TMIN score were constructed for 11 of the most valuable prognostic variables, including white blood cells (WBCs), neutrophils (N), platelets (PLT), albumin (ALB), globulin (GLB), prealbumin (PAB), carcinoembryonic antigen (CEA), cytokeratin fragment 21-1 (CYFRA21-1), fibrinogen (FIB), platelet/lymphocyte ratio (PLR), and lymphocyte/monocyte ratio (LMR), and patients were divided into low-risk and high-risk groups using optimal cutovers. The TMIN score showed good predictive value for both OS and PFS. In addition, The TMIN score and sex, smoke, pathological classification, American Joint Committee on Cancer stage (AJCC stage), tumor diameter and Eastern Cooperative Oncology Group-performance status (ECOG-PS) and other clinical indicators showed a strong correlation. Univariate and multivariate analyses confirmed that TMIN score was an independent risk factor for OS and PFS in NSCLC patients. It is worth noting that the TMIN nomogram model of OS and PFS based on multivariate analysis combined with TMIN score has very good prognostic value for NSCLC patients.

Conclusions

TMIN is a promising predictor for PFS and OS in NSCLC patients. The TMIN-nomogram prediction model can be used as an effective tool for the comprehensive prognosis evaluation of NSCLC patients.

Prognostic Biomarkers of Systemic Inflammation in Non-Small Cell Lung Cancer: A Narrative Review of Challenges and Opportunities

Non-small cell lung cancer (NSCLC) is a common malignancy and is associated with poor survival outcomes. Biomarkers of systemic inflammation derived from blood tests collected as part of routine clinical care offer prognostic information for patients with NSCLC that may assist clinical decision making. They are an attractive tool, as they are inexpensive, easily measured, and reproducible in a variety of healthcare settings. Despite the wealth of evidence available to support them, these inflammatory biomarkers are not yet routinely used in clinical practice. In this narrative review, the key inflammatory indices reported in the literature and their prognostic significance in NSCLC are described. Key challenges limiting their clinical application are highlighted, including the need to define the optimal biomarker of systemic inflammation, a lack of understanding of the systemic inflammatory landscape of NSCLC as a heterogenous disease, and the lack of clinical relevance in reported outcomes. These challenges may be overcome with standardised recording and reporting of inflammatory biomarkers, clinicopathological factors, and survival outcomes. This will require a collaborative approach, to which this field of research lends itself. This work may be aided by the rise of data-driven research, including the potential to utilise modern electronic patient records and advanced data-analysis techniques.

The Naples Prognostic Score Is a Useful Tool to Assess Surgical Treatment in Non-Small Cell Lung Cancer

Different prognostic scores have been applied to identify patients with non-small cell lung cancer who have a higher probability of poor outcomes. In this study, we evaluated whether the Naples Prognostic Score, a novel index that considers both inflammatory and nutritional values, was associated with long-term survival. This study presents a retrospective propensity score matching analysis of patients who underwent curative surgery for non-small cell lung cancer from January 2016 to December 2021. The score considered the following four pre-operative parameters: the neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, serum albumin, and total cholesterol. The Kaplan-Meier method and Cox regression analysis were performed to evaluate the relationship between the score and disease-free survival, overall survival, and cancer-related survival. A total of 260 patients were selected for the study, though this was reduced to 154 after propensity score matching. Post-propensity Kaplan-Meier analysis showed a significant correlation between the Naples Prognostic Score, overall survival (p = 0.018), and cancer-related survival (p = 0.007). Multivariate Cox regression analysis further validated the score as an independent prognostic indicator for both types of survival (p = 0.007 and p = 0.010, respectively). The Naples Prognostic Score proved to be an easily achievable prognostic factor of long-term survival in patients with non-small cell lung cancer after surgical treatment.