Prognostic nutritional index and systemic immune-inflammation index are prognostic biomarkers for non-small-cell lung cancer brain metastases

Prognostic significance of systemic immune inflammatory index in NSCLC: a meta-analysis

Aim: The aim of this meta-analysis was to investigate the relationship between the baseline systemic immune inflammatory index (SII) and prognosis in patients with NSCLC. Materials & methods: The relation between pretreatment SII and overall survival, disease-free survival, cancer-specific survival, progression-free survival and recurrence-free survival in NSCLC patients was analyzed combined with hazard ratio and 95% CI. Results: The results showed that high SII was significantly correlated with overall survival and progression-free survival of NSCLC patients, but not with disease-free survival, cancer-specific survival and recurrence-free survival. Conclusion: The study suggests that a higher SII has association with worse prognosis in NSCLC patients. PROSPERO registration number: CRD42022336270.

Surgical excision and radiotherapy for brain metastasis from colorectal cancer: How frailty and comorbidity indices influence outcome

The incidence of brain metastasis (BM) from colorectal cancer (CRC) is increasing. This study aims to identify the clinical prognosticators and evaluate the prognostic validity of common comorbidity indices in patients with BM from CRC. This retrospective single-center study analyzed 93 patients with BM from CRC who received surgical excision and/or radiotherapy. The clinical characteristics and prognostic indices including the 5-item modified frailty index (mFI-5) and prognostic nutritional index (PNI) were calculated from the collected patient data and analyzed. In this study, 66 (71.0%), 10 (10.8%), and 17 (18.3%) patients received whole-brain radiotherapy (WBRT) alone, surgery alone, and surgery plus WBRT, respectively. The median survival of all patients was 3.98 months (IQR: 1.74-7.99). The 2- and 3-year survival rates were 7.4% and 3.7%, respectively. Controlled primary tumor (p = 0.048), solitary BM (p = 0.001), surgery + radiation (p < 0.001), and greater PNI (p = 0.001) were independent predictors of favorable survival. In surgically treated patients, uncontrolled primary tumor (p = 0.006), presence of multiple BM (p < 0.001), and MFI-5 ≥ 2 (p = 0.038) were independent prognosticators. For patients who received WBRT, the presence of two (p = 0.004) or multiple (p < 0.001) BM and PNI (p < 0.001) were independent survival predictors MFI-5, multiple BM, and the status of the primary tumor were independent prognosticators for patients who underwent surgery for CRCBM. For patients who received WBRT, the PNI and the number of BM were independent survival predictors.

Prognostic Significance of the Cachexia Index in Patients with Non-Small-Cell Lung Cancer and Brain Metastases after Stereotactic Radiotherapy

Background

The cachexia index (CXI) has been proposed as a novel biomarker of cancer cachexia. We aimed to investigate the association between CXI and survival outcomes after stereotactic radiotherapy (SRT) in patients with non-small cell lung cancer (NSCLC) and brain metastases.

Methods

Data from 145 patients with NSCLC, who underwent SRT for brain metastases between April 2016 and August 2020, were retrospectively analyzed. Cachexia index was calculated as skeletal muscle index (SMI) × serum albumin level/neutrophil-to-lymphocyte ratio, whereas SMI was calculated from computed tomography images captured at the L1 level. Kaplan-Meier curves and Cox proportional hazards models were used to assess progression-free survival (PFS) and overall survival (OS). The prognostic values of CXI and other cachexia biomarkers were assessed using receiver operating characteristic (ROC) curve analysis.

Results

Lower pretreatment CXI (<30.8) was significantly associated with older age (P = .039), lower Karnofsky performance score (P = .009), and a high likelihood of extracranial metastases (P = .001). Patients with a lower pretreatment CXI had a significantly shorter PFS and OS than those with a higher CXI (P < .001). Multivariate analysis revealed that pretreatment CXI was an independent risk factor for both PFS, hazard ratio (HR) = 2.375; 95% confidence interval (CI) = 1.610-3.504; P < .001, and OS, HR = 2.340; 95% CI = 1.562-3.505; P < .001. Compared with other biomarkers, pretreatment CXI had the highest area under the ROC curve value for prognostic assessment, reaching 0.734. Moreover, the loss of CXI was a strong risk factor for survival independent of pretreatment CXI (P = .011).

Conclusions

Cachexia index may serve as a clinically useful tool for predicting survival outcomes of patients with NSCLC and brain metastases who undergo SRT.

Exploring the Molecular Tumor Microenvironment and Translational Biomarkers in Brain Metastases of Non-Small-Cell Lung Cancer

Brain metastases represent a significant clinical challenge in the treatment of non-small-cell lung cancer (NSCLC), often leading to a severe decline in patient prognosis and survival. Recent advances in imaging and systemic treatments have increased the detection rates of brain metastases, yet clinical outcomes remain dismal due to the complexity of the metastatic tumor microenvironment (TME) and the lack of specific biomarkers for early detection and targeted therapy. The intricate interplay between NSCLC tumor cells and the surrounding TME in brain metastases is pivotal, influencing tumor progression, immune evasion, and response to therapy. This underscores the necessity for a deeper understanding of the molecular underpinnings of brain metastases, tumor microenvironment, and the identification of actionable biomarkers that can inform multimodal treatment approaches. The goal of this review is to synthesize current insights into the TME and elucidate molecular mechanisms in NSCLC brain metastases. Furthermore, we will explore the promising horizon of emerging biomarkers, both tissue- and liquid-based, that hold the potential to radically transform the treatment strategies and the enhancement of patient outcomes.

High prognostic nutritional index could be associated with improved survival in patients with brain metastases: a retrospective observational study

BACKGROUND

Prognostic nutritional index (PNI) is an indicator of immunonutritional status. The present study aimed to evaluate the association between PNI and overall survival in patients with brain metastases.

METHODS

A total of 257 patients with histologically confirmed brain metastasis who underwent surgery at our center between April 2011 and April 2021 were investigated retrospectively.Demographic, clinical, and radiologic data of all cases were extracted. Patients were divided into the low PNI group(PNI <45) (malnutrition status) and the high PNI group (PNI ≥45)(normal nutritional status). Survival analyses were performed using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate analyses were performed using the Cox proportional hazards method.

RESULTS

From the 257 cases of brain metastases, there were 148 (57.6%) males and 109 (42.4%) females. The mean age was 57.02 ± 8.7. The median overall survival was 13 months. The results of the multivariate Cox regression analyses showed primary cancer site (HR 2.196, 95% CI 1.988-6.52605, P = 0.000), the number of metastases (HR 1.829, 95% CI 1.380-2.872, P = 0.037), extracranial involvement (HR 2.186, 95% CI 1.213-4.171, P = 0.026), adjuvant radiotherapy (HR 2.823, 95% CI 1.187-5.415, P = 0.017) and PNI (HR 1.961, 95% CI 1.168-3.515, P = 0.021) as the independent predictors of overall survival in patients with brain metastases.

CONCLUSION

Our results suggest that PNI could be associated with survival in patients with brain metastases. Patients with a lower PNI had a significantly worse outcome in comparison with those with a higher PNI. Evaluation of PNI may provide additional prognostic information in patients with brain metastases.

The development and validation of a nomogram for predicting brain metastases after chemotherapy and radiotherapy in male small cell lung cancer patients with stage III

OBJECTIVE

The purpose of this research was to develop a model for brain metastasis (BM) in limited-stage small cell lung cancer (LS-SCLC) patients and to help in the early identification of high-risk patients and the selection of individualized therapies.

METHODS

Univariate and multivariate logic regression was applied to identify the independent risk factors of BM. A receiver operating curve (ROC) and nomogram for predicting the incidence of BM were then conducted based on the independent risk factors. The decision curve analysis (DCA) was performed to assess the clinical benefit of prediction model.

RESULTS

Univariate regression analysis showed that the CCRT, RT dose, PNI, LLR, and dNLR were the significant factors for the incidence of BM. Multivariate analysis showed that CCRT, RT dose, and PNI were independent risk factors of BM and were included in the nomogram model. The ROC curves revealed the area under the ROC (AUC) of the model was 0.764 (95% CI, 0.658-0.869), which was much higher than individual variable alone. The calibration curve revealed favorable consistency between the observed probability and predicted probability for BM in LS-SCLC patients. Finally, the DCA demonstrated that the nomogram provides a satisfactory positive net benefit across the majority of threshold probabilities.

CONCLUSIONS

In general, we established and verified a nomogram model that combines clinical variables and nutritional index characteristics to predict the incidence of BM in male SCLC patients with stage III. Since the model has high reliability and clinical applicability, it can provide clinicians with theoretical guidance and treatment strategy making.

Naples Prognostic Score as an Independent Predictor of Survival Outcomes for Resected Locally Advanced Non-Small Cell Lung Cancer Patients After Neoadjuvant Treatment

Background

The Naples Prognostic Score (NPS) can reflect patient's nutritional and inflammatory status, which is identified as a prognostic indicator for various malignant tumors. However, its significance in patients with resected locally advanced non-small cell lung cancer (LA-NSCLC) patients who receive neoadjuvant treatment remains unclear so far.

Methods

A total of 165 LA-NSCLC patients surgically treated from May 2012 to November 2017 were retrospectively investigated. The LA-NSCLC patients were divided into three groups according to NPS scores. The receiver operating curve (ROC) analysis was performed to reveal the discriminatory ability of NPS and other indicators for predicting the survival. The NPS and clinicopathological variables were further evaluated the prognostic value by univariate and multivariate Cox analysis.

Results

The NPS was related to age (P = 0.046), smoking history (P = 0.004), Eastern Cooperative Oncology Group (ECOG) score (P = 0.005), and adjuvant treatment (P = 0.017). Patients with high NPS scores had worse overall survival (OS) (group 1 vs 0, P = 0.006; group 2 vs 0, P < 0.001) and disease-free survival (DFS) (group 1 vs 0, P < 0.001; group 2 vs 0, P < 0.001). The ROC analysis demonstrated that NPS had better predictive ability than other prognostic indicators. Multivariate analysis revealed that NPS was independent prognostic indicator of OS (group 1 vs 0, hazard ratio [HR] =2.591, P = 0.023; group 2 vs 0, HR = 8.744, P = 0.001) and DFS (group 1 vs 0, HR =3.754, P < 0.001; group 2 vs 0, HR = 9.673, P < 0.001).

Conclusion

The NPS could be an independent prognostic indicator in patients with resected LA-NSCLC receiving neoadjuvant treatment and more reliable than the other nutritional and inflammatory indicators.

A novel quantitative prognostic model for initially diagnosed non-small cell lung cancer with brain metastases

Background

The prognosis of non-small cell lung cancer (NSCLC) with brain metastases (BMs) had been researched in some researches, but the combination of clinical characteristics and serum inflammatory indexes as a noninvasive and more accurate model has not been described.

Methods

We retrospectively screened patients with BMs at the initial diagnosis of NSCLC at Sun Yat-Sen University Cancer Center. LASSO-Cox regression analysis was used to establish a novel prognostic model for predicting OS based on blood biomarkers. The predictive accuracy and discriminative ability of the prognostic model was compared to Adjusted prognostic Analysis (APA), Recursive Partition Analysis (RPA), and Graded Prognostic Assessment (GPA) using concordance index (C-index), time-dependent receiver operating characteristic (td-ROC) curve, Decision Curve Analysis(DCA), net reclassification improvement index (NRI), and integrated discrimination improvement index (IDI).

Results

10-parameter signature's predictive model for the NSCLC patients with BMs was established according to the results of LASSO-Cox regression analysis. The C-index of the prognostic model to predict OS was 0.672 (95% CI = 0.609 ~ 0.736) which was significantly higher than APA,RPA and GPA. The td-ROC curve and DCA of the predictive model also demonstrated good predictive accuracy of OS compared to APA, RPA and GPA. Moreover, NRI and IDI analysis indicated that the prognostic model had improved prediction ability compared with APA, RPA and GPA.

Conclusion

The novel prognostic model demonstrated favorable performance than APA, RPA, and GPA for predicting OS in NSCLC patients with BMs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02671-2.