Nuclear factor-κB activation in perihematomal brain tissue correlates with outcome in patients with intracerebral hemorrhage.

BACKGROUND: Nuclear factor-κB (NF-κB) plays an important role in the inflammatory response after intracerebral hemorrhage (ICH). We therefore proposed that NF-κB activation in perihematomal brain tissue might correlate with clinical outcome in patients with ICH. To confirm this, we studied clinical data of 45 patients with ICH and NF-κB activation in perihematomal brain tissue and analyzed predictors of clinical outcome as well as the predictive value of NF-κB activation. METHODS: Forty-five patients with spontaneous basal ganglia hemorrhage were prospectively investigated. The clinical data were collected, which include demographics, alcohol and tobacco abuse, stroke risk factors, neuroimaging variables at presentation, Glasgow Coma Scale (GCS) at admission, number of days in hospital, mechanical ventilation, pneumonia, and outcome. Clinical outcome was assessed by the modified Rankin Scale at 6 months after ICH. Perihematomal brain tissue was collected, and NF-κB activation was detected using immunohistochemistry. Univariate analysis and multivariate logistic regression analysis were performed to determine predictors of the poor outcome. RESULTS: Immunohistochemical detection showed that NF-κB p65 was expressed in the nuclei of neurons and glial cells in all patients. The number of nuclear NF-κB p65-positive cells was 54 ± 21. Six months after ICH, 18 (40%) patients achieved a favorable functional outcome (mRS ≤ 3) while 27 (60%) had a poor functional outcome (mRS 4 to 6). In univariate analysis, predictors of poor functional outcome were lower GCS score on admission (P = 0.004), larger hematoma volume (P = 0.004), intraventricular extension (P = 0.047), midline shift (P = 0.005), NF-κB activation (P < 0.0001), mechanical ventilation (P = 0.018), and co-morbidity with pneumonia (P = 0.002). In multivariate logistic regression analysis, NF-κB activation was the only independent predictor of poor outcome at 6 months after ICH. CONCLUSIONS: NF-κB activation is closely related to clinical outcome 6 months after ICH in humans. Therefore, it could be useful to predict prognosis of ICH accurately and should be further evaluated as a target for therapeutic strategies of ICH in the future.

Preoperative albumin-to-globulin ratio and prognostic nutrition index predict prognosis for glioblastoma.

OBJECTIVE: Impaired immunonutritional status has disadvantageous effects on outcomes for cancer patients. Preoperative albumin-to-globulin ratio (AGR) and the prognostic nutrition index (PNI) have been used as prognostic factors in various cancers. We aimed to evaluate the clinical significance of the AGR and PNI in glioblastoma. MATERIALS AND METHODS: This retrospective analysis involved 166 patients. Demographic, clinical, and laboratory data were collected. AGR and the PNI were calculated as AGR = albumin/(total serum protein - albumin) and PNI = albumin (g/L) + 5 × total lymphocyte count (109/L). Overall survival (OS) was estimated by Kaplan-Meier analysis. Receiver-operating characteristic analysis was used to assess the predictive ability of AGR and the PNI. Cox proportional-hazard models estimating hazard ratios (HRs) and 95% confidence intervals (CIs) were used for univariable and multivariable survival analyses. RESULTS: The cutoff values of AGR and PNI were 1.75 and 48. OS was enhanced, with high AGR (>1.75) and the PNI (>48) (P<0.001 for both). Areas under the receiver-operating characteristic curve for AGR and the PNI were 0.68 and 0.631 for 1-year survival and 0.651 and 0.656 for 2-year survival (P<0.05 for all), respectively. On multivariable analyses, both AGR and the PNI were independent predictors of OS (AGR, HR 0.785, 95% CI 0.357-0.979 [P=0.04]; PNI, HR 0.757, 95% CI 0.378-0.985 [P=0.039]). On subgroup analysis, AGR and the PNI were significant prognostic factors for OS in patients with adjuvant therapy (AGR P<0.001; PNI P=0.001). CONCLUSION: Preoperative AGR and the PNI may be easy-to-perform and inexpensive indices for predicting OS with glioblastoma. AGR and the PNI could also help in developing good adjuvant-therapy schedules.