Age-adjusted Charlson comorbidity index in recurrent glioblastoma: a new prognostic factor?

Optimizing Prediction of In-Hospital Mortality in Elderly Patients With Acute Myocardial Infarction: A Nomogram Approach Using the Age-Adjusted Charlson Comorbidity Index Score

BACKGROUND

To study the age-adjusted Charlson comorbidity index (ACCI) scale, which is a comprehensive quantification of multimorbidity coexistence, for the assessment of the risk of acute myocardial infarction death in elderly people.

METHODS AND RESULTS

A total of 502 older patients with acute myocardial infarction were studied at Qilu Hospital from September 2017 to March 2022. They were categorized on the basis of ACCI into low (≤5), intermediate (6, 7), and high (≥8) risk groups. Hospitalization duration was observed, with death as the end point. least absolute shrinkage and selection operator regression was used to screen variables, 10-fold cross-validation was performed to validate the screened variables, a Cox regression nomogram predicting the risk of patient death was prepared, hazard ratio with 95% CI was calculated, a nomogram calibration curve was constructed, and a receiver operating characteristic curve, decision curve analysis, and a clinical impact curve were established. From 62 potential factors in a least absolute shrinkage and selection operator regression, 12 were selected via 10-fold cross-validation. Retain variables with significant statistical differences in the Cox regression. A nomogram of the risk of death from acute infarction was constructed, and risk factors included ventricular tachycardia/fibrillation, atrial fibrillation, nicorandil, angiotensin-converting enzyme inhibitors/angiotensin-converting enzyme inhibitors, β blockers, and ACCI score, carbon dioxide combining power, and blood calcium concentration.

CONCLUSIONS

The ACCI score effectively assesses multimorbidity in the older patients. As ACCI rises, the death risk from acute myocardial infarction grows. The study's nomogram is valid and clinically applicable.

Personalized prognosis stratification of newly diagnosed glioblastoma applying a statistical decision tree model

PURPOSE

Glioblastoma (GBM) is the most frequent glioma in adults with a high treatment resistance resulting into limited survival. The individual prognosis varies depending on individual prognostic factors, that must be considered while counseling patients with newly diagnosed GBM. The aim of this study was to elaborate a risk stratification algorithm based on reliable prognostic factors to facilitate a personalized prognosis estimation early on after diagnosis.

METHODS

A consecutive patient cohort with confirmed GBM treated between 2010 and 2021 was retrospectively analyzed. Clinical, radiological, and molecular parameters were assessed and included in the analysis. Overall survival (OS) was the primary outcome parameter. After identifying the strongest prognostic factors, a risk stratification algorithm was elaborated with estimated odds of survival.

RESULTS

A total of 462 GBM patients were analyzed. The strongest prognostic factors were Charlson Comorbidity Index (CCI), extent of tumor resection, and adjuvant treatment. Patients with CCI ≤ 1 receiving tumor resection had the highest survival odds (88% for 10 months). On the contrary, patients with CCI > 3 receiving no adjuvant treatment had the lowest survival odds (0% for 10 months). The 10-months survival rate in patients with CCI > 3 receiving adjuvant treatment was 56% for patients younger than 70 years and 22% for patients older than 70 years.

CONCLUSION

A risk stratification algorithm based on significant prognostic factors allowed a personalized early prognosis estimation at the time of GBM diagnosis, that can contribute to a more personalized patient counseling.

Network analysis of symptoms, physiological, psychological and environmental risk factors based on unpleasant symptom theory in patients with chronic heart failure

BACKGROUND

Somatic symptoms and related factors in patients with chronic heart failure have been extensively researched. However, more insight into the complex interconnections among these constructs is needed, as most studies focus on them independently from each other.

AIMS

The aim of this study is to gain a comprehensive understanding of how somatic symptoms and related factors are interconnected among patients with chronic heart failure.

METHODS

A total of 379 patients were enrolled. Network analysis was used to explore the interconnections among the somatic symptoms and related risk factors.

RESULTS

The four core symptoms of chronic heart failure were daytime dyspnea, dyspnea when lying down, fatigue and difficulty sleeping. Within the network, the edge weights of depression-anxiety, subjective social support-objective social support, and subjective social support-social support availability were more significant than others. Among physiological, psychological and environmental factors, the edge weights of NYHA-dyspnea, depression-difficulty sleeping, and social support availability-dyspnea when lying down were more significant than others. Depression and anxiety had the highest centrality, indicating stronger and closer connections with other nodes.

CONCLUSIONS

Psychological and environmental factors stood out in the network, suggesting the potential value of interventions targeting these factors to improve overall health.

Glioblastoma and Internal Carotid Artery Calcium Score: A Possible Novel Prognostic Partnership?

Purpose: Clinical evidence suggests an association between comorbidities and outcome in patients with glioblastoma (GBM). We hypothesised that the internal carotid artery (ICA) calcium score could represent a promising prognostic biomarker in a competing risk analysis in patients diagnosed with GBM. Methods: We validated the use of the ICA calcium score as a surrogate marker of the coronary calcium score in 32 patients with lung cancer. Subsequently, we assessed the impact of the ICA calcium score on overall survival in GBM patients treated with radio-chemotherapy. Results: We analysed 50 GBM patients. At the univariate analysis, methyl-guanine-methyltransferase gene (MGMT) promoter methylation (p = 0.048), gross total tumour resection (p = 0.017), and calcium score (p = 0.011) were significant prognostic predictors in patients with GBM. These three variables also maintained statistical significance in the multivariate analysis. Conclusions: the ICA calcium score could be a promising prognostic biomarker in GBM patients.

The Hospital Frailty Risk Score Independently Predicts Postoperative Outcomes in Glioblastoma Patients

OBJECTIVE

The Hospital Frailty Risk Score (HFRS) is a tool for quantifying patient frailty using International Classification of Diseases, Tenth Revision codes. This study aimed to determine the utility of the HFRS in predicting surgical outcomes after resection of glioblastoma (GBM) and compare its prognostic ability with other validated indices such as American Society of Anesthesiologists score and Charlson Comorbidity Index.

METHODS

A retrospective analysis was conducted using a GBM patient database (2017-2019) at a single institution. HFRS was calculated using International Classification of Diseases, Tenth Revision codes. Bivariate logistic regression was used to model prognostic ability of each frailty index, and model discrimination was assessed using area under the receiver operating characteristic curve. Multivariate linear and logistic regression models were used to assess for significant associations between HFRS and continuous and binary postoperative outcomes, respectively.

RESULTS

The study included 263 patients with GBM. The HFRS had a significantly greater area under the receiver operating characteristic curve compared with American Society of Anesthesiologists score (P = 0.016) and Charlson Comorbidity Index (P = 0.037) for predicting 30-day readmission. On multivariate analysis, the HFRS was significantly and independently associated with hospital length of stay (P = 0.0038), nonroutine discharge (P = 0.018), and 30-day readmission (P = 0.0051).

CONCLUSIONS

The HFRS has utility in predicting postoperative outcomes for patients with GBM and more effectively predicts 30-day readmission than other frailty indices. The HFRS may be used as a tool for optimizing clinical decision making to reduce adverse postoperative outcomes in patients with GBM.

Brain metastases in the elderly – Impact of residual tumor volume on overall survival

Background

Due to demographic changes and an increased incidence of cancer with age, the number of patients with brain metastases (BMs) constantly increases, especially among the elderly. Novel systemic therapies, such as immunotherapy, have led to improved survival in recent years, but intracranial tumor progression may occur independently of a systemically effective therapy. Despite the growing number of geriatric patients, they are often overlooked in clinical trials, and there is no consensus on the impact of BM resection on survival.

Objectives

The aim of this study was to analyze the impact of resection and residual tumor volume on clinical outcome and overall survival (OS) in elderly patients suffering from BM.

Methods

Patients ≥ 75 years who had surgery for BM between April 2007 and January 2020 were retrospectively included. Residual tumor burden (RTB) was determined by segmentation of early postoperative brain MRI (72 h). Contrast-enhancing tumor subvolumes were segmented manually. “Postoperative tumor volume” refers to the targeted BMs. Impact of preoperative Karnofsky performance status scale (KPSS), age, sex and RTB on OS was analyzed. Survival analyses were performed using Kaplan-Meier estimates for the univariate analysis and the Cox regression proportional hazards model for the multivariate analysis.

Results

One hundred and one patients were included. Median age at surgery was 78 years (IQR 76-81). Sixty-two patients (61%) had a single BM; 16 patients (16%) had two BMs; 13 patients (13%) had three BMs; and 10 patients (10%) had more than three BMs. Median preoperative tumor burden was 10.3 cm3 (IQR 5–25 cm3), and postoperative tumor burden was 0 cm3 (IQR 0–1.1 cm3). Complete cytoreduction (RTB = 0) was achieved in 52 patients (52%). Complete resection of the targeted metastases was achieved in 78 patients (78%). Median OS was 7 months (IQR 2–11). In univariate analysis, high preoperative KPSS (HR 0.986, 95% CI 0.973–0.998, p = 0.026) and small postoperative tumor burden (HR 1.025, 95% CI 1.002–1.047, p = 0.029) were significantly associated with prolonged OS. Patients with RTB = 0 survived significantly longer than those with residual tumor did (12 [IQR 5–19] vs. 5 [IQR 3–7] months, p = 0.007). Furthermore, prolongation of survival was significantly associated with surgery in patients with favorable KPSS, with an adjusted HR of 0.986 (p = 0.026). However, there were no significances regarding age.

Conclusions

RTB is a strong predictor for prolonged OS, regardless of age or cancer type. Postoperative MRI should confirm the extent of resection, as intraoperative estimates do not warrant a complete resection. It is crucial to aim for maximal cytoreduction to achieve the best long-term outcomes for these patients, despite the fact the patients are advanced in age.

Cervical body composition on radiotherapy planning computed tomography scans predicts overall survival in glioblastoma patients

Background and purpose

Glioblastoma (GBM) patients face a strongly unfavorable prognosis despite multimodal therapy regimens. However, individualized mortality prediction remains imprecise. Harnessing routine radiation planning cranial computed tomography (CT) scans, we assessed cervical body composition measures as novel biomarkers for overall survival (OS) in GBM patients.

Materials and methods

We performed threshold-based semi-automated quantification of muscle and subcutaneous fat cross-sectional area (CSA) at the levels of the first and second cervical vertebral body. First, we tested this method's validity by correlating cervical measures to established abdominal body composition in an open-source whole-body CT cohort. We then identified consecutive patients undergoing radiation planning for recent GBM diagnosis at our institution from 2010 to 2020 and quantified cervical body composition on radiation planning CT scans. Finally, we performed univariable and multivariable time-to-event analyses, adjusting for age, sex, body mass index, comorbidities, performance status, extent of surgical resection, extent of tumor at diagnosis, and MGMT methylation.

Results

Cervical body composition measurements were well-correlated with established abdominal markers (Spearman's rho greater than 0.68 in all cases). Subsequently, we included 324 GBM patients in our study cohort (median age 63 years, 60.8% male). 293 (90.4%) patients died during follow-up. Median survival time was 13 months. Patients with below-average muscle CSA or above-average fat CSA demonstrated shorter survival. In multivariable analyses, continuous cervical muscle measurements remained independently associated with OS.

Conclusion

This exploratory study establishes novel cervical body composition measures routinely available on cranial radiation planning CT scans and confirms their association with OS in patients diagnosed with GBM.

Diabetes Mellitus Management in the Context of Cranial Tumors

The study of the relationship between cancer and diabetes mellitus (DM) has been under investigation for many decades. Particularly in the field of neurology and neurosurgery, increasing emphasis has been put on the examination of comorbid DM in patients with cranial tumors. Namely, as the most common and invasive type of malignant adult brain tumor, glioblastoma (GBS) has been the focus of said research. Several mechanisms have been described in the attempt to elucidate the underlying association between DM and GBS, with the metabolic phenomenon known as the Warburg effect and its consequential downstream effects serving as the resounding culprits in recent literature. Since the effect seen in cancers like GBS exploits an upregulated form of aerobic glycolysis, the role of a sequela of DM, known as hyperglycemia, will be investigated. In particular, in the treatment of GBS, surgical resection and subsequent chemotherapy and/or radiotherapy are used in conjunction with corticosteroid therapy, the latter of which has been linked to hyperglycemia. Unsurprisingly, comorbid DM patients are significantly susceptible to this disposition. Further, this fact is reflected in recent literature that demonstrates the impact of hyperglycemia on cancer advancement and patient outcomes in several preclinical and clinical studies. Thus, this review will aim to underline the significance of diabetes and glycemic control via standard-of-care treatments such as metformin administration, as well as to describe emerging treatments such as the signaling modulation of insulin-like growth factor and the employment of the ketogenic diet.