Anti-cholinergic load, health care utilization, and survival in people with advanced cancer: a pilot study.

INTRODUCTION: Anti-cholinergic medications have been associated with increased risks of cognitive impairment, premature mortality and increased risk of hospitalisation. Anti-cholinergic load associated with medication increases as death approaches in those with advanced cancer, yet little is known about associated adverse outcomes in this setting. METHODS: A substudy of 112 participants in a randomised control trial who had cancer and an Australia modified Karnofsky Performance Scale (AKPS) score (AKPS) of 60 or above, explored survival and health service utilisation; with anti-cholinergic load calculated using the Clinician Rated Anti-cholinergic Scale (modified version) longitudinally to death. A standardised starting point for prospectively calculating survival was an AKPS of 60 or above. RESULTS: Baseline entry to the sub-study was a mean 62 +/- 81 days (median 37, range 1-588) days before death (survival), with mean of 4.8 (median 3, SD 4.18, range 1 - 24) study assessments in this time period. Participants spent 22% of time as an inpatient. There was no significant association between anti-cholinergic score and time spent as an inpatient (adjusted for survival time) (p = 0.94); or survival time. DISCUSSION: No association between anti-cholinergic load and survival or time spent as an inpatient was seen. Future studies need to include cognitively impaired populations where the risks of symptomatic deterioration may be more substantial.

Knowledge Modeling for The Outcome of Brain Stereotactic Radiosurgery

Purpose: To build a model that will predict the survival time for patients that were treated with stereotactic radiosurgery for brain metastases using support vector machine (SVM) regression.

Methods and Materials: This study utilized data from 481 patients, which were equally divided into training and validation datasets randomly. The SVM model used a Gaussian RBF function, along with various parameters, such as the size of the epsilon insensitive region and the cost parameter (C) that are used to control the amount of error tolerated by the model. The predictor variables for the SVM model consisted of the actual survival time of the patient, the number of brain metastases, the graded prognostic assessment (GPA) and Karnofsky Performance Scale (KPS) scores, prescription dose, and the largest planning target volume (PTV). The response of the model is the survival time of the patient. The resulting survival time predictions were analyzed against the actual survival times by single parameter classification and two-parameter classification. The predicted mean survival times within each classification were compared with the actual values to obtain the confidence interval associated with the model’s predictions. In addition to visualizing the data on plots using the means and error bars, the correlation coefficients between the actual and predicted means of the survival times were calculated during each step of the classification.

Results: The number of metastases and KPS scores, were consistently shown to be the strongest predictors in the single parameter classification, and were subsequently used as first classifiers in the two-parameter classification. When the survival times were analyzed with the number of metastases as the first classifier, the best correlation was obtained for patients with 3 metastases, while patients with 4 or 5 metastases had significantly worse results. When the KPS score was used as the first classifier, patients with a KPS score of 60 and 90/100 had similar strong correlation results. These mixed results are likely due to the limited data available for patients with more than 3 metastases or KPS scores of 60 or less.

Conclusions: The number of metastases and the KPS score both showed to be strong predictors of patient survival time. The model was less accurate for patients with more metastases and certain KPS scores due to the lack of training data.

Metabolism Regulates the Fate and Function of T Lymphocytes

Proper balancing of the activities of metabolic pathways to meet the challenge of providing necessary products for biosynthetic and energy demands of the cell is a key requirement for maintaining cell viability and allowing for cell proliferation. Cell metabolism has been found to play a crucial role in numerous cell settings, including in the cells of the immune system, where a successful immune response requires rapid proliferation and successful clearance of dangerous pathogens followed by resolution of the immune response. Additionally, it is now well known that cell metabolism is markedly altered from normal cells in the setting of cancer, where tumor cells rapidly and persistently proliferate. In both settings, alterations to the metabolic profile of the cells play important roles in promoting cell proliferation and survival.

It has long been known that many types of tumor cells and actively proliferating immune cells adopt a metabolic phenotype of aerobic glycolysis, whereby the cell, even under normoxic conditions, imports large amounts of glucose and fluxes it through the glycolytic pathway and produces lactate. However, the metabolic programs utilized by various immune cell subsets have only recently begun to be explored in detail, and the metabolic features and pathways influencing cell metabolism in tumor cells in vivo have not been studied in detail. The work presented here examines the role of metabolism in regulating the function of an important subset of the immune system, the regulatory T cell (Treg) and the role and regulation of metabolism in the context of malignant T cell acute lymphoblastic leukemia (T-ALL). We show that Treg cells, in order to properly function to suppress auto-inflammatory disease, adopt a metabolic program that is characterized by oxidative metabolism and active suppression of anabolic signaling and metabolic pathways. We found that the transcription factor FoxP3, which is highly expressed in Treg cells, drives this phenotype. Perturbing the metabolic phenotype of Treg cells by enforcing increased glycolysis or driving proliferation and anabolic signaling through inflammatory signaling pathways results in a reduction in suppressive function of Tregs.

In our studies focused on the metabolism of T-ALL, we observed that while T-ALL cells use and require aerobic glycolysis, the glycolytic metabolism of T-ALL is restrained compared to that of an antigen activated T cell. The metabolism of T-ALL is instead balanced, with mitochondrial metabolism also being increased. We observed that the pro-anabolic growth mTORC1 signaling pathway was limited in primary T-ALL cells as a result of AMPK pathway activity. AMPK pathway signaling was elevated as a result of oncogene induced metabolic stress. AMPK played a key role in the regulation of T-ALL cell metabolism, as genetic deletion of AMPK in an in vivo murine model of T-ALL resulted in increased glycolysis and anabolic metabolism, yet paradoxically increased cell death and increased mouse survival time. AMPK acts to promote mitochondrial oxidative metabolism in T-ALL through the regulation of Complex I activity, and loss of AMPK reduced mitochondrial oxidative metabolism and resulted in increased metabolic stress. Confirming a role for mitochondrial metabolism in T-ALL, we observed that the direct pharmacological inhibition of Complex I also resulted in a rapid loss of T-ALL cell viability in vitro and in vivo. Taken together, this work establishes an important role for AMPK to both balance the metabolic pathways utilized by T-ALL to allow for cell proliferation and to also promote tumor cell viability by controlling metabolic stress.

Overall, this work demonstrates the importance of the proper coupling of metabolic pathway activity with the function needs of particular types of immune cells. We show that Treg cells, which mainly act to keep immune responses well regulated, adopt a metabolic program where glycolytic metabolism is actively repressed, while oxidative metabolism is promoted. In the setting of malignant T-ALL cells, metabolic activity is surprisingly balanced, with both glycolysis and mitochondrial oxidative metabolism being utilized. In both cases, altering the metabolic balance towards glycolytic metabolism results in negative outcomes for the cell, with decreased Treg functionality and increased metabolic stress in T-ALL. In both cases, this work has generated a new understanding of how metabolism couples to immune cell function, and may allow for selective targeting of immune cell subsets by the specific targeting of metabolic pathways.

Daily intake of antioxidants in relation to survival among adult patients diagnosed with malignant glioma.

BACKGROUND: Malignant glioma is a rare cancer with poor survival. The influence of diet and antioxidant intake on glioma survival is not well understood. The current study examines the association between antioxidant intake and survival after glioma diagnosis. METHODS: Adult patients diagnosed with malignant glioma during 1991-1994 and 1997-2001 were enrolled in a population-based study. Diagnosis was confirmed by review of pathology specimens. A modified food-frequency questionnaire interview was completed by each glioma patient or a designated proxy. Intake of each food item was converted to grams consumed/day. From this nutrient database, 16 antioxidants, calcium, a total antioxidant index and 3 macronutrients were available for survival analysis. Cox regression estimated mortality hazard ratios associated with each nutrient and the antioxidant index adjusting for potential confounders. Nutrient values were categorized into tertiles. Models were stratified by histology (Grades II, III, and IV) and conducted for all (including proxy) subjects and for a subset of self-reported subjects. RESULTS: Geometric mean values for 11 fat-soluble and 6 water-soluble individual antioxidants, antioxidant index and 3 macronutrients were virtually the same when comparing all cases (n=748) to self-reported cases only (n=450). For patients diagnosed with Grade II and Grade III histology, moderate (915.8-2118.3 mcg) intake of fat-soluble lycopene was associated with poorer survival when compared to low intake (0.0-914.8 mcg), for self-reported cases only. High intake of vitamin E and moderate/high intake of secoisolariciresinol among Grade III patients indicated greater survival for all cases. In Grade IV patients, moderate/high intake of cryptoxanthin and high intake of secoisolariciresinol were associated with poorer survival among all cases. Among Grade II patients, moderate intake of water-soluble folate was associated with greater survival for all cases; high intake of vitamin C and genistein and the highest level of the antioxidant index were associated with poorer survival for all cases. CONCLUSIONS: The associations observed in our study suggest that the influence of some antioxidants on survival following a diagnosis of malignant glioma are inconsistent and vary by histology group. Further research in a large sample of glioma patients is needed to confirm/refute our results.

Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates.

MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.