TNM cancer staging: can it help develop a novel staging system for type 2 diabetes?

Abstract: Type 2 diabetes (DM2) constitutes 90%–95% of the diabetes cases and is increasing at an alarming rate in the world. The Centers for Disease Control and Prevention (CDC) esti- mates that more than 29 million people in the United States have diabetes, which often causes mortality from macrovascular complications and morbidity from microvascular complications. Despite these troubling facts, there is currently no widely accepted staging system for DM2 like there is for cancer. TNM oncologic staging has taken a complex condition like cancer and conveyed likelihood of survival in simple alpha-numeric terms that both patients and providers can understand. Oncology is now entering the era of precision medicine where cancer treatment is increasingly being tailored to each patient’s cancer. In contrast, DM2 lacks a staging system and remains a largely invisible disease even though it kills more Americans and costs more to treat than cancer. Is a comparable staging system for DM2 possible? We propose the Diabetes Staging System for DM2 that utilizes macrovascular events, microvascular complications, estimated glomerular filtration rate (GFR), and hemoglobin A1C to stage DM2

Clinical Associations of an Updated Medication Effect Score for Measuring Diabetes Treatment Intensity

OBJECTIVES: The medication effect score reflects overall intensity of a diabetes regimen by consolidating dosage and potency of agents used. Little is understood regarding how medication intensity relates to clinical factors. We updated the medication effect score to account for newer agents and explored associations between medication effect score and patient-level clinical factors. METHODS: Cross-sectional analysis of baseline data from a randomized controlled trial involving 263 Veterans with type 2 diabetes and hemoglobin AIc levels ≥8.0% (≥7.5% if under age 50). Medication effect score was calculated for all patients at baseline, alongside additional measures including demographics, comorbid illnesses, hemoglobin AIc, and self-reported psychosocial factors. We used multivariable regression to explore associations between baseline medication effect score and patient-level clinical factors. RESULTS: Our sample had a mean age of 60.7 (SD = 8.2) years, was 89.4% male, and 57.4% non-White. Older age and younger onset of diabetes were associated with a higher medication effect score, as was higher body mass index. Higher medication effect score was significantly associated with medication nonadherence, although not with hemoglobin AIc, self-reported hypoglycemia, diabetes-related distress, or depression. DISCUSSION: We observed several expected associations between an updated medication effect score and patient-level clinical factors. These associations support the medication effect score as an appropriate measure of diabetes regimen intensity in clinical and research contexts

TNM cancer staging: can it help develop a novel staging system for type 2 diabetes?

Type 2 diabetes (DM2) constitutes 90%-95% of the diabetes cases and is increasing at an alarming rate in the world. The Centers for Disease Control and Prevention (CDC) estimates that more than 29 million people in the United States have diabetes , which often causes mortality from macrovascular complications and morbidity from microvascular complications. Despite these troubling facts , there is currently no widely accepted staging system for DM2 like there is for cancer. TNM oncologic staging has taken a complex condition like cancer and conveyed likelihood of survival in simple alpha-numeric terms that both patients and providers can understand. Oncology is now entering the era of precision medicine where cancer treatment is increasingly being tailored to each patient's cancer. In contrast , DM2 lacks a staging system and remains a largely invisible disease even though it kills more Americans and costs more to treat than cancer. Is a comparable staging system for DM2 possible? We propose the Diabetes Staging System for DM2 that utilizes macrovascular events , microvascular complications , estimated glomerular filtration rate (GFR) , and hemoglobin A1C to stage DM2. filtration rat

TNM cancer staging: can it help develop a novel staging system for type 2 diabetes?

Abstract: Type 2 diabetes (DM2) constitutes 90%--95% of the diabetes cases and is increasing at an alarming rate in the world. The Centers for Disease Control and Prevention (CDC) esti- mates that more than 29 million people in the United States have diabetes, which often causes mortality from macrovascular complications and morbidity from microvascular complications. Despite these troubling facts, there is currently no widely accepted staging system for DM2 like there is for cancer. TNM oncologic staging has taken a complex condition like cancer and conveyed likelihood of survival in simple alpha-numeric terms that both patients and providers can understand. Oncology is now entering the era of precision medicine where cancer treatment is increasingly being tailored to each patient"s cancer. In contrast, DM2 lacks a staging system and remains a largely invisible disease even though it kills more Americans and costs more to treat than cancer. Is a comparable staging system for DM2 possible? We propose the Diabetes Staging System for DM2 that utilizes macrovascular events, microvascular complications, estimated glomerular filtration rate (GFR), and hemoglobin A1C to stage DM2

Transcriptomic characterization of signaling pathways associated with osteoblastic differentiation of MC-3T3E1 cells.

Bone remodeling involves the coordinated actions of osteoclasts, which resorb the calcified bony matrix, and osteoblasts, which refill erosion pits created by osteoclasts to restore skeletal integrity and adapt to changes in mechanical load. Osteoblasts are derived from pluripotent mesenchymal stem cell precursors, which undergo differentiation under the influence of a host of local and environmental cues. To characterize the autocrine/paracrine signaling networks associated with osteoblast maturation and function, we performed gene network analysis using complementary "agnostic" DNA microarray and "targeted" NanoString nCounter datasets derived from murine MC3T3-E1 cells induced to undergo synchronized osteoblastic differentiation in vitro. Pairwise datasets representing changes in gene expression associated with growth arrest (day 2 to 5 in culture), differentiation (day 5 to 10 in culture), and osteoblast maturation (day 10 to 28 in culture) were analyzed using Ingenuity Systems Pathways Analysis to generate predictions about signaling pathway activity based on the temporal sequence of changes in target gene expression. Our data indicate that some pathways involved in osteoblast differentiation, e.g. Wnt/β-catenin signaling, are most active early in the process, while others, e.g. TGFβ/BMP, cytokine/JAK-STAT and TNFα/RANKL signaling, increase in activity as differentiation progresses. Collectively, these pathways contribute to the sequential expression of genes involved in the synthesis and mineralization of extracellular matrix. These results provide insight into the temporal coordination and complex interplay between signaling networks controlling gene expression during osteoblast differentiation. A more complete understanding of these processes may aid the discovery of novel methods to promote osteoblast development for the treatment of conditions characterized by low bone mineral density