Clinical Variation Reduction in Propensity-matched Patients Treated for Malignant Pleural Effusion.

BACKGROUND: The potential advantages of clinical variation reduction are improved patient outcomes and cost reduction through optimizing and standardizing care. Malignant pleural effusion (MPE) is a common condition encountered by thoracic surgeons that has significant variation in cost and outcomes. The purpose of this investigation was to assess the opportunity of improving patient outcomes and reducing cost by using a standardized treatment algorithm based on evidenced-based care. METHODS: Patients treated for MPE using a standardized treatment algorithm at the study institution over a 2 year period were identified and propensity matched to MPE patients from 1 of 6 affiliated hospitals with comprehensive oncology and thoracic surgery services. Matched patients were treated at their physicians' discretion. Factors used in propensity matching were age, performance status, and tumor histology. The 2 cohorts were then compared for interventions, admissions and readmissions, morbidity, and pleural effusion-associated costs. Patients who desired only comfort or hospice care were excluded. RESULTS: From 2016 through 2018, 60 patients were treated using the standardized algorithm. These patients were propensity matched and the 2 cohorts compared. Patients treated with the algorithm experienced significantly fewer hospital admissions, readmissions, interventions, and costs while having a comparable procedural morbidity. CONCLUSIONS: An evidence-based treatment algorithm for MPE produces superior clinical outcomes to individualized therapy while significantly reducing the costs of care.

Plasma protein patterns as comprehensive indicators of health.

Proteins are effector molecules that mediate the functions of genes1,2 and modulate comorbidities3-10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12-16 coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check.

The Impact of the Glomerular Filtration Rate on the Human Plasma Proteome.

PURPOSE: The application of proteomics in chronic kidney disease (CKD) can potentially uncover biomarkers and pathways that are predictive of disease. EXPERIMENTAL DESIGN: Within this context, this study examines the relationship between the human plasma proteome and glomerular filtration rate (GFR) as measured by iohexol clearance in a cohort from Sweden (n = 389; GFR range: 8-100 mL min-1 /1.73 m2 ). A total of 2893 proteins are quantified using a modified aptamer assay. RESULTS: A large proportion of the proteome is associated with GFR, reinforcing the concept that CKD affects multiple physiological systems (individual protein-GFR correlations listed here). Of these, cystatin C shows the most significant correlation with GFR (rho = -0.85, p = 1.2 × 10-97 ), establishing strong validation for the use of this biomarker in CKD diagnostics. Among the other highly significant protein markers are insulin-like growth factor-binding protein 6, neuroblastoma suppressor of tumorigenicity 1, follistatin-related protein 3, trefoil factor 3, and beta-2 microglobulin. These proteins may indicate an imbalance in homeostasis across a variety of cellular processes, which may be underlying renal dysfunction. CONCLUSIONS AND CLINICAL RELEVANCE: Overall, this study represents the most extensive characterization of the plasma proteome and its relation to GFR to date, and suggests the diagnostic and prognostic value of proteomics for CKD across all stages.

Reduced MTHFD1 activity in male mice perturbs folate- and choline-dependent one-carbon metabolism as well as transsulfuration.

Impaired utilization of folate is caused by insufficient dietary intake and/or genetic variation and has been shown to prompt changes in related pathways, including choline and methionine metabolism. These pathways have been shown to be sensitive to variation within the Mthfd1 gene, which codes for a folate-metabolizing enzyme responsible for generating 1-carbon (1-C)-substituted folate derivatives. The Mthfd1(gt/+) mouse serves as a potential model of human Mthfd1 loss-of-function genetic variants that impair MTHFD1 function. This study investigated the effects of the Mthfd1(gt/+) genotype and folate intake on markers of choline, folate, methionine, and transsulfuration metabolism. Male Mthfd1(gt/+) and Mthfd1(+/+) mice were randomly assigned at weaning (3 wk of age) to either a control (2 mg/kg folic acid) or folate-deficient (0 mg/kg folic acid) diet for 5 wk. Mice were killed at 8 wk of age following 12 h of food deprivation; blood and liver samples were analyzed for choline, methionine, and transsulfuration biomarkers. Independent of folate intake, mice with the Mthfd1(gt/+) genotype had higher hepatic concentrations of choline (P = 0.005), betaine (P = 0.013), and dimethylglycine (P = 0.004) and lower hepatic concentrations of glycerophosphocholine (P = 0.002) relative to Mthfd1(+/+) mice. Mthfd1(gt/+) mice also had higher plasma concentrations of homocysteine (P = 0.0016) and cysteine (P < 0.001) as well as lower plasma concentrations of methionine (P = 0.0003) and cystathionine (P = 0.011). The metabolic alterations observed in Mthfd1(gt/+) mice indicate perturbed choline and folate-dependent 1-C metabolism and support the future use of Mthfd1(gt/+) mice as a tool to investigate the impact of impaired 1-C metabolism on disease outcomes.