Estimation of the optimal surrogate based on a randomized trial.

A common scientific problem is to determine a surrogate outcome for a long-term outcome so that future randomized studies can restrict themselves to only collecting the surrogate outcome. We consider the setting that we observe n independent and identically distributed observations of a random variable consisting of baseline covariates, a treatment, a vector of candidate surrogate outcomes at an intermediate time point, and the final outcome of interest at a final time point. We assume the treatment is randomized, conditional on the baseline covariates. The goal is to use these data to learn a most-promising surrogate for use in future trials for inference about a mean contrast treatment effect on the final outcome. We define an optimal surrogate for the current study as the function of the data generating distribution collected by the intermediate time point that satisfies the Prentice definition of a valid surrogate endpoint and that optimally predicts the final outcome: this optimal surrogate is an unknown parameter. We show that this optimal surrogate is a conditional mean and present super-learner and targeted super-learner based estimators, whose predicted outcomes are used as the surrogate in applications. We demonstrate a number of desirable properties of this optimal surrogate and its estimators, and study the methodology in simulations and an application to dengue vaccine efficacy trials.

A Two-Biomarker Model Predicts Mortality in the Critically Ill with Sepsis.

RATIONALE: Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge. OBJECTIVES: To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis. METHODS: A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas. MEASUREMENTS AND MAIN RESULTS: We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors. CONCLUSIONS: We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction.

Association of markers of endothelial dysregulation Ang1 and Ang2 with acute kidney injury in critically ill patients.

BACKGROUND: The role of endothelial dysregulation with acute kidney injury (AKI) in critically ill patients is unclear. METHODS: We retrospectively assessed the associations of AKI with biomarkers of endothelial function and inflammation among 948 subjects admitted to the intensive care unit (ICU) at Harborview Medical Center (Seattle, WA, USA). From plasma obtained within 24 h of enrollment, we measured angiopoietin (Ang)-1 and Ang-2 alongside biomarkers of inflammation, including interleukin (IL)-6, IL-17 and granulocyte colony-stimulating factor. We tested for associations between standardized concentrations of biomarkers and AKI, defined by serum creatinine, from ICU admission to up to 7 days later. RESULTS: All biomarkers of inflammation and endothelial dysfunction were associated with AKI. After adjustment for demographics, comorbidities, and IL-6 concentration, every standard deviation of Ang-1 concentration was associated with a 19 % lower risk of AKI (relative risk (RR) = 0.85, 95 % confidence interval (CI) 0.77-0.93, p < 0.001). Conversely, higher Ang-2 concentration was associated with higher risk of AKI (RR per standard deviation = 1.17, 95 % CI 1.13-1.22, p < 0.001). CONCLUSIONS: In critically ill patients, plasma concentration of the endothelial growth factors Ang-1 and Ang-2 are associated with AKI, independently of inflammation.

Biomarkers of Endothelial Activation Are Associated with Poor Outcome in Critical Illness.

BACKGROUND: Endothelial activation plays a role in organ dysfunction in the systemic inflammatory response syndrome (SIRS). Angiopoietin-1 (Ang-1) promotes vascular quiescence while angiopoietin-2 (Ang-2) mediates microvascular leak. Circulating levels of Ang-1 and Ang-2 in patients with SIRS could provide insight on risks for organ dysfunction and death distinct from inflammatory proteins. In this study, we determined if biomarkers of endothelial activation and inflammation exhibit independent associations with poor outcomes in SIRS. METHODS: We studied 943 critically ill patients with SIRS admitted to an Intensive Care Unit (ICU) of an academic medical center. We measured plasma levels of endothelial markers (Ang-1, Ang-2, soluble vascular cell adhesion molecule-1 (sVCAM-1)) and inflammatory markers (interleukin-6 (IL-6), interleukin-8 (IL-8), granulocyte-colony stimulating factor (G-CSF), soluble tumor necrosis factor receptor-1 (sTNFR-1)) within 24 hours of enrollment. We tested for associations between each marker and 28 day mortality, shock, and day 3 sequential organ failure assessment (SOFA) score. For 28 day mortality, we performed sensitivity analysis for those subjects with sepsis and those with sterile inflammation. We used multivariate models to adjust for clinical covariates and determine if associations identified with endothelial activation markers were independent of those observed with inflammatory markers. RESULTS: Higher levels of all biomarkers were associated with increased 28 day mortality except levels of Ang-1 which were associated with lower mortality. After adjustment for comorbidities and sTNFR-1 concentration, a doubling of Ang-1 concentration was associated with lower 28 day mortality (Odds ratio (OR) = 0.81; p<0.01), shock (OR = 0.82; p<0.001), and SOFA score (ß = -0.50; p<0.001), while Ang-2 concentration was associated with increased mortality (OR = 1.55; p<0.001), shock (OR = 1.51; p<0.001), and SOFA score (ß = +0.63; p<0.001). sVCAM-1 was not independently associated with SIRS outcomes. CONCLUSIONS: In critically ill patients with SIRS, early measurements of Ang-1 and Ang-2 are associated with death and organ dysfunction independently of simultaneously-measured markers of inflammation.