Search

Objectives: The aim of this study was to examine the independent and joint associations of baseline coronary artery calcium score (CACS) and cystatin C (Cys‐C) with the risk of major adverse cardiac and cerebrovascular events (MACCEs) and all‐cause death in symptomatic populations. Methods: The study included 7140 patients with symptom of chest pain who underwent cardiac computerized tomography examinations to measure CACS. All of them had serum Cys‐C results. Endpoints were set for MACCEs and all‐cause death events. Results: A total of 7140 participants were followed for a median of 1106 days. A total of 305 patients had experienced MACCEs and 191 patients had experienced all‐cause death. CACS ≥ 100 and Cys‐C ≥ 0.995 mg/L were independently associated with an increased risk of MACCEs (adjusted hazard ratio [HR]: 1.46; 95% confidence interval [CI]: 1.15–1.85; p =.002 and adjusted HR: 1.57; 95% CI: 1.24–2.00; p <.001, respectively). Compared with CACS < 100 and Cys‐C < 0.995 mg/L patients, CACS ≥ 100 and Cys‐C ≥ 0.995 mg/L patients had the highest risk of MACCEs and all‐cause death (adjusted HR: 2.33; 95% CI: 1.64–3.29; p <.001 and adjusted HR: 2.85; 95% CI: 1.79–4.55; p <.001, respectively). Even in patients with CACS < 100, Cys‐C ≥ 0.995 mg/L was also associated with a higher risk of MACCEs and all‐cause death than Cys‐C < 0.995 mg/L (adjusted HR: 1.76; p =.003 and adjusted HR: 2.02; p =.007, respectively). Conclusions: The combined stratification of CACS and Cys‐C showed an incremental risk of MACCEs and all‐cause death, reflecting complementary prognostic value. Our results support the combination of the two indicators for risk stratification and event prediction. [ABSTRACT FROM AUTHOR]

Quantitative systems pharmacology holds the promises of integrating results from laboratory animals or in vitro human systems into the design of human pharmacokinetic/pharmacodynamic (PK/PD) models allowing for precision and personalized medicine. However, reliable and general in vitro‐to‐in vivo extrapolation and interspecies scaling methods are still lacking. Here, we developed a translational strategy for the anticancer drug oxaliplatin. Using ex vivo PK data in the whole blood of the mouse, rat, and human, a model representing the amount of platinum (Pt) in the plasma and in the red blood cells was designed and could faithfully fit each dataset independently. A "purely physiologically‐based (PB)" scaling approach solely based on preclinical data failed to reproduce human observations, which were then included in the calibration. Investigating approaches in which one parameter was set as species‐specific, whereas the others were computed by PB scaling laws, we concluded that allowing the Pt binding rate to plasma proteins to be species‐specific permitted to closely fit all data, and guaranteed parameter identifiability. Such a strategy presenting the drawback of including all clinical datasets, we further identified a minimal subset of human data ensuring accurate model calibration. Next, a "whole body" model of oxaliplatin human PK was inferred from the ex vivo study. Its three remaining parameters were estimated, using one third of the available patient data. Remarkably, the model achieved a good fit to the training dataset and successfully reproduced the unseen observations. Such validation endorsed the legitimacy of our scaling methodology calling for its testing with other drugs. [ABSTRACT FROM AUTHOR]