Prediction of mortality in acute pulmonary embolism in cancer-associated thrombosis (MAUPE-C): derivation and validation of a multivariable model

AbstractOptimal risk stratification of patients with cancer and pulmonary embolism (PE) remains unclear. We constructed a clinical prediction rule (CPR) named ‘MAUPE-C’ to identify patients with low 30 days mortality. The study retrospectively developed and internally validated a CPR for 30 days mortality in a cohort of patients with cancer and PE (both suspected and unsuspected). Candidate variables were chosen based on the EPIPHANY study, which ca tegorized patients into 3 groups based on symptoms, signs, suspicion and patient setting at PE diagnosis. The performance of ‘MAUPE-C’ was compared to RIETE and sPESI scores. Univariate analysis confirmed that the presence of symptoms, signs, suspicion and inpatient diagnosis were associated wit h 30 days mortality. Multivariable logistic regression analysis led to the exclusion of symptoms as predictive variable. ‘MAUPE-C’ was developed by assigning weights to risk factors related to the β coefficient, yielding a score range of 0 to 4.5. After receiver operating characteristic (ROC) curve analysis, a cutoff point was established at ≤ 1. Prognostic accuracy was good with an area under the curve (AUC) of 0.77 (95% CI 0.71–0.82), outperforming RIETE and sPESI scores in this cohort (AUC of 0.64 [95% CI 0.57–0.71] and 0.57 [95% CI 0.49–0.65], respectively). Forty-five pe r cent of patients were classified as low risk and experienced a 2.79% 30 days mortality. MAUPE-C has good prognostic accuracy in identif...
Source: Journal of Thrombosis and Thrombolysis - Category: Hematology Source Type: research