Please use this identifier to cite or link to this item:
Title: Predicting serious complications in patients with cancer and pulmonary embolism using decision tree modelling: the EPIPHANY Index.
Authors: Carmona-Bayonas, A
Jiménez-Fonseca, P
Font, C
Fenoy, F
Otero, R
Beato, C
Plasencia, J M
Biosca, M
Sánchez, M
Benegas, M
Calvo-Temprano, D
Varona, D
Faez, L
de la Haba, I
Antonio, M
Madridano, O
Solis, M P
Ramchandani, A
Castañón, E
Marchena, P J
Martín, M
Ayala de la Peña, F
Vicente, V
metadata.dc.subject.mesh: Area Under Curve
Decision Support Techniques
Decision Trees
Follow-Up Studies
Health Status Indicators
Middle Aged
Neoplasm Staging
Pulmonary Embolism
Risk Assessment
Severity of Illness Index
Survival Rate
Issue Date: 7-Mar-2017
Abstract: Our objective was to develop a prognostic stratification tool that enables patients with cancer and pulmonary embolism (PE), whether incidental or symptomatic, to be classified according to the risk of serious complications within 15 days. The sample comprised cases from a national registry of pulmonary thromboembolism in patients with cancer (1075 patients from 14 Spanish centres). Diagnosis was incidental in 53.5% of the events in this registry. The Exhaustive CHAID analysis was applied with 10-fold cross-validation to predict development of serious complications following PE diagnosis. About 208 patients (19.3%, 95% confidence interval (CI), 17.1-21.8%) developed a serious complication after PE diagnosis. The 15-day mortality rate was 10.1%, (95% CI, 8.4-12.1%). The decision tree detected six explanatory covariates: Hestia-like clinical decision rule (any risk criterion present vs none), Eastern Cooperative Group performance scale (ECOG-PS; We have developed and internally validated a prognostic index to predict serious complications with the potential to impact decision-making in patients with cancer and PE.
metadata.dc.identifier.doi: 10.1038/bjc.2017.48
Appears in Collections:Producción 2020

Files in This Item:
File SizeFormat 
PMC5396106.pdf556,87 kBAdobe PDFView/Open

This item is protected by original copyright

This item is licensed under a Creative Commons License Creative Commons