RT Journal Article
T1 A data mining based clinical decision support system for survival in lung cancer.
A1 Pontes, Beatriz
A1 Nuñez, Francisco
A1 Rubio, Cristina
A1 Moreno, Alberto
A1 Nepomuceno, Isabel
A1 Moreno, Jesus
A1 Cacicedo, Jon
A1 Praena-Fernandez, Juan Manuel
A1 Escobar-Rodriguez, German Antonio
A1 Parra, Carlos
A1 Delgado-Leon, Blas David
A1 Del-Campo, Eleonor Rivin
A1 Couñago, Felipe
A1 Riquelme, Jose
A1 Lopez-Guerra, Jose Luis
K1 clinical decision support system
K1 data mining
K1 lung cancer
K1 prognosis
K1 survival
AB A clinical decision support system (CDSS ) has been designed to predict the outcome (overall survival) by extracting and analyzing information from routine clinical activity as a complement to clinical guidelines in lung cancer patients. Prospective multicenter data from 543 consecutive (2013-2017) lung cancer patients with 1167 variables were used for development of the CDSS. Data Mining analyses were based on the XGBoost and Generalized Linear Models algorithms. The predictions from guidelines and the CDSS proposed were compared. Overall, the highest (> 0.90) areas under the receiver-operating characteristics curve AUCs for predicting survival were obtained for small cell lung cancer patients. The AUCs for predicting survival using basic items included in the guidelines were mostly below 0.70 while those obtained using the CDSS were mostly above 0.70. The vast majority of comparisons between the guideline and CDSS AUCs were statistically significant (p  0.90) areas under the receiver-operating characteristics curve AUCs for predicting survival were obtained for small cell lung cancer patients. The AUCs for predicting survival using basic items included in the guidelines were mostly below 0.70 while those obtained using the CDSS were mostly above 0.70. The vast majority of comparisons between the guideline and CDSS AUCs were statistically significant (p  The CDSS successfully showed potential for enhancing prediction of survival. The CDSS could assist physicians in formulating evidence-based management advice in patients with lung cancer, guiding an individualized discussion according to prognosis.
PB Wydawnictwo Via Medica
SN 1507-1367
YR 2021
FD 2021-12-30
LK https://hdl.handle.net/10668/27937
UL https://hdl.handle.net/10668/27937
LA en
NO Pontes B, Núñez F, Rubio C, Moreno A, Nepomuceno I, Moreno J, et al. A data mining based clinical decision support system for survival in lung cancer. Rep Pract Oncol Radiother. 2021 Dec 30;26(6):839-848.
DS RISalud
RD Apr 11, 2025