Zsuzsanna Varga, Csilla Andorka, Margit Pataki, Unoke Meder, Eniko Szakmar, Attila J Szabo, Miklos Szabo, Agnes Jermendy
Higher parental education was associated with good cognitive outcomes in infants with hypoxic-ischaemic encephalopathy
Acta paediatrica (Oslo, Norway : 1992)
synthetic patient data spd generation survival analysis oncology trials holds significant potential accelerating clinical development various machine learning methods including classification regression trees cart random forest rf bayesian network bn ctgan employed purpose performance reflecting actual patient survival data remains investigation aim study determine suitable spd generation method oncology trials specifically focusing progression free survival pfs overall survival os primary evaluation endpoints oncology trials achieve goal conducted comparative simulation 4 generation methods cart rf bn ctgan performance method evaluated using multiple clinical trial datasets 1000 datasets generated using method clinical trial dataset evaluated follows 1 median survival time mst pfs os 2 hazard ratio distance hrd indicates similarity actual survival function synthetic survival function 3 visual analysis kaplanmeier km plots methods ability mimic statistical properties real patient data evaluated multiple angles simulation cases cart demonstrated high percentages msts synthetic data falling within range 95 confidence interval ci mst actual data percentages ranged 888 980 pfs 608 961 os evaluation hrd cart demonstrated hrd values concentrated approximately 09 conversely methods consistent trend observed either pfs os reason cart demonstrated better similarity rf cart caused overfitting rf kind ensemble learning prevented spd generation statistical properties close actual data focus wellgeneralized prediction model bn ctgan methods cannot accurately reflect statistical properties actual data small datasets suitable method generating spd survival data small datasets clinical trial data cart demonstrated effective method compared rf bn ctgan additionally possible improve cartbased generation methods incorporating feature engineering methods future work