Objective To create nomogram prediction and random survival forest models for patients with isocitric dehydrogenase(IDH)wild-type glioblastoma to estimate their survival probabilities.Methods The clinical data of 127 patients diagnosed with IDH wild-type glioblastoma at Xijing Hospital Affiliated to Air Force Military Medical University from January 2017 to December 2020 were analyzed retrospectively.Prognostic factor analysis was conducted and a column chart model and a random survival forest model were established.The discrimination,calibration,and clinical net benefit rate of the model were evaluated through the C-index,calibration curve,and decision curve.Results Multivariate analysis using Cox proportional hazards model revealed that patients had preoperative Karnofsky performance scale(KPS),acceptance of concurrent radiotherapy and chemotherapy,age,the expression of O6-methylguanine-DNA methyltransferase(MGMT)protein were an independent prognostic factor(P＜0.05).The nomogram prediction model was developed using Cox regression,while the random survival forest model was established via the software R.Both models demonstrated excellent discrimination and calibration,with the random survival forests exhibiting a superior clinical net benefit compared to nomograms.Conclusion The established column chart model and random survival forest model help clinical doctors determine the survival probability of patients at specific time points.
IDH wild-type glioblastomanomogramrandom survival forestprediction modelMGMT protein
维普
万方数据
