Tag Archives: Oncology

A deep learning framework (DLF) to identify clinical predictors of disease progression and mortality in metastatic castration-resistant prostate cancer (mCRPC) patients treated with docetaxel/prednisone (DP)

Background: Treatment with DP improves survival in mCRCP but is associated with significant toxicity. The question remains as to whether the improved survival is worth the toxicity risk. In this study, we have investigated the ability of a DLF to identify those patients on which treatment with DP is likely to be beneficial. Methods: The…

Profiling of clinically relevant subgroups of asymptomatic or mild-symptomatic metastatic castration-resistant prostate cancer (mCRPC) patients using PSA and testosterone levels and deep learning

Background: The optimal time to begin therapy in mCRPC patients who have either no, or minimal symptoms is not defined yet. Estimating prognosis of these patients can avoid undertreatment or overtreatment and guide the follow-up intensity. This study has investigated the ability of a deep learning framework (DLF) to identify asymptomatic or mildly symptomatic mCRPC…

Development and validation of a predictive score to identify K-Ras wild-type (WT) metastatic colorectal cancer (mCRC) patients who are likely to benefit from Panitumumab (P) treatment

Background: Practice guidelines recommend using P to treat K-Ras WT mCRC patients where it was shown to significantly extend overall survival (OS). Still, a proportion of patients will not achieve this goal. We propose a simplified predictive score to identify patients who are likely to benefit from P treatment. Methods: NCT00364013 was used as training…