gdc-0068 has been researched along with Hyperglycemia* in 2 studies
1 trial(s) available for gdc-0068 and Hyperglycemia
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Safety Profile of Ipatasertib Plus Abiraterone vs Placebo Plus Abiraterone in Metastatic Castration-resistant Prostate Cancer.
Adding ipatasertib to abiraterone and prednisone/prednisolone significantly improved radiographic progression-free survival for patients with metastatic castration-resistant prostate cancer (mCRPC) with PTEN-loss tumours by immunohistochemistry in the IPATential150 trial (NCT03072238). Here we characterise the safety of these agents in subpopulations and assess manageability of key adverse events (AEs).. In this randomised, double-blind, phase 3 trial, patients with previously untreated asymptomatic or mildly symptomatic mCRPC were randomised 1:1 to receive ipatasertib-abiraterone or placebo-abiraterone (all with prednisone/prednisolone). AEs were analysed, focusing on key AEs of diarrhoea, hyperglycaemia, rash and transaminase increased.. 1097 patients received study medication and were assessed for safety (47% with PTEN-loss tumours by immunohistochemistry and 20% were Asian). Ipatasertib was associated with increased Grade 3/4 AEs and AEs leading to treatment discontinuation vs placebo. The rate of discontinuation of ipatasertib was 18% in patients with PTEN-loss and 21% overall. The frequencies of all-grade, Grade 3/4 and serious AEs were similar between the PTEN-loss and overall populations. Diarrhoea, hyperglycaemia, rash and transaminase elevation were more frequent in ipatasertib-treated patients, appearing rapidly after treatment initiation (median onset: 8-43 days for ipatasertib arm and 56-104 days for placebo). The ipatasertib discontinuation rate was 32% and 18% in Asian and non-Asian patients, respectively, despite similar baseline characteristics and Grade 3/4 AE frequencies between groups.. Ipatasertib plus abiraterone had an overall tolerable safety profile consistent with known toxicities. More AEs leading to drug discontinuation were observed with ipatasertib than placebo, but incidence would likely be lessened with prophylactic measures. Topics: Abiraterone Acetate; Antineoplastic Combined Chemotherapy Protocols; Exanthema; Humans; Hyperglycemia; Male; Prednisolone; Prednisone; Prostatic Neoplasms, Castration-Resistant | 2023 |
1 other study(ies) available for gdc-0068 and Hyperglycemia
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Risk Factors of Hyperglycemia After Treatment With the AKT Inhibitor Ipatasertib in the Prostate Cancer Setting: A Machine Learning-Based Investigation.
Hyperglycemia is a major adverse event of phosphatidylinositol 3-kinase/AKT inhibitor class of cancer therapeutics. Machine learning (ML) methodologies can identify and highlight how explanatory variables affect hyperglycemia risk.. Using data from clinical trials of the AKT inhibitor ipatasertib (IPAT) in the metastatic castrate-resistant prostate cancer setting, we trained an XGBoost ML model to predict the incidence of grade ≥2 hyperglycemia (HGLY ≥ 2). Of the 1,364 patients included in our analysis, 19.4% (n = 265) of patients had HGLY ≥2 events with a median time of first onset of 28 days (range, 0-753 days), and 30.0% (n = 221) of patients on an IPAT regimen had at least one HGLY ≥2 event compared with 7.0% (n = 44) of patients on placebo.. An 11-variable XGBoost model predicted HGLY ≥2 events well with an AUROC of 0.83 ± 0.02 (mean ± standard deviation). Using SHapley Additive exPlanations analysis, we found IPAT exposure and baseline HbA1c levels to be the strongest predictors of HGLY ≥2, with additional predictivity of baseline measurements of fasting glucose, magnesium, and high-density lipoproteins.. The findings support using patients' prediabetic status as a key factor for hyperglycemia monitoring and/or trial exclusion criteria. Additionally, the model and relationships between explanatory variables and HGLY ≥2 described herein can help identify patients at high risk for hyperglycemia and develop rational risk mitigation strategies. Topics: Humans; Hyperglycemia; Machine Learning; Male; Prostatic Neoplasms; Protein Kinase Inhibitors; Proto-Oncogene Proteins c-akt; Risk Factors | 2023 |