Backfill Bayesian Ordered Lattice Design for Phase I Clinical Trials
WANG, G.-M.; Tatsuoka, C.
Show abstract
The Bayesian Ordered Lattice Design (BOLD) method for Phase I clinical trials is extended to address an important challenge. It is widely understood that conventional Phase I trial designs are not consistently effective in determining safe and active dose levels. The US FDA launched the Project Optimus, aimed at reforming the paradigms of dose optimization and selection. We propose a backfill BOLD design (BF-BOLD) that centers on BOLD for dose-finding but also adds an activity evaluation for each patient. Our method for determining the optimal biological dose (OBD) first involves identifying the maximum tolerated dose (MTD) and then assessing activity rates among dose levels below the identified MTD. This approach is straightforward and does not require complex statistical modeling. The results of the simulation indicate that performing dose-finding trials with backfilling can both enhance safety and activity assessment, thereby improving treatment sustainability while also preserving the potential for efficacy of the Recommended Phase II Dose (RP2D). We also demonstrate the applicability of the backfill design for reducing overdose rates, and as a more attractive alternative to small-scale dose expansion trials that follow dose escalation. Backfill designs are an important design approach for early phase trials.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Cluster-Based Toxicity Estimation of Osteoradionecrosis via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification 92%
- Revisiting a null hypothesis: exploring the parameters of oligometastasis treatment 92%
- Bayesian Learning to Reduce Cardiac Risk for Locally Advanced NSCLC Patients Based on Personalized Radiotherapy Prescription 91%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Intermittent radiotherapy as alternative treatment for recurrent high grade glioma: A modelling study based on longitudinal tumor measurements 92%
- Reinforcement learning derived chemotherapeutic schedules for robust patient-specific therapy 91%
- Multiwell-based G0-PCC assay for radiation biodosimetry 90%
Similar papers in this journal
- Chemotherapy-Induced Cachexia and Model-Informed Dosing to Preserve Lean Mass in Cancer Treatment 92%
- Combination Treatment Optimization Using aPan-Cancer Pathway Model 92%
- Contrasting model mechanisms of alanine aminotransferase (ALT) release from damaged and necrotic hepatocytes as an example of general biomarker mechanisms 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.