Improving early phase oncology clinical trial design: The case for finding the optimal biological dose.

Historically early phase oncology drug development programmes have been based on the belief that "more is better". Furthermore, rule-based study designs such as the "3 + 3" design are still often used to identify the MTD. Phillips and Clark argue that newer Bayesian model-assisted designs such as the BOIN design should become the go to designs for statisticians for MTD finding. This short communication goes one stage further and argues that Bayesian model-assisted designs such as the BOIN12 which balances risk-benefit should be included as one of the go to designs for early phase oncology trials, depending on the study objectives. Identifying the optimal biological dose for future research for many modern targeted drugs, immunotherapies, cell therapies and vaccine therapies can save significant time and resources.

Improving early phase oncology clinical trial design: An opportunity for statisticians.

This short communication supports that rule-based study designs such as the '3 + 3' study design are still being used in early phase oncology development programs despite their inferior performance to model-based and model-assisted designs. Statisticians have an opportunity to shape and improve early phase oncology drug development programs by introducing newer, more efficient study designs that estimate the Optimal Biological dose to their oncology trialist colleges.

Evaluating Patterns and Factors Related to Sleep Disturbances in Prostate Cancer Patients.

Prostate cancer patients may experience disturbed sleep as a result of their diagnosis or treatment. This study sought to evaluate disturbed sleep and excessive daytime sleepiness in newly diagnosed patients and those receiving androgen deprivation therapy (ADT). This study was conducted with 74 patients. Subjective data using the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) and actigraphy data on ADT/ADT-naïve patients were collected. The prevalence of poor sleep quality, determined from PSQI and ESS scores, was 50% and 16.7% respectively. Those on ADT (n = 20) had poorer sleep quality as determined by significantly higher PSQI scores (70 vs. 40% scoring > 5) and were more likely to have poor sleep quality, sleep latency, and sleep efficiency than ADT-naïve patients (n = 40). Actigraphy data showed that ADT patients slept significantly longer (7.7 vs. 6.8 h), experienced a higher Fragmentation Index (48.3 vs. 37.4%), and had longer daytime nap duration (64.1 vs. 45.2 min) than ADT-naïve patients. The use of objective measures such as actigraphy in the clinical arena is recommended and may be used as a valuable tool for research into sleep assessment in prostate cancer patients.