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.

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.

e17046 Background: Sleep disturbances and cancer related fatigue are commonly associated. Prostate cancer patients may suffer from disturbed sleep as a result of their diagnosis and following treatment, especially with androgen deprivation therapy (ADT). Wrist actigraphy is a non-invasive objective method of sleep data collection. This feasibility study compares sleep data obtained by actigraphy with subjective data from sleep questionnaires in order to determine the nature and severity of sleep disturbances in patients with and without ADT use. Methods: A prospective cross-sectional pilot study was conducted on 74 patients with prostate cancer attending a regional oncology clinic. Two validated subjective sleep questionnaires namely the Pittsburgh Sleep Quality Index [PSQI] and the Epworth Sleepiness Scale [ESS] were used. Patients wore actigraphy watches for a minimum of five consecutive days. The parameters of interest included: actual sleep time, sleep efficiency, fragmentation index, daytime napping frequency and duration. The questionnaire and actigraphy data were compared between 20 patients receiving ADT and 41 who were treatment-naive. Results: The compliance rate for completed actigraphy was 85%. Complete data sets with actigraphy and questionnaires were available from 61 patients. Those already receiving ADT were on LHRH analogues for a median duration of 2.35 years. Poor sleep quality as self-identified by patients from the PSQI (cut-off > 5) was 49% in the treatment-naive group which increased to 70% for those on ADT. For daytime sleepiness as assessed by ESS (cut-off > 10) this was 16% and 20% respectively. Actigraphy showed that patients on ADT reported longer sleep duration (7.4 vs 6.5 hours, p = 0.02), higher levels of nocturnal wakings (51.1% vs 36.7%, p = 0.002), with greater daytime napping duration (80.7mins vs 53.0mins, p = 0.04), and frequency (8.6 vs 5.6, p = 0.02) compared to treatment-naive patients. Conclusions: Self-reported poor sleep quality is common in prostate cancer patients, which appears worse for those receiving ADT. In patients receiving ADT, data derived from actigraphy suggests that although they were sleeping for longer at night, the quality of sleep was poor which, in turn, may be responsible for an increase in the frequency and duration of daytime napping. Based on the current findings, we recommend the use of actigraphy to characterise patients’ sleep patterns and to assess if sleep treatment is needed. Actigraphic data may allow for direct comparisons of different hormonal agents on sleep whilst identifying those with specific sleep disorders amenable to therapeutic intervention.

No abstract

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.