Patient and trial design factors influencing participation in prospective bladder and kidney cancer clinical trials.

Abstract

655 Background: Patients on clinical trials with renal cell carcinoma (RCC) or urothelial carcinoma (UC) have better outcomes than those receiving standard of care. However, some patients choose not to participate in trials. Overrepresentation of certain groups can bias trial results. Here, we explore the characteristics of patients who decline participation in RCC and UC trials. Methods: We retrospectively reviewed patients with RCC or UC who were referred to a single uro-oncology cancer centre, St Bartholomew’s Hospital, between January 2020 and December 2022. Each patient was followed until October 2024. We assessed associations between consent and patient characteristics (age, gender, ethnicity) and trial characteristics (randomisation, phase, comparator: placebo vs active treatment). Reasons for not starting screening were classified as patient preference, performance status, comorbidities, histology or others. Independent predictors of screening initiation were identified using multivariable logistic regression analysis (MVA). Results: A total of 406 patients (189 UC, 217 RCC) were included. Older age and non-white ethnicity were associated with lower consent rates (Table 1). Patient preference was the most common reason for non-screening (34% overall, 31% among non-white patients). Trial design characteristics also had an impact, with lower participation in randomised trials (48.1%) compared to non-randomised (73.7%) (p=0.032). The presence of a placebo arm was not significant in the MVA (p=0.293). Consent was higher in early phase than late phase trials on univariable analysis (p<0.001), with lower rates in phase 3 (42.6%) compared to early phase trials (86%). However, it was not an independent predictor in the MVA. Conclusions: Specific trial and patient characteristics predispose to non-clinical trial participation. Addressing these factors may result in a more broadly representative patient population in clinical trials. Multivariable logistic regression analysis. Variable OR 95% CI p value Age 0.96 0.93-0.98 0.0008 Ethnicity 0.27 0.11-0.63 0.0028 Randomisation 0.33 0.11-0.94 0.032 Phase 1 and 2 1.64e-7 1e-170 – 5e7 0.987 Phase 3 1.2e-8 NA – 7.4e20 0.985 Active treatment 1.80 0.02-1.56 0.127 Placebo 1.09 0.04-2.50 0.293