Systemic therapy clinical trial participation in patients with bladder and kidney cancers.
Bibliographic record
Abstract
451 Background: Patient participation in clinical trials has led to numerous treatment advances in renal cell carcinoma (RCC) and urothelial carcinoma (UC) over the past decade. The rate of patient participation in RCC and UC trials and factors influencing participation are unknown. This study evaluates patient participation rates in RCC and UC clinical trials at a major United Kingdom cancer centre. Methods: All referrals to St Bartholomew’s Hospital (SBH) Genitourinary Cancer Department between Jan 2020 to Sept 2022 were reviewed. Patients with RCC or UC of any stage were included. Dates of consultation and follow up visits were cross-referenced with a list of systemic therapy clinical trials open at SBH from Jan 2020 to Oct 2024. The proportion of patients who a) had a trial available to them, b) entered trial screening, and c) were eligible for a trial, was determined. Multilevel mixed-effects logistic regression models were used to assess the likelihood of clinical trial screening and enrolment with adjustment for relevant baseline variables (age, cancer type, gender, line of therapy, and performance status [PS]). Results: 403 patients were included in the analysis: 215 RCC (44% stage I-III and 60% had or developed metastatic disease) and 188 UC (41% stage I-III and 69% had or developed metastatic disease). 63% (254/403) of patients had at least one eligibility opportunity to be screened for a trial during the follow up. 40% (161/403) consented to trial screening, and 30% (118/403) were enrolled into at least one trial. The table shows trial availability, screening, and enrolment by line of therapy (rates were similar between RCC and UC, data not shown). Variables associated with increased odds of entering trial screening were line of therapy (second line odds ratio (OR) 8.6 (2.3-31.8), p<0.01, third line OR 3.4 (1.3-9.0) p=0.02, compared to adjuvant) and UC vs RCC trials OR 2.4 (1.3-4.3) p<0.01. Poor PS decreased the odds of entering trial screening (OR 0.21 (0.1-0.5) p<0.01). Gender and age were not associated with screening rates. No variables were associated with trial enrolment after a patient had consented to screening. Conclusions: At a major UK clinical trial centre, 40% of patients with RCC or UC entered clinical trial screening and 30% participated. Most patient characteristics were not associated with increased screening except for PS. Screening rates were higher in later line treatment studies. The effect of ethnicity and randomisation will be presented at the meeting. These data highlight patient willingness to screen for trials when they are available. Clinical trial availability, screening rates, and enrollment rates by line of therapy for patients with RCC and UC. Neo/Adjuvant 1L 2L 3/4L Trial Available 45% (86/248) 58% (151/259) 34% (35/104) 66% (40/60) Screened 56% (48/86) 52% (78/151) 91% (32/35) 83% (33/40) Enrolled 73% (35/48) 68% (53/78) 63% (20/32) 82% (27/33)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".