What drives cancer clinical trial accrual? An empirical analysis of studies leading to FDA authorisation (2015–2020)

Abstract

ObjectiveTo examine factors associated with accrual rate in industry sponsored clinical trials supporting US Food and Drug Administration (FDA) cancer drug approvals from 2015 to 2020.Design, setting and participantsRetrospective cross-sectional study included 194 pivotal trials supporting cancer drug approvals by the US FDA from 2015 to 2020.InterventionsClinical trials were analysed for the type of blinding, primary endpoint, whether crossover was specified in the publication, study phase, line of therapy, response rate, investigational sites, manufacturer and randomisation ratio.Main outcome measuresThe main outcome was the rate of accrual, which is the number of patients accrued in the study per open month of enrolment.ResultsThe study consisted of 133 randomised (68%) and 61 (32%) non-randomised clinical trials. In randomised studies, we found the accrual rate was higher in trials investigating first and second line drugs (adjusted rate ratios (aRR): 1.55, 95% CI 1.18 to 2.09), phase III trials (aRR: 2.13, 95% CI 1.48 to 2.99), and for studies sponsored by Merck (aRR: 1.47, 95% CI 1.18 to 2.37), adjusting for other covariates. In contrast, the primary endpoint of a study, presence of crossover, single agent response rate, the number of investigational sites, population disease burden and skewed randomisation ratios were not associated with the rate of accrual. In the non-randomised adjusted model, the accrual rate was 2.03 higher (95% CI 1.10 to 3.92) for clinical trials sponsored by manufacturer, specifically Merck. Primary endpoint, crossover, trial phase, response rate, the number of investigational sites, disease burden or line of therapy were not associated with the rate of accrual.ConclusionIn this cross-sectional study, line of therapy, study phase and manufacturer were the only factors associated with accrual rate. These findings suggest many proffered factors for speedy trial accrual are not associated with greater enrolment rates.

Ideal recruitment rate in clinical trials in phases II–III

“…По данным литературы [23][24][25][26][27] только 2 из 13 клинических исследований выполняют набор пациентов в запланированный срок по протоколу и наблюдается очень большой разброс в количестве набранных пациентов в клинических центрах, и, по нашим данным, мы также наблюдали большой разброс в клинических центрах по набранным пациентам. Влияние факторов на набор пациентов отмечено многими авторами и, в частности, скорость набора пациентов в онкологических исследованиях III фазы составляет 1,47-2,13 пациента в месяц [28], а в исследованиях орфанных заболеваний очень низкая из-за редкости патологии. По нашим данным, скорость набора пациентов с онкологическим заболеванием составляла 1,1 пациента в месяц, с ИТП -0,06 пациента в месяц, что согласуется с данными литературы.…”

Accrual and statistical power failure in published adjuvant phase III oncology trials: a comprehensive analysis from 2013 to 2023

“…Compared with RCTs in the metastatic setting, adjuvant studies tend to recruit more patients (661 versus 466), have longer accrual periods (4.3 versus 1.8 years) and less frequently use unequal randomisation ratios such as 2 : 1 or 3 : 1 (3.2% versus 29%). 29 Among adjuvant trials evaluating superiority, only 31.1% achieved statistical significance for the primary endpoint. These results highlight (i) the competitive landscape in drug development in the adjuvant setting, (ii) the need to design better phase I-II studies and (iii) the challenges in integrating new treatments into the therapeutic arsenal for early-stage disease.…”

Bayesian Interim Analysis and Efficiency of Phase III Randomized Trials

“…This estimation yielded a median accrual rate of 15 patients per month, with an interquartile range (IQR) of 9 to 24 patients per month, also consistent with the findings of an independent study. 24 While accrual dynamics were simulated, the survival duration and censoring status of each patient were set to the ab origine values observed in the published trial after the patient met the requisite follow-up time. In this way, patient fates were predetermined, not subject to simulation, and consistent with their published outcomes.…”