Abstract 108P
Background
Biomarkers play a critical role in advancing personalized cancer therapy by enabling tailored treatments that improve patient outcomes. These therapies leverage molecular and genetic insights to target cancer more effectively, reducing toxicity and enhancing efficacy. Despite their transformative potential, a substantial proportion of clinical trials investigating biomarker-driven therapies face discontinuation or remain unpublished, limiting their impact on evidence-based practice. This study evaluates the rates, causes, and predictors of trial discontinuation and nonpublication among biomarker-based and personalized cancer therapy studies.
Methods
A cross-sectional analysis was conducted using data from ClinicalTrials.gov. Inclusion criteria encompassed trials classified as “Completed,” “Suspended,” “Terminated,” or “Withdrawn.” Data on study phase, enrollment, funding source, study type, and publication status were analyzed. Logistic regression was employed to assess predictors of publication and discontinuation.
Results
Out of 3,802 trials analyzed, 2,832 (74.5%) were completed, and 970 (25.5%) were discontinued. Among completed trials, 40% were published, while 34.5% remained unpublished. Discontinued trials had a lower publication rate (6.6%), with 18.9% unpublished. Most trials targeted adults and older adults (60.4%) and involved both sexes (57.8%). Drug-only interventions dominated, with smaller enrollment (<100 participants) significantly associated with higher discontinuation rates (p < 0.001). Multi-center trials were more likely to be published compared to single-center trials (p < 0.001). Non-industrial funding accounted for 70% of trials but showed lower publication odds than industrial funding (p = 0.055).
Conclusions
High rates of nonpublication and discontinuation persist in biomarker-based cancer trials, particularly those with smaller enrollments, non-industrial funding, and single-center designs. Enhanced strategies are needed to address these gaps and improve the translational impact of biomarker-driven personalized cancer therapies.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.