Prediction of clinical trial enrollment rates

Enhancing site selection strategies in clinical trial recruitment using real-world data modeling

Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clinical trial timelines. To meet the planned trial recruitment, site selection strategies are used during clinical trial planning to identify research sites that are most likely to recruit a sufficiently high number of subjects within trial timelines. We developed a machine learning approach that outperforms baseline methods to rank research sites based on their expected recruitment in future studies. Indication level historical recruitment and real-world data are used in the machine learning approach to predict patient enrollment at site level. We define covariates based on published recruitment hypotheses and examine the effect of these covariates in predicting patient enrollment. We compare model performance of a linear and a non-linear machine learning model with common industry baselines that are constructed from historical recruitment data. Performance of the methodology is evaluated and reported for two disease indications, inflammatory bowel disease and multiple myeloma, both of which are actively being pursued in clinical development. We validate recruitment hypotheses by reviewing the covariates relationship with patient recruitment. For both indications, the non-linear model significantly outperforms the baselines and the linear model on the test set. In this paper, we present a machine learning approach to site selection that incorporates site-level recruitment and real-world patient data. The model ranks research sites by predicting the number of recruited patients and our results suggest that the model can improve site ranking compared to common industry baselines.

Discontinuation and nonpublication of clinical trials in orthopaedic oncology

BACKGROUND

Despite the pivotal role of clinical trials in advancing orthopaedic oncology knowledge and treatment strategies, the persistent issues of trial discontinuation and nonpublication are significant problems. This study conducted an analysis examining clinical trial discontinuation rates, associations between intervention types and discontinuation/nonpublication, and the role of funding, enrollment size, and their implications for trial success and completion.

METHODS

This study, conducted on May 1, 2023, utilized a cross-sectional design to comprehensively analyze phase 3 and 4 randomized controlled trials within the realm of orthopaedic oncology. We specifically incorporated Phase 3 and 4 trials as they are designed to evaluate prolonged outcomes in human subjects and are more likely to reach publication. Study characteristics of interest included the intervention utilized in the clinical trial, presence of funding, whether the trial was published, completed, and trial enrollment size. The investigation involved an examination of ClinicalTrials.gov, a prominent online repository of clinical trial data managed by the National Library of Medicine of the USA. Descriptive statistics and multivariate logistic regressions were used to determine statistical significance.

RESULTS

Among the cohort of 130 trials, 19.2% were prematurely discontinued. Completion rates varied based on intervention type; 111 pharmaceutical trials demonstrated a completion rate of 83.8%, whereas 19 non-pharmaceutical trials exhibited a completion rate of 8.0% (P < .001). Surgical trials, totaling 10, showed a completion rate of 90%. The overall trial publication rate was 86.15%, with pharmaceutical interventions achieving a publication rate of 91.96%. Larger-scale trials (≥ 261 participants) emerged as a protective factor against both discontinuation (Adjusted Odds Ratio [AOR]: 0.85, 95% Confidence Interval [CI] 0.42-0.95) and nonpublication (AOR: 0.19, 95% CI 0.13-.47), compared to smaller-scale trials.

CONCLUSION

This study accentuates the heightened vulnerability of non-pharmaceutical interventions and trials exhibiting lower rates of enrollment to the issues of discontinuation and nonpublication. Moving forward, the advancement of clinical trials necessitates a concerted effort to enhance trial methodologies, especially concerning nonpharmaceutical interventions, along with a meticulous refinement of participant enrollment criteria.