T-08: A Quantitative Analysis to Determine Whether Clinical Trials are Proportionately Distributed Across Cancer Indications
Poster Presenter
Jennifer Emerson
Head Quality Analytics & Risk Management
Boehringer Ingelheim Germany
Objectives
The study objective was to determine if there proportional availability of clinical trials relative to the number of cancer patients for 35 different tumor types; 2 demographic covariates were also explored for a possible association with proportional trial availability.
Method
This study used a literature-derived average rate of expected enrollment and compared it to cross-sectional data collected in 2013 from the Surveillance Epidemiology and End Results and the Clinicaltrials.gov databases; recruitment requirements from 1,156 oncology clinical trials were examined.
Results
The clinical trial ratio of the number of patients required for clinical trials of first line cancer treatment (RR) divided by the number of newly diagnosed cancer patients (INCIDENCE) is a measure of clinical trial opportunities. RR is an indication of the number of clinical trials, as RR increases, it means there are more clinical trials available for cancer patients. The ratio of RR/INCIDENCE was then subtracted from expected rate of cancer clinical trial enrollment as noted in the literature. The difference is the AVAILABILITY variable. The AVAILABILITY variable was then analyzed for 35 different tumor types to determine for which tumor types clinical trials are available relative to the number of cancer patients. Only Acute Lymphocytic Leukemia (ALL) demonstrated that there are more clinical trials requiring patients than there are newly diagnosed patients available to participate. For all other tumor types, the results indicate that there are fewer clinical trials than patients.
When all tumor types were taken together, 2 covariates were explored for an association with the AVAILABILITY variable. AGE is median age at diagnosis, RACE is the racial/ethnic group with the highest age-adjusted tumor specific incidence rate. There was a statistically significant relationship between AGE and the AVAILABILITY variable (r = 0.40226, p = 0.0166). As median age at diagnosis increased, so too did the AVAILABILITY variable. An increase in the AVAILABILITY variable indicated that there were few recruitment requirements relative to the number of patients, meaning fewer clinical trials. Therefore, as median age at diagnosis increased there were fewer clinical trials relative to the number of patients. RACE and AVAILABILITY showed no statistically significant relationship (t = 0.72, p > .05). A linear regression model with RACE and AGE predictors and AVAILABILITY as the outcome variable was tested. The model had an R2 of 0.19.
Conclusion
The literature suggests that one reason for slow enrollment in cancer clinical trials and long drug development timelines is that there are more clinical trials than cancer patients eligible and available to participate. The AVAILABILITY variable for ALL was the only tumor type where it is possible to say that the ratio of RR (which is an indication of the number of clinical trials) to the number of cancer patients is higher than the literature-derived rate of cancer clinical trial enrollment. For all other tumor types, the results suggest that the ratio of recruitment requirements to the number of cancer patients is lower than the average rate of clinical trial enrollment. To examine if there are sub-population characteristics of specific tumor types that affect proportional distribution of clinical trials, two covariates, RACE and AGE, were also analyzed for an association with the AVAILABILITY variable. These variables were selected because the literature suggests racial/ethnic and age-related differences in clinical trial participation. The AGE variable showed a positive statistically significant relationship with the AVAILABILITY variable indicating that there are fewer clinical trials available for those tumor indications where the median age at diagnosis is higher. The RACE variable did not show a statistically significant relationship with the AVAILABILITY variable. Enrollment in clinical trials is a complex process; one factor, availability of clinical trials, was examined in this study. Because RACE and AGE explain just 19% of the variance in the AVAILABILITY variable, future research should examine other possible covariates that may explain the reasons for disproportionate distribution of clinical trials relative to the number of cancer patients. Other reasons for slow enrollment in cancer clinical trials should also be explored.
