TY - JOUR
T1 - Developing a model to predict accrual to cancer clinical trials
T2 - Data from an NCI designated cancer center
AU - Iruku, Praveena
AU - Goros, Martin
AU - Gelfond, Jonathan
AU - Chang, J.
AU - Padalecki, S.
AU - Mesa, R.
AU - Kaklamani, Virginia G.
N1 - Publisher Copyright:
© 2019
PY - 2019/9
Y1 - 2019/9
N2 - Introduction: As cancer center funds are allocated toward several resources, clinical trial offices and the clinical trial infrastructure is constantly scrutinized. It has been shown that 20% of clinical trials fail to achieve their accrual goal and in an institutional level several trials are open with poor accrual. We sought to identify factors that are associated with clinical trial accrual and develop a model to predict clinical trial accrual Methods and material: We identified all clinical trials from 1999 to 2015 at UT Health Cancer Center San Antonio. We included observational as well as interventional clinical trials. We collected several variables such as type of study, type of malignancy, trial phase, PI of study. Results: In total we included 297 clinical trials. We identified several factors to be associated with clinical trial accrual (Sponsor type, trial phase, disease category, type of trial, disease state and whether the trial involved a new investigational agent). We developed a predictive model with an AUC of 0.65 that showed that observational, interventional, industry-sponsored trials and trials authored by the local PI were more likely to achieve their accrual goal. Conclusion: We were able to identify several factors that were significantly associated with clinical trial accrual. Based on these factors we developed a prediction model for clinical trial accrual. We believe that use of this model can help improve our cancer centers clinical trial portfolio and help in fund allocation.
AB - Introduction: As cancer center funds are allocated toward several resources, clinical trial offices and the clinical trial infrastructure is constantly scrutinized. It has been shown that 20% of clinical trials fail to achieve their accrual goal and in an institutional level several trials are open with poor accrual. We sought to identify factors that are associated with clinical trial accrual and develop a model to predict clinical trial accrual Methods and material: We identified all clinical trials from 1999 to 2015 at UT Health Cancer Center San Antonio. We included observational as well as interventional clinical trials. We collected several variables such as type of study, type of malignancy, trial phase, PI of study. Results: In total we included 297 clinical trials. We identified several factors to be associated with clinical trial accrual (Sponsor type, trial phase, disease category, type of trial, disease state and whether the trial involved a new investigational agent). We developed a predictive model with an AUC of 0.65 that showed that observational, interventional, industry-sponsored trials and trials authored by the local PI were more likely to achieve their accrual goal. Conclusion: We were able to identify several factors that were significantly associated with clinical trial accrual. Based on these factors we developed a prediction model for clinical trial accrual. We believe that use of this model can help improve our cancer centers clinical trial portfolio and help in fund allocation.
KW - Accrual
KW - Cancer center
KW - Clinical trials
KW - Model
KW - Prediction
UR - http://www.scopus.com/inward/record.url?scp=85069607523&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069607523&partnerID=8YFLogxK
U2 - 10.1016/j.conctc.2019.100421
DO - 10.1016/j.conctc.2019.100421
M3 - Article
C2 - 31372575
AN - SCOPUS:85069607523
SN - 2451-8654
VL - 15
JO - Contemporary Clinical Trials Communications
JF - Contemporary Clinical Trials Communications
M1 - 100421
ER -