Predicting enrollment performance of investigational centers in phase III multi-center clinical trials

Contemporary Clinical Trials Communications

Volumn 7, Issue , 2017, Pages 208-216

  van den Bor, Rutger M ^a,b   Grobbee, Diederick E ^a,b   Oosterman, Bas J ^a   Vaessen, Petrus W J ^a   Roes, Kit C B ^b  

^a Julius Clinical   (Netherlands)

^b UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

Author keywords

Feasibility studies; Risk based monitoring; Site performance prediction; Site questionnaires; Trial accrual; Trial recruitment

Indexed keywords

ARTICLE; FEASIBILITY STUDY; HUMAN; LOGISTIC REGRESSION ANALYSIS; MULTICENTER STUDY (TOPIC); PERFORMANCE; PHASE 3 CLINICAL TRIAL (TOPIC); PREDICTION; PRIORITY JOURNAL; PROBABILITY; QUESTIONNAIRE; STATISTICAL MODEL;

EID: 85026918607     PISSN: 24518654     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conctc.2017.07.004     Document Type: Article

References (22)

1. Benson, A.B. III, Pregler, J.P., Bean, J.A., Rademaker, A.W., Eshler, B., Anderson, K., Oncologists' reluctance to accrue patients onto clinical trials: an Illinois cancer center study. J. Clin. Oncol. 9:11 (1991), 2067–2075.
2. R Core Team, A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. 2016 http://www.r-project.org/ Version 3.3.1.
3. Desai, P.B., Anderson, C., Sietsema, W.K., A comparison of the quality of data, assessed using query rates, from clinical trials conducted across developed versus emerging global regions. Drug Inf. J. 46 (2012), 455–463, 10.1177/0092861512446807.
4. Donovan, J.L., Peters, T.J., Noble, S., Powell, P., Gillatt, D., Oliver, S.E., Lane, J.A., Neal, D.E., Hamdy, F.C., For the ProtecT Study Group. Who can best recruit to randomized trials? Randomized trial comparing surgeons and nurses recruiting patients to a trial of treatments for localized prostate cancer (the ProtecT study). J. Clin. Epidemiol. 56 (2003), 605–609, 10.1016/S0895-4356(03)00083-0.
5. Fletcher, B., Gheorghe, A., Moore, D., Wilson, S., Damery, S., Improving the recruitment activity of clinicians in randomized controlled trials: a systematic review. BMJ Open, 2, 2012, e000496, 10.1136/bmjopen-2011-000496.
6. Ford, E., Jenkins, V., Fallowfield, L., Stuart, N., Farewell, D., Farewell, V., Clinicians' attitudes towards clinical trials of cancer therapy. Br. J. Cancer 104:10 (2011), 1535–1543, 10.1038/bjc.2011.119 Epub 2011 Apr 12.
7. Friedman, L.M., Furberg, C.D., DeMets, D.L., Fundamentals of Clinical Trials. fourth ed., 2010, Springer, 10.1007/978-1-4419-1586-3.
8. Getz, K., Predicting successful site performance. Appl. Clin. Trials, November 1st, 2011 http://www.appliedclinicaltrialsonline.com/predicting-successful-site-performance.
9. Lincoff, A.M., Tardif, J.-C., Neal, B., Nicholls, S.J., Rydén, L., Schwartz, G.G., Malmberg, K., Buse, J.B., Henry, R.R., Wedel, H., Weichert, A., Cannata, R., Grobbee, D.E., Evaluation of the dual peroxisome proliferator-activated receptor α/γ agonist aleglitazar to reduce cardiovascular events in patients with acute coronary syndrome and type 2 diabetes mellitus: rationale and design of the AleCardio trial. Am. Heart J. 166:3 (2013), 429–434, 10.1016/j.ahj.2013.05.013.
10. Lincoff, A.M., Tardif, J.-C., Schwartz, G.G., Nicholls, S.J., Rydén, L., Neal, B., Malmberg, K., Wedel, H., Buse, J.B., Henry, R.R., Weichert, A., Cannata, R., Svensson, A., Volz, D., Grobbee, D.E., Effect of aleglitazar on cardiovascular outcomes after acute coronary syndrome in patients with type 2 diabetes mellitus: the AleCardio randomized clinical trial. J. Am. Med. Assoc. 311:15 (2014), 1515–1525, 10.1001/jama.2014.3321.
11. Lovato, L.C., Hill, K., Hertert, S., Hunninghake, D.B., Probstfield, J.L., Recruitment for controlled clinical trials: literature summary and annotated bibliography. Control Clin. Trials 18 (1997), 328–357.
12. McDonald, A.M., Knight, R.C., Campbell, M.K., Entwistle, V.A., Grant, A.M., Cook, J.A., Elbourne, D.R., Francis, D., Garcia, J., Roberts, I., Snowdon, C., What influences recruitment to randomised controlled trials? A review of trials funded by two UK funding agencies. Trials, 7, 2006, 9, 10.1186/1745-6215-7-9.
13. Meier, L., Grplasso: Fitting User Specified Models with Group Lasso Penalty. 2015 https://CRAN.R-project.org/package=grplasso Version 0.4-5.
14. Oude Rengerink, K., Hooft, L., Van den Boogaard, N.M., Van der Goes, B.Y., Bossuyt, P.M.M., Mol, B.W.J., Why Do Some Centres Recruit Better than Others? an Analysis of Recruitment Rates in 17 Randomized Clinical Trials in Obstetrics and Gynaecology. Chapter 4 in ‘Embedding Trials in Evidence-based Clinical Practice’ by Oude Rengerink, K., 2014, University of Amsterdam, The Netherlands PhD thesis.
15. Parker, R.N., Fenwick, R., The Pareto curve and its utility for open-ended income distributions in survey research. Soc. Forces 61:3 (1983), 872–885, 10.2307/2578140.
16. Rahman, S., Majumder, A.A., Shaban, S.F., Rahman, N., Ahmed, M., Abdulrahman, K.B., D'Souza, U.J.A., Physician participation in clinical research and trials: issues and approaches. Adv. Med. Educ. Pract. 2 (2011), 85–93, 10.2147/AMEP.S14103.
17. Reuter, S., Esche, G., How effective are site questionnaires in predicting site performance?. J. Clin. Res. Best Pract., 3(4), 2007.
18. Roberts, S., Nowak, G., Stabilizing the LASSO against cross-validation variability. Comput. Stat. Data Anal. 70 (2014), 198–211, 10.1016/j.csda.2013.09.008.
19. Shea, S., Bigger, J.T., Campion, J., Fleiss, J.L., Rolnitzky, L.M., Schron, E., Gorkin, L., Handshaw, K., Kinney, M.R., Branyon, M., Enrollment in clinical trials: institutional factors affecting enrollment in the cardiac arrhythmia suppression trial (CAST). Control. Clin. Trials 13 (1992), 466–486.
20. Tibshirani, R., Regression shrinkage and selection via the LASSO. J. R. Stat. Soc. Ser. B 58:1 (1996), 267–288.
21. Van Buuren, S., Groothuis-Oudshoorn, K., Mice: multivariate imputation by chained equations in R. J. Stat. Soft 45:3 (2011), 1–67 http://www.jstatsoft.org/v45/i03/ Version 2.30.
22. Levett, K.M., Roberts, C.L., Simpson, J.M., Morris, J.M., Site-specific predictors of successful recruitment to a perinatal clinical trial. Clin. Trials 11 (2014), 584–589, 10.1177/1740774514543539.