Abstract
As breast cancer is a diverse disease, clinical trials are becoming increasingly diversified and are consequently being conducted in very small subgroups of patients, making study recruitment increasingly difficult. The aim of this study was to assess the use of data from a remote data entry system that serves a large national registry for metastatic breast cancer. The PRAEGNANT network is a real-time registry with an integrated biomaterials bank that was designed as a scientific study and as a means of identifying patients who are eligible for clinical trials, based on clinical and molecular information. Here, we report on the automated use of the clinical data documented to identify patients for a clinical trial (EMBRACA) for patients with metastatic breast cancer. The patients’ charts were assessed by two independent physicians involved in the clinical trial and also by a computer program that tested patients for eligibility using a structured query language script. In all, 326 patients from two study sites in the PRAEGNANT network were included in the analysis. Using expert assessment, 120 of the 326 patients (37 %) appeared to be eligible for inclusion in the EMBRACA study; with the computer algorithm assessment, a total of 129 appeared to be eligible. The sensitivity of the computer algorithm was 0.87 and its specificity was 0.88. Using computer-based identification of patients for clinical trials appears feasible. With the instrument’s high specificity, its application in a large cohort of patients appears to be feasible, and the workload for reassessing the patients is limited.
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Schmidt M, Fasching PA, Beckmann MW, Kolbl H (2012) Biomarkers in breast cancer—an update. Geburtshilfe Frauenheilkd 72(9):819–832. doi:10.1055/s-0032-1315340
Fasching PA, Ekici AB, Wachter DL, Hein A, Bayer CM, Haberle L, Loehberg CR, Schneider M, Jud SM, Heusinger K, Rubner M, Rauh C, Bani MR, Lux MP, Schulz-Wendtland R, Hartmann A, Beckmann MW (2013) Breast cancer risk—from genetics to molecular understanding of pathogenesis. Geburtshilfe Frauenheilkd 73(12):1228–1235. doi:10.1055/s-0033-1360178
von Minckwitz G, Loibl S, Schneeweiss A, Salat CT, Rezai M, Zahm DM, Klare P, Blohmer JU, Tesch H, Khandan F, Fasching PA, Jakisch C, Nekljudova V, Untch M (2015) Early survival analysis of the randomized phase II trial investigating the addition of carboplatin to neoadjuvant therapy for triple-negative and HER2-positive early breast cancer (GeparSixto) Cancer Res 76(4 Suppl):Abstract nr S2-04. (76(4 Suppl)):Abstract nr S2-04
ClinicalTrials.gov (2016) Olaparib as Adjuvant Treatment in Patients With Germline BRCA Mutated High Risk HER2 Negative Primary Breast Cancer (OlympiA). https://clinicaltrials.gov/ct2/show/NCT02032823 Accessed on 10 Mar 2016
ClinicalTrials.gov (2016) A Study Evaluating Talazoparib (BMN 673), a PARP Inhibitor, in Advanced and/or Metastatic Breast Cancer Patients With BRCA Mutation (EMBRACA Study) (EMBRACA). https://clinicaltrials.gov/ct2/show/NCT01945775 Accessed on 10 Mar 2016
Fasching PA, Brucker SY, Fehm TN, Overkamp F, Janni W, Wallwiener M, Hadji P, Belleville E, Haberle L, Taran FA, Luftner D, Lux MP, Ettl J, Muller V, Tesch H, Wallwiener D, Schneeweiss A (2015) Biomarkers in patients with metastatic breast cancer and the PRAEGNANT study network. Geburtshilfe Frauenheilkd 75(1):41–50. doi:10.1055/s-0034-1396215
Tu SW, Kemper CA, Lane NM, Carlson RW, Musen MA (1993) A methodology for determining patients eligibility for clinical-trials. Methods Inf Med 32(4):317–325
Embi PJ, Jain A, Clark J, Bizjack S, Hornung R, Harris CM (2005) Effect of a clinical trial alert system on physician participation in trial recruitment. Arch Intern Med 165(19):2272–2277. doi:10.1001/archinte.165.19.2272
Dugas M, Lange M, Mueller-Tidow C, Kirchhof P, Prokosch H-U (2010) Routine data from hospital information systems can support patient recruitment for clinical studies. Clini Trials 7(2):183–189. doi:10.1177/1740774510363013
Cuggia M, Besana P, Glasspool D (2011) Comparing semi-automatic systems for recruitment of patients to clinical trials. Int J Med Inform 80(6):371–388. doi:10.1016/j.ijmedinf.2011.02.003
Kopcke F, Prokosch HU (2014) Employing computers for the recruitment into clinical trials: a comprehensive systematic review. J Med Internet Res 16(7):26–43. doi:10.2196/jmir.3446
Doods J, Lafitte C, Ulliac-Sagnes N, Proeve J, Botteri F, Walls R, Sykes A, Dugas M, Fritz F (2015) A european inventory of data elements for patient recruitment. Stud Health Technol Inform 210:506–510
ClinicalTrials.gov (2015, accessed Dec 14, 2015) A Study Evaluating Talazoparib (BMN 673), a PARP Inhibitor, in Advanced and/or Metastatic Breast Cancer Patients With BRCA Mutation (EMBRACA Study). https://clinicaltrials.gov/ct2/show/NCT01945775
Ellis PM (2000) Attitudes towards and participation in randomised clinical trials in oncology: a review of the literature. Ann Oncol 11(8):939–945. doi:10.1023/a:1008342222205
Campbell MK, Snowdon C, Francis D, Elbourne D, McDonald AM, Knight R, Entwistle V, Garcia J, Roberts I, Grant A, Grant A, group S (2007) Recruitment to randomised trials: strategies for trial enrollment and participation study. The STEPS study. Health technology assessment 11 (48):iii, ix-105
Siminoff LA (2008) Why learning to communicate with our patients is so important: using communication to enhance accrual to cancer clinical trials. J clin Oncol 26(16):2614–2615. doi:10.1200/JCO.2008.16.2610
Mannel RS, Walker JL, Gould N, Scribner DR, Kamelle S, Tillmanns T, McMeekin DS, Gold MA (2003) Impact of individual physicians on enrollment of patients into clinical trials. Am J Clin Oncol 26(2):171–173. doi:10.1097/00000421-200304000-00014
Comis RL, Miller JD, Aldige CR, Krebs L, Stoval E (2003) Public attitudes toward participation in cancer clinical trials. J of clin oncol : off j of the Am Soc of Clin Oncol 21(5):830–835. doi:10.1200/jco.2003.02.105
Wallwiener M, Wallwiener CW, Brucker SY, Hartkopf AD, Fehm TN, Kansy JK (2010) The brustkrebs-studien.de website for breast cancer patients: user acceptance of a German internet portal offering information on the disease and treatment options, and a clinical trials matching service. BMC Cancer 10:663. doi:10.1186/1471-2407-10-663
Embi PJ, Jain A, Clark J, Harris CM (2005) Development of an electronic health record-based Clinical Trial Alert system to enhance recruitment at the point of care. AMIA Annual Symposium proceedings/AMIA Symposium AMIA Symposium:231-235
Olesen F, Kjeldsen HC, Christensen MB (1996) Identifying patients for research in general practice. Scand J Prim Health Care 14(1):62–63. doi:10.3109/02813439608997070
Acknowledgments
The PRAEGNANT network is supported by grants from Novartis and Pfizer. We thank BioMarin Pharmaceutical Inc. for valuable cooperation. The study was supported in part by the German Federal Ministry of Economic Affairs and Energy through the ″Clinical Data Intelligence″ grant (01MT14001E).
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Hein, A., Gass, P., Walter, C.B. et al. Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients. Breast Cancer Res Treat 158, 59–65 (2016). https://doi.org/10.1007/s10549-016-3850-8
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DOI: https://doi.org/10.1007/s10549-016-3850-8