Research ExplorerPublicationsComputerized patient identification for the EMBRACA clinical...

Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients

Standard

Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients. / Hein, Alexander; Gass, Paul; Walter, Christina Barbara; Taran, Florin-Andrei; Hartkopf, Andreas; Overkamp, Friedrich; Kolberg, Hans-Christian; Hadji, Peyman; Tesch, Hans; Ettl, Johannes; Wuerstlein, Rachel; Lounsbury, Debra; Lux, Michael P; Lüftner, Diana; Wallwiener, Markus; Müller, Volkmar; Belleville, Erik; Janni, Wolfgang; Fehm, Tanja N; Wallwiener, Diethelm; Ganslandt, Thomas; Ruebner, Matthias; Beckmann, Matthias W; Schneeweiss, Andreas; Fasching, Peter A; Brucker, Sara Y.

In: BREAST CANCER RES TR, Vol. 158, No. 1, 07.2016, p. 59-65.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Hein, A, Gass, P, Walter, CB, Taran, F-A, Hartkopf, A, Overkamp, F, Kolberg, H-C, Hadji, P, Tesch, H, Ettl, J, Wuerstlein, R, Lounsbury, D, Lux, MP, Lüftner, D, Wallwiener, M, Müller, V, Belleville, E, Janni, W, Fehm, TN, Wallwiener, D, Ganslandt, T, Ruebner, M, Beckmann, MW, Schneeweiss, A, Fasching, PA & Brucker, SY 2016, 'Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients', BREAST CANCER RES TR, vol. 158, no. 1, pp. 59-65. https://doi.org/10.1007/s10549-016-3850-8

APA

Hein, A., Gass, P., Walter, C. B., Taran, F-A., Hartkopf, A., Overkamp, F., Kolberg, H-C., Hadji, P., Tesch, H., Ettl, J., Wuerstlein, R., Lounsbury, D., Lux, M. P., Lüftner, D., Wallwiener, M., Müller, V., Belleville, E., Janni, W., Fehm, T. N., ... Brucker, S. Y. (2016). Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients. BREAST CANCER RES TR, 158(1), 59-65. https://doi.org/10.1007/s10549-016-3850-8

Vancouver

Hein A, Gass P, Walter CB, Taran F-A, Hartkopf A, Overkamp F 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 TR. 2016 Jul;158(1):59-65. https://doi.org/10.1007/s10549-016-3850-8

Bibtex

@article{8e9416c09dd649dbaea0e1fdde1a1f8c,
title = "Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients",
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.",
keywords = "Journal Article",
author = "Alexander Hein and Paul Gass and Walter, {Christina Barbara} and Florin-Andrei Taran and Andreas Hartkopf and Friedrich Overkamp and Hans-Christian Kolberg and Peyman Hadji and Hans Tesch and Johannes Ettl and Rachel Wuerstlein and Debra Lounsbury and Lux, {Michael P} and Diana L{\"u}ftner and Markus Wallwiener and Volkmar M{\"u}ller and Erik Belleville and Wolfgang Janni and Fehm, {Tanja N} and Diethelm Wallwiener and Thomas Ganslandt and Matthias Ruebner and Beckmann, {Matthias W} and Andreas Schneeweiss and Fasching, {Peter A} and Brucker, {Sara Y}",
year = "2016",
month = jul,
doi = "10.1007/s10549-016-3850-8",
language = "English",
volume = "158",
pages = "59--65",
journal = "BREAST CANCER RES TR",
issn = "0167-6806",
publisher = "Springer New York",
number = "1",

}

RIS

TY - JOUR

T1 - Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients

AU - Hein, Alexander

AU - Gass, Paul

AU - Walter, Christina Barbara

AU - Taran, Florin-Andrei

AU - Hartkopf, Andreas

AU - Overkamp, Friedrich

AU - Kolberg, Hans-Christian

AU - Hadji, Peyman

AU - Tesch, Hans

AU - Ettl, Johannes

AU - Wuerstlein, Rachel

AU - Lounsbury, Debra

AU - Lux, Michael P

AU - Lüftner, Diana

AU - Wallwiener, Markus

AU - Müller, Volkmar

AU - Belleville, Erik

AU - Janni, Wolfgang

AU - Fehm, Tanja N

AU - Wallwiener, Diethelm

AU - Ganslandt, Thomas

AU - Ruebner, Matthias

AU - Beckmann, Matthias W

AU - Schneeweiss, Andreas

AU - Fasching, Peter A

AU - Brucker, Sara Y

PY - 2016/7

Y1 - 2016/7

N2 - 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.

AB - 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.

KW - Journal Article

U2 - 10.1007/s10549-016-3850-8

DO - 10.1007/s10549-016-3850-8

M3 - SCORING: Journal article

C2 - 27283834

VL - 158

SP - 59

EP - 65

JO - BREAST CANCER RES TR

JF - BREAST CANCER RES TR

SN - 0167-6806

IS - 1

ER -