PRAEGNANT Study: Home PRAEGNANT

PRAEGNANT study

PRAEGNANT - Prospective Academic translational research network for the optimization of oncological health care quality in the advanced setting. This german study network was set up to take account of some of the recent developments in molecular medicine in the treatment of patients with metastatic breast cancer.

It is an academic registry and translational diagnostics study with the aim to build a healthcare research data base with the objective:

to carry out molecular tests under study conditions
to identify suitable breast cancer patients for clinical trials based on molecular testing
to identify breast cancer patients suitable for clinical trials based on conventional inclusion criteria
to record treatment-induced toxicities and patient´s quality of life in routine clinical practice
to record, show and benchmark the reality of medical care provided to patients with advanced/metastatic breast cancer

PRAEGNANT is subdivided into three main phases. In phase I, only advanced breast cancer patients are included. In phases II and III the data base should be expanded by (neo-)adjuvant breast cancer patients and in the end by other tumor entities.

The protocol was amended and updated in March 2019 reaching Phase II to enroll patients with the diagnosis of early breast cancer in the neoadjuvant or adjuvant curative treatment setting.

Patient information

If you are interested to take part in the study. Please don´t hesitate to contact a study center in your vicinity.

Some fundamental backgrund information:

your peronal data will be treated confidentially and are transferred anonimysed
you are asked to give a blood sample, which is needed for biomarker detection
the achieved therapy successes in this study will help to improve breast cancer treatment
to record treatment-induced toxicities and patient´s quality of life in routine clinical practice
to record, show and benchmark the reality of medical care provided to patients with advanced/metastatic breast cancer

What´s your benefit?
Your personal biomarker profile will be given to your treating phyisician, if you wish so. Then your treatment may be changed or you can be introduced in other clinical studies which show a good prognosis according to your biomarker profile.

All treatements and collected data will be treated confidentially.

news

Research Proposals

Submitted Sub-Protocols

Mutation analysis of putatively clinically relevant genes within cfDNA of PRAEGNANT study participants	Burwinkel et al.
Thyroid Dysfunction in Metastasized Breast Cancer - Prevalence and Clinical Impact	Heublein et al.
Patient identification for the clinical trial EMBRACA by real time utilization of data within the PRAEGNANT network for metastatic breast cancer patients.	Hein A, Fasching PA, Brucker SY
Implementation and Feasibility of Electronic Patient Reported Outcome (ePRO) Data Entry in local advanced and metastatic breast cancer patients	Gass P, Wallwiender M
PRAEGNANT CAM: Attitude, demand and use of complementary and integrative medicine across German metastatic breast cancer patients	Hack C, Wallwiener M
Incidence and impact of Cytomegalovirus (CMV) infections in patients with metastatic breast cancer (MBC) and brain metastases (BM) within the PRAEGNANT network.	Müller et al.
Quality of Life Assessment in Breast Cancer Patients with Brain Metastases	Müller et al.
Companion diagnostics for aromatase inhibitor treatment using the estrogen receptor pathway	Müller et al.
Frequency of high and moderate penetrance germline mutations in breast cancer susceptibility genes in leukocyte DNA and circulating free (cf) nucleic acids.	Fasching PA, Couch FJ et al.
Discovery Study of Mutations in Tumor and circulating DNA by sequencing methods.	Huober J, Schramm A
Big Data Utilization with PRAEGNANT Data	Fasching PA
Evaluation of quality of documentation for breast centre certification by use of electronic case report form (eCRF)	Gass P
PRAEGNANT mTNBC Immunoscore Identification of immune biomarkers in metastatic triple negative breast cancer patients	Lüftner D, Busse A, Wagner K
Factors determing physicians choice of chemotherapy over antihormonal therapy in hormone receptor positive metastatic breast cancer patients – an analysis of first and second line breast cancer patients within PRAEGNANT	Hein A, Fasching PA
Evaluation of the course of treatment of patients with metastatic breast cancer within PRAEGNANT	Huober J, Fasching PA
PEPPER PiiA ehealth Portal for individualized treatment monitoring and patient engagement in oncology research focused on capture of patient reported outcomes within the PRAEGNANT study Network	Wallwiener M
Clonal evolution and subclonal characterization of breast cancer in axillary and distant metastases	Sinn P
BREAKOUT – International Breast Cancer Biomarker, Standard of Care and Real World Outcomes Study / PRAEGNANT data pooling	Fasching PA, Belleville E
MESI-STRAT: Systems Medicine of Metabolic-Signaling networks: A new Concept for Breast Cancer Patient Stratification	Schott S, Schneeweiss A, Opitz C
Influence of a metastatic tumor progression on Quality of Life in patients with advanced breast cancer	Wallwiener M, Fasching PA, Müller V
Comprehensive analysis of real-world patterns of concurrent advanced breast cancer treatment patterns at the Department of Gynecology and Obstetrics of the University Hospital Ulm	Huober J
Predicting the response of CDK4/6 inhibitors in metastatic breast cancer: Immunoscore and DNMT1-Expression	Ettl J, Bronger H

Publications

Fasching PA et al. Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network. Geburtshilfe Frauenheilkd. 2015 Jan;75(1):41-50.
Hein A 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. 2016 Jul;158(1):59-65.
Yinchong Yong et al. Predictive Clinical Decision Support System with RNN Encoding and Tensor Decoding. December 2016
Fremd C et al. Use of complementary and integrative medicine among German breast cancer patients: predictors and implications for patient care within the PRAEGNANT study network. Arch Gynecol Obstet. 2017 May;295(5):1239-1245.
Yinchong Yong et al. Modeling Clinical Decisions with Multinomial Hierarchical Classification
Yinchong Yong et al. Predictive Modeling of Therapy Decisions in Metastatic Breast Cancer with Recurrent Neural Network Encoder and Multinomial Hierarchical Regression Decoder
Wallwiener et al. Implementation and Feasibility of Electronic Patient-Reported Outcome (ePRO) Data Entry in the PRAEGNANT Real-Time Advanced and Metastatic Breast Cancer Registry. Geburtshilfe Frauenheilkd. 2017 Aug;77(8):870-878
Hartkopf AD et al. Treatment landscape of advanced breast cancer patients with hormone receptor positive HER2 negative tumors – Data from the German PRAEGNANT breast cancer registry. Breast. 2018 Feb;37:42-51.
Müller V et al. Impact of disease progression on health-related quality of life in patients with metastatic breast cancer in the PRAEGNANT breast cancer registry. Breast. 2018 Feb;37:154-160.
Fasching PA, Hartkopf AD et al. Efficacy of neoadjuvant pertuzumab in addition to chemotherapy and trastuzumab in routine clinical treatment of patients with primary breast cancer: a multicentric analysis. Breast Cancer Res and Treat. 2019 Jan;173(2):319-328
Lux MP, Nabieva N et al. Therapy landscape of patients with metastatic, HER2 positive breast cancer – data from the real-world breast cancer registry PRAEGNANT. Cancers. 2018 Dec 21;11(1)