TY - JOUR
T1 - (Very) Early technology assessment and translation of predictive biomarkers in breast cancer
AU - Miquel-Cases, Anna
AU - Schouten, Philip C
AU - Steuten, Lotte M G
AU - Retèl, Valesca P
AU - Linn, Sabine C
AU - van Harten, Wim H
N1 - Publisher Copyright:
© 2016 The Author(s)
PY - 2017/1
Y1 - 2017/1
N2 - Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical validity and clinical utility. While attaining analytical and clinical validity is relatively straightforward, by following methodological recommendations, the achievement of clinical utility is extremely challenging. It requires demonstrating three associations: the biomarker with the outcome (prognostic association), the effect of treatment independent of the biomarker, and the differential treatment effect between the prognostic and the predictive biomarker (predictive association). In addition, economical, ethical, regulatory, organizational and patient/doctor-related aspects are hampering the translational process. Traditionally, these aspects do not receive much attention until formal approval or reimbursement of a biomarker test (informed by Health Technology Assessment (HTA)) is at stake, at which point the clinical utility and sometimes price of the test can hardly be influenced anymore. When HTA analyses are performed earlier, during biomarker research and development, they may prevent further development of those biomarkers unlikely to ever provide sufficient added value to society, and rather facilitate translation of the promising ones. Early HTA is particularly relevant for the predictive biomarker field, as expensive medicines are under pressure and the need for biomarkers to guide their appropriate use is huge. Closer interaction between clinical researchers and HTA experts throughout the translational research process will ensure that available data and methodologies will be used most efficiently to facilitate biomarker translation.
AB - Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical validity and clinical utility. While attaining analytical and clinical validity is relatively straightforward, by following methodological recommendations, the achievement of clinical utility is extremely challenging. It requires demonstrating three associations: the biomarker with the outcome (prognostic association), the effect of treatment independent of the biomarker, and the differential treatment effect between the prognostic and the predictive biomarker (predictive association). In addition, economical, ethical, regulatory, organizational and patient/doctor-related aspects are hampering the translational process. Traditionally, these aspects do not receive much attention until formal approval or reimbursement of a biomarker test (informed by Health Technology Assessment (HTA)) is at stake, at which point the clinical utility and sometimes price of the test can hardly be influenced anymore. When HTA analyses are performed earlier, during biomarker research and development, they may prevent further development of those biomarkers unlikely to ever provide sufficient added value to society, and rather facilitate translation of the promising ones. Early HTA is particularly relevant for the predictive biomarker field, as expensive medicines are under pressure and the need for biomarkers to guide their appropriate use is huge. Closer interaction between clinical researchers and HTA experts throughout the translational research process will ensure that available data and methodologies will be used most efficiently to facilitate biomarker translation.
KW - Biomarkers, Tumor
KW - Breast Neoplasms
KW - Breast cancer
KW - Health Technology Assessment
KW - Humans
KW - Predictive Value of Tests
KW - Predictive biomarkers
KW - Prognosis
KW - Technology Assessment, Biomedical
UR - http://www.scopus.com/inward/record.url?scp=85006356214&partnerID=8YFLogxK
U2 - 10.1016/j.ctrv.2016.11.008
DO - 10.1016/j.ctrv.2016.11.008
M3 - Article
C2 - 27992844
SN - 0305-7372
VL - 52
SP - 117
EP - 127
JO - Cancer Treatment Reviews
JF - Cancer Treatment Reviews
ER -