Linking Precision Medicine and Public Health: An Economic Perspective on Mammography Screening

Research output: ThesisDoctoral Thesis



Publication details

QualificationDoctor of Philosophy
Awarding Institution
  • Ludwig-Maximilians-Universität München
  • Leidl, Reiner, Supervisor, External person
  • Sundmacher, Leonie, Supervisor, External person
  • Verlag Dr. Hut
Place of PublicationMunich
Original languageEnglish
Print ISBNs978-3-8439-3707-8


Breast cancer is the most common form of cancer found in women. As a response to the high burden of disease, many countries have established mammography screening programs. These programs aim at detecting the early onset of breast cancer. Women between 50 and 70 years, the population with the highest probability of developing breast cancer, are routinely invited to attend mammography screening.

Mammography screening is subject to controversy due to a high probability of harmful screening effects, most importantly the false identification of breast cancer among healthy women. One of the potential improvement could lie in the selecting women at high risk and reduce efforts among women who are less likely to benefit from screening. This risk selection process is called ‘precision screening’. By focusing on those with higher risk, precision screening aims at finding a better balance between screening benefits and harmful effects and thus improve public health outcomes.

Until recently, ‘precision medicine’ approaches focused primarily on genetic risk components. Genetic risk was found to be helpful in explaining the very early disease onset in younger women, but genetic risk does not explain the variation in risk found in women between the age of 50 and 70, who are invited to mammography screening. Other non-genetic risk factors, such as biologic or behavioral risks, show potential to explain some of the variation in risk.

The question arises whether precision screening could be an alternative to uniform mammography screening and if precision screening can and should incorporate factors beyond genetic risk?

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