Breast cancer care in the precision medicine era – prospects for patients and life insurers

With more than 2 million women diagnosed each year, breast cancer is the most common malignancy worldwide – resulting in almost 700,000 annual deaths. In the U.S. 1 in 8 women will be diagnosed with breast cancer during their lifetime. Despite significant mortality reduction over the past decades breast cancer continues to significantly impact the lives of countless patients and their families.

Besides addressing modifiable risk factors such as lifestyle (metabolic ill-health including obesity, physical inactivity, smoking, alcohol consumption), there are two principal ways to improve breast cancer outcomes, (1) earlier detection through screening, and (2) treatment advances. In both areas, more personalized and targeted approaches play an increasing role.

Breast cancer is one of the few malignancies for which effective screening programs exist. Earlier disease detection through mammography screening has shown to save lives and reduce treatment-associated morbidity. While there are significant benefits, risks such as overdiagnosis and false positive results and related issues (biopsies, anxiety) have been debated. Benefits and risks differ by age which currently is the major factor that determines timing of screening. However, not all women are at the same risk of the same type of breast cancer.

In the era of personalized medicine, screening is evolving towards a more individualized approach employing more precise risk profiles of women to inform a tailored decision as to who, when and how is screened. Ongoing clinical trials aim to demonstrate the feasibility and clinical applicability of such combined risk assessment tools considering classic risk factors (age; family history; alterations in known risk genes such as BRCA) and more comprehensive genetic data. This combined risk assessment could help to determine age at which screening should start and end, intervals (e.g., annual, biennial, etc.), and screening techniques (mammogram, MRI, or ultrasound). Still, there is an ongoing debate on the feasibility of this endeavor.

Although a multitude of risk-prediction models have been developed to facilitate stratification, implementing personalized screening still poses challenges including lack of evidence on feasibility, acceptability as well as legal and ethical aspects. Studies have shown that women are keen to receive risk information, and this information helps to increase attendance to subsequent screenings. Broader uptake of more innovative screening may also lead to higher breast cancer awareness – still a striking issue in the general population. Finally, leveraging advanced technologies such as 3-D mammography or artificial intelligence (AI)-based tools for cancer detection to increase diagnostic precision are currently being evaluated.

Current treatment trends show a shift towards a more personalized, more precise and less invasive therapeutic approach. The aim is to improve patient outcomes, reduce side effects and increase quality of life. Innovations in surgery and radiotherapy, systemic treatments have become more precise and address new cancer 'targets' by integrating comprehensive molecular tumor data into the development and application of innovative treatment modalities. Targeted drugs work by interfering with (e.g. blocking) mechanisms critical for the growth and survival of cancer cells, while immunotherapy comprises a set of drugs that help our immune system to recognize and fight cancer.

A multitude of targeted drugs have been approved (as single therapy or in combination with other treatments) and a variety of different molecules are being investigated. These include monoclonal antibodies, antibody-drug conjugates (ADCs), PARP inhibitors, and tyrosine kinase inhibitors:

• ADCs are currently revolutionizing the treatment of many different malignancies and represent a powerful new class of precision cancer drugs. They are a molecular "smart bomb" designed to deliver anti-cancer agents specifically into the tumor while theoretically sparing healthy cells. These "biological missiles" currently show promising results in trials involving patients with advanced breast cancer (e.g. HER2-low), and other challenging constellations such as TNBC. New-generation ADCs are being designed and evaluated in future studies including at earlier stages.

Immunotherapy includes checkpoint inhibitors (the most prominent group of immunotherapy drugs), adoptive cell transfer (CAR T cell therapy: immune cells are collected from the patient, re-engineered in the lab to attack the cancer, and given back to the patient), and cancer vaccines (the patient is vaccinated against their own cancer). So far, immunotherapy showed limited success in breast cancer therapy, but novel options and various combinations have increasingly shown promise in TNBC. Furthermore, instead of fighting the cancer itself, another approach has been to attack the tumor environment that helps the tumor to grow and survive.

To identify who may benefit from what kind of drug and their combination, personalizing treatment plans may not only require molecular tumor profiling but also analysis of tumor particles in the blood, i.e. liquid biopsies. In addition, these predictive tools may also be helpful to decide in which patients' chemotherapy can be safely avoided. Finally, researchers try to replace "static" with dynamic biomarkers, i.e. using the predictive value of sequential patterns over time, instead of one test result at one point in time. As lots of complex data is involved, AI models support the identification of patterns, potentially being applied in drug development, risk stratification, treatment planning, and treatment response evaluation.

These advances in breast cancer research have substantially improved the understanding of this disease, and novel treatments offer hope for patients. With more therapy options becoming available, breast cancer patients will have the largest and most effective treatment resources available ever although there are still challenges around implementation and access to optimal care.

If outcomes of one of the most common causes of claim in life insurance continue to improve, the industry could benefit as well. On the other hand, risk information from genetic testing may result in information asymmetry in jurisdictions where using this information for underwriting purposes is limited or prohibited. Being informed about these developments helps insurers to predict and respond to epidemiological trends and cope with the impact of genetic testing. It may also improve insurability where evidence-based and enhance further product development with the main goal to support patients and their families.