Munich Re look at improving Cancer outcomes
As part of Munich Re’s Life Science Report 2025, they have investigated the projected impact of advances in cancer treatment and research. These advances will change how cancers are defined, prevented, diagnosed and treated and are expected to significantly improve cancer mortality.
Cancer is the leading cause of death among policyholders for most insurers worldwide, as such it demands investigation. Much progress has been made in the past couple of decades to improve cancer mortality, through both reducing cancer risk factors (such as the dramatic downturn in tobacco use) and better diagnosis and treatment. Mortality improvement trends are expected to accelerate as our understanding of cancer genetics are combined with artificial intelligence (AI).
AI will be used to both improve cancer risk prevention and diagnostics. AI analysis of an individual’s personal information such as health data, family history, genetic and epigenetic profiles, microbiome, living environment and exposure history, sometimes called a statistical biopsy, will give a better understanding of risk for a wide range of cancers. This could potentially allow for a personalised approach to risks, behaviours, and identification of which strategies may be most effective in addressing these factors.
Being able to diagnose cancer more accurately, and at earlier stages, should improve cancer mortality. AI has already led to refinements in imaging studies, and in blood, urine and tissue samples. AI can also be used to analyse the tumour’s genetic pattern, other associated biomarkers and an individual’s risk profile to allow for better prognosis and management approach. AI’s ability to recognise patters not apparent to humans will help with diagnostic tools such as imaging studies, pathologic specimen interpretation and photograph analysis.
More effective screening approaches will lead to earlier cancer diagnosis and improved cancer mortality. An important technology, ‘liquid biopsy’, is currently used to analyse fluids to look for markers indicating the presence of a cancer, typically used to detect residual cancer after treatment or recurrence. If a liquid biopsy test that can screen for multiple cancers in asymptomatic individuals could be brought to market at a price point where it is accessible to the masses, it would be a game changer. Though it would also raise concerns about over-diagnosis and surveillance bias, as some identified cancers may never post a significant mortality risk.
The combination of AI and genomic analysis of tumour cells and immune cells has led to the development of targeted treatments that exploit specific genetic patterns. These treatments are more precise and safer than chemotherapy, with the four key categories of therapies emerging being targeted monoclonal antibodies, immune checkpoint inhibitors, cancer vaccines and adoptive cell immunotherapy.
With potential changes in how cancers are classified, product definitions will need to be modified. Instead of being classified based on their tissue of origin, it’s expected new cancer tests will be able to categorise cancers based on their underlying genetic causes – potentially leading to thousands of cancer subtypes.
Where previously terminal cancers become able to be managed and instead turn into chronic disease, there may be implications for living benefits products. Reduced mortality should be favourable for life insurances businesses, though the costs of more sophisticated, individualised cancer treatments may have a negative cost impact on health insurance businesses. Munich Re predict that advances in diagnosis and changes in diagnostic criteria are going to increase cancer incidence rates in the short term, but may decrease critical illness rates if major advances in cancer prevention are realised.
AI will also have implications for underwriting. AI-based diagnosis is likely to be more accurate and predictive than current methods, with fewer false positive and false negative results, enabling risk to be better assessed. Better monitoring post-cancer treatment will mean recurrence risk can be more accurately assessed too.
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