Evolving cancer prognoses require nuanced underwriting, balancing risk assessment with medical advancements for fair and accurate underwriting decisions.
Before you read: Test your knowledge of cancer and insurance.
There is no such thing as “good cancer.” Yet, thanks to advances in cancer detection and prevention, it has become a colloquial expression applied to some diagnoses.
“Good” is a relative term in this context. Despite the increasingly wide spectrum of outcomes, cancer is most often a life-altering diagnosis. Underwriting models are built on practices that reflect a nuanced understanding of the disease, incorporating evidence-based guidelines that address its short- and long-term morbidity and mortality risks.
As medical science advances and our understanding of cancer deepens, it is becoming clear that not all cancers are created equal. Some types demonstrate long-term health complications.
This article addresses cancer’s complex, multifaceted nature and examines the implications of the “Right to be Forgotten” (RTBF) legislation on the insurance industry.
In the context of life insurance, RTBF legislation prohibits the collection and/or use of health information for risk stratification from survivors of cancer and/or certain other chronic diseases after a certain period of time. Patient groups and legislators for RTBF argue that the adoption of this policy would expand cancer survivors’ access to financial services, especially mortgage insurance.
The conversation on this topic is bound to be sensitive. Therefore, to understand the impact of RTBF on the insurance industry, it is best to focus on the facts.
Cancer remains a leading cause of death worldwide. In Canada, it accounts for approximately 26% of all deaths; in the US, it is the second leading cause, after cardiovascular diseases (Figure 1).
This prevalence is also reflected in the insurance industry experience, where cancer is the primary cause of life claims (Figure 2).
For critical illness (CI) insurance, the impact is even more pronounced. For example, in Canada, cancer generates 72% of all CI claims.1
But there is reason for optimism. Data from the US Centers for Disease Control and Prevention shows that the cancer mortality rate had been on a steady decline since the turn of the century until a small uptick in 2023. In fact, the annual rate fell 27.5% from 2000 to 2022 (Figure 3).
The term “good cancer” is relative. No cancer diagnosis is welcomed, but some types have significantly better prognoses than others (Figure 4). Understanding this spectrum of severity is crucial for insurance underwriting.
Critical illness (CI) insurance cancer definitions are complex and often include numerous exclusions.
Full benefits are typically awarded for cancers meeting certain severity criteria, while premalignant conditions or early stage cancers may be excluded or only partially covered under the early intervention benefit or partial benefit CI.
The prognosis and treatment outcomes for different cancer types can vary widely, influenced by multiple factors such as the location of the tumor, the stage and grade of the cancer, and the genetic makeup of the cancer cells.
This variability necessitates a nuanced approach to risk assessment in insurance underwriting. Two case studies illustrate the complexity and highlight the challenges insurers can face.
A female, age 45, has a history of stage 1 papillary thyroid cancer (PTC), a well-differentiated form of thyroid cancer, diagnosed in 2023. She received adequate treatment and follow-up consults have been favorable with no recurrences.
Is this a “good cancer” from an insurance perspective?
This woman’s pathology report noted tall cell morphology (TC-PTC). Well-differentiated classic PTC has an excellent prognosis, with a 10-year survival rate of 97%-99%, which supports a standard offer after a brief six-month postponement post completion of treatment. But the five-year disease-specific survival rate for this variant of PTC indicated on this woman’s pathology report is significantly less: 81.9%-93%.2
But tall cell thyroid cancers can differ. Some can be quite aggressive, while others behave as classic PTC. The natural history of the disease in the first few years post-diagnosis will give a good indication of the specific outcome, prognosis, and longer-term survival rates.
This case study demonstrates how even cancer types with excellent prognoses can have subtypes that are more aggressive. Thorough cancer risk assessment requires underwriters to delve deeper into medical reports and research.
A 60-year-old male nonsmoker is seeking life insurance coverage. He has a recent history of Stage 2 lung adenocarcinoma, diagnosed in February 2024. He received appropriate treatment and is doing well so far.
Underwriting manuals indicated coverage should be declined, guidelines which the underwriter applied.
The man filed a complaint as to why he was declined. He was told by his oncologist that his one-year survival rate was approximately 80%, which seemed to him a positive outlook. From his perspective, he had a “good cancer” distinct from more lethal varieties.
But assessing risk in insurance is not a short-term endeavor. Life insurance requires evidence-based assessment of long-term health risks and survival rates that reflect advances in cancer outcomes and prognosis. A one-year survival rate means little when assessing risk for 10- to 30-year life policies.
Cancer statistics often use an overall five-year or 10-year survival rate – the percentage of people who survive a certain type of cancer for a specific amount of time. For example, the overall five-year survival rate for localized lung adenocarcinoma is around 65%. For regional lung adenocarcinoma, that number drops to 37%.
Risk in insurance medicine is often expressed as a mortality ratio (actual mortality rate/expected mortality rate). One of the key questions for insurers is how an applicant’s mortality rate, after a diagnosis of a certain medical condition, compares to someone of the same demographic without the same disease. This leads to Kaplan-Meier survival curves, which are used to estimate the survival function. Figure 5 looks at comparative hypothetical survival rates for someone aged 55 without disease, with mild disease and advanced disease.
It is obvious that someone without a disease has a better initial survival rate than someone with an advanced form. But what about at Year 5 or Year 10? The steeper the drop-off for someone with mild or advanced forms of a disease compared to someone of the same age without the disease, the greater the mortality risk and the more likely that application will be denied.
Looking at a study on non-small cell lung cancer from Korea (Figure 6), the five-year survival curve is quite steep, indicating a higher long-term mortality rate, i.e., at Year 5 compared to one year post diagnosis.3
With this evidence, it was possible to explain to this applicant why his insurance submission was denied; his mortality ratio was exceedingly high, and making an offer one year after a diagnosis of stage 2 lung adenocarcinoma was not a financially viable decision. Furthermore, the five- and 10-year mortality ratios calculated by applying classical actuarial and insurance medicine methods were very high (exceeding 400%) and moderately increased (exceeding 200%), demonstrating an increased short- and long-term risk.
Fast-forward 10 years. Are the medical histories of the two people in our case studies still relevant to an insurer? The thyroid cancer case would qualify for a standard offer, while the lung cancer history demonstrates a long tail risk. How can insurers make evidence-based decisions if parts of the medical record for a disease such as lung cancer with long-term health implications are unavailable?
That is the challenge of RTBF legislation, which has gained traction in several European countries. This legislation aims to protect disease survivors from potential discrimination in financial services, particularly in obtaining life insurance coverage.
RTBF prohibits insurers from considering a person’s cancer history in risk assessment after a specified period following successful treatment. France pioneered this legislation in 2016 with Loi Sapin 2.4 Belgium followed suit in 2019,5 and Luxembourg and the Netherlands adopted similar measures in 20206 and 2021,7 respectively.
This legislation primarily applies to life insurance associated with mortgage loans, though in some countries it extends to other types of insurance (e.g., critical illness, disability).
Resulting industry impacts include the following:
Looking ahead, some countries are considering extending RTBF to other chronic diseases. The desire to ensure survivors’ access to financial services is well intentioned, but it needs to be balanced with insurers’ need for accurate underwriting assessment and risk-based pricing.
The insurance industry continues to assess the long-term implications of RTBF on risk pools and pricing. But as RTBF gains traction in Europe, insurers operating globally must navigate increasingly varied regulatory frameworks and market characteristics, including the effects on distribution channels and anti-selective behavior.
As our understanding of cancer evolves and societal attitudes shift, the insurance industry must adapt. This may involve more nuanced policy designs, refined underwriting practices, and a deeper engagement with medical advancements in treatment and prognoses. The potential for widespread adoption of RTBF legislation should be considered throughout this process.
Countries such as US, Canada, and EU countries are seeing a higher number of cancer survivors, sitting at approximately 5% of the general population; this percentage is expected to grow. However, medical evidence confirms that despite significant advances in screening, diagnosis, and treatment, some cancer survivors have an increased long-term mortality risk, leading to the need to deviate from applying standard rates.
The future of cancer risk assessment will likely involve more personalized approaches and advanced analytics to provide more accurate and fair underwriting decisions. This must be balanced with ethical considerations and regulatory compliance to strike a balance between customer protection and industry viability.
To better navigate the changing insurance industry landscape medical directors and underwriters would be well served to upgrade their technical expertise and use available risk stratification tools and statistical modeling methods to refine their decision-making processes.
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