The question is whether we should follow a dogmatic evaluation of an FBC knowing that a personalized approach could provide us with valuable data. At OIA, we seek to increase the validity of this rather outdated population-based method in today’s age of technology.
Impact on public health: case example Sepsis
From a clinical perspective, it is not uncommon for the diagnosis of infection or sepsis to be ‘missed’ or delayed because the WBC blood test is ‘normal’, especially when the ‘baseline’ blood results of the individual are not established, providing no basis for comparison. In healthcare, blood tests are performed so infrequently, and because the data is not integrated into a centralized system, if at all, the data can be difficult to access. From a public health perspective, this would be invaluable in preventing deaths from sepsis. For reference, the Global Sepsis Alliance published that in the UK in 2021 there were 245,000 cases of sepsis, with 48,500 deaths, of which 14,000 were estimated to be preventable.
Not attempting to capture this data and investing in the digital infrastructure to integrate the data with other known health metrics is a colossal loss of opportunity to improve personalized care and health outcomes.
Immune System Monitoring: Opportunities
Emerging evidence supports the claim that variations in immune cells within the ‘normal’ range may have important health implications. A study by Shah et al, published in the British Journal of Medicine in 2017, pointed out that the total number of white blood cells in “healthy” individuals was found to be predictive of short-term and long-term risk of death, even when other known risk factors such as age, smoking, diabetes, high blood pressure, ethnicity and blood cholesterol level were taken into account. In this study of more than 194,000 people, those with higher “normal” white blood cell counts between 8.65 and 10.05 were almost three times more likely to die within 6 months than those with higher white blood cell counts between 8.65 and 10.05. Lower “normal” white blood cells were between 5.35 and 6.25. To further illustrate this, Alpert et al, published a 2019 article in Nature Medicine Journal which explained that the immune system of healthy individuals, as assessed by the number of a subset of their lymphocytes, which is a sub -type of white blood cell, was a better predictor of risk of death than age. This led to the development of the concept of immune age.
These studies, and there are several others, provide compelling reasons for a paradigm shift in how we monitor immune health from a population-based to a personalized approach. To better understand the disease and enable accelerated personalized diagnosis, follow-up and treatment, we need to redefine the standards when it comes to a patient’s individual physiology. As noted, this involves establishing an individual’s baseline values and generating health and disease data, to truly understand “what is a personal normal” and thereby bridge the gap between population and care. personalized health.
It is important to note that a white blood cell count is an accessible starting point for determining how to monitor immune health, but by no means exhaustive. How often an FBC should be repeated really depends on an individual’s “comorbidities” or current medical conditions, financial resources, and personal motivation to stratify health risk.
A call to action
The key to a deeper understanding of the immune system’s role in health and disease is therefore the systematic collection of longitudinal data that allows changes in the immune system to be tracked over time and correlated with internal and external factors. external, including symptoms. and sign of disease and stress of normal life. Fulfilling this promise requires three pillars: One: democratizing access to blood testing, so that people have convenient, accurate, frequent and affordable access to regular health monitoring; Two: collection of all relevant physiological and clinical data, such as clinical symptoms and treatments; and three: the ability to bring together, integrate, and analyze that data using state-of-the-art artificial intelligence and machine learning approaches to generate new insights. If done in an ethical and sustainable way, with the right changes in medical culture, this approach has the potential to dramatically transform the way we think about our own medical data.
Shah, AD, et al. White blood cell counts within the normal range and short- and long-term mortality: international comparisons of electronic health record cohorts in England and New Zealand. BMJ Open, 2017. 7(2): p. e013100.
Alpert, A., et al., A clinically meaningful measure of immune age derived from high-dimensional longitudinal surveillance. Nat Med, 2019. 25(3): p. 487-495.