The manner in which we shop, handle our finances, watch television, and enjoy music has transformed beyond recognition since three decades past—yet as a physician, my approach to conducting tests, treating patients, and forecasting their prognoses remains rooted in the 1990s during which I first entered medical school.
Healthcare across the globe remains largely an analog service in our increasingly digital world. Therefore, even as these programs develop, Netflix implies that the recommendations provided by Amazon for products are tailored specifically for you. However, when it comes to your role as a patient, all our actions aim at catering to what would typically be best for an average person—essentially serving Mr. and Mrs. Average, which represents about 95 percent of the general populace.
For example, similar to every doctor, I will contrast my patient’s blood test results with those of the broader population. Based on this comparison, I'll prescribe a treatment regimen considering how typically, individuals with that specific condition react to such treatments, while also alerting my patient regarding the common side effects encountered by most people.
For the past 30 years, we’ve been waiting for the promised breakthrough in ‘personalised’ and ‘precision’ medicine, where a patient is treated as an individual and so truly benefits from the advances so prevalent in virtually every other aspect of our lives.
For instance, with personalized medicine, rather than relying on standard reference ranges for blood tests, we would consider your individual baseline and compare your test results against that.
It might occur earlier than anticipated, as recent research published in the journal Nature highlights the feasibility of this personalized method – indeed, you can begin experimenting with it right away (though I'll elaborate further on that shortly).
Why is this significant? Consider the patient I encountered lately in the emergency department, exhibiting several symptoms such as fatigue.
The blood test revealed his hemoglobin levels (indicating the quantity of red blood cells) stood at 139 g/L — which is within the typical range for the general population (135-180 g/L for men). Therefore, I told him not to worry as the findings were perfectly normal.
However, this only indicates that his outcomes fall within the span covered by 95 percent of average individuals – not necessarily what is typical for him. Yet since these figures aligned with those considered standard for the general populace, we assured him that all was well.
However, if his hemoglobin levels were previously at 150, his current result could potentially be the initial sign of either the onset of kidney disease or an undisclosed case of bowel cancer, leading to minor bleeding episodes. This exemplifies what we refer to as 'individualized' healthcare.
Precision medicine goes an extra mile. By leveraging advanced technologies like genetic analysis and artificial intelligence-powered diagnostic tools, it aims to foresee, ward off, and address illnesses with treatments uniquely suited to each individual. This approach contrasts starkly with providing standardized medications to all, opting instead for personalized therapies designed specifically for your physiology.
I remember a patient in his 30s who came to A&E with chest pains a few years ago.
Similar to conventional medical procedures, I initially estimated the likelihood of him having a heart attack based on my knowledge before conducting any tests. Subsequently, I analyzed the test results in light of this assessment. While his electrocardiogram (ECG), which monitors heart activity, wasn't entirely typical, it did not indicate concern. Additionally, his blood work came back normal.
Upon evaluating him and considering his account of chest discomfort, along with the absence of typical risks like hypertension, I assessed his likelihood of experiencing a heart attack to be minimal and subsequently released him.
Sadly, a few hours later, he died after a heart attack that I did not – and could not – have predicted he was going to have.
If I'd had access to the genetic testing options available today (although they aren’t commonly utilized in standard medical practices yet), I may have detected his genetic indicators, including genes linked to lipoprotein(a) and apolipoprotein E, both known to increase the likelihood of experiencing a heart attack. Additionally, the ECG that appeared as a benign variation could have been cross-referenced with an earlier test conducted during a regular health examination a couple of years prior.
Subsequently, the AI might have analyzed the minor alterations relative to his previous ECG and recognized them as indications of reduced blood supply to the heart—the initial symptoms thereof.
However, my analysis of his ECG relied on comparing it with those from others within the broader population.
Precision medicine also implies that if I had to administer treatment, I would customize his dosage based on how his specific genetic makeup influences drug metabolism.
This scenario is presently theoretical, yet it's not out of reach. The study I referenced indicates that it's imminent.
Released just last month in one of the leading academic journals, this pioneering research conducted by scientists affiliated with Massachusetts General Hospital and Harvard Medical School examined comprehensive blood count test data from over 12,000 healthy individuals across two decades.
What they discovered was truly impressive: every participant's blood levels stayed remarkably consistent over time, varying within a tight, personalized spectrum—the researchers referred to these as distinct 'hematologic set points'.
They discovered that even if your blood test results varied from your usual levels—even when still falling within ranges typically considered normal—it could indicate a possible health issue.
For instance, a white blood cell count that remained within the normal range but showed an increase compared to the patient’s previous levels was associated with a greater likelihood of mortality in the subsequent year.
The research indicated that not all 'normal' findings are comforting. For instance, if the level of hemoglobin in your red blood cells was slightly higher or lower than typical, it was linked to an increased chance of experiencing a heart attack or stroke over the next decade.
The potential impacts of this research are significant. Utilizing individual setpoints rather than general population means allows us to create more precise diagnostic tools for illnesses like diabetes and kidney disease, along with enhanced screening methods.
By abandoning 'one-size-fits-all' standardized thresholds for diagnostics and therapies—while having physicians monitor your individual health metrics over time—it could revolutionize medical care, enabling doctors to identify diseases at their initial, most curable phase.
This might also minimize unwarranted treatments, alleviating stress and avoiding procedures for ailments that individuals do not genuinely suffer from.
What steps can you take for your personal health before personalized and precision medicine becomes standard practice?
Initially, monitor your blood test results and focus on identifying patterns instead of simply determining whether they fall within normal ranges.
If your physician informs you that something is 'somewhat below normal' or 'somewhat above normal,' request a subsequent test in several months to monitor any changes.
It could be a single anomaly or part of an ongoing pattern. Likewise, if your blood test comes back as abnormal because it falls outside the range of 95 percent of the general population, there's no immediate cause for alarm – it might simply be typical for you.
The traditional approach of depending on population means will quickly seem as antiquated as using leeches to treat infections.
For now, the most effective action you can take is ensuring that the blood extracted from you is utilized in the optimal manner.
Read more
0 Comments