Decoding Your Lab Tests
Tommi Vaskivuo
Chief Medical Officer at SYNLAB North Europe. Experience from all aspects of the clinical laboratory, from R&D and laboratory operations to the end-users point-of-view. Deep insight into the use and economics of laboratory testing in and outside of the clinical setting. Expert integrator of medical needs, laboratory performance and healthcare IT solutions. Has published from genetics and molecular biology to clinical trials and practical laboratory medicine.
Tommi Vaskivuo, Chief Medical Officer at Synlab, explores the
You can't manage what you don't measure. You have to measure something to know where you are going, and if you are getting better or worse.
Summary
- Laboratory tests provide essential objective data to manage health, allowing individuals to track progress, establish accurate diagnoses, and monitor if medical conditions are improving. - Reference ranges represent 95% of healthy individuals; statistically, 5% of healthy people may fall outside these ranges, meaning an outlier result does not always indicate a medical problem. - Curated laboratory panels for specific needs—such as athlete performance, heart health, or anemia—simplify the selection process and help monitor complex biological functions more effectively. - Advanced options like pharmacogenetic testing enable personalized drug dosing based on genetic metabolism, while ceramide tests provide more accurate cardiovascular risk assessments than cholesterol. - Conducting annual laboratory tests establishes a personal health baseline, making it easier to identify long-term trends and helping medical professionals recognize significant health changes.
Article
Decoding Your Lab Tests
Personalized Diagnostics And The Quiet Revolution In Health Optimization
At Biohacker Summit 2018 Tallinn, held on 15 September 2018 in Tallinn, Estonia, Tommi Vaskivuo offered a deceptively simple proposition: if people wanted to manage their health with any seriousness, they first had to learn how to measure it.
Vaskivuo, Chief Medical Officer at SYNLAB North Europe, spoke not in the language of miracle cures or fashionable wellness promises, but in the cooler, more exacting vocabulary of laboratory medicine. His presentation, *Decoding Your Lab Tests*, argued that modern diagnostics had become one of the most powerful tools in personal health optimization, not because they promised certainty, but because they made it possible to track the body with unprecedented precision.
“Taking a basic test panel once a year is a good intervention to understand your overall status and establish a personal background for your health,” Vaskivuo said.
It was, in many ways, a plea for discipline over intuition.
The Case For Measuring What The Body Is Doing
The central idea of Vaskivuo’s talk was almost managerial in its clarity: what could not be measured could not be meaningfully managed. In medicine, that principle carried particular force. Blood tests, he said, did more than generate numbers. They helped establish diagnosis, monitor whether a condition was improving or worsening, and create a longitudinal picture of health that symptoms alone often failed to reveal.
Laboratory diagnostics, in this view, became a form of biological memory. A single test could provide a snapshot. A decade of tests could tell a story.
That distinction mattered. Vaskivuo stressed that trends over time often revealed more than isolated results. “Knowing your health trends over time tells you and your doctor quite a lot and makes it easier to reach the right medical conclusions,” he said.
For patients arriving at a clinic with no prior baseline, interpretation was necessarily more difficult. For those who had tracked hemoglobin, blood sugar or other markers over the years, change itself became clinically meaningful.
Precision Improved, Trust Increased
Part of the confidence Vaskivuo placed in laboratory testing rested on a technological shift that had unfolded over decades. He pointed to glucose testing as an example of how modern diagnostics had become markedly more reliable. In the 1990s and early 2000s, error rates could exceed five or even seven percent. By 2018, he said, that margin had fallen to roughly two percent.
To a lay audience, the improvement might have sounded incremental. In practice, it was profound. When individuals monitored biomarkers repeatedly, the difference between noise and genuine physiological change could determine whether a doctor adjusted treatment, investigated disease or offered reassurance.
The hidden machinery of laboratory medicine, Vaskivuo suggested, deserved more public understanding than it usually received. A lab result was not simply a number appearing on a page. It was the final output of a complex chain of sampling, analysis, calibration and quality control. The credibility of personalized medicine depended, in part, on the rigor of that invisible system.
The Myth Of The “Normal” Result
If the first lesson of the talk was that numbers mattered, the second was that numbers could also mislead.
Much of the confusion around blood tests, Vaskivuo explained, came from reference ranges. These ranges are typically built from measurements taken from large groups of healthy people. The laboratory then defines the “normal” interval to include 95 percent of that healthy population.
The implication was striking and often overlooked: five percent of healthy people would, by definition, fall outside the range.
“Reference ranges represent ninety-five percent of healthy people, meaning you can still be healthy even if your result is outside that range,” Vaskivuo said.
Statistically, he noted, an average person could expect roughly one in every twenty test results to sit outside the reference range even if nothing was medically wrong. A flagged result, then, was not automatically evidence of illness. It was a signal that required context, judgment and, where symptoms or risk factors were present, proper medical follow-up.
“If you want to optimize your health, understand that each of us is an individual and we all have our own variations,” he said.
This was the deeper philosophical turn in the lecture: the body was not an average, and health could not always be read by comparing a person to a population mean.
From Broad Screening To Curated Panels
Vaskivuo also addressed a more practical problem. If modern diagnostic providers could offer thousands of individual tests, how was anyone supposed to know where to begin?
His answer was the curated panel: groups of tests assembled around specific goals or conditions. General health panels offered a broad overview of biological function. Athlete panels focused more closely on muscles, recovery and performance. More targeted packages addressed concerns such as heart health, anemia or allergies.
The logic was not merely commercial convenience. It was an attempt to make complexity usable.
Rather than asking people to navigate an enormous catalogue of biomarkers, these panels created pathways through the data. For the health-conscious but medically untrained, that structure could be the difference between meaningful monitoring and expensive confusion.
Personalized Medicine Moved From Theory To Practice
Where the talk became most forward-looking was in its discussion of testing that aimed not merely to identify disease, but to tailor care to the individual.
One example was pharmacogenetic testing, which analyzes genes involved in drug metabolism. Vaskivuo described how such testing could reveal whether a person processed certain medications quickly or slowly, allowing treatment to be adjusted more precisely than standard dosing guidelines permitted.
“Personalized testing allows you to understand your own biology so you can adjust treatments based on your unique needs rather than an average person's needs,” he said.
This was a substantial challenge to one-size-fits-all medicine. Two patients could receive the same prescription, yet their bodies might metabolize that drug at very different rates. In that gap between standard dosage and individual biology lay the promise of pharmacogenetics.
Vaskivuo said these results could even be accessed through a mobile app, enabling patients to consult their metabolic profile when discussing medications with doctors or pharmacists. The image was unmistakably modern: the laboratory report no longer buried in a folder, but carried in a pocket, ready to shape real-time decisions.
Why Ceramides Could Matter More Than Cholesterol
The second example Vaskivuo offered was ceramide testing, which he framed as a more sophisticated successor to traditional cholesterol markers.
For decades, public understanding of cardiovascular risk had revolved around HDL and LDL cholesterol. Those measures remained useful, but Vaskivuo argued they were no longer the most refined tools available. Ceramides, a class of lipid molecules measured in blood, could provide a more accurate picture of risk for cardiovascular disease and type 2 diabetes.
It was a subtle but important shift. Rather than discarding older markers altogether, the newer test promised to deepen interpretation, moving risk assessment closer to the complexity of actual human biology.
In a health culture still saturated with simplistic narratives about “good” and “bad” cholesterol, Vaskivuo’s point landed as both corrective and invitation: better diagnostics did not merely create more data, they could create better judgment.
The Annual Baseline As A Form Of Prevention
When asked how often he personally took blood tests, Vaskivuo’s answer was strikingly modest. Once a year, he said, he usually took a basic panel.
The recommendation did not carry the glamour of extreme biohacking. Yet that was precisely its strength. Annual testing, in his account, was not about obsessively searching for pathology. It was about building a baseline while healthy, so that future deviations would be easier to spot and easier to interpret.
In an age of wellness maximalism, this was a restrained and medically grounded form of self-knowledge.
The lesson of *Decoding Your Lab Tests* was not that everyone should chase every available biomarker. It was that intelligent, periodic testing could anchor health decisions in evidence rather than guesswork.
At Biohacker Summit 2018 Tallinn, Tommi Vaskivuo made the case that the future of health optimization would belong not only to those who wanted more data, but to those who learned how to read it.
Part of Biohacker Summit 2018 Tallinn