When the Lab Test Replaces the Patient: The Difference Between a Causal Factor and a Causal System

The analytical triumph of twentieth-century medicine created a recurrent clinical temptation. Once a measurable variable was shown to predict disease or participate in its pathogenesis, that variable gradually began to substitute for the disease process itself.

Cholesterol, blood pressure, glucose, and amyloid transformed modern medicine and remain indispensable. Yet they also encouraged a subtle conceptual shortcut: treating an isolated number became easier than understanding the biological system in which that number acted.

The problem is not that these biomarkers are irrelevant or uncausal. ApoB-containing lipoproteins, elevated blood pressure, chronic hyperglycemia, and amyloid pathology became central measurable targets of modern medicine and remain indispensable to clinical practice.

The deeper problem lies elsewhere: a causal factor is not identical to a causal system.

A causal factor is not the whole disease

Atherosclerosis provides the classical example. A century of experimental work, human genetics, epidemiology, and randomized trials has established the causal role of apolipoprotein B-containing lipoproteins. Yet an artery is not a passive drainage pipe.

Atherogenesis begins when circulating apoB-containing particles enter and become retained within the arterial intima. There they interact with the extracellular matrix, undergo modification, promote endothelial activation, recruit monocytes and macrophages, generate foam cells, and stimulate smooth-muscle and inflammatory responses.

But the process does not remain confined to the arterial wall.

Atherosclerosis emerges from a dynamic interaction between systemic lipid metabolism, arterial-wall injury and retention, and inflammation. Although plaque formation is anatomically localized, the inflammatory process is not. Circulating immune cells, cytokine signaling, hepatic acute-phase responses, bone-marrow-derived cell recruitment, and metabolic influences connect the arterial lesion to a broader systemic response.

Particle concentration and duration of exposure matter, but so do hemodynamics, extracellular-matrix properties, inflammatory signaling, smoking, metabolic state, genetics, blood pressure, and time.

Similar circulating lipid concentrations can therefore coexist with very different disease burdens. That does not make lipoproteins noncausal. It means that causality does not equal causal sufficiency.

This distinction becomes clinically important when estimating individual risk. Two patients may present with similar lipid levels yet possess very different cumulative exposures and plaque burdens.

Coronary artery calcium scoring illustrates the difference. A calcium score of zero does not make an elevated lipid profile harmless, nor does it exclude noncalcified plaque, but it provides objective information about the current burden of calcified coronary disease that circulating lipid concentrations alone cannot reveal.

Personalization begins when exposure and tissue state are evaluated together.

When lowering the number does not automatically improve the patient

A second error appears when a causal relationship is translated into a simplistic therapeutic assumption: if lowering an abnormal number helps, lowering it further must always help more.

Sometimes it does. Often the relationship is more complex.

Type 2 diabetes exposed this problem clearly. Chronic hyperglycemia is harmful and contributes directly to microvascular injury. Yet in the ACCORD trial, intensive pharmacological lowering of glycated hemoglobin in high-risk patients with established type 2 diabetes did not improve survival and was stopped early because mortality was higher in the intensive-treatment arm.

The lesson was not that glucose was unimportant. It demonstrated that three distinct questions had been conflated:

Is the target biologically important?

Can treatment change it?

Does changing it through this specific intervention improve an outcome that truly matters to the patient?

These are related questions, but they are not identical. A biologically valid target is not automatically a perfect therapeutic surrogate.

Hypertension illustrates the same principle from another perspective. Chronically elevated blood pressure causes vascular and target-organ damage, and lowering it reduces stroke, heart failure, and cardiovascular risk.

The SPRINT trial demonstrated substantial benefit from intensive systolic blood-pressure reduction in appropriately selected high-risk adults. Yet more intensive treatment also increased rates of hypotension, syncope, acute kidney injury, and electrolyte disturbances.

Again, this does not argue against treating hypertension. It demonstrates that blood pressure is both a damaging mechanical force and an essential regulated variable required for organ perfusion.

The clinical objective is not simply to reach the lowest possible number on a gauge. It is to achieve the greatest net benefit for the individual patient.

Biomarker clearance is not biological recovery

Alzheimer disease provides perhaps the clearest contemporary example.

For decades, beta-amyloid occupied the center of neurodegenerative research. Recent monoclonal antibodies such as lecanemab and donanemab have demonstrated that amyloid plaques can be substantially reduced. Clinical decline also slows, but only modestly.

The contrast is striking: the biomarker changes dramatically, while the clinical outcome changes far less.

This does not disprove the biological involvement of amyloid. On the contrary, the trials support its role in the pathogenic pathway. But they also reveal the limits of treating one component of an advanced biological system.

By the time symptomatic Alzheimer disease is established, amyloid pathology coexists with tau pathology, synaptic dysfunction, neuronal injury, neuroinflammation, vascular contributions, and declining network reserve.

Removing one upstream pathological component cannot be expected to reverse everything that has already developed downstream.

The biomarker mattered, but the biomarker was not the whole disease.

The real meaning of personalization

The objective of personalized medicine is not to discard biomarkers or stop treating them. Modifying genuine causal factors has prevented enormous morbidity and saved millions of lives.

The error occurs when the measurable variable becomes an unquestioned substitute for the living patient.

A lower LDL level is not identical to a healthy artery.

A lower blood pressure reading is not identical to preserved organ function.

A lower glycated hemoglobin level is not identical to longer survival.

A lower amyloid burden is not identical to preserved cognition.

The next step in clinical medicine is not to abandon population evidence, but to place it inside the biological context of the individual.

The diagnostic question must move beyond asking what number is abnormal on a laboratory sheet.

More about this topic can be found in our books on Our Books on Google Play and related articles in the Index.

Mykola Iabluchanskyi together with Andriy Yabluchanskiy