The original study, led by Ludovic Semenzato and colleagues and published in JAMA Network Open, drew on the French National Healthcare Data System, known as SNDS, which records healthcare reimbursements for nearly the entire population. The researchers followed more than 33 million adults aged 18 to 59 from November 2021 onward and compared all-cause death rates between those who had received an mRNA vaccine and those who had not. Over 39 months of follow-up, the vaccinated group showed a substantially lower annual mortality rate than the unvaccinated group, and this difference has been widely cited as evidence that the French vaccination campaign saved lives.

Günther and his colleagues did not dispute the raw numbers. Instead, they asked a deceptively simple question: do the mortality rates in the study’s two groups match what is known about mortality in the French population as a whole? Using official demographic and mortality data from the French statistics institute Insee, they calculated that the nationwide all-cause mortality rate for 18 to 59 year olds in 2022 was approximately 0.001715 per person per year. The unvaccinated group in the study, with a mean annual rate of 0.001694, sat almost exactly at this national average. The vaccinated group, however, showed a rate of just 0.001330—far below what the national figures would predict.

The discrepancy, the authors argue, points to a systematic distortion introduced at the very start of the study. Approximately 4 million people aged 18 to 59 who were vaccinated before May 2021 were excluded from the analysis, along with smaller groups who were vaccinated later or who received non-mRNA vaccines. These excluded individuals, according to the age distribution reported in the original study, were on average older than those who remained. Because mortality risk rises steeply with age even within this relatively young adult range, removing the oldest and presumably most vulnerable vaccinated individuals from the analyzed cohort would mechanically lower the death rate observed among the vaccinated group.

To quantify this effect, the team performed a conservation calculation. They reasoned that the roughly 33.9 million people actually analyzed should be representative of the full French population of 35.3 million in that age bracket. If the unvaccinated and vaccinated groups in the study had mortality rates of 0.001694 and 0.001330 respectively, then the excluded group—about 5.16 million people who were vaccinated early, vaccinated during a six-month lag period, or received non-mRNA vaccines—must have had a mortality rate roughly twice the national average to make the total number of deaths add up. This is not, the authors stress, a claim that vaccination doubled mortality risk in that group; rather, it reflects that the excluded individuals were older and more vulnerable on average, which is precisely why they were vaccinated first.

The authors also tested whether their conclusion was sensitive to assumptions about people who moved between groups during follow-up. About 642,000 individuals initially classified as unvaccinated received their first vaccine dose after October 2021 and thus crossed into the vaccinated category during the study period. When the researchers adjusted for this movement by ignoring the first three months of follow-up, the unvaccinated group’s mortality rate rose to 0.001832, and the implied mortality rate of the excluded vaccinated group remained approximately 1.83 times the national average. The overall conclusion held under this alternative accounting.

When the excluded vaccinated individuals are folded back into the vaccinated group, the apparent mortality advantage largely disappears. The combined mortality rate of all vaccinated people, including those excluded from the original analysis, would be close to or above the national average rather than substantially below it. The hazard ratio that the original study reported—a measure of relative risk between vaccinated and unvaccinated groups—would shift from the favorable range of roughly 0.73 to 0.79 toward values consistent with no meaningful difference in all-cause mortality between the two groups.

This pattern is a variant of what epidemiologists call the healthy vaccinee effect, a well-documented bias in observational vaccine research. People who choose to get vaccinated, or who are prioritized for vaccination in ways that exclude the frail, tend to differ systematically from those who do not. In this case, the bias was not primarily a matter of individual health-seeking behavior but of study design: the decision to exclude everyone vaccinated before May 2021 removed a disproportionate share of older and sicker individuals from the vaccinated group being analyzed. The comparison group was therefore not comparable in the way the study’s conclusions assumed.

The authors acknowledge limitations in their approach. The original study’s published data do not include detailed information about how the age profile of the unvaccinated group shifted over time as younger people got vaccinated and left that group, which introduces some uncertainty into the corrected estimates. Nevertheless, they argue that the direction and approximate magnitude of the distortion are clear enough to undermine the central claim that vaccination was associated with a 25 percent reduction in all-cause mortality in this population.

The critique arrives at a moment when claims about vaccine benefits and risks continue to generate intense public debate. The authors emphasize that their analysis concerns a specific methodological question about one observational study, not a judgment about whether COVID-19 vaccines prevent severe disease or death from infection—outcomes that randomized trials and other evidence have addressed separately. But they contend that when observational studies are held up as evidence of population-level mortality benefits, the composition of the groups being compared must be scrutinized as carefully as the headline numbers. In this case, they conclude, the apparent benefit dissolves once the full vaccinated population is accounted for, and the study’s design, rather than the vaccine itself, produced the celebrated result.

Subject of Research: Healthy vaccinee bias in observational studies of COVID-19 vaccination and all-cause mortality in France

Article Title: Healthy vaccinee effect by study design

Article References: Günther, M., Walach, H., Rockenfeller, R., Reitzner, M., & Meyer, C. (2026). Healthy vaccinee effect by study design. Frontiers in Epidemiology, 6, Article 1837295. https://doi.org/10.3389/fepid.2026.1837295

Image Credits: AI Generated

DOI: 10.3389/fepid.2026.1837295

Keywords: healthy vaccinee effect, COVID-19 vaccination, all-cause mortality, observational study bias, France, SNDS database, mRNA vaccines, epidemiological methods, hazard ratio, study design, Frontiers in Epidemiology, Semenzato study

The study under scrutiny, led by Banker and colleagues and published online in December 2025, examined patients with lobar intracerebral hemorrhage, a form of bleeding stroke that occurs in the lobes of the brain rather than deep structures such as the basal ganglia or thalamus. Lobar hemorrhages are strongly associated with cerebral amyloid angiopathy, an age-related condition in which amyloid protein deposits weaken vessel walls, and they carry a particularly high risk of subsequent seizures. Because clinical seizures can worsen outcomes after hemorrhagic stroke, physicians have long debated whether to prescribe preventive antiseizure drugs even in patients who have never seized, despite growing concern that these medications may themselves be harmful.

That concern was echoed in 2025 clinical practice guidelines from the Neurocritical Care Society, authored by Frontera and colleagues, which recommended against routine prophylactic antiseizure medication for most patients with nontraumatic intracerebral hemorrhage, citing trials suggesting possible harm, particularly with older agents such as phenytoin. Against this backdrop, observational studies comparing treated and untreated patients carry enormous weight. If such studies are methodologically sound, they can suggest when cautious prophylaxis might still help selected patients; if they are flawed, they can mislead clinicians and guideline developers alike.

The letter by Kobayashi and colleagues centers on the mechanics of immortal time bias, a problem first articulated in detail by epidemiologist Samy Suissa in a landmark 2008 paper in the American Journal of Epidemiology. The bias arises whenever a study classifies patients by a treatment that can only be started after they have survived for some period, yet counts that survival period as if it belonged to the treated group. Patients who die early, before ever receiving the drug, are automatically assigned to the untreated comparison group, even if they would have received the medication had they lived longer. The treated group thus appears to be populated by people who, by construction, could not die during the time window in question. They are, in a literal sense, immortal within that interval, and any apparent survival advantage may reflect nothing more than the way time was allocated.

In the context of lobar intracerebral hemorrhage, the problem is especially acute because the timing of antiseizure medication initiation is tightly linked to disease trajectory. Sicker patients, those with larger hemorrhages, deeper depressions of consciousness, or impending withdrawal of life-sustaining therapy, often die or transition to comfort care before prophylaxis is ever considered. Survivors who stabilize, by contrast, are the ones who live long enough to be started on medication. If the original analysis grouped patients from the moment of admission according to whether they ultimately received prophylaxis, while allowing the days before treatment to count toward the treated group’s follow-up time, the comparison would systematically favor the treated cohort for reasons unrelated to any pharmacological benefit.

Recent work has clarified just how pervasive and structurally varied this bias can be. In 2025, Hernán, Sterne, Higgins, Shrier, and Hernández-Díaz published a formal structural description in the journal Epidemiology showing how different causal structures generate immortal time, emphasizing that the bias is not a statistical nuisance to be adjusted away but a design-level misalignment between the question being asked and the analysis being performed. Their companion concept, the target trial, introduced by Hernán and colleagues in the Journal of Clinical Epidemiology in 2016, urges observational researchers to first specify the randomized trial they would ideally conduct, including a clearly defined time zero at which eligibility and treatment assignment both begin, and then emulate that design as faithfully as the data allow.

Applying that framework to seizure prophylaxis after lobar hemorrhage reveals the core difficulty: treatment is not assigned at a single moment but initiated at heterogeneous times, often days into the hospital course. Modern methods exist to handle this. The clone-censor-weight approach, increasingly used in pharmacoepidemiology and described in accessible detail by Gaber and colleagues in Cancer Medicine in 2024, creates artificial copies of each patient at time zero, one assigned to each treatment strategy, and then censors the copies when they deviate from their assigned strategy, using inverse probability weighting to correct for the informative censoring that results. This preserves the integrity of time zero and prevents the spurious survival advantage that plagues naive comparisons.

The exchange between the letter writers and the authors of the original study, with a formal response also published in Neurocritical Care, illustrates a broader and increasingly visible shift in how the medical literature polices itself. Methodological letters were once relegated to statistical footnotes; today, as large observational datasets drive clinical guidelines in neurocritical care, they sit at the center of practice-defining debates. The authors of the letter report no funding and no conflicts of interest and disclose that language-model tools were used only to refine phrasing and check citation consistency, with all content verified by the authors themselves. Their intervention does not claim that prophylactic antiseizure medication is definitively harmful or beneficial after lobar hemorrhage; it claims something more fundamental, that the existing estimate cannot be trusted until the time-zero problem is resolved.

For clinicians, the practical message is one of humility: observational evidence suggesting that prophylaxis is safe or effective in lobar hemorrhage should be weighed carefully against the randomized-trial signals of harm that shaped current guidelines. For researchers, the letter is a template for how to interrogate pharmacoepidemiologic analyses in acute neurology, where treatment timing, mortality, and disease severity are deeply entangled. As big-data studies continue to fill the evidence gaps left by trials that are difficult to conduct in critically ill stroke patients, the battle against immortal time bias, fought in the pages of methodological letters like this one, may prove as consequential for patient care as any new drug.

Subject of Research: Immortal time bias in observational studies of prophylactic antiseizure medication after lobar intracerebral hemorrhage

Article Title: Addressing Immortal Time Bias in Estimating the Effect of Prophylactic Antiseizure Medication after Lobar Intracerebral Hemorrhage

Article References: Kobayashi, G., Shibata, T., & Shiraishi, A. (2026). Addressing Immortal Time Bias in Estimating the Effect of Prophylactic Antiseizure Medication after Lobar Intracerebral Hemorrhage. Neurocritical Care. https://doi.org/10.1007/s12028-026-02643-8

Image Credits: AI Generated

DOI: 10.1007/s12028-026-02643-8

Keywords: immortal time bias, lobar intracerebral hemorrhage, antiseizure medication, seizure prophylaxis, neurocritical care, observational study design, target trial emulation, clone-censor-weight method, epidemiology, stroke, cerebral amyloid angiopathy, clinical guidelines