The research team, led by endocrinologists Xueli Ren and Li Quan, combed through the electronic health records of 2,634 patients exposed to immune checkpoint inhibitors between January 2020 and July 2025. From this pool, 812 patients had both a normal thyroid-stimulating hormone (TSH) level and a normal free thyroxine (FT4) measurement in the 90 days before their first infusion, making them clean starting points for tracking thyroid-axis changes. After applying the remaining baseline criteria, 627 patients had at least 365 days of administrative follow-up opportunity. But here is where the study takes an unusual and technically important turn: only 240 of those 627 patients, or 38.3 percent, actually had a qualifying TSH retest within the first year after treatment.

This monitoring gap is the analytical heart of the paper. Among the 240 patients who did receive a retest, 30, or 12.5 percent, had a clinically adjudicated thyroid event within the study’s definitions, with a Wilson 95 percent confidence interval spanning 8.9 to 17.3 percent. That figure sounds like a one-year incidence rate, but the authors are emphatic that it is not. It is an observed detection proportion under incomplete monitoring. The distinction matters enormously for anyone trying to compare real-world studies of immune-related endocrine toxicity, because different centers test different patients at different times, and the resulting numbers are not directly comparable.

The depth of the monitoring shortfall becomes vivid when the researchers examine what happened to the 210 retested patients who had no recorded event. Of these, 196, or 93.3 percent, had their last available thyroid test before day 365. In other words, even among the monitored minority, most patients stopped being checked well before the end of the follow-up year. Laboratory surveillance in routine clinical practice is driven by symptoms, ordering habits, and competing clinical priorities, not by a standardized protocol. Any thyroid dysfunction that emerges after the last test simply goes unrecorded, invisible to retrospective analyses built on electronic health records.

So who was more likely to be retested, and who was more likely to have an event recorded? The team ran exploratory logistic regressions with Benjamini-Hochberg adjustment for multiple comparisons, a statistical technique that controls the false discovery rate when many baseline variables are tested simultaneously. Two associations stood out after adjustment. Patients with thyroid antibody positivity in the baseline window had dramatically higher odds of a recorded event, with an odds ratio of 8.73 and a 95 percent confidence interval of 3.44 to 22.14, yielding a Benjamini-Hochberg q value below 0.001. Higher baseline TSH also predicted recorded events, with an odds ratio of 1.69 per 1 mIU/L and a confidence interval of 1.25 to 2.27, with a q value of 0.0027. Both associations persisted in a limited-adjustment Firth model, a penalized likelihood approach designed for situations where events are sparse and conventional maximum likelihood estimation can fail or produce unstable estimates.

The antibody finding has a plausible biological mechanism. Thyroid peroxidase and thyroglobulin antibodies signal that the immune system has already broken tolerance to thyroid antigens. When PD-1 inhibitors release the molecular brakes on T cells, this pre-existing autoreactivity can flare into destructive thyroiditis, often producing a transient hyperthyroid phase followed by permanent hypothyroidism requiring lifelong levothyroxine replacement. The baseline TSH association is more subtle. A TSH level at the upper edge of normal may reflect early subclinical thyroid failure, so patients with higher baseline values may be closer to the threshold at which dysfunction becomes detectable. But the authors caution that these exploratory associations may partly reflect differential detection rather than pure causation, because patients with known risk factors may simply be monitored more intensively, making events more likely to be found.

To address this selection problem, the researchers deployed inverse probability weighting, a statistical method that reweights the monitored patients so that their measured baseline characteristics mirror those of the entire baseline-eligible cohort. The idea is to estimate what the recorded-event proportion would look like if the monitored group were representative of everyone. With capped weights to prevent a few extreme observations from dominating, the standardized recorded-event proportion came out at 12.6 percent, with a bootstrap 95 percent confidence interval of 8.5 to 17.1 percent. The near-identity of this standardized figure with the raw 12.5 percent suggests that, at least for the measured baseline variables, the monitored patients were not dramatically different from the full cohort. But the method can only adjust for variables that were actually measured, and unmeasured drivers of monitoring selection remain a residual concern.

Sensitivity analyses probed the robustness of the findings from different angles. When the team required paired retesting, meaning both TSH and FT4 had to be rechecked rather than TSH alone, the analysis recorded 30 events among 239 patients. When the baseline window was restricted to laboratory reports strictly before the calendar date of the first ICI infusion, excluding same-day results that might reflect treatment-day perturbations, the analysis recorded 22 events among 171 patients. The event counts shifted modestly across these stricter definitions, illustrating how sensitive real-world event tallies are to explicit outcome definitions and laboratory timing, a point the authors elevate to a central recommendation of the paper.

The study’s most consequential message may be methodological rather than clinical. The authors argue that real-world studies of thyroid toxicity after checkpoint inhibitor therapy should routinely report monitoring coverage, laboratory timing, and explicit outcome definitions. Without these elements, the reported proportions from different centers are essentially incommensurable, and pooled estimates across studies can be badly misleading. The team points to established reporting frameworks, including the STROBE guidelines for observational studies and the RECORD framework for studies using routinely collected health data, as templates for making monitoring selection transparent. A center that tests every patient quarterly will report far higher event proportions than one that tests only symptomatic patients, even if the underlying biology is identical.

For clinicians managing patients on PD-1 inhibitors, the practical implications are nonetheless tangible. Roughly one in eight monitored patients developed a study-defined thyroid event within a year, and the strongest predictors were pre-existing thyroid autoantibodies and a baseline TSH at the higher end of normal. Patients with these features may warrant particularly vigilant laboratory surveillance, since early detection of hypothyroidism allows prompt levothyroxine initiation and prevents the fatigue, weight gain, and cold intolerance that can erode quality of life during cancer treatment. Conversely, the study also warns against overinterpreting event proportions from centers with incomplete monitoring, because the true burden of thyroid dysfunction in the unmonitored majority remains unknown. As checkpoint inhibitors continue to expand across tumor types, the study stands as a reminder that the thyroid axis is a frequent casualty of immunotherapy, and that honest accounting of endocrine toxicity requires confronting not just the biology of immune attack, but the messy realities of who gets tested and when.

Subject of Research: Thyroid dysfunction after PD-1 inhibitor therapy: selection into post-treatment monitoring and thyroid-axis trajectories in a single-centre real-world cohort study

Article Title: Thyroid dysfunction after PD-1 inhibitor therapy: selection into post-treatment monitoring and thyroid-axis trajectories in a single-centre real-world cohort study

Article References: Ren, X., & Quan, L. (2026). Thyroid dysfunction after PD-1 inhibitor therapy: selection into post-treatment monitoring and thyroid-axis trajectories in a single-centre real-world cohort study. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02650-y

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02650-y

Keywords: Thyroid, dysfunction, PD-1, inhibitor, therapy, selection, post-treatment, monitoring, thyroid-axis, trajectories, single-centre, real-world