Increase in major osteoporotic fractures after therapy with immune checkpoint inhibitors
Bibliographic record
Abstract
Background: Immune checkpoint inhibitors (ICIs) can cause severe and sometimes long-standing immune-related adverse events (irAEs). Enhanced immune activation from ICI can theoretically result in osteoclast activation, bone loss and fracture. The objective of this study was to evaluate the incidence rates of major osteoporotic fractures (MOFs) in patients with melanoma treated with ICI. Methods: We conducted a before-after cohort study using a commercial healthcare claims dataset of adult patients with melanoma from the USA who received ICI therapy between 2011 and 2022. Incidence rates of MOF before and after ICI initiation were ascertained using International Classification of Diseases 9/10 diagnostic codes. Results: The study cohort included 3137 patients, mean age was 68 years, of which 2010 (64%) were men. 40 (1.3%) patients had an MOF in the year before ICI initiation and 57 (1.8%) and 34 (1.8%) had an MOF in the first and second years after ICI initiation, respectively. The HR for MOF over the first year after versus the year before the first ICI dose was 1.82 (95% CI 1.24 to 2.66), and it was 1.85 (95% CI 1.12 to 2.90) over the second year. Prior fracture, older age, female sex and combination ICI therapy were associated with greater risk of MOF after ICI initiation. Conclusion: Patients who receive ICI are at increased risk of MOF after receiving therapy. Given the plausible biological pathway, osteoporosis and osteoporotic fractures may represent a novel irAE of ICI therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".