Fracture Risk Associated with Immune Checkpoint Inhibitors: A Systematic Literature Review and Meta-Analysis
Bibliographic record
Abstract
Objectives Immune checkpoint inhibitors (ICIs) have caused a paradigm shift in treating numerous malignancies. While ICIs work by activating T lymphocytes to attack tumor cells, they may inadvertently promote osteoclast activation as an off-target effect, leading to osteoporosis development and fragility fractures. Randomized controlled trials (RCTs) assessing ICIs do not consider fractures as immune-related adverse events (irAEs), with fracture data solely available in supplementary appendices. Additionally, the infrequent occurrence of fractures makes meaningful risk analysis difficult within a given RCT. Objective: To conduct a systematic literature review (SLR) and meta-analysis to determine fracture risk associated with ICI. Methods We conducted an SLR and meta-analysis of phase II and III ICI RCTs in patients with solid cancers. We performed a search using MEDLINE and Embase from inception to June 12, 2024. All studies were independently reviewed by 2 researchers at each stage of screening and conflicts were resolved by a third reviewer in Covidence. We reviewed the supplementary materials at the full-text review stage and included studies which reported fracture events. Fractures were categorized as any fracture and major osteoporotic fracture (MOF) (vertebrae, forearm, hip, and humerus). Random effects meta-analysis was performed to determine the overall risk of any fracture and MOF in ICI users as compared with non-ICI users and heterogeneity was assessed using Cochran’s Q test. Subgroup analysis was performed on placebo-controlled RCTs. Results We screened 5050 titles and abstracts, 424 full-text articles, and identified 33 studies that met our inclusion criteria. The overall relative risk (ORR) of any fractures was 1.008 (95% CI 0.711 to 1.430, p-value=0.963) and the ORR of MOF was 1.048 (95% CI 0.673 to 1.630, p-value=0.837). The ORR of MOF for the 17 placebo-controlled studies was 1.25 (95% CI 0.62 to 2.52, p-value=0.870) as shown in the forest plot (Figure). The I2 statistics showed no heterogeneity among the studies, with consistent values of 0.0%. Conclusion There is no statistically significant increased fracture risk between ICI users and non-ICI users during the active treatment period in ICI RCTs. However, the overall effect estimate shows a trend toward higher risk of fractures, particularly MOFs in ICI users, which was most pronounced in the placebo-controlled RCTs. These non-significant results may be related to limited number of reported events and short duration of adverse events monitoring. Longer monitoring of adverse events could yield more comprehensive data, allowing for more precise assessment of the fracture risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.045 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".