Cancer after Total Joint Arthroplasty: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Some epidemiologic and laboratory studies have suggested that total joint arthroplasty could increase the risk of cancer. In this meta-analysis, we attempt to clarify the association of joint arthroplasty with subsequent cancer incidence. METHODS: We identified population-based studies reporting standardized incidence ratios (SIR) for cancer following large joint arthroplasty. After summing the observed and expected numbers of cases across all qualifying studies, we calculated SIRs for all cancers, and for those at 28 anatomic sites. Latency analysis involving 175,166 patients characterized short-term and long-term cancer associations. RESULTS: The analyses included 1,435,356 person-years of follow-up and 20,045 cases of cancer. Overall cancer risk among patients with arthroplasty was equal to that for the general population. The relative risk of lung cancer, reduced in the first 5 years after arthroplasty, increased significantly over time to approach that of the general population. Risks for all sites in the luminal gastrointestinal tract were significantly reduced by 10% to 20%; with relative risks that were generally stable over time. Increased risks were seen for cancer of the prostate (SIR, 1.12; 95% confidence interval, 1.08-1.16); similar relative risks were seen in each time period after the procedure. For melanoma, relative risks increased with follow-up to a SIR of 1.43 (95% confidence interval, 1.13-1.79) for 10 or more years after arthroplasty. There was a similar delayed emergence of increased risks for cancers of the urinary tract and oropharynx. The relative risk for bone cancer decreased with time after the procedure. CONCLUSIONS: There does not seem to be an overall increased risk of cancer following total joint arthroplasty. Although the risks of prostate cancer and melanoma seem to be elevated, there is no obvious mechanism for these associations. Reductions in risk for some malignancies may not be causal.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.067 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".