Is Malignancy Associated With Arthroplasty? A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although implants have been linked to malignancies in other medical contexts, such as the relationship between anaplastic large cell lymphoma and breast implants, the potential association between orthopaedic implants and cancer remains unclear. Several studies have investigated this question, but findings have been inconsistent. A comprehensive meta-analysis is needed to clarify whether total joint arthroplasty increases the risk of malignancy. QUESTIONS/PURPOSES: (1) Is receiving a THA or TKA associated with an increased risk of cancer? (2) Are certain implant types (such as metal-on-metal or cemented) associated with increased cancer risk? (3) Is follow-up duration associated with changes in observed cancer risk estimates? METHODS: A systematic review and meta-analysis were conducted using PubMed, Embase, and SCOPUS to identify studies assessing cancer incidence rates in patients who received hip or knee arthroplasty compared to patients in control groups who did not receive arthroplasty. Databases were queried from inception through the final search date (November 23, 2024). Eligible studies reported or allowed derivation of an effect estimate comparing overall cancer incidence rates in recipients of THA or TKA with an external reference population. From 1838 screened articles, 16 studies were included, all of which provided extractable effect estimates that were entered into one or more of our meta-analyses. Included studies consisted primarily of record-linkage studies connecting national, longitudinally maintained arthroplasty registers to similarly longitudinal national mortality and cancer registers. Study quality was assessed using the Newcastle-Ottawa Scale, which awards up to nine points across three categories, with higher scores indicating lower risk of bias. The 16 included studies scored between 6 and 8 (mean ± SD 7.1 ± 0.8), reflecting generally high methodological quality. The primary analysis included data from 977,465 patients of both sexes and all age groups who underwent hip or knee arthroplasty and were followed up for over 7,415,134 person-years. Effect estimates were pooled with a random-effects model because heterogeneity was present (between-study σ 2 = 0.016 versus within-study σ 2 = 0.002; Q = 1195, p < 0.001), and a funnel plot showed no evidence of publication bias. To explore associations between implant type and cancer risk for patients undergoing THA, we conducted separate meta-analyses for studies reporting on metal-on-metal bearing surfaces and those reporting on cemented fixation. To assess latency effects, we compared cancer incidence rates in patients with more or less than 10 years of follow-up and conducted a meta-regression to evaluate the association between follow-up duration and cancer risk. We did not perform an a priori power analysis. RESULTS: Patients who underwent THA or TKA did not have an increased risk of cancer compared with the general population (pooled random-effects estimate [REE] = 0.99 [95% confidence interval (CI) 0.92 to 1.07]; p = 0.88). Subgroup analyses showed no increased cancer risk after TKA (pooled REE = 1.02 [95% CI 0.85 to 1.21]; p = 0.83) or THA (pooled REE = 0.99 [95% CI 0.91 to 1.07]; p = 0.73). Cancer risk did not increase among patients undergoing THA who received cemented implants (pooled REE = 1.00 [95% CI 0.87 to 1.15]; p = 0.93) or metal-on-metal implants (pooled REE = 1.02 [95% CI 0.85 to 1.21]; p = 0.86) compared with the general population. Among patients with ≥ 10 years of follow-up, cancer incidence did not differ from the general population (pooled REE = 1.05 [95% CI 0.97 to 1.14]; p = 0.21); similarly, among patients with < 10 years of follow-up, no increased cancer risk was observed (pooled REE = 0.93 [95% CI 0.81 to 1.06]; p = 0.27). Meta-regression showed no association between follow-up duration and cancer risk (β = -0.004 [95% CI -0.024 to 0.015]; p = 0.66). CONCLUSION: Based on these findings, clinicians can continue to recommend arthroplasty without additional cancer-related concern based on current evidence. However, future studies should ensure longer follow-up, improved global representation in large linkage studies, and detailed patient- and implant-specific data to better characterize potential rare or long-latency malignancies. LEVEL OF EVIDENCE: Level III, therapeutic study.
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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 | 0.021 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.079 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".