Do silicone breast implants cause rheumatologic disorders?: A systematic review for a Court-Appointed National Science Panel
Bibliographic record
Abstract
OBJECTIVE: To assist in evaluating expert testimony and scientific evidence presented in law suits brought against silicone breast implant manufacturers, a US District Court Order established a National Science Panel to assess whether existing studies provide scientific evidence of an association between silicone breast implants and systemic classic/accepted connective disease, atypical connective disease, and certain signs and symptoms identified by plaintiffs in the law suits. Local disorders potentially associated with these implants were not addressed in this review. Therefore, we performed a systematic review of published studies on the association between silicone breast implants and systemic connective tissue disorders. METHODS: Data from relevant studies (human cohort, case-control, or cross-sectional studies with > or = 10 participants and appropriate controls) were identified through literature searches of Medline, Current Contents, HealthStar, Biological Abstracts, EMBase, Toxline, and Dissertation Abstracts. Two independent reviewers, using standard collection forms, extracted data from the included studies. Adjusted relative risks (RRs) in cohort studies and odds ratios (ORs) in case-control and cross-sectional studies were reported if provided; otherwise, unadjusted RRs and ORs were calculated. RESULTS: Twenty-four studies meeting inclusion criteria were identified. No association was evident between breast implants and any established or atypical connective tissue disorder. There was discordance among studies in reports of arthralgias, lymphadenopathy, myalgias, sicca symptoms, skin changes, and stiffness. CONCLUSION: The panel found no evidence to support expert testimony suggesting an association between silicone breast implants and connective diseases. Discordance for symptoms may reflect differences in symptoms included in various categories, the small number of cases, and the effect of having single subjects with > 1 symptom represented in analyses of each symptom reported. The process presented here is an early example of the use of independent scientific panels to help courts clarify scientific evidence in legal proceedings.
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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 | 0.024 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| 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".