Association between SLCO1B1 −521T>C and −388A>G polymorphisms and risk of statin-induced adverse drug reactions: A meta-analysis
Bibliographic record
Abstract
An increasing number of studies have investigated the association between SLCO1B1 -521T>C and -388A>G polymorphisms and the risk of statin-induced adverse drug reactions (ADRs), but the results have been inconsistent. This meta-analysis was performed to gain more insight into the relationship. PubMed, Embase, Cochrane Library and Web of Science were searched for relevant articles published before March 5th, 2015. The quality of included studies was evaluated by the Newcastle-Ottawa Quality scale. Pooled effect estimates (odds ratios [ORs] or hazard ratios [HRs) and corresponding 95 % confidence intervals (CIs) were calculated to assess the association in overall and subgroup analyses for various genetic models. Begg's rank correlation test and Egger's linear regression test were used to examine the publication bias. A total of nine cohort and four case-control studies involving 11, 246 statin users, of whom 2, 355 developing ADRs were included in the analysis. Combined analysis revealed a significant association between the SLCO1B1-521T>C polymorphism and increased risk for ADRs caused by various statins, but the synthesis heterogeneity was generally large (dominant model: pooled effect estimate = 1.85, 95 % CI 1.20-2.85, P = 0.005; I (2) = 80.70 %, Pheterogeneity < 0.001). Subgroup analysis by statin type showed that the ADRs risk was significantly elevated among simvastatin users (dominant model: pooled effect estimate = 3.43, 95 % CI 1.80-6.52, P = 0.001; I (2) = 59.60 %, Pheterogeneity = 0.060), but not among atorvastatin users. No significant relationship was found between the -388A>G polymorphism and ADRs caused by various statins (dominant model: pooled effect estimate = 0.94, 95 % CI 0.79-1.13, P = 0.526; I (2) = 40.10 %, Pheterogeneity = 0.196). The meta-analysis suggests that SLCO1B1 -521T>C polymorphism may be a risk factor for statin-induced ADRs, especially in simvastatin therapy. Conversely, there may be no significant association for -388A>G polymorphism.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.047 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".