Question · asked by 1 review

Composite resin vs Amalgam restoration: Restoration failure

Population
Permanent posterior teeth (molars/premolars) receiving direct restoration
Intervention
Composite resin
Comparison
Amalgam restoration
Outcome
Restoration failure

There was no statistically significant difference in failure risk between composite resin and amalgam restorations in permanent posterior teeth (pooled RR 0.96, 95% CI 0.68 to 1.34; 13 studies; not GRADE-rated, with very high heterogeneity, I2 = 97%).

What each review found

Current versions only
FindingEffectStudiesGRADE certainty
Composite resin restorations vs Amalgam restorations
Restoration failure (replacement, tooth/restoration fracture, secondary caries, postoperative sensitivity, toothache) · Permanent posterior teeth (molars/premolars) receiving direct restoration · At least 12 months follow-up (included studies followed 24 to 144 months), Permanent posterior teeth; clinical/practice settings across multiple countries (not clearly specified)
There was no statistically significant difference in failure risk between composite resin and amalgam restorations in permanent posterior teeth (pooled RR 0.96, 95% CI 0.68 to 1.34; 13 studies; not GRADE-rated, with very high heterogeneity, I2 = 97%).
Failure Risk of Composite Resin and Amalgam Restorations: A Systematic Review and Meta-Analysis. (2025) All outcomes
RR 0.96 [0.68, 1.34]13 studiesGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Failure Risk of Composite Resin and Amalgam Restorations: A Systematic Review and Meta-Analysis.
2025 All outcomes
Search performed August 2023 to December 2023 (records from 1990 onwards)21Critically Low / Critically Low

The same intervention and outcome, asked in another population or against another comparator.

Studies behind the findings

The primary studies the full-text reviews tie to this outcome. Reviews with headline outcomes only do not list them here.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.