Background: Implant-based breast reconstruction (IBR), following mastectomy, significantly impacts patients’ quality of life (QoL), necessitating accurate measurement through psychometrically robust patient-reported outcome measure (PROM) tools. This bibliometric analysis aims to discern trends, identify gaps, and evaluate the use of such tools in the IBR literature.

Methods: The 100 most cited publications regarding QoL in implant-based reconstruction were identified on Web of Science, across all available journal years (from 1977 to 2024) on 10 March 2024. Study details, including the citation count, main content focus, outcome measures, and usage of psychological questionnaires, were extracted and tabulated from each publication. The Oxford Centre for Evidence-Based Medicine (OCEBM) levels of evidence (LOE) of each study were assessed.

Results: The 100 most cited publications on QoL in implant-based reconstruction were identified, encompassing 64,192 patients and 28,114 reconstructed breasts. Citations per publication ranged from 62 to 457 (mean, 124.95 ± 73.05), with the highest-cited study being authored by Al-Ghazal (n = 457). The vast majority of publications were LOE II (n = 52), representative of prospective cohort studies, systematic reviews of non-randomised studies, and systematic review and meta-analysis. The number of publications for LOE V, IV, III, and I was 0, 7, 41, and 0, respectively. The main content focus was “quality of life” in 83 publications, with significant utilisation of the BREAST-Q questionnaire. A total of 80 publications used validated questionnaires with psychometric development.

Conclusions: This analysis demonstrates that the research methodologies within IBR mostly consist of moderate-quality publications; however, notably, there was a lack of LOE I studies, underscoring a gap in high-quality research within the field. Moreover, only 62/100 used validated PROM tools. Future IBR research studies should be focussed on most robust methodologies, incorporating validated PROM tools, to optimise shared-decision making and informed consent.