Background: While the risks and benefits of autologous breast reconstruction have been widely examined, nationally representative, longitudinal data on complication burden, flap utilization trends, and patient-level risk factors remain limited. The NIH All of Us Research Program provides an opportunity to address these gaps using a diverse, population-scale cohort. Methods: We identified 260 patients who underwent autologous breast reconstruction using CPT codes within the All of Us Registered Tier Dataset (1995–2025). Complications were tracked at 30 days and 1 year postoperatively. Logistic, multivariate regressions and Kaplan-Meier analyses evaluated predictors and timing of complications. Unsupervised machine learning via K-means clustering was utilized to uncover phenotypic subgroups by age and BMI. Results: DIEP flap utilization increased over time, particularly among younger patients. Complication rates did not significantly differ across flap types. BMI >32.7 kg/m² was associated with increased 30-day complications, while age and race were not independent predictors. Chronic pain and persistent postoperative pain were the most common 1-year complications. Flap failure occurred in fewer than 2% of cases. Clustering revealed three patient subgroups with distinct complication profiles; older patients and those with higher BMI experienced greater morbidity but maintained high flap success rates. Conclusion: Autologous breast reconstruction is broadly effective across diverse patient populations. Complication risk is more strongly influenced by BMI than age or race. Chronic pain emerged as a common long-term morbidity, underscoring the need for improved detection and management efforts. The diversity, depth, and follow-up available through All of Us enable nuanced insights into reconstructive outcomes not possible with traditional datasets.
Parekh et al. (2025) studied this question.