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.
