Abstract
OBJECTIVES: Previous analyses of the volume-outcome relationship have focused on short-term outcomes such as early mortality. The current study aims to update a novel statistical methodology, facilitating the evaluation of the relation between procedural volume and time-to-event outcomes such as long-term survival, using surgery for acute type A aortic dissection as an illustrative example. METHODS: This study employed an existing dataset of type A dissection outcomes, retrieved from literature. Studies were included when reporting on annual case load and long-term survival, which served as the primary outcome of interest. Individual patient data were reconstructed from the included studies, and a hazard ratio was determined per study in relation to overall survival, after which the calculated hazard ratios were incorporated in a restricted cubic-spline model, facilitating the application of the elbow method. RESULTS: Fifty-two studies were included (n = 14 878 patients), with a median follow-up of 5 years. One-, 3-, 5- and 10-year survival of the overall cohort were 82% [95% confidence interval (CI) 82-83%], 79% (95% CI 78-80%), 74% (95% CI 74-75%) and 60% (95% CI 59-62%), respectively. A significant non-linear volume-outcome relation for long-term survival was observed in both the unadjusted and adjusted analyses (P = 0.030 and P = 0.002), with an optimal annual case load of 32 cases/year (95% CI 31-33). CONCLUSIONS: Based on the available data, these findings imply that the annual case volume to achieve optimal long-term survival is located near a procedural volume of 32 cases/year. After accrual of more annual procedures, long-term survival may no longer significantly improve any further.
Original language | English |
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Article number | ezaf022 |
Number of pages | 8 |
Journal | European Journal of Cardio-Thoracic Surgery |
Volume | 67 |
Issue number | 2 |
DOIs | |
Publication status | Published - 4 Feb 2025 |
Keywords
- Volume-outcome relationship
- acute type A aortic dissection
- annual case volume
- hospital volume
- long-term survival
- optimal case volume