Is There a Plateau to the Learning Curve for Acoustic Neuroma Resection?—Experience and Outcomes from a Single Interdisciplinary Team Over Thirty Years

Abstract

Objective The evolution of acoustic neuroma (AN) care continues to shift focus on balancing optimized tumor resection and control with preservation of neurological function. Prior learning curve analyses of AN resection have demonstrated a plateau between 20 and 100 surgeries. In this study of 860 consecutive AN surgeries, we investigate the presence of an extended learning curve tail for AN resection.

Methods A retrospective cohort study of AN resections by a single interdisciplinary team between 1988 and 2018 was performed. Proportional odds models and restricted cubic splines were used to determine the association between the timing of surgery and odds of improved postoperative outcomes.

Results The likelihood of improved postoperative House-Brackmann (HB) scores increased in the first 400 procedures, with HB 1 at 36% in 1988 compared with 79% in 2004. While the probability of a better HB score increased over time, there was a temporary decrease in slope of the cubic spline between 2005 and 2009. The last 400 cases continued to see improvement in optimal HB outcomes: adjusted odds of HB 1 score were twofold higher in both 2005 to 2009 (adjusted odds ratio [aOR]: 2.11, 95% confidence interval [CI]: 1.38–3.22, p < 0.001) and 2010 to 2018 (aOR: 2.18, 95% CI: 1.49–3.19, p < 0.001).

Conclusion In contrast to prior studies, our study demonstrates the steepest growth for learning, as measured by rates of preservation of facial function outcomes (HB 1), occurs in the first 400 AN resections. Additionally, improvements in patient outcomes continued even 30 years into practice, underlining the importance of lifelong learning.

Keywords

acoustic neuroma - learning curve - retrosigmoid - spline - translabyrinthine

This work was presented in part as an oral presentation at the 31st annual North American Skull Base Society (NASBS) meeting, Phoenix, AZ, USA.

Publikationsverlauf

Eingereicht: 26. Juni 2022

Angenommen: 01. Dezember 2022

Accepted Manuscript online:
06. Dezember 2022

Artikel online veröffentlicht:
16. Januar 2023

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