Background: Carotid body tumors (CBTs) are rare neoplasms that pose significant surgical challenges. This study aims to evaluate the predictive utility of preoperative radiological characteristics on postoperative complications in patients undergoing CBT resection at a tertiary care center.
Methods: A retrospective analysis was conducted on 106 patients who underwent CBT resection between 2003 and 2023. Patient demographics, tumor characteristics, and operative details were collected. The primary outcomes were an estimated blood loss (EBL) >250 mL and cranial nerve (CN) injury. Logistic regression models were used to identify significant preoperative radiological predictors, including Shamblin grade, Peking Union Medical College Hospital (PUMCH) grade, tumor distance to the base of the skull (DTBOS), and tumor volume.
Results: One hundred and six patients were included. Higher Shamblin and PUMCH grades were significantly associated with increased EBL and CN injury. Specifically, the Shamblin grade alone predicted an EBL >250 mL with a McFadden R2 value of 0.14, which slightly decreased to 0.13 when DTBOS and tumor volume were added. For CN injury, the Shamblin grade alone had an R2 of 0.16, which significantly improved to 0.27 with the addition of DTBOS and further to 0.29 with tumor volume. The PUMCH grade alone predicted an EBL >250 mL with an R2 value of 0.08, which did not significantly change with the addition of DTBOS and tumor volume. For CN injury, the PUMCH grade alone had an R2 of 0.14, improving to 0.21 with DTBOS and to 0.22 with tumor volume. Furthermore, a 1-cm decrease in DTBOS significantly increased the odds of requiring a blood transfusion (OR = 2.26, 95% CI: 1.28-4.01, p=0.0051) and the risk of CN injury (OR = 3.65, 95% CI: 1.98-6.73, p<0.0001).
Conclusion: This study identified novel preoperative radiological predictors that enhance the predictive accuracy of standard classification systems, offering valuable insights for preoperative planning. While the Shamblin and PUMCH classifications are useful tools on their own, our findings demonstrate that incorporating additional radiological features, such as DTBOS and tumor volume, can substantially increase their predictive utility. Surgeons are encouraged to incorporate multiple preoperative radiological variables alongside traditional classification systems to better assess the risk of postoperative complications. Further research with larger, multi-institutional cohorts are necessary to validate these findings and refine predictive models.
Keywords: Carotid body tumor; Complications; Cranial Nerve Injury; Predictors.
Copyright © 2024. Published by Elsevier Inc.