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Predictors of Gastrostomy Tube Placement in Patients with Head and Neck Cancer Undergoing Resection and Flap-based Reconstruction: Systematic Review and Meta-Analysis

Published:August 22, 2022DOI:https://doi.org/10.1016/j.bjps.2022.08.040

      ARTICLE SUMMARY

      Background

      Nutritional status may be impaired in patients with head and neck cancer undergoing surgical treatment, often necessitating gastrostomy tube (G-tube) placement. Identifying which patients will require a G-tube remains a challenge. This study identifies predictors of G-tube requirement in patients undergoing tumor resection and reconstruction with pedicled or free flaps.

      Methods

      Systematic review of the PubMed, Cochrane and Scopus databases was performed of English-language articles discussing risk factors of perioperative G-tube placement among patients >18 years. Data on patient, tumor, and treatment factors, as well as need for G-tube, were collected. Univariable meta-analysis was conducted to identify predictors for G-tube placement.

      Results

      Eleven studies (1,112 patients) met inclusion criteria. Overall pooled prevalence of postoperative G-tube placement was 25%. Patients with advanced cancer stage IV/recurrence were more likely to require a G-tube (OR 2.81 [CI 1.03-7.69]; p<0.05), as were those who had undergone preoperative radiation (OR 3.55 [CI 2.03-6.20], p<0.05). Reconstruction with a radial forearm free flap was associated with a lower need for G-tube versus rectus abdominis (OR 0.25 [CI 0.08-0.83], p=0.02), and latissimus dorsi flap (OR 0.21 [CI 0.04-1.09], p=0.06). There was no difference in G-tube placement between those receiving pedicled flaps versus free flaps (OR 1.54 [CI 0.38-6.20], p=0.54).

      Conclusions

      Among patients with head and neck cancer undergoing resection with immediate pedicled or free flap reconstruction, advanced tumor stage and history of prior radiation therapy are associated with increased likelihood of G-tube placement. More randomized controlled trials are needed to develop a decision-making algorithm.

      Keywords

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