Simultaneous Comparison of Efficacy and Adverse Events of Interventions for Patients with Esophageal Cancer: Protocol for a Systematic Review and Bayesian Network Meta-analysis

• Published in: Asian Pacific journal of cancer prevention : APJCP Vol. 17; no. 2; pp. 867 - 872
• Main Authors: Doosti-Irani, Amin, Mansournia, Mohammad Ali, Rahimi-Foroushani, Abbas, Cheraghi, Zahra, Holakouie-Naieni, Kourosh
• Format: Journal Article
• Language: Korean
• Published: 2016
• Subjects: treatment outcomes; network meta-analysis; Esophageal cancer
• ISSN: 1513-7368; 2476-762X

Background: Esophageal cancer is one of the most serious malignancies. Due to the aggressive nature of this cancer, the prognosis is poor. A network meta-analysis with simultaneous comparison of multiple treatments can help determine better treatment options that have higher effects on overall survival of patients with lower adverse events. The aim of this review is to simultaneously compare efficacy and adverse events of treatment interventions for esophageal cancer. Materials and Methods: In this review, only randomized control trials (RCT) will be considered for network meta-analysis. All international electronic databases including Medline, Web of Sciences, Scopus, Cochran's library, EMBASE and Cancerlit will be searched to find randomized control trials which compared two or more treatment interventions for esophageal cancer. A network plot will be drawn for visual representation of all available treatment interventions. Bayesian approach will be used to combine the direct and indirect evidence. Treatment effects (e.g. hazard ratio for time to event outcomes, risk ratio for binary outcomes, and rate ratio for count outcomes with 95% credible interval) will be reported. Moreover, cumulative probability of the treatment ranks will be reported using the surface under the cumulative ranking (SUCRA) graphs. Consistency assumption will be assessed by the loop-specific and design-by-treatment interaction approaches. Conclusions: The results of this study may be helpful for the patients, clinicians and health policy makers in selecting treatments that have the best effect on survival and lowest adverse events.