title: A Bayesian meta-analysis of multiple treatment comparisons of systemic regimens for advanced pancreatic cancer.
abstract: BACKGROUND
  For advanced pancreatic cancer, many regimens have been compared with gemcitabine (G) as the standard arm in randomized controlled trials. Few regimens have been directly compared with each other in randomized controlled trials and the relative efficacy and safety among them remains unclear.
  
  
  METHODS
  A systematic review was performed through MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and ASCO meeting abstracts up to May 2013 to identify randomized controlled trials that included advanced pancreatic cancer comparing the following regimens: G, G+5-fluorouracil, G+ capecitabine, G+S1, G+ cisplatin, G+ oxaliplatin, G+ erlotinib, G+ nab-paclitaxel, and FOLFIRINOX. Overall survival and progression-free survival with 95% credible regions were extracted using the Parmar method. A Bayesian multiple treatment comparisons was performed to compare all regimens simultaneously.
  
  
  RESULTS
  Twenty-two studies were identified and 16 were included in the meta-analysis. Median overall survival, progression free survival, and response rates for G arms from all trials were similar, suggesting no significant clinical heterogeneity. For overall survival, the mixed treatment comparisons found that the probability that FOLFIRINOX was the best regimen was 83%, while it was 11% for G+ nab-paclitaxel and 3% for G+ S1 and G+ erlotinib, respectively. The overall survival hazard ratio for FOLFIRINOX versus G+ nab-paclitaxel was 0.79 [0.50-1.24], with no obvious difference in toxicities. The hazard ratios from direct pairwise comparisons were consistent with the mixed treatment comparisons results.
  
  
  CONCLUSIONS
  FOLFIRINOX appeared to be the best regimen for advanced pancreatic cancer probabilistically, with a trend towards improvement in survival when compared with other regimens by indirect comparisons.
authors.affiliation: Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, ON, Canada; Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
authors.forename: Kelvin
authors.initials: K
authors.lastname: Chan
authors.affiliation: Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, ON, Canada.
authors.forename: Keya
authors.initials: K
authors.lastname: Shah
authors.affiliation: Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, ON, Canada.
authors.forename: Kelly
authors.initials: K
authors.lastname: Lien
authors.affiliation: University of Ottawa, Ottawa, ON, Canada.
authors.forename: Doug
authors.initials: D
authors.lastname: Coyle
authors.affiliation: Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, ON, Canada.
authors.forename: Henry
authors.initials: H
authors.lastname: Lam
authors.affiliation: Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, ON, Canada.
authors.forename: Yoo-Joung
authors.initials: YJ
authors.lastname: Ko
mesh_terms: D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D001499:Bayes Theorem; D003841:Deoxycytidine / Q000031:analogs & derivatives / Q000627:therapeutic use; D006801:Humans; D009367:Neoplasm Staging; D010190:Pancreatic Neoplasms / Q000188:drug therapy* / Q000473:pathology*; D011336:Probability; D016016:Proportional Hazards Models; D016019:Survival Analysis; D000093542:Gemcitabine
chemical_list: D003841:Deoxycytidine; D000093542:Gemcitabine