Markov decision analysis of neoadjuvant treatment pathway versus surgery first pathway for resectable pancreatic cancer

Background:
Surgery first (SF) versus neoadjuvant approach (NAT) to management of potentially resectable pancreatic ductal adenocarcinoma (PDAC) is controversial. This study is unique in utilizing institutional data to offer Markov decision-analysis of overall treatment pathways for resectable PDAC.

Methods:
An advanced Markov decision analysis model was constructed and populated with data from a retrospective institutional database. Patients presenting with resectable PDAC from 2008-2012 were included in the SF arm. Those presenting with resectable PDAC from 2012-2016 and treated within NAT pathway populated the NAT arm. Model uncertainties were tested with one and two-way deterministic sensitivity analysis and probabilistic Monte Carlo sensitivity analysis set to 1000 cycles with variables altered between highest and lowest observed values.

Results:
NAT pathway gave an additional 0.58 QALMs (22.43 vs. 21.85 QALMs). Monte Carlo analysis reported indifference between treatment strategies. One-way deterministic sensitivity analysis showed that probability of resection in the SF pathway must be greater than 0.82, or below 0.72 in NAT pathway, and probability of receiving adjuvant therapy above 0.6 to alter pathway superiority. Two-way deterministic sensitivity analysis demonstrated treatment superiority depended on resection rate in each pathway and receiving adjuvant therapy in SF pathway. Markov cohort analysis demonstrated superiority of neoadjuvant pathway (Table).

Conclusions:
Optimal treatment pathway remains debatable on an intention-to-treat Markov decision analysis. Markov cohort analysis of treatment received demonstrated benefit with NAT pathway.