Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis

Abstract

Background: Neoadjuvant therapy has emerged as an alternative treatment strategy for potentially resectable pancreatic cancer. In the absence of large randomized controlled trials offering a direct comparison, this study aims to use Markov decision analysis to compare efficacy of traditional surgery first (SF) and neoadjuvant treatment (NAT) pathways for potentially resectable pancreatic cancer.

Methods: An advanced Markov decision analysis model was constructed to compare SF and NAT pathways for potentially resectable pancreatic cancer. Transition probabilities were calculated from randomized control and Phase II/III trials after comprehensive literature search. Utility outcomes were measured in overall and quality-adjusted life months (QALMs) on an intention-to-treat basis as the primary outcome. Markov cohort analysis of treatment received was the secondary outcome. Model uncertainties were tested with one and two-way deterministic and probabilistic Monte Carlo sensitivity analysis.

Results: SF gave 23.72 months (18.51 QALMs) versus 20.22 months (16.26 QALMs). Markov Cohort Analysis showed that where all treatment modalities were received NAT gave 35.05 months (29.87 QALMs) versus 30.96 months (24.86QALMs) for R0 resection and 34.08 months (29.87 QALMs) versus 25.85 months (20.72 QALMs) for R1 resection. One-way deterministic sensitivity analysis showed that NAT was superior if the resection rate was greater than 51.04% or below 75.68% in SF pathway. Two-way sensitivity analysis showed that pathway superiority depended on obtaining multimodal treatment in either pathway.

Conclusion: Whilst NAT is a viable alternative to traditional SF approach, superior pathway selection depends on the individual patient's likelihood of receiving multimodal treatment in either pathway.

Fig 1. Overview of the structure of the Markov decision-tree.

Fig 2. One-way deterministic sensitivity analysis.

This figure shows the effect of altering the baseline probability of resection first in the NAT pathway then in the SF pathway on overall model outcome.

Fig 3. Two-way sensitivity analysis.

Y-axis shows probability of receiving adjuvant therapy in SF pathway and x-axis shows probability of receiving resection in NAT pathway. The red area represents where patients, given competing probability of receiving multimodal treatment in competing pathways, would benefit from SF approach. The blue area represents where NAT would be the superior treatment option in terms of quality-adjusted survival. The corresponding predicted survival time in QALMs are detailed below. X and Y-axis provide altering probabilities of multimodal treatment in each pathway with corresponding survival time given in QALMs.