Projects per year
This review aims to compare both treatment strategies for resectable pancreatic cancer. PubMed, MEDLINE, Embase, Cochrane Database and Cochrane Databases were searched for studies comparing neoadjuvant and surgery-first with adjuvant therapy for resectable pancreatic cancer. A Bayesian network meta-analysis was conducted using the Markov chain Monte Carlo method. Cochrane Collaboration’s risk of bias, ROBINS-I and GRADE tools were used to assess quality and risk of bias of included trials.
9 studies compared neoadjuvant therapy and surgery-first with adjuvant therapy (n = 22,285). Aggregate rate (AR) of R0 resection for neoadjuvant therapy was 0.8008 (0.3636–0.9144) versus 0.7515 (0.2026–0.8611) odds ratio (O.R.) 1.27 (95% CI 0.60–1.96). 1-year survival AR for neoadjuvant therapy was 0.7969 (0.6061–0.9500) versus 0.7481 (0.4848–0.8500) O.R. 1.38 (95% CI 0.69–2.96). 2-year survival AR for neoadjuvant therapy was 0.5178 (0.3000–0.5970) versus 0.5131 (0.2727–0.5346) O.R. 1.26 (95% CI 0.94–1.74). 5-year AR survival for neoadjuvant therapy was 0.2069 (0.0323–0.3300) versus 0.1783 (0.0606–0.2300) O.R. 1.19 (95% CI 0.65–1.73).
In conclusion neoadjuvant therapy may offer benefit over surgery-first and adjuvant therapy. However, further randomized controlled trials are needed.
- pancreatic cancer
- neoadjuvant therapy
- Bayesian network model
Computer simulated comparison of neoadjuvant versus upfront surgery for resectable pancreatic cancer: the application of machine-learning algorithms to support personalised decision-makingBradley, A., Van Der Meer, R. & McKay, C., 7 Dec 2020, In: British Journal of Surgery. 107, S4, p. 141-141 1 p., WS15.014.
Research output: Contribution to journal › Meeting abstract › peer-reviewOpen Access
Optimising outcomes for resectable pancreatic cancer by learning lessons from military strategy and the stockmarket: creation of a prognostic Bayesian belief network that makes personalised pre and post-operative predictions of outcome across competing treatment strategiesBradley, A., van der Meer, R. & McKay, C. J., 7 Dec 2020, In: British Journal of Surgery. 107, S4, p. 141 1 p., WS15.015.
Research output: Contribution to journal › Meeting abstract › peer-review
A prognostic Bayesian network that makes personalized predictions of poor prognostic outcome post resection of pancreatic ductal adenocarcinomaBradley, A., Van der Meer, R. & McKay, C. J., 9 Sep 2019, In: PLoS ONE. 14, 9, 14 p., e0222270.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile1 Citation (Scopus)2 Downloads (Pure)