Prognostic models to predict survival in patients with pancreatic cancer

a systematic review

Review (2022)

Authors

Liane J. Ioannou Monash University
A.D. Maharaj Monash University
Elizabeth A. Burmeister University of Queensland
Kate White University of Sydney
Rachel E. Neale Queensland Institute of Medical Research
Sue M. Evans Monash University
John R. Zalcberg Monash University
Jesse T. Loughnan Monash University
Daniel Croagh Monash University
Charles H.C. Pilgrim Monash University
David Goldstein University of New South Wales Faculty of Medicine
James G. Kench Royal Prince Alfred Hospital, University of Sydney
Neil D. Merrett Western Sydney University
Arul Earnest Monash University
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Published Date

2022

Language

English

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Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) has poor survival. Current treatments offer little likelihood of cure or long-term survival. This systematic review evaluates prognostic models predicting overall survival in patients diagnosed with PDAC. Methods: We conducted a comprehensive search of eight electronic databases from their date of inception through to December 2019. Studies that published models predicting survival in patients with PDAC were identified. Results: 3297 studies were identified; 187 full-text articles were retrieved and 54 studies of 49 unique prognostic models were included. Of these, 28 (57.1%) were conducted in patients with advanced disease, 17 (34.7%) with resectable disease, and four (8.2%) in all patients. 34 (69.4%) models were validated, and 35 (71.4%) reported model discrimination, with only five models reporting values >0.70 in both derivation and validation cohorts. Many (n = 27) had a moderate to high risk of bias and most (n = 33) were developed using retrospective data. No variables were unanimously found to be predictive of survival when included in more than one study. Conclusion: Most prognostic models were developed using retrospective data and performed poorly. Future research should validate instruments performing well locally in international cohorts and investigate other potential predictors of survival.