Precise Prognostic and Predictive Signature, Stage I-II Pancreatic Ductal Adenocarcinoma (PDAC)
Conditions
Brief summary
The current TNM staging system is not sufficient for prediction of prognosis and cannot precisely identify the patients who are in greater need of adjuvant therapy in pancreatic ductal adenocarcinoma (PDAC). Tumor mutation and copy number variation (CNV) markers may have a higher predictive value. In this study, whole exosome sequencing was performed for patients with stage I-II PDAC undergoing R0 resection. The investigators aimed to identify genes with discrepant statuses of mutations or CNVs between patients with and without relapse within 1 year after R0 resection, and then to construct a support vector machine (SVM)-based prognostic classifier (the SVM signature) for PDAC using machine learning; the investigators then aimed to further validate the SVM signature in an independent cohort.
Interventions
PROCEDUREResection
radical R0 resection of pancreatic adenocarcinoma
Sponsors
The Fourth Affiliated Hospital of Anhui Medical University
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
* Availability of hematoxylin and eosin slides with invasive tumor components * Availability of clinicopathologic characteristics and follow-up data * No previous history of cancer
Exclusion criteria
* No formalin-fixed, paraffin-embedded (FFPE) tumor sample of primary tumor * Receipt of any neoadjuvant and/or adjuvant cancer-directed therapy * Survival time \<3 months after resection
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Disease-free survival | 3-year | the time to recurrence at any site or all-cause death, whichever occurred first |
| Overall survival | 3-year | the time to death from any cause |
Countries
China
Outcome results
None listed