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. 2023 Jan 1;277(1):151-158.
doi: 10.1097/SLA.0000000000004915. Epub 2021 Apr 9.

Surgical Decision-Making in Pancreatic Ductal Adenocarcinoma: Modeling Prognosis Following Pancreatectomy in the Era of Induction and Neoadjuvant Chemotherapy

Affiliations

Surgical Decision-Making in Pancreatic Ductal Adenocarcinoma: Modeling Prognosis Following Pancreatectomy in the Era of Induction and Neoadjuvant Chemotherapy

Joseph R Habib et al. Ann Surg. .

Abstract

Objective: To develop a predictive model of oncologic outcomes for patients with pancreatic ductal adenocarcinoma (PDAC) undergoing resection after neoadjuvant or induction chemotherapy use.

Background: Early recurrence following surgical resection for PDAC is common. The use of neoadjuvant chemotherapy prior to resection may increase the likelihood of long-term systemic disease control. Accurately characterizing an individual's likely oncologic outcome in the perioperative setting remains challenging.

Methods: Data from patients with PDAC who received chemotherapy prior to pancreatectomy at a single high-volume institution between 2007 and 2018 were captured in a prospectively collected database. Core clinicopathologic data were reviewed for accuracy and survival data were abstracted from the electronic medical record and national databases. Cox-proportional regressions were used to model outcomes and develop an interactive prognostic tool for clinical decision-making.

Results: A total of 581 patients were included with a median overall survival (OS) and recurrence-free survival (RFS) of 29.5 (26.5-32.5) and 16.6 (15.8-17.5) months, respectively. Multivariable analysis demonstrates OS and RFS were associated with type of chemotherapeutic used andthe number of chemotherapy cycles received preoperatively. Additional factors contributing to survival models included: tumor grade, histopathologic response to therapy, nodal status, and administration of adjuvant chemotherapy. The models were validated using an iterative bootstrap method and with randomized cohort splitting. The models were well calibrated with concordance indices of 0.68 and 0.65 for the final OS and RFS models, respectively.

Conclusion: We developed an intuitive and dynamic decision-making tool that can be useful in estimating OS, RFS, and location-specific disease recurrence rates. This prognostic tool may add value to patient care in discussing the benefits associated with surgical resection for PDAC.

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Conflict of interest statement

The authors declare no conflicts of interest.

Comment in

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