Prediction of resection after preoperative FOLFIRINOX in patients with localized pancreatic adenocarcinoma: a Trans-Atlantic Pancreatic Surgery (TAPS) Consortium study.
retrospective_cohort · Level III
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- Also identified by DOI 10.1093/jnci/djag033.
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Abstract
Neoadjuvant chemotherapy is increasingly used for patients with localized pancreatic ductal adenocarcinoma (PDAC), although the likelihood of subsequent resection remains uncertain. The aim of this study was to develop a prediction model using baseline characteristics to estimate the probability of meeting prespecified criteria for resection after induction FOLFIRINOX. This retrospective study included patients with localized PDAC who received (m)FOLFIRINOX as initial treatment in five referral centers in the United States and the Netherlands (2012-2019). Multivariable logistic regression identified independent predictors of resection and was used to develop a prediction model. Among 1,835 patients, 18.9% were classified as potentially resectable (PR), 28.9% as borderline resectable (BR), and 52.2% as locally advanced (LA). Observed resection rates were 70.5% for PR, 53.1% for BR, and 17.8% for LA PDAC. Unfavourable independent factors for resection were advanced anatomical stage (BR, OR 0.51; 95% CI 0.37 to 0.69 and LA, OR 0.11; 95% CI 0.08 to 0.15), baseline CA19-9 > 500U/mL (OR 0.60; 95% CI 0.46 to 0.77), a WHO performance status of ≥ 1 (OR 0.41; 95% CI 0.33 to 0.52), and tumor size on baseline imaging >40mm (OR 0.62; 95% CI 0.48 to 0.80). Depending on these factors, the predicted probability of resection ranged from 6.7% to 81.7%. At diagnosis, the probability of resection after induction (m)FOLFIRINOX for localized PDAC ranged from 7% to 82%, depending on anatomical stage, CA19-9 level, performance status, and tumor size at baseline. This prediction model may help communicating realistic expectations for the probability of resection. Resection probabilities after induction (m)FOLFIRINOX for localized pancreatic ductal adenocarcinoma range from 7% to 82% at diagnosis, based on baseline characteristics. The prediction model developed in this study can guide shared decision-making by providing individualized, evidence-based estimates of resectability.