Validation of a prediction rule to maximize curative (R0) resection of early-stage pancreatic adenocarcinoma

Abstract

Background: The surgeon's contribution to patients with localized pancreatic adenocarcinoma (PAC) is a margin negative (R0) resection. We hypothesized that a prediction rule based on pre-operative imaging would maximize the R0 resection rate while reducing non-therapeutic intervention.

Methods: The prediction rule was developed using computed tomography (CT) and endoscopic ultrasound (EUS) data from 65 patients with biopsy-proven PAC who underwent attempted resection. The rule classified patients as low or high risk for non-R0 outcome and was validated in 78 subsequent patients.

Results: MODEL VARIABLES WERE: any evidence of vascular involvement on CT; EUS stage and EUS size dichotomized at 2.6 cm. In the validation cohort, 77% underwent resection and 58% achieved R0 status. If only patients in the low-risk group underwent surgery, the prediction rule would have increased the resection rate to 92% and the R0 rate to 73%. The R0 rate was 40% higher in low-risk compared with high-risk patients (P < 0.001). High risk was associated with a 67% rate of non-curative surgery (unresectable disease and metastases).

Conclusion: The prediction rule identified patients most likely to benefit from resection for PAC using pre-operative CT and EUS findings. Model predictions would have increased the R0 rate and reduced non-therapeutic interventions.

Figures

Figure 1

Classification tree and surgical outcomes after application of the prediction rule. R0 margin-negative resection; R1 margin-positive; LA locally advanced unresectable disease; met metastases