Development and Validation of a Survival Prediction Model for Patients with Pancreatic Cancer.
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INTRODUCTION: Patients with pancreatic ductal adenocarcinoma (PDAC) face challenging treatment decisions following their diagnosis. We developed and validated a survival prognostication model using routinely available clinical information, patient-reported symptoms, performance status, and initial cancer-directed treatment. METHODS: This retrospective cohort study included PDAC patients from 2007 to 2020 using linked administrative databases in Ontario, Canada. Patients were randomly selected for model development (75%) and validation (25%). Using the development cohort, a multivariable Cox proportional hazards regression with backward stepwise variable selection was used to predict the probability of survival. Model performance was assessed on the validation cohort using the concordance index and calibration plots. RESULTS: There were 17,450 patients (49% female) with a median age of 72 (IQR 63-81) and a mean survival time of nine months. In the derivation cohort, 1,469 (11%) patients had early stage, 4,202 (32%) had advanced stage disease, and 7,417 (57%) had unknown stage. The following factors were associated with an increased risk of death by more than 10%: tumour in the tail of the pancreas, advanced stage, hospitalization three months prior to diagnosis, congestive heart failure or dementia, low, moderate, or high pain score, moderate or high appetite score, high dyspnea and tiredness score, and a performance status score of 60-70 or lower. The calibration plot indicated good agreement with a C index of 0.76. DISCUSSION: This model accurately predicted one-year survival for PDAC using clinical factors, symptoms, and performance status. This model may foster shared decision making for patients and their providers.
