JMIR Publications

ABSTRACT

Background:

The Pancreatic Cancer Action Network (PanCAN) established its Patient Registry to gather real-world data from patients with pancreatic cancer and their caregivers, related to their diagnosis, symptoms and symptom management, treatments, and more. Described here are results from version 2 of the PanCAN Registry.

Objective:

We sought to gather and evaluate patient-reported outcomes (PRO) data inputted into the PanCAN Patient Registry from December 2020 to January 2024, the period of time that the registry was housed on the LunaDNA platform. Statistical analyses were employed to identify significant findings from a relatively small sample size (271 participants, as defined by people who filled out the Basics survey of the PanCAN Registry).

Methods:

Participation in the PanCAN Patient Registry was voluntary, and participants filled out an online consent form prior to joining the registry. Participants were identified through the PanCAN Patient Services Help Line or navigated to the registry directly via the pancan.org website. Data analysis took place via bivariate analysis using the Chi-square test for categorical variables, with a P-value of < 0.1 considered significant.

Results:

Pain was reported by 186 out of the 207 (89.9%) PanCAN Patient Registry participants who filled out the pain-related questions in the General Assessment survey. We observed a significant (P=0.061) difference between the reporting of pain by patients younger than 65 (93.5%) and those 65 or older (84.6%). Depression was also a common condition experienced by patients with pancreatic cancer, with 64/103 (62.1%) indicating that they were experiencing or had experienced depression during the course of their illness. Depression was more frequently reported among the subset of patients who also reported pain (66.3%) compared to those who did not report pain (38.5%) (P=0.066).

Conclusions:

The dissemination of these results demonstrates the value of PROs for patients with pancreatic cancer and the use of real-world data with the potential to have direct impact on clinical practice.