Abstract
PURPOSE: Few population studies have examined patterns of systemic therapy administration in metastatic pancreatic cancer (MPC) or the predictors associated with specific treatment choices. PATIENTS AND METHODS: We assessed 4,011 consecutive MPC patients who received chemotherapy between January 2005 and December 2015 at academic, private, and community-based oncology practices subscribing to a U.S.-wide chemotherapy order entry system capturing disease, patient, provider, and treatment data. Multivariate analyses of these prospectively recorded characteristics identified significant predictors of specific therapeutic choices. RESULTS: Overall, 100 different regimens were used in first-line treatment of MPC. First-line gemcitabine monotherapy usage fell steadily from 72% in 2006 to 16% in 2015. This steep decline mirrored increases in first-line usage of both 5 fluorouracil, leucovorin, irinotecan and oxaliplatin (FOLFIRINOX) and gemcitabine + nab-paclitaxel. Younger male patients were more likely to receive FOLFIRINOX as first-line treatment, whereas patients treated at community practices and by oncologists with lower MPC patient volume were more likely to receive gemcitabine plus nab-paclitaxel (all p ≤ .05). Among all patients receiving first-line chemotherapy for MPC, 49% went on to receive second-line therapy and 19% received third-line therapy; administration of second- and third-line therapies increased steadily over the time course of follow-up. Younger patients and those treated by oncologists with higher MPC patient volume were more likely to receive second- and third-line therapies. CONCLUSION: This population-based study provides insight into treatment patterns of MPC in the U.S. Usage patterns varied greatly according to patient and provider characteristics. IMPLICATIONS FOR PRACTICE: This study examined real world metastatic pancreatic cancer treatment patterns in the United States with the goals of understanding changes in chemotherapy treatment frequencies over time and determining the individual predictors that underlie the chemotherapy choices oncologists make for their patients. Our data set is unique in that it captured not only patient-level data, but also oncologist-level data. It also captured data from private and community practices as well as academic centers. To our knowledge, this is the only data set that can give this degree of insight into oncologist decision making practices.