Author(s)
Wong HL1, Degeling K2, Jalali A1, Shapiro J3, Kosmider S4, Wong R5, Lee B1, Burge M6, Tie J1, Yip D7, Nott L8, Khattak A9, Lim S10, Caird S11, IJzerman M12, Gibbs P1
1Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia, 2University of Twente, Enschede, Netherlands, 3Cabrini Health, Malvern, VIC, Australia, 4Western Health, Footscray, VIC, Australia, 5Walter and Eliza Hall Institute of Medical Research, Box Hill, Australia, 6Royal Brisbane and Women’s Hospital,, South Brisbane, QLD, Australia, 7The Canberra Hospital, Garran, ACT, Australia, 8Royal Hobart Hospital, Hobart, TAS, Australia, 9FIona Stanley Hospital, Murdoch, Australia, 10Campbelltown Hospital, Campbelltown, NSW, Australia, 11Gold Coast University Hospital, Southport, QLD, Australia, 12University of Melbourne, Melbourne, VIC, Australia
OBJECTIVES: The wide range of possible treatment combinations and sequences available for metastatic colorectal cancer (mCRC) treatment presents a major challenge to clinicians, who need to determine the optimal approach for an individual patient or patient subset. Real world data are a valuable resource to understand variation in treatment patterns and outcomes in routine practice. This study aimed to develop a data visualization tool to improve understanding of treatment complexity in mCRC and target further research efforts. METHODS: Real world data from an Australian mCRC registry were used to develop an online tool that visualizes variation in treatment sequences using interactive Sankey and sunburst diagrams. These diagrams were customizable to specific patient subsets based on patient and disease characteristics. To allow for different levels of detail, treatments were recoded according to different levels of abstraction. RESULTS: Of 2694 patients, 2057 (76%) started first-line treatment with chemotherapy or a biological agent, 1087 (40%) and 428 (16%) received second and third-line therapy, respectively. Combined, these three lines of treatment accounted for 733 unique sequences. After recoding treatment to the most intensive chemotherapy and the first exposed biologic, 472 unique sequences remained. The most frequent treatment decision by clinicians was whether to initiate first-line doublet chemotherapy with or without bevacizumab (n=1481, 72%), with median progression-free survival (95% confidence interval) of 10.1 months (9.5, 10.8) and 9.2 days (8.5, 10.7), respectively. CONCLUSIONS: This initial exploration of the use of data visualization tools to inform understanding mCRC treatment practice, showed the potential for such tools to define variation in practice patterns and to identify opportunities to improve care and outcomes. Ultimately, clinicians and health system providers may use such tools to improve the delivery of personalized cancer care, where other applications such as health economic simulation models may be useful.
Conference/Value in Health Info
2019-05, ISPOR 2019, New Orleans, LA, USA
Value in Health, Volume 22, Issue S1 (2019 May)
Acceptance Code
ON1
Topic
Clinical Outcomes, Health Service Delivery & Process of Care
Topic Subcategory
Clinician Reported Outcomes, Disease Management, Treatment Patterns and Guidelines
Disease
Oncology, personalized-and-precision-medicine
