From waterfall plots to spaghetti plots in early oncology clinical development. (3rd April 2019)

• Record Type: Journal Article
• Authors: Mercier, Francois; Consalvo, Nicola; Frey, Nicolas; Phipps, Alex; Ribba, Benjamin
• Is Part Of: Pharmaceutical statistics. Volume 18:Number 5(2019)
• Page Start: 526
• Page End: 532
• Publication Date: 2019-04-03
• Subjects: disease progression -- graphical perception -- longitudinal data -- percentage change from baseline -- tumor size; Pharmacy -- Statistical methods -- Periodicals; Pharmacy -- Statistics -- Periodicals; 615.10727
• DOI: 10.1002/pst.1944
• Languages: English
• ISSNs: 1539-1604

Abstract

SUMMARY: Waterfall plots are used to describe changes in tumor size observed in clinical studies. They are frequently used to illustrate the overall drug response in oncology clinical trials because of its simple representation of results. Unfortunately, this visual display suffers a number of limitations including (1) potential misguidance by masking the time dynamics of tumor size, (2) ambiguous labelling of the y ‐axis, and (3) low data‐to‐ink ratio. We offer some alternatives to address these shortcomings and recommend moving away from waterfall plots to the benefit of plots showing the individual time profiles of sum of lesion diameters (according to RECIST). The spider plot presents the individual changes in tumor measurements over time relative to baseline tumor burden. Baseline tumor size is a well‐known confounding factor of drug effect which has to be accounted for when analyzing data in early clinical trials. While spider plots are conveniently correct for baseline tumor size, they cannot be presented in isolation. Indeed, percentage change from baseline has suboptimal statistical properties (including skewed distribution) and can be overly optimistic in favor of drug efficacy. We argued that plots of raw data (referred to as spaghetti plots) should always accompany spider plots to provide an equipoised illustration of the drug effect on lesion diameters.