Precision Medicine and Imaging A Method to Summarize Toxicity in Cancer Randomized Clinical Trials Mariana Carbini 1 , Mayte Su arez-Fari ~ nas 2 , and Robert G. Maki 1,3 Abstract Purpose: Despite development of clinical "value frame- works" by national and international groups, there remains no generally accepted method to summarize toxicity in cancer clinical trials. We explored ways to simplify toxicity data of an arm of a cancer clinical trial to a single value, termed a "weighted toxicity score" (WTS). Experimental Design: We compiled 58 randomized clin- ical trials of FDA-approved kinase-directed inhibitors. We generated 5 models, each of which assigned different weights for each observed grade 1 to 4 toxicities. For each model, we calculated WTS values as different weighted averages of the sum of the toxicities. We correlated each WTS with the dose reduction rate in each trial, using the dose reduction rate as a clinically relevant surrogate of treatment that is too toxic. The WTS method yielding the strongest correlation with frequency of dose reduction was declared the best model. Results: Nineteen of 58 trials were placebo controlled and had complete data. Of the 5 models examined, differences in dose reduction rates correlated best with differences in WTS using a model with a clinician-weighted scale for toxicities (model M5). The WTS difference thus serves as a surrogate for a desired dose reduction rate difference and could be used to adjust dose/schedule as patients are accrued to a clinical trial. Conclusions: The WTS distills a tabular listing of toxicities of a treatment into a single value, and provides a simple method that can be incorporated into value frameworks, or used to guide discussion of the risks and benefits of systemic therapy. Clin Cancer Res; 24(20); 4968–75. Ó2018 AACR. See related commentary by Vaishampayan, p. 4918 Introduction In randomized trials of systemic therapy in oncology, clinicians examine and compare both efficacy and toxicity of treatments. Efficacy is reported using well-established parameters such as progression-free survival (PFS), and comparisons are made using P values and 95% confidence intervals, based on the statistical design (1). Tabular data remain the principal method that adverse effects of treatment are reported in clinical trials. However, toxicity reporting is not done consistently from one study to the next. Occasionally, the differences in individual toxicities are reported using P values, but in most studies, there is only a tacit comparison between toxicities in treatment arms. Furthermore, there are very few data published on toxicity as a function of time (2). How are benefits and toxicities compared in cancer clinical trials? The use of patient-reported outcomes constitutes one way of measuring the impact of toxicity on patients (3, 4). For example, the Patient Reported Outcomes-Common Toxicity Criteria for Adverse Events (PRO-CTCAE) was developed to capture patient adverse events directly from the patient without the filter of a clinician (5). The American Society of Clinical Oncology (ASCO), European Society for Medical Oncology (ESMO), and others have generated tools to integrate both toxicity and benefits of chemotherapy to determine the relative value of a specific treatment to a patient, and by extension to society in general (6–9). These frameworks attempt to quan- titate the gestalt a clinician develops regarding the benefit and toxicity of different treatments. The ASCO framework uses a semiquantitative method to calculate net toxicity of a therapy; the ESMO framework presently does not assess toxicity. Fur- thermore, the ASCO and ESMO frameworks examine different aspects of patient benefit (10). Thus, the question of the role of toxicity in comparing the costs and benefits of a given therapy in a cancer clinical trial remains an open issue. Our initial interest in drug toxicity stems from participation in clinical trials of novel agents in cancer patients. A number of agents that received regulatory approval in cancer are too toxic at the approved doses for the average patient, either in terms of acute toxicity requiring early dose reduction, or chronic toxicity for people remaining on systemic therapy for extended periods of time. In the most extreme situations, over half of patients required dose reductions in phase III trials of anticancer agents, exposing patients to undue toxicity and potentially leading to premature termination of potentially useful therapy, far in excess of what one would have expected from typical phase I trial design, in which the goal of a classic 3þ3 design is to see dose-limiting toxicity in no more than 1 in 6 patients (11–14). We sought to simplify and make more objective the quantita- tion of toxicity, which might allow a more direct comparison of outcomes to summary toxicity. Our hypothesis was that reducing the tabular data to a single number will facilitate the discussion of the cost-benefit ratio within an individual clinical trial. 1 Monter Cancer Center, Northwell Cancer Institute, Lake Success, New York. 2 Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York. 3 Cold Spring Harbor Laboratory, Cold Spring Harbor, New York. Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/). Prior Presentation: Presented in part at the 52nd Annual Meeting of the American Society of Clinical Oncology, June 3–7, 2016. Corresponding Author: Robert G. Maki, Northwell Cancer Institute and Cold Spring Harbor Laboratory, 450 Lakeville Road, Lake Success, NY 11042. Phone: 516-734-8976; Fax: 516-734-8633; E-mail: bobmakimd@gmail.com doi: 10.1158/1078-0432.CCR-17-3314 Ó2018 American Association for Cancer Research. Clinical Cancer Research Clin Cancer Res; 24(20) October 15, 2018 4968 on June 5, 2020. © 2018 American Association for Cancer Research. clincancerres.aacrjournals.org Downloaded from Published OnlineFirst May 8, 2018; DOI: 10.1158/1078-0432.CCR-17-3314