Adverse event load, onset, and maximum grade: A novel method of reporting adverse events in cancer clinical trials

Guilherme S. Lopes, Christophe Tournigand, Curtis L. Olswold, Romain Cohen, Emmanuelle Kempf, Leonard Saltz, Richard M. Goldberg, Herbert Hurwitz, Charles Fuchs, Aimery de Gramont, Qian Shi

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Current adverse event reporting practices do not document longitudinal characteristics of adverse effects, and alternative methods are not easily interpretable and have not been employed by clinical trials. Introducing time parameters in the evaluation of safety that are comprehensive yet easily interpretable could allow for a better understanding of treatment quality. In this study, we developed and applied a novel adverse event reporting method based on longitudinal adverse event changes to aid describing, summarizing, and presenting adverse event profile. We termed it the “Adverse Event Load, Onset, and Maximum Grade” method. Methods: We developed two adverse event summary metrics to complement the traditional maximum grade report. Onset time indicates the time period in which the maximum grade for a specific adverse event occurred and was defined as “early” (i.e. maximum grade happened for the first time before 6 weeks) or “late” (i.e. after the 6th week). Adverse event load indicates the overall severity of a specific adverse event over the entire treatment. Higher adverse event load indicates a worse overall experience. These metrics can be calculated for adverse events with different maximum grades, in treatments with planned changes (e.g. dosage changes), using data sets with different number of adverse event data points between treatments (e.g. treatments with longer cycle lengths may have less adverse event data points) and on data sets with different adverse event data availability (e.g. cycle basis and patient-outcome reports). We tested the utility of this method using individual patient data from two major backbone therapies (“Irinotecan” and “Oxaliplatin”) from the N9741 trial available in the Fondation ARCAD database (fondationarcad.org). We investigated profiles of diarrhea, neutropenia/leukopenia, and nausea/vomiting. Results: Our method provided additional information compared to traditional adverse event reports. For example, for nausea/vomiting, while patients in Irinotecan had a higher risk of experiencing maximum grade 3–4 (15.6% vs 7.6%, respectively; p < 0.001), patients in both groups experienced similar severity over time (adverse effect load = 0.102 and 0.096, respectively; p = 0.26), suggesting that patients in Oxaliplatin experienced a lower-grade but more persistent nausea/vomiting. For neutropenia/leukopenia, more patients in Irinotecan experienced their maximum grade for the first time early in the treatment compared to patients in Oxaliplatin (67.9% vs 41.7%; p < 0.001), regardless of maximum grade. Longitudinal information can help compare treatments or guide clinicians on choosing appropriate interventions for low-grade but persistent adverse event or early adverse event onset. Conclusion: We developed an adverse event reporting method that provides clinically relevant information about treatment toxicity by incorporating two longitudinal adverse event metrics to the traditional maximum grade approach. Future research should establish clinical benchmarks for metrics included in this adverse event reporting method.

Original languageEnglish (US)
Pages (from-to)51-60
Number of pages10
JournalClinical Trials
Volume18
Issue number1
DOIs
StatePublished - Feb 2021

Keywords

  • Adverse events
  • adverse event load
  • clinical trials
  • longitudinal analysis
  • onset time
  • safety
  • toxicity

ASJC Scopus subject areas

  • Pharmacology

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