A toolbox of different approaches to analyze and present PRO-CTCAE data in oncology studies.

Abstract

BACKGROUND:

The patient-reported outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) is used to assess symptomatic adverse events in oncology trials. Currently, no standard for PRO-CTCAE analysis exists.

METHODS:

Key methods of descriptive analysis and longitudinal modeling using PRO-CTCAE data from an oncology clinical trial, DRiving Excellence in Approaches to Multiple Myeloma-2 (DREAMM-2), a phase II trial of belantamab mafodotin in multiple myeloma (NCT03525678), were explored. Descriptive methods included maximum postbaseline ratings, mean change over time, ratings above a predefined cutoff, line graphs, and stacked bar charts to illustrate patient-reported adverse events at one timepoint or dynamics over time. Analysis methods involving modeling over time included toxicity over time (ToxT) (repeated measurement model, time-to-event, area under the curve analyses), generalized estimating equations (GEE), and ordinal log-linear models (OLLMs).

RESULTS:

Visualizations of PRO-CTCAE data highlighted different aspects of the data. Selection of the appropriate visualization will depend on the audience and message to be conveyed. Consistent results were obtained by all modeling approaches; no difference was found between dose groups of the DREAMM-2 study in any PRO-CTCAE item by the ToxT approach or the more sophisticated GEE and OLLM methods. Interpretation of GEE results was the most challenging. OLLM supported the interval nature of the PRO-CTCAE response scale in the DREAMM-2 study. All modeling approaches account for multiple testing (driven by the number of items).

CONCLUSIONS:

Descriptive analyses and longitudinal modeling approaches are complementary approaches to presenting PRO-CTCAE data. In modeling, the ToxT approach may be a good compromise compared with more sophisticated analyses.

• Authors: Antoine Regnault, Angély Loubert, Boris Gorsh, Randy Davis, Anna Cardellino, Kristin Creel, Stéphane Quéré, Sandhya Sapra, Linda Nelsen, Laurie Eliason
• Journal: Journal of the National Cancer Institute (J Natl Cancer Inst) Vol. 115 Issue 5 Pg. 586-596 (05 08 2023) ISSN: 1460-2105 [Electronic] United States
• PMID: 36715639 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © The Author(s) 2023. Published by Oxford University Press.

Chemical References

• Antibodies, Monoclonal, Humanized

Topics

• Humans
• Multiple Myeloma (drug therapy)
• Neoplasms (drug therapy)
• Medical Oncology
• Patient Reported Outcome Measures
• Antibodies, Monoclonal, Humanized
• Linear Models