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Personalized outcomes in neuropathic pain: a clinical relevance and assay sensitivity analysis from a randomized
Karim Saab1, Umang Gada2, Eva Culakova2
1Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, United States.
Objective:
To explore the clinical relevance and assay sensitivity of using personalized outcomes using data from a randomized clinical trial (RCT) in people with chemotherapy-induced peripheral neuropathy (CIPN).
Design:
This study is a secondary analysis that leveraged data from a RCT of transcutaneous electrical stimulation for CIPN to test whether personalized outcomes could minimize potential floor effects and increase the assay sensitivity of pain clinical trials (ie, ability to detect a true treatment effect).
Setting:
Participants were recruited for a RCT from community oncology clinics in the United States.
Participants:
Adults with CIPN (N = 72) who reported on average ≥4 intensity (measured via a 7-day baseline diary) for at least 1 of the following pain qualities: hot/burning pain, sharp/shooting pain, and/or cramping.
Methods:
Personalized outcomes were defined based on participants' unique presentation of pain qualities at baseline, measured via 0-10 numeric rating scales (NRS), or ranking of the distress caused by the pain qualities. Analysis of covariance models estimated the treatment effect as measured by personalized and non-personalized outcomes.
Results:
The adjusted mean difference between groups was higher using personalized outcomes (ie, 1.21-1.25 NRS points) compared to a non-personalized outcome (ie, 0.97 NRS points), although the standardized effect sizes were similar between outcomes (0.49-0.54).
Conclusions:
These results suggest that personalized pain quality outcomes could minimize floor effects, while providing similar assay sensitivity to non-personalized pain quality outcomes. Personalized outcomes better reflect an individual's unique experience, inherently providing more clinically relevant estimates of treatment effects. Personalized outcomes may be advantageous, particularly for clinical trials in populations with high inter-individual variability in pain qualities.
