# Duloxetine to Prevent Oxaliplatin-Induced Chemotherapy-Induced Peripheral Neuropathy: A Randomized, Double-Bind, Placebo-Controlled Phase II to Phase III Study

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $195,405

## Abstract

In the United States in 2017, most of the 135,000 people diagnosed with colorectal cancer received oxaliplatin
to treat stage II-IV disease. About 70% of patients develop oxaliplatin-induced peripheral neuropathy (OIPN)
that is characterized by upper and lower extremity numbness (N) and tingling (T), which can persist for years.
Painful OIPN develops after N and T in 30% of patients. OIPN (N, T, and pain) poses a major health risk
because it is associated with impaired function, falls, depression, impaired sleep, poor quality of life, and is a
common reason for chemotherapy dose reductions. A critical gap in our scientific knowledge is that no known
preventive interventions for OIPN exist. To address this gap, our overall objective is to test whether duloxetine
prevents oxaliplatin-induced N, T, and pain, using a sequential Phase II to Phase III design that will be
conducted via the National Cancer Institute (NCI) Community Oncology Research Program (NCORP), a large,
multisite research network with access to diverse patient populations. Duloxetine will be tested in this study
based on evidence of its efficacy for established OIPN from two clinical trials (Yang et al, 2012; Smith et al.,
2013), and our pre-clinical data showing that duloxetine prevents painful OIPN in rats. We will first conduct a
randomized, 3-arm, double-blind, placebo-controlled, non-comparative, multi-center study (N = 171) to screen
two daily doses of duloxetine—30 mg and 60 mg—to prevent OIPN (N, T, and pain). If duloxetine is shown to
be clinically active in the Phase II study, we will proceed to a randomized, double-blind, placebo-controlled,
multi-center Phase III study to compare what appears to be the most promising duloxetine dose to placebo. To
maximize the use of patient resources, the Phase II data from patients who either completed treatment with
placebo (n = 54) or the most promising duloxetine dose (n = 54) will be pooled with data obtained from new
Phase III trial accruals to the placebo (n = 70) and most promising duloxetine dose arms (n = 70), respectively
(N = 248). We will use pre-established stopping rules to determine the optimal dose based on the proportions
of patients who do not develop N, T, and pain, and adverse event severity. The two primary hypotheses in the
Phase III study are that the most promising duloxetine dose will be more effective than placebo to prevent 1) N,
T, & pain during oxaliplatin treatment and 2) chronic neuropathic pain one month after treatment. The temporal
patterns of OIPN and functional impairment will be assessed for 18 months after oxaliplatin treatment. This
study addresses the NCI Cancer Moonshot goal to minimize cancer treatment-associated debilitating side
effects, and the priority recommendation outlined in the Institute of Medicine's Relieving Pain in America report
regarding the need for non-opioid treatments for chronic pain. By addressing these priorities, we expect to
make a major advancement in the field of sympt...

## Key facts

- **NIH application ID:** 9849262
- **Project number:** 5R01CA235726-02
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Ellen Mary Lavoie Smith
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $195,405
- **Award type:** 5
- **Project period:** 2019-01-10 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9849262

## Citation

> US National Institutes of Health, RePORTER application 9849262, Duloxetine to Prevent Oxaliplatin-Induced Chemotherapy-Induced Peripheral Neuropathy: A Randomized, Double-Bind, Placebo-Controlled Phase II to Phase III Study (5R01CA235726-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9849262. Licensed CC0.

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