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Background Persistent cancer-related fatigue is one of the most common and burdensome symptoms experienced by ovarian cancer survivors. Despite the high burden of fatigue in ovarian cancer survivors, there are few available treatments. Previous research has shown self-acupressure to be a safe method for improving persistent fatigue, sleep, and quality of life among fatigued breast cancer survivors, yet there are no studies examining self-acupressure for fatigue in ovarian cancer survivors. Methods A three group parallel, randomized controlled trial will be conducted to evaluate the efficacy of self-acupressure taught and delivered via a patient-designed, custom-built mobile app ("MeTime") and accompanying hand-held device ("AcuWand") to help guide correct pressure application. A sample of 165 ovarian cancer survivors, who have completed primary cancer treatment will be recruited from tumor registries in Michigan and Los Angeles. Participants will be mailed a tablet preloaded with the app and a device, and all visits will be conducted remotely. Participants will be randomized to 6-weeks of daily self-acupressure via the app and device, or a sham app and device, or no care group. Self-report measures will be completed at baseline, 6-weeks (post-intervention), 3-, and 6-months. Primary outcome is the Brief Fatigue Inventory; secondary outcomes are sleep, quality of life, and symptoms commonly associated with persistent fatigue. Discussion An app based self-acupressure treatment may be an easily-accessible and inexpensive treatment to reduce fatigue in ovarian cancer survivors. The results of the study will provide information on the possible benefits of app-based self-acupressure for fatigue in ovarian cancer survivors. Trial registration: This study is registered at ClinicalTrials.gov Identifier: NCT03763838, date registered on December 4, 2018., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Fibromyalgia is a chronic pain syndrome characterized by widespread pain, fatigue, and memory and mood disturbances. Despite advances in our understanding of the underlying pathophysiology, treatment is often challenging. New research indicates that changes in functional connectivity between brain regions, as can be measured by magnetic resonance imaging (fcMRI) of the resting state, may underlie the pathogenesis of this and other chronic pain states. As such, this parameter may be able to be used to monitor changes in brain function associated with pharmacological treatment, and might also be able to predict treatment response. We performed a resting state fcMRI trial using a randomized, placebo-controlled, cross-over design to investigate mechanisms of action of milnacipran (MLN), a selective serotonin and norepinephrine reuptake inhibitor (SNRI), in fibromyalgia patients. Our aim was to identify functional connectivity patterns at baseline that would differentially predict treatment response to MLN as compared to placebo. Since preclinical studies of MLN suggest that this medication works by augmenting antinociceptive processes, we specifically investigated brain regions known to be involved in pain inhibition. 15 fibromyalgia patients completed the study, consisting of 6 weeks of drug and placebo intake (order counterbalanced) with an interspersed 2 week wash out period. As a main finding we report that reductions in clinical pain scores during MLN were associated with decreased functional connectivity between pro-nociceptive regions and antinociceptive pain regions at baseline, specifically between the rostral part of the anterior cingulate cortex (ACC) and the insular cortex (IC), as well as between the periaqueductal gray (PAG) and the IC: patients with lower preexisting functional connectivity had the greatest reduction in clinical pain. This pattern was not observed for the placebo period. However a more robust placebo response was associated with lower baseline functional connectivity between the ACC and the dorsolateral prefrontal cortex. This study indicates that ACC-IC connectivity might play a role in the mechanism of action of MLN, and perhaps more importantly fcMRI might be a useful tool to predict pharmacological treatment response.