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Record W2907894812 · doi:10.2196/12125

Safety of Intranasal Ketamine for Reducing Uncontrolled Cancer-Related Pain: Protocol of a Phase I/II Clinical Trial

2018· article· en· W2907894812 on OpenAlexvenueno aff
Jack W. Shteamer, R. Donald Harvey, Boris Spektor, Kimberly Curseen, Katherine Egan, Zhengjia Chen, Theresa Gillespie, Roman M. Sniecinski, Vinita Singh

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesWinship Cancer InstituteNational Institutes of HealthEmory University
KeywordsNasal administrationProtocol (science)KetamineMedicineClinical trialCancer painAnesthesiaCancerPharmacologyAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Approximately 12 million Americans are affected with cancer. Of these, 53% experience pain at all stages of cancer. Pain may remain uncontrolled despite high-dose opioid therapy, and opioids have many well-documented harmful side effects. Intranasal ketamine has been shown to be effective in controlling breakthrough noncancer pain in a double-blind randomized control trial (DBRCT) by Carr et al in 2003 as well as to help with depression in a DBRCT by Lapidus et al in 2014. We seek to obtain preliminary data on the safety, feasibility, and utility of this novel technique for the treatment of uncontrolled cancer pain. OBJECTIVE: This study aimed to obtain preliminary data via a clinical trial addressing the safety, feasibility, pharmacokinetics, and pharmacodynamics of intranasal ketamine. These initial findings will be applied to a subsequent trial to determine the effectiveness and associated toxicities of ketamine in a larger sample of cancer patients and to address the compelling need to identify new, successful management therapies for cancer pain. METHODS: This is an institutional review board- and investigational new drug-approved, prospective phase I/II trial to investigate the safety and use of intranasal ketamine in patients with uncontrolled pain related to cancer or cancer treatment. Informed consent will be obtained prior to all study procedures. All patients will be assigned to the same investigational treatment arm. After patient selection via inclusion/exclusion criteria, patients will be seen over 5 visits, with each visit conducted 2-7 days apart. Patients will be administered ketamine on visits 1-4 and monitored for 240 minutes with continuous pulse oximetry and regular blood pressure checks. Blood samples as well as patient-reported outcomes will be collected at set time points at baseline and after drug delivery. Patients will receive 10 mg intranasal ketamine on visit 1, 10 mg intravenous ketamine on visit 2, 30 mg intranasal ketamine on visit 3, and 50 mg intranasal ketamine on visit 4. On visit 5, an addition blood sample will be drawn. RESULTS: As of March 2019, enrollment is in progress, and a total of 7 subjects have completed the study. Enrollment is expected to be completed by April 2019. Final data analysis will commence soon after, and the results are expected to be submitted for publication in 2019. CONCLUSIONS: If intranasal ketamine can be utilized for pain control in cancer patients, it could provide superior analgesia and better quality of life, without the risk of significant respiratory depression and constipation associated with opioid medications. These findings will be an important initial step toward testing the effectiveness of intranasal ketamine as a nonopioid medication for cancer pain and as potential maintenance outpatient therapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT03146806; https://clinicaltrials.gov/ct2/show/NCT03146806. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12125.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.036
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.017
Meta-epidemiology (narrow)0.0060.002
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0360.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.246
GPT teacher head0.599
Teacher spread0.353 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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