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Record W2761205222 · doi:10.1186/s12885-017-3664-z

Selection of opioids for cancer-related pain using a biomarker: a randomized, multi-institutional, open-label trial (RELIEF study)

2017· article· en· W2761205222 on OpenAlexaboutno aff
Hiromichi Matsuoka, Junji Tsurutani, Yasutaka Chiba, Yoshihiko Fujita, Masato Terashima, Takeshi Yoshida, Kiyohiro Sakai, Yoichi Otake, Atsuko Koyama, Kazuto Nishio, Kazuhiko Nakagawa

Bibliographic record

VenueBMC Cancer · 2017
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
FundersMinistry of Health, Labour and WelfareJapan Agency for Medical Research and Development
KeywordsMedicineSurgical oncologyRandomized controlled trialCancer painBiomarkerSelection (genetic algorithm)Open labelOncologyPain medicineCancerInternal medicineAnesthesiaAnesthesiologyArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer patients experience pain that has physiological, sensory, affective, cognitive, behavioral, and sociocultural dimensions. Opioids are used in treatment of pain in patients with various types of cancer. We previously showed that the catechol-O-methyltransferase (COMT) genotype is related to the plasma level of morphine and the required dose of morphine in an exploratory prospective study. The findings showed that a group of patients with a GG single nucleotide polymorphism (SNP) rs4680 in COMT required a significantly higher dose of morphine than a non-GG group. A biomarker for selection of opioids for cancer pain relief would be particularly useful clinically, and therefore we have planned a randomized comparative study of morphine and oxycodone, using the COMT rs4680 SNP as a biomarker. This study is aimed at verifying the assumption that patients in the GG group require an increased morphine dose for pain relief. METHODS: The RELIEF study is a randomized, multi-institutional, open-label trial with a primary endpoint of the proportion of subjects requiring high-dose opioids, as calculated from the dose of a rescue preparation administered on day 0. Secondary endpoints include the Hospital Anxiety and Depression Scale, Short form McGill Pain Questionnaire-2, European Organization for Research and Treatment of Cancer QLQ-C15-PAL, Pain Catastrophizing Scale, and adverse events, Eligibility criteria are patients with advanced carcinoma with non-daily use of opioids in initial screening for registration; and cancer pain targeted for daily opioid treatment, NSAIDs or acetaminophen, NRS ≥3(average over 24 h), opioid-treatment naive within 30 h, no chemotherapy, radiotherapy, or bisphosphonate administration newly started within 2 weeks, and written informed consent at the time of second registration. Between November 2014 and June 2017, an estimated 110 patients from two sites in Japan were randomized (1:1) to morphine or oxycodone in GG and non-GG groups. DISCUSSION: A method for selection of appropriate opioids in cancer patients is a high unmet medical need. This study was designed to evaluate the efficacy of different opioids in patients with cancer based on gene polymorphism, as the first potential multi-institutional registration trial to be conducted in cancer patients with pain. TRIAL REGISTRATION: UMIN000015579 Date of registration: 4 November 2014. It is updated once every six months, the latest update is 30 June 2017. Trial status. The enrollment started in November 2014. At the time of manuscript submission (July 2017), Three-quarters of patients have participated. We thus expect to complete the recruitment by March 2018.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.156
GPT teacher head0.426
Teacher spread0.270 · 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 teacher head, not a consensus.

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

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

Citations10
Published2017
Admission routes1
Has abstractyes

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