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Enregistrement W2332339741 · doi:10.1097/01.cot.0000327540.54871.79

New Tool in Development to Assess Geriatric Cancer Pain

2008· article· en· W2332339741 sur OpenAlexaboutno aff
Peggy Eastman

Notice bibliographique

RevueOncology Times · 2008
Typearticle
Langueen
DomaineMedicine
ThématiquePain Management and Opioid Use
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPain medicineMedicineGeriatric oncologyGeriatricsCompetence (human resources)PopulationHealth carePain assessmentCancer painWorkforceQuality of life (healthcare)GerontologyFamily medicineCancerPain managementPhysical therapyNursingPsychologyInternal medicinePsychiatryAnesthesiology

Résumé

récupéré en direct d'OpenAlex

BETHESDA, MD—As the population ages and the number of older people living with cancer increases, so too will the number of older people living with cancer pain, necessitating new options for improved pain control. So said speakers at the Third Annual Symposium on Advances in Pain Research of the National Institutes of Health, hosted by the NIH Pain Consortium and held here on the NIH campus. “The unmet need for better pain control is substantial,” said Andreas Beutler, MD, Assistant Professor of Medicine (Oncology) at Mount Sinai School of Medicine in New York City. A recent Institute of Medicine report concluded that the entire health care workforce needs to gain greater competence in geriatrics, in order to improve the way care is delivered to older patients. In that regard, a presentation at the pain symposium focused on development of a new evidence-based tool—a “pain item bank”—to assess pain in geriatric oncology patients. The new evidence-based assessment tool is called a “pain item bank.” “Pain management in cancer among older adults is a pressing issue given societal demographics,” said Chih-Hung Chang, PhD, Associate Professor of Medicine at Northwestern University's Buehler Center on Aging, Health and Society, who is developing the tool for use in the clinic. “Quality pain assessment in gero-oncology is a challenging but necessary first step to optimize individual pain treatment and management. A plethora of pain questionnaires exists, but not for the assessment of gero-oncology pain and its specific domains.” 4 Goals Dr. Chang said that in developing his pain assessment tool he and his colleagues have four distinct goals: To identify and refine the domains of pain assessment for a geriatric oncology population, using existing theoretical frameworks in biopsychosocial medicine and palliative care as a guide. To compile the items for a multidimensional pain item bank, drawing from existing pain questionnaires and supplementing them with newly written items. To empirically develop a pain item bank applicable to a geriatric oncology population. To pilot-test a computerized adaptive testing platform to administer individualized pain assessments to geriatric oncology patients in clinical settings. As part of the process of developing the pain-assessment tool, Dr. Chang turned to 22 patients age 58 to 88, and asked them 30 open-ended questions about what should be included in such a tool. The patients mentioned exacerbation of pain, causes of pain, relief of pain, medication, characteristics of pain, impact of pain, the role of support, and the help of health care providers as important to include in the assessment. The assessment prototype will demonstrate how the system should be implemented and tested in clinical settings, taking into account different linguistic populations and cultures. Pain-Relief Gene-Delivery System In addition to assessing pain in older cancer patients more accurately, new methods of pain delivery for patients in chronic pain need to be developed, Dr. Beutler said, explaining that gene therapy offers one such option. He reported on a novel preclinical pain-relief gene delivery system he is studying in rats. The system uses intrathecal adeno-associated virus as a vector to deliver pain relief. Via lumbar puncture, the viral vector carries an endorphin gene into rodent primary sensory neurons, where it selectively activates opiate receptors. Dr. Beutler said that theoretically any secreted protein could be a drug for this kind of viral transfer. The delivery system, which he described as a candidate platform for translational research, could likely bypass the unwanted side effects of opiates such as constipation, hallucinations, and drowsiness and bring pain relief to patients in intractable pain due to advanced cancer. One clinical problem in bringing this research from bench to bedside, said Dr. Beutler, is that “vector production is still not on an industrial scale,” although it can be done in trials. Dr. Beutler published an article on the approach in the January 22 issue of Proceedings of the National Academy of Sciences. Novel Cannabinoids Also discussed at the NIH meeting were novel cannabinoids, drugs for pain relief derived from Cannabis sativa, the hemp plant from which marijuana is produced. The synthetic cannabinoid nabilone, approved for treatment of nausea and vomiting during chemotherapy, has also been shown to relieve pain. In August 2007, Canada approved the cannabinoid Sativex as adjunctive analgesic treatment in patients with advanced cancer who experience moderate to severe pain during the highest tolerated dose of strong opioid therapy for persistent background pain. Sativex, used as an oral spray, is currently in late-state clinical trials in the United States and Europe, and according to the NIH's ClinicalTrials.gov site, several cannabinoid drugs are in clinical trials. In rats, cannabinoids appear to activate different families of receptors to relieve pain, said Ken M. Hargreaves, DDS, PhD, Professor and Chair of the Department of Endodontics at the University of Texas Health Science Center. He is studying cannabinoid pain relief via desensitization of a specific neuronal channel. M & M Of marked clinical interest is the synergy of opioids and cannabinoids, said Sandra P. Welch, PhD, Professor of Pharmacology and Toxicology at Virginia Commonwealth University. She noted that in mice, tetrahydrocannabinol (THC), the active ingredient in the approved cannabinoid dronabinol (Marinol), releases natural endogenous opioids, leading to what Dr. Welch called the “M and M” hypothesis for improved pain relief: low-dose Marinol plus morphine. Because the effects of morphine are enhanced by low-dose THC, she said a possible clinical strategy to relieve pain would be to use low-dose THC and a lower than usual dose of an opioid for pain relief, in hopes of controlling persistent pain with fewer opioid side effects. “I think this is a really interesting approach; these are good models for the human condition,” commented John Kusiak, PhD, Program Director for Molecular and Cellular Neurosciences at the National Institute of Dental and Craniofacial Research (NIDCR), speaking about Dr. Welch's research. Still, while new cannabinoids are promising for pain relief, they must be viewed with some caution, said Wen G. Chen, PhD, Program Director for Sensory and Motor Disorders of Aging at the National Institute on Aging. “Cannabinoids have been hyped; they are the ‘molecule on the block’ for neuroscientists,” he said. Genetic Variations Finally, several speakers said there are genetic variations in human pain susceptibility that may eventually lead to better pain control. For example, patients with low levels of neuropeptide Y (NPY), the most abundant peptide in the brain, tend to respond more to pain, noted David Goldman, MD, Chief of the Laboratory of Neurogenetics and Senior Investigator in the Human Neurogenetics Section, National Institute on Alcohol Abuse and Alcoholism. Noting that NPY expression affects pain, stress response, and emotion, Dr. Goldman predicted that physicians will someday have in their hands a panel of genetic variances in pain susceptibility to use when prescribing pain relief to patients. Coming in Future Issues M. D. Anderson Paves Academic Route to Oncology Nursing Excellence. Testing Advised for Hepatitis B and C in Lymphoma Patients Prior to Treatment with Rituximab. Updates on DLBCL from the International Conference on Malignant Lymphoma. 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Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,497
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,038
Tête enseignante GPT0,326
Écart entre enseignants0,288 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2008
Routes d'admission1
Résumé présentoui

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