Dataset Information

Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

ABSTRACT:

Objectives

Fibromyalgia is frequently treated with opioids due to limited therapeutic options. Long-term opioid use is associated with several adverse outcomes. Identifying factors associated with long-term opioid use is the first step in developing targeted interventions. The aim of this study was to evaluate risk factors in fibromyalgia patients newly initiated on opioids using machine learning.

Methods

A retrospective cohort study was conducted using a nationally representative primary care dataset from the UK, from the Clinical Research Practice Datalink. Fibromyalgia patients without prior cancer who were new opioid users were included. Logistic regression, a random forest model and Boruta feature selection were used to identify risk factors related to long-term opioid use. Adjusted ORs (aORs) and feature importance scores were calculated to gauge the strength of these associations.

Results

In this study, 28 552 fibromyalgia patients initiating opioids were identified of which 7369 patients (26%) had long-term opioid use. High initial opioid dose (aOR: 31.96, mean decrease accuracy (MDA) 135), history of self-harm (aOR: 2.01, MDA 44), obesity (aOR: 2.43, MDA 36), high deprivation (aOR: 2.00, MDA 31) and substance use disorder (aOR: 2.08, MDA 25) were the factors most strongly associated with long-term use.

Conclusions

High dose of initial opioid prescription, a history of self-harm, obesity, high deprivation, substance use disorder and age were associated with long-term opioid use. This study underscores the importance of recognising these individual risk factors in fibromyalgia patients to better navigate the complexities of opioid use and facilitate patient-centred care.

SUBMITTER: Ramirez Medina CR

PROVIDER: S-EPMC11308899 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature

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Publications

Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

Ramírez Medina Carlos Raúl CR Feng Mengyu M Huang Yun-Ting YT Jenkins David A DA Jani Meghna M

RMD open 20240520 2

<h4>Objectives</h4>Fibromyalgia is frequently treated with opioids due to limited therapeutic options. Long-term opioid use is associated with several adverse outcomes. Identifying factors associated with long-term opioid use is the first step in developing targeted interventions. The aim of this study was to evaluate risk factors in fibromyalgia patients newly initiated on opioids using machine learning.<h4>Methods</h4>A retrospective cohort study was conducted using a nationally representative ...[more]

PMID: 38772680

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Project description:IntroductionIn chronic pain conditions such as fibromyalgia (FM), pain amplification within the central nervous system, or "central sensitization," may contribute to the development and maintenance of chronic pain. Chronic pain treatments include opioid therapy, and opioid therapy may maladaptively increase central sensitization, particularly in patients who take opioids long-term. However, it has remained unknown how central sensitization is impacted in patients who use opioids long-term.MethodsTo investigate how long-term opioid therapy affects central sensitization, we used the validated measure of temporal summation. The temporal summation measurement consists of applying a series of noxious stimuli to a patient's skin and then calculating changes in the patient's pain rating to each stimulus. Using this measurement, we evaluated temporal summation in study participants with fibromyalgia who take opioids long-term (i.e., greater than 90 days duration; n = 24, opioid-FM). We compared opioid-FM responses to 2 control groups: participants with fibromyalgia who do not take opioids (n = 33, non-opioid FM), and healthy controls (n = 31). For the temporal summation measurement, we applied a series of 10 noxious heat stimuli (sensitivity-adjusted temperatures) to the ventral forearm (2s duration of each stimulus, applied once every 3 s). Additionally, we collected responses to standard pain and cognitive-affective questionnaires to assess pain severity and other factors.Results and discussionGroup differences in sensitivity-adjusted stimulus temperatures were observed, with only the non-opioid FM group requiring significantly lower stimulus temperatures (The opioid-FM group also required lower temperatures, but not significantly different from the control group). However, all 3 groups exhibited similar magnitudes of temporal summation. Across combined FM groups, temporal summation negatively correlated with pain severity (r = -0.31, p = 0.021). Within the opioid-FM group, higher pain sensitivity to heat (i.e., lower sensitivity-adjusted temperatures) showed a trend relationship with higher opioid dosage (r = -0.45, p = 0.036), potentially reflective of opioid-related hyperalgesia. Our findings also indicated that heightened pain severity may skew sensitivity-adjusted temporal summation, thereby limiting its utility for measuring central sensitization. Overall, in participants taking opioids, temporal summation may be influenced by hypersensitivity to heat pain, which appeared to vary with opioid dosage.

Project description:Background/objectivesOverall and long-term opioid use among older adults have increased since 1999. Less is known about opioid use in older adults in nursing homes (NHs).DesignCross-sectional.SettingU.S. NHs (N = 13,522).ParticipantsLong-stay NH resident Medicare beneficiaries with a Minimum Data Set 3.0 (MDS) assessment between April 1, 2012, and June 30, 2012, and 120 days of follow-up (N = 315,949).MeasurementsWe used Medicare Part D claims to measure length of opioid use in the 120 days from the index assessment (short-term: ≤30 days, medium-term: >30-89 days, long-term: ≥90 days), adjuvants (e.g., anticonvulsants), and other pain medications (e.g., corticosteroids). MDS assessments in the follow-up period were used to measure nonpharmacological pain management use. Modified Poisson models were used to estimate adjusted prevalence ratios (aPR) and 95% confidence intervals (CI) for age, gender, race and ethnicity, cognitive and physical impairment, and long-term opioid use.ResultsOf all long-stay residents, 32.4% were prescribed any opioid, and 15.5% were prescribed opioids long-term. Opioid users (versus nonusers) were more commonly prescribed pain adjuvants (32.9% vs 14.9%), other pain medications (25.5% vs 11.0%), and nonpharmacological pain management (24.5% vs 9.3%). Long-term opioid use was higher in women (aPR = 1.21, 95% CI = 1.18-1.23) and lower in racial and ethnic minorities (non-Hispanic blacks vs whites: APR = 0.93, 95% CI = 0.90-0.94) and those with severe cognitive impairment (vs no or mild impairment, aPR = 0.82, 95% CI = 0.79-0.83).ConclusionOne in seven NH residents was prescribed opioids long-term. Recent guidelines on opioid prescribing for pain recommend reducing long-term opioid use, but this is challenging in NHs because residents may not benefit from nonpharmacological and nonopioid interventions. Studies to address concerns about opioid safety and effectiveness (e.g., on pain and functional status) in NHs are needed.

Project description:Opinion statementPreventing depression in cancer patients on long-term opioid therapy should begin with depression screening before opioid initiation and repeated screening during treatment. In weighing the high morbidity of depression and opioid use disorder in patients with chronic cancer pain against a dearth of evidence-based therapies studied in this population, patients and clinicians are left to choose among imperfect but necessary treatment options. When possible, we advise engaging psychiatric and pain/palliative specialists through collaborative care models and recommending mindfulness and psychotherapy to all patients with significant depression alongside cancer pain. Medications for depression should be reserved for moderate to severe symptoms. We recommend escitalopram/citalopram or sertraline among selective serotonin reuptake inhibitors (SSRIs), or the serotonin and norepinephrine reuptake inhibitors (SNRIs) duloxetine, venlafaxine, or desvenlafaxine if patients have a significant component of neuropathic pain or fibromyalgia. Tricyclic antidepressants (TCAs) (consider nortriptyline or desipramine, which have better anticholinergic profiles) should be considered for patients who do not respond to or tolerate SSRI/SNRIs. Existing evidence is inadequate to definitively recommend methylphenidate or novel agents, such as ketamine or psilocybin, as adjunctive treatments for cancer-related depression and pain. Physicians who treat patients with cancer pain should utilize universal precautions to limit the risk of non-medical opioid use (non-medical opioid use). Patients should be screened for non-medical opioid use behaviors at initial consultation and at regular intervals during treatment using a non-judgmental approach that reduces stigma. Co-management with an addiction specialist may be indicated for patients at high risk of non-medical opioid use and opioid use disorder. Buprenorphine and methadone are indicated for the treatment of opioid use disorder, and while they have not been systematically studied for treatment of opioid use disorder in patients with cancer pain, they do provide analgesia for cancer pain. While an interdisciplinary team approach to manage psychological stress may be beneficial, this may not be possible for patients treated outside of comprehensive cancer centers.

Dataset Information

Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

Objectives

Methods

Results

Conclusions

Publications

Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

Similar Datasets

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