Predicting Persistent Opioid Use, Abuse, and Toxicity Among Cancer Survivors

Moving towards the use of artificial intelligence in pain management

BACKGROUND AND OBJECTIVE

While the development of artificial intelligence (AI) technologies in medicine has been significant, their application to acute and chronic pain management has not been well characterized. This systematic review aims to provide an overview of the current state of AI in acute and chronic pain management.

DATABASES AND DATA TREATMENT

This review was registered with PROSPERO (ID# CRD42022307017), the international registry for systematic reviews. The search strategy was prepared by a librarian and run in four electronic databases (Embase, Medline, Central, and Web of Science). Collected articles were screened by two reviewers. Included studies described the use of AI for acute and chronic pain management.

RESULTS

From the 17,601 records identified in the initial search, 197 were included in this review. Identified applications of AI were described for treatment planning as well as treatment delivery. Described uses include prediction of pain, forecasting of individualized responses to treatment, treatment regimen tailoring, image-guidance for procedural interventions and self-management tools. Multiple domains of AI were used including machine learning, computer vision, fuzzy logic, natural language processing and expert systems.

CONCLUSION

There is growing literature regarding applications of AI for pain management, and their clinical use holds potential for improving patient outcomes. However, multiple barriers to their clinical integration remain including lack validation of such applications in diverse patient populations, missing infrastructure to support these tools and limited provider understanding of AI.

SIGNIFICANCE

This review characterizes current applications of AI for pain management and discusses barriers to their clinical integration. Our findings support continuing efforts directed towards establishing comprehensive systems that integrate AI throughout the patient care continuum.

Depression, non-medical pain prescriptions, and suicidal behavior in cancer survivors

PURPOSE

A cancer diagnosis results in significant distress and adverse psychosocial sequelae, including suicide, the 10th leading cause of death in the USA. Primary risks for death by suicide include depression and opioid abuse, which are prevalent among cancer survivors. Yet, it remains unclear whether they are also associated with other suicidal outcomes, such as ideation, planning, and suicidal attempt.

METHODS

We used cross-sectional data from the National Survey on Drug Use and Health (2015-2019, N = 214,271), a nationwide study in the USA that provides data on mental health and other health concerns. Outcome of interest was suicidality (suicidal ideation, planning, and attempt). Main exposures were history of depression and non-medical use of pain prescriptions. Using weighted logistic regression analyses adjusted for sociodemographic factors and substance use, we estimated odds of suicidal ideation, planning, and attempt.

RESULTS

There were 7635 cancer survivors in our study, which was our analytic sample. We found an associations between a history of cancer and suicidal ideation (aOR = 1.32, 95% CI 1.10, 1.58). Among cancer survivors, depression and non-medical use of pain prescriptions were consistently associated with suicidal ideation (aORdepression = 7.37, 95% CI 4.52, 12.03; aORpain prescriptions = 3.36, 95% CI 1.27, 8.91, planning (aORdepression = 10.31, 95% CI 5.79, 18.34; and aORpain prescriptions = 3.77, 95% CI 1.20, 11.85), and attempt (aORdepression = 4.29, 95% CI 1.41, 13.06).

CONCLUSION

Both depression and non-medical pain prescriptions are independently associated with increased odds of suicidal behavior among cancer survivors. Routinely assessing for depression and history of non-medical use of pain prescriptions could be an important suicide prevention strategy in oncology.

IMPLICATIONS FOR CANCER SURVIVORS

Given the increased risk of suicide mortality among cancer survivors, it is critical that risk factors for suicidal behavior, such as depression and use of non-medical pain prescriptions, are routinely screened for as part of cancer care.

Patterns of prescription opioid use and opioid-related harms among adult patients with hematologic malignancies

INTRODUCTION

Treatment advances for hematologic malignancies (HM) have dramatically improved life expectancy, necessitating greater focus on long-term cancer pain management. This study explored real-world patterns of opioid use among patients with HM.

METHODS

This retrospective cohort study identified adults diagnosed with HM from January 1, 2013 through December 31, 2019 using the Truven MarketScan Commercial Claims and Encounters database. Across several HM types, we described rates of high-risk opioid use (based on Pharmacy Quality Alliance measures) and opioid-related harms, including incident opioid use disorder (OUD) diagnoses and opioid-related hospitalizations or emergency department (ED) visits. We used multivariable Cox regression to generate adjusted hazard ratios and 95% confidence intervals comparing the risk of opioid-related harms between patients with versus without high-risk opioid use.

RESULTS

Our sample included 43,190 patients with HM. Median age at HM diagnosis was 54 years (interquartile range  =  44-60). Most patients (61.9%) were diagnosed with lymphoma. Approximately half (49.2%) had an opioid dispensed in the follow-up period. Among all patients, 20.0% met criteria for high-risk opioid use, 0.9% had an OUD diagnosis, and 0.3% experienced an opioid-related hospitalization/ED visit in follow-up. High-risk opioid use increased the risk of an OUD diagnosis by 3.3 times (p < 0.0001) and an opioid-related hospitalization/ED visit 4.2 times (p < 0.0001).

CONCLUSION

High-risk opioid use was prevalent among patients with HM and significantly increased the risk of opioid-related harms. However, rates of opioid-related harms were low. These findings highlight the importance of continually monitoring pain and opioid use throughout HM survivorship to provide safe, effective HM pain management.

The prevalence and predictors of discharge opioid overprescribing in opioid-naïve patients after breast, gynecologic, and head and neck cancer surgery: a prospective cohort study

PURPOSE

The management of pain following cancer-related surgeries involves the use of opioid analgesics. Nevertheless, there is little evidence characterizing the utility and prescription patterns of opioids after these procedures. Our primary aim was to identify patients from three types of cancer surgery who were overprescribed with opioids. The secondary aim was to determine the potential predictors of overprescribing in the same period.

METHODS

We conducted the study at a single cancer referral hospital. Opioid-naïve patients with breast, gynecologic, or head and neck cancer were studied. Patients were considered opioid-naïve if they had a history of opioid use ≤ 30 mg oral morphine equivalent daily dose for less than seven days in the preceding three months before surgery. We recruited eligible participants by convenience sampling on the wards until at least 102 patients were included in the final analysis. After discharge, we followed up on the participants on day 7 via telephone using a structured proforma including questions to identify the last date and amount of opioid dose taken. The equivalent days of opioid use were calculated by their 24-hr use before discharge and the number of doses prescribed for discharge. Our primary outcome was the prevalence of overprescribing in the three surgical specialties defined as the number of patients taking less than 50% of discharge opioids within the first seven days after discharge. We examined the predictors on incidents of overprescribing using multivariable Poisson regression as the secondary outcome.

RESULTS

We recruited 119 patients, and 107 patients were included in the final analysis. There were 59/107 (55%) patients found to be overprescribed with opioids. At discharge, they exhibited lower mean numerical rating scale pain scores, lower mean pain severity scores, higher equivalent days of opioids prescribed, and not used opioids in the last 24 hr before discharge. The incidence of overprescribing was 2.4 times greater for patients prescribed with opioids without 24-hr opioid use (relative risk [RR], 2.38; 95% confidence interval [CI], 1.30 to 4.35; P = 0.005). Similarly, the incidence of overprescribing was 1.7 times greater for patients who had opioids 24 hr before discharge and were supplied with opioids for five equivalent days or more at the time of discharge (RR, 1.67; 95% CI, 1.09 to 2.56; P = 0.02).

CONCLUSION

Our study shows that the majority of recruited patients undergoing breast, gynecologic, or head and neck cancer surgery were overprescribed opioids. Individualized assessments on patients' 24-hr opioid requirements before discharge and supplying for less than five days are important considerations to reduce overprescribing in opioid-naïve patients after cancer surgery.

Predictive Models to Assess Risk of Persistent Opioid Use, Opioid Use Disorder, and Overdose

BACKGROUND

This systematic review summarizes the development, accuracy, quality, and clinical utility of predictive models to assess the risk of opioid use disorder (OUD), persistent opioid use, and opioid overdose.

METHODS

In accordance with Preferred Reporting Items for a Systematic Review and Meta-analysis guidelines, 8 electronic databases were searched for studies on predictive models and OUD, overdose, or persistent use in adults until June 25, 2023. Study selection and data extraction were completed independently by 2 reviewers. Risk of bias of included studies was assessed independently by 2 reviewers using the Prediction model Risk of Bias ASsessment Tool (PROBAST).

RESULTS

The literature search yielded 3130 reports; after removing 199 duplicates, excluding 2685 studies after abstract review, and excluding 204 studies after full-text review, the final sample consisted of 41 studies that developed more than 160 predictive models. Primary outcomes included opioid overdose (31.6% of studies), OUD (41.4%), and persistent opioid use (17%). The most common modeling approach was regression modeling, and the most common predictors included age, sex, mental health diagnosis history, and substance use disorder history. Most studies reported model performance via the c statistic, ranging from 0.507 to 0.959; gradient boosting tree models and neural network models performed well in the context of their own study. One study deployed a model in real time. Risk of bias was predominantly high; concerns regarding applicability were predominantly low.

CONCLUSIONS

Models to predict opioid-related risks are developed using diverse data sources and predictors, with a wide and heterogenous range of accuracy metrics. There is a need for further research to improve their accuracy and implementation.

Opioid tapering in older cancer survivors does not increase psychiatric or drug hospitalization rates

BACKGROUND

Opioid tapering in the general population is linked to increases in hospitalizations or emergency department visits related to psychiatric or drug-related diagnoses. Cancer survivors represent a unique population with different opioid indications, prescription patterns, and more frequent follow-up care. This study sought to describe patterns of opioid tapering among older cancer survivors and to test the hypothesis of whether older cancer survivors face increased risks of adverse events with opioid tapering.

METHODS

Using the Surveillance, Epidemiology and End Results Medicare-linked database, we identified 15 002 Medicare-beneficiary cancer survivors diagnosed between 2010 and 2017 prescribed opioids consistently for at least 6 months after their cancer diagnosis. Tapering was defined as a binary time-varying event occurring with any monthly oral morphine equivalent reduction of 15% or more from the previous month. Primary diagnostic billing codes associated with emergency room or hospital admissions were used for the composite endpoint of psychiatric- or drug-related event(s).

RESULTS

There were 3.86 events per 100 patient-months, with 97.8% events being mental health emergencies, 1.91% events being overdose emergencies, and 0.25% involving both. Using a generalized estimating equation for repeated measure time-based analysis, opioid tapering was not statistically associated with acute events in the 3-month posttaper period (odds ratio [OR] = 1.02; P = .62) or at any point in the future (OR = 0.96; P = .46).

CONCLUSIONS

Opioid tapering in older cancer survivors does not appear to be linked to a higher risk of acute psychiatric- or drug-related events, in contrast to prior research in the general population.

Trends in new and persistent opioid use in older adults with and without cancer

BACKGROUND

The impact of ongoing efforts to decrease opioid use on patients with cancer remains undefined. Our objective was to determine trends in new and additional opioid use in patients with and without cancer.

METHODS

This retrospective cohort study used data from Surveillance, Epidemiology, and End Results program-Medicare for opioid-naive patients with solid tumor malignancies diagnosed from 2012 through 2017 and a random sample of patients without cancer. We identified 238 470 eligible patients with cancer and further focused on 4 clinical strata: patients without cancer, patients with metastatic cancer, patients with nonmetastatic cancer treated with surgery alone ("surgery alone"), and patients with nonmetastatic cancer treated with surgery plus chemotherapy or radiation therapy ("surgery+"). We identified new, early additional, and long-term additional opioid use and calculated the change in predicted probability of these outcomes from 2012 to 2017.

RESULTS

New opioid use was higher in patients with cancer (46.4%) than in those without (6.9%) (P < .001). From 2012 to 2017, the predicted probability of new opioid use was more stable in the cancer strata (relative declines: 0.1% surgery alone; 2.4% surgery+; 8.8% metastatic cancer), than in the noncancer stratum (20.0%) (P < .001 for each cancer to noncancer comparison). Early additional use declined among surgery patients (‒14.9% and ‒17.5% for surgery alone and surgery+, respectively) but was stable among patients with metastatic disease (‒2.8%, P = .50).

CONCLUSIONS

Opioid prescribing declined over time at a slower rate in patients with cancer than in patients without cancer. Our study suggests important but tempered effects of the changing opioid climate on patients with cancer.

Identification the Low Oxidative Stress Subtype of Periodontitis

OBJECTIVE

The aim of this research was to identify the low oxidative stress-related genes expression (L-OS) subtype in patients with periodontitis.

METHODS

Microarray data (MA) were retrieved from the Gene Expression Omnibus database. The different oxidative stress (OS) subtypes of periodontitis were identified by K-means clustering analysis and gene set variation analysis (GSVA). Differentially expressed genes (DEGs) (|Log fold change (FC)| >1, q < 0.05) amongst the OS subtypes and healthy controls (HCs) were identified by Limma R package. The genomic feature of L-OS subtype and corresponding medicines were evaluated and visualised with Drug-Gene Interaction Database and cytoscape-v3.7.2 software (Pearson correlation coefficient > 0.4). Finally, the LASSO-Logistic regression model was adopted to evaluate and predict patients' OS phenotype in routine clinical practice.

RESULTS

The 241 periodontitis samples and 69 HCs were included. Thirty-three DEGs between the L-OS and high oxidative stress-related genes expression (H-OS) subtypes and 96 DEGs, including 8 transcription factors, between L-OS subtype and HCs were identified, respectively. Then, the network of TFs-Genes-Drugs was constructed to determine genomic feature of L-OS subtype. Finally, a 4-gene signature formula and the cutoff value were identified by ML with LASSO model to predict patients' classification.

CONCLUSIONS

For the first time, we identified L-OS subtype of periodontitis and evaluated its genomic feature with MA.

Race, Ethnicity, and Sustained Opioid Use After Major Abdominal Surgery for Cancer

Purpose

Sustained opioid use is a well-known complication after surgery. Our objective was to determine whether there is any association between a patient's race or ethnicity and the sustained use of opioids in the year following surgery. Opioid use over the initial 3, 6, and 12 postoperative months was categorized as "sustained early", persistent, and chronic, respectively.

Patients and Methods

Single-institution retrospective study of adults (≥18 years) who had undergone open abdominal surgery for cancer. Multivariable logistic regression was used to evaluate the association between race/ethnicity and opioid use.

Results

Of the 3523 patients included in the study, 2543 (72.2%) were non-Hispanic (NH) White, 476 (13.5%) were Hispanic or Latino, 262 (7.4%) were NH-Black, 186 (5.3%) were Asian, and 56 (1.6%) belonged to other racial or ethnic groups. The overall rates of sustained early, persistent, and chronic opioid use were 15.9%, 7.1%, and 2.6%, respectively. In the multivariable analysis, patient race/ethnicity was associated with sustained early postoperative opioid use (p-value=0.037), with Hispanics/Latinos having significantly higher odds than NH-Whites (OR = 1.382 [95% CI: 1.057-1.808]; p = 0.018). However, neither persistent nor chronic opioid use was associated with race/ethnicity (p = 0.697 and p = 0.443, respectively).

Conclusion

In this retrospective study of adults who had undergone open abdominal surgery, patient race/ethnicity was not consistently associated with the development of sustained opioid use over the first 12 postoperative months.

Poor handling of continuous predictors in clinical prediction models using logistic regression: a systematic review

BACKGROUND AND OBJECTIVES

When developing a clinical prediction model, assuming a linear relationship between the continuous predictors and outcome is not recommended. Incorrect specification of the functional form of continuous predictors could reduce predictive accuracy. We examine how continuous predictors are handled in studies developing a clinical prediction model.

METHODS

We searched PubMed for clinical prediction model studies developing a logistic regression model for a binary outcome, published between July 01, 2020, and July 30, 2020.

RESULTS

In total, 118 studies were included in the review (18 studies (15%) assessed the linearity assumption or used methods to handle nonlinearity, and 100 studies (85%) did not). Transformation and splines were commonly used to handle nonlinearity, used in 7 (n = 7/18, 39%) and 6 (n = 6/18, 33%) studies, respectively. Categorization was most often used method to handle continuous predictors (n = 67/118, 56.8%) where most studies used dichotomization (n = 40/67, 60%). Only ten models included nonlinear terms in the final model (n = 10/18, 56%).

CONCLUSION

Though widely recommended not to categorize continuous predictors or assume a linear relationship between outcome and continuous predictors, most studies categorize continuous predictors, few studies assess the linearity assumption, and even fewer use methodology to account for nonlinearity. Methodological guidance is provided to guide researchers on how to handle continuous predictors when developing a clinical prediction model.

Personalized Medicine in Cancer Pain Management

BACKGROUND

Previous studies have documented pain as an important concern for quality of life (QoL) and one of the most challenging manifestations for cancer patients. Thus, cancer pain management (CPM) plays a key role in treating pain related to cancer. The aim of this systematic review was to investigate CPM, with an emphasis on personalized medicine, and introduce new pharmacogenomics-based procedures for detecting and treating cancer pain patients.

METHODS

This study systematically reviewed PubMed from 1990 to 2023 using keywords such as cancer, pain, and personalized medicine. A total of 597 publications were found, and after multiple filtering processes, 75 papers were included. In silico analyses were performed using the GeneCards, STRING-MODEL, miRTargetLink2, and PharmGKB databases.

RESULTS

The results reveal that recent reports have mainly focused on personalized medicine strategies for CPM, and pharmacogenomics-based data are rapidly being introduced. The literature review of the 75 highly relevant publications, combined with the bioinformatics results, identified a list of 57 evidence-based genes as the primary gene list for further personalized medicine approaches. The most frequently mentioned genes were CYP2D6, COMT, and OPRM1. Moreover, among the 127 variants identified through both the literature review and data mining in the PharmGKB database, 21 variants remain as potential candidates for whole-exome sequencing (WES) analysis. Interestingly, hsa-miR-34a-5p and hsa-miR-146a-5p were suggested as putative circulating biomarkers for cancer pain prognosis and diagnosis.

CONCLUSIONS

In conclusion, this study highlights personalized medicine as the most promising strategy in CPM, utilizing pharmacogenomics-based approaches to alleviate cancer pain.

Prevalence and correlates of high-dose opioid use among survivors of head and neck cancer

BACKGROUND

We characterized prescription opioid medication use up to 2 years following the head and neck cancer (HNC) diagnosis and examined associations with moderate or high daily opioid prescription dose.

METHODS

Using administrative data from Veterans Health Administration, we conducted a retrospective cohort analysis of 5522 Veterans treated for cancers of the upper aerodigestive tract between 2012 and 2019. Data included cancer diagnosis and treatments, pain severity, prescription opioid characteristics, demographics, and other clinical factors.

RESULTS

Two years post-HNC, 7.8% (n = 428) were receiving moderate or high-dose opioid therapy. Patients with at least moderate pain (18%, n = 996) had 2.48 times higher odds (95% CI = 1.94-3.09, p < 0.001) to be prescribed a moderate opioid dose or higher at 2 years post diagnosis.

CONCLUSIONS

Survivors of HNC with at least moderate pain were at elevated risk of continued use of moderate and high dose opioids.

Outcome class imbalance and rare events: An underappreciated complication for overdose risk prediction modeling

BACKGROUND AND AIMS

Low outcome prevalence, often observed with opioid-related outcomes, poses an underappreciated challenge to accurate predictive modeling. Outcome class imbalance, where non-events (i.e. negative class observations) outnumber events (i.e. positive class observations) by a moderate to extreme degree, can distort measures of predictive accuracy in misleading ways, and make the overall predictive accuracy and the discriminatory ability of a predictive model appear spuriously high. We conducted a simulation study to measure the impact of outcome class imbalance on predictive performance of a simple SuperLearner ensemble model and suggest strategies for reducing that impact.

DESIGN, SETTING, PARTICIPANTS

Using a Monte Carlo design with 250 repetitions, we trained and evaluated these models on four simulated data sets with 100 000 observations each: one with perfect balance between events and non-events, and three where non-events outnumbered events by an approximate factor of 10:1, 100:1, and 1000:1, respectively.

MEASUREMENTS

We evaluated the performance of these models using a comprehensive suite of measures, including measures that are more appropriate for imbalanced data.

FINDINGS

Increasing imbalance tended to spuriously improve overall accuracy (using a high threshold to classify events vs non-events, overall accuracy improved from 0.45 with perfect balance to 0.99 with the most severe outcome class imbalance), but diminished predictive performance was evident using other metrics (corresponding positive predictive value decreased from 0.99 to 0.14).

CONCLUSION

Increasing reliance on algorithmic risk scores in consequential decision-making processes raises critical fairness and ethical concerns. This paper provides broad guidance for analytic strategies that clinical investigators can use to remedy the impacts of outcome class imbalance on risk prediction tools.

Racial disparities in opioid prescription and pain management among breast cancer survivors

BACKGROUND

We examined whether there are racial disparities in pain management, opioid medicine prescriptions, symptom severity, and quality of life constructs in breast cancer survivors.

METHODS

We conducted a secondary analysis of longitudinal data from the Women's Hormonal Therapy Initiation and Persistence (WHIP) study (n = 595), a longitudinal study of hormonal receptor-positive breast cancer survivors. Upon study enrollment, patients completed a survey assessing an array of psychological, behavioral, and treatment outcomes, including adjuvant endocrine therapy (AET)-induced symptoms, and provided a saliva biospecimen. Opioid prescription records were extracted from the health maintenance organizations (HMOs) pharmacy database. The final analytic sample included women with complete HMO pharmacy records for 1 year.

RESULTS

There were 251 eligible patients, of which 169 (67.3%) were White. The average age was 61.09 years old (SD = 11.07). One hundred seventy-two patients (68.5%) had received at least one opioid medication and 37.1% were prescribed opioids longer than 90 days (n = 93). Sixty-four Black patients (78%) had a record of being prescribed with opioids compared to 64% of White patients (n = 108, p = 0.03). Black patients reported worse vasomotor, neuropsychological, and gastrointestinal symptoms, as well as lower quality of life and greater healthcare discrimination than White patients (p's < 0.05). Black patients were more likely to be prescribed opioids for 90 days or longer compared to White patients, when controlling for age, marital status, income, body mass index (BMI), cancer stage, and chemotherapy status (adjusted Odds Ratio = 2.72, p = 0.014).

CONCLUSION

Findings indicate that there are racial differences in opioid prescriptions supplied for pain management and symptomatic outcomes. Future research is needed to understand the causes of disparities in cancer pain management and symptomatic outcomes.

Use of Opioids for Adults With Pain From Cancer or Cancer Treatment: ASCO Guideline

PURPOSE

To provide guidance on the use of opioids to manage pain from cancer or cancer treatment in adults.

METHODS

A systematic review of the literature identified systematic reviews and randomized controlled trials of the efficacy and safety of opioid analgesics in people with cancer, approaches to opioid initiation and titration, and the prevention and management of opioid adverse events. PubMed and the Cochrane Library were searched from January 1, 2010, to February 17, 2022. American Society of Clinical Oncology convened an Expert Panel to review the evidence and formulate recommendations.

RESULTS

The evidence base consisted of 31 systematic reviews and 16 randomized controlled trials. Opioids have primarily been evaluated in patients with moderate-to-severe cancer pain, and they effectively reduce pain in this population, with well-characterized adverse effects. Evidence was limited for several of the questions of interest, and the Expert Panel relied on consensus for these recommendations or noted that no recommendation could be made at this time.

RECOMMENDATIONS

Opioids should be offered to patients with moderate-to-severe pain related to cancer or active cancer treatment unless contraindicated. Opioids should be initiated PRN (as needed) at the lowest possible dose to achieve acceptable analgesia and patient goals, with early assessment and frequent titration. For patients with a substance use disorder, clinicians should collaborate with a palliative care, pain, and/or substance use disorder specialist to determine the optimal approach to pain management. Opioid adverse effects should be monitored, and strategies are provided for prevention and management.Additional information is available at www.asco.org/supportive-care-guidelines.

Role of Cannabidiol for Improvement of the Quality of Life in Cancer Patients: Potential and Challenges

There is currently a growing interest in the use of cannabidiol (CBD) to alleviate the symptoms caused by cancer, including pain, sleep disruption, and anxiety. CBD is often self-administered as an over-the-counter supplement, and patients have reported benefits from its use. However, despite the progress made, the mechanisms underlying CBD’s anti-cancer activity remain divergent and unclear. Herein, we provide a comprehensive review of molecular mechanisms to determine convergent anti-cancer actions of CBD from pre-clinical and clinical studies. In vitro studies have begun to elucidate the molecular targets of CBD and provide evidence of CBD’s anti-tumor properties in cell and mouse models of cancer. Furthermore, several clinical trials have been completed testing CBD’s efficacy in treating cancer-related pain. However, most use a mixture of CBD and the psychoactive, tetrahydrocannabinol (THC), and/or use variable dosing that is not consistent between individual patients. Despite these limitations, significant reductions in pain and opioid use have been reported in cancer patients using CBD or CBD+THC. Additionally, significant improvements in quality-of-life measures and patients’ overall satisfaction with their treatment have been reported. Thus, there is growing evidence suggesting that CBD might be useful to improve the overall quality of life of cancer patients by both alleviating cancer symptoms and by synergizing with cancer therapies to improve their efficacy. However, many questions remain unanswered regarding the use of CBD in cancer treatment, including the optimal dose, effective combinations with other drugs, and which biomarkers/clinical presentation of symptoms may guide its use.

Increased pain catastrophizing longitudinally predicts worsened pain severity and interference in patients with chronic pain and cancer: A collaborative health outcomes information registry study (CHOIR)

OBJECTIVE

Little is known about how changes in psychosocial factors impact changes in pain outcomes among patients with cancer and chronic pain. This longitudinal cohort study of cancer patients investigated the relationships between changes in psychosocial factors and changes in pain severity and interference over time.

METHODS

Data from patients with cancer and chronic pain (n = 316) treated at a tertiary pain clinic were prospectively collected. At their baseline visit (Time 1), patients provided demographic and clinical information, and completed validated psychosocial and pain assessments. Psychosocial and pain assessments were repeated at a follow-up visit (Time 2), on average 4.9 months later. Change scores (Time 2-Time 1) were computed for psychosocial and pain variables. Multivariable hierarchical linear regressions assessed the associations between changes in psychosocial factors with changes in pain outcomes over time.

RESULTS

Participants were an average age of 59 years, were 61% female, and 69% White. Overall, a decrease in pain severity (p ≤ 0.001), but not pain interference, was observed among the group over time. In multivariable analyses, increased pain catastrophizing was significantly associated with increased pain severity over time (β = 0.24, p ≤ 0.001). Similarly, increased pain catastrophizing (β = 0.21, p ≤ 0.001) and increased depression (β = 0.20, p ≤ 0.003) were significantly associated with increased pain interference over time. Demographic and clinical characteristics were not significantly related to changes in pain outcomes.

CONCLUSIONS

Increased pain catastrophizing was uniquely associated with increased chronic pain severity and interference. Our findings indicate that cancer patients with chronic pain would likely benefit from the incorporation of nonpharmacological interventions, simultaneously addressing pain and psychological symptoms.

Differential patterns of opioid misuse between younger and older adults - a retrospective observational study using data from South Carolina's prescription drug monitoring program

Background: Most research on opioid misuse focuses on younger adults, yet opioid-related mortality has risen fastest among older Americans over age 55.Objectives: To assess whether there are differential patterns of opioid misuse over time between younger and older adults and whether South Carolina's mandatory Prescription Drug Monitoring Program (PDMP) affected opioid misuse differentially between the two groups.Methods: We used South Carolina's Reporting and Identification Prescription Tracking System from 2010 to 2018 to calculate an opioid misuse score for 193,073 patients (sex unknown) using days' supply, morphine milligram equivalents (MME), and the numbers of unique prescribers and dispensaries. Multivariable regression was used to assess differential opioid misuse patterns by age group over time and in response to implementation of South Carolina's mandatory PDMP in 2017.Results: We found that between 2011 and 2018, older adults received 57% (p < .01) more in total MME and 25.4 days more (p < .01) in supply, but received prescriptions from fewer doctors (-0.063 doctors, p < 01) and pharmacies (-0.11 pharmacies, p < 01) per year versus younger adults. However, older adults had lower odds of receiving a high misuse score (OR 0.88, p < .01). After the 2017 legislation, misuse scores fell among younger adults (OR 0.79, p < .01) relative to 2011, but not among older adults.Conclusion: Older adults may misuse opioids differently compared to younger adults. Assessment of policies to reduce opioid misuse should take into account subgroup differences that may be masked at the population level.

Long-term opioid use in patients treated with head and neck intensity-modulated radiotherapy

PURPOSE

Acute and chronic pain during and after radiotherapy is an important driver of poor quality of life. We aimed to identify risk factors associated with increased chronic opioid use in head and neck squamous cell cancer survivors.

METHODS

We performed a retrospective cohort analysis on head and neck squamous cell cancer patients treated with definitive or adjuvant intensity-modulated radiotherapy. We tracked their oncologic opioid prescription profile from initial presentation to the last follow-up date. We determined the incidences of 1- and 2-year opioid use and performed multivariate logistic regression for both outcomes.

RESULTS

Our analytic cohort consisted of 403 head and neck squamous cell cancer survivors. The numbers of patients requiring opioids at 3 months, 6 months, and 1 year after treatment were 316 (78%), 203 (50%), and 102 (25%), respectively. On multivariate logistic regression, positive smoking history (95% CI 1.86 [1.03, 3.43], p = 0.04), unemployment (95% CI 2.33 [1.16, 4.67], p = 0.02), prior psychiatric illness (95% CI 2.15 [1.05, 4.40], p = 0.03), and opiate use before radiotherapy (95% CI 2.75 [1.49, 5.20], p = 0.01) were independently associated with significantly greater odds of opioid use at 1 year.

CONCLUSIONS

Our institutional analysis has shown that a substantial amount of head and neck cancer survivors are chronically dependent on opioids following radiotherapy. We have identified a cohort at highest risk for long-term use, for whom early interventions should be targeted.

Effectiveness of gabapentin in reducing opioid requirements after radiation in head and neck cancer in a single institution

BACKGROUND

Gabapentin has been shown to reduce opioid use in head and neck cancer patients. Here, we examine the efficacy of prophylactic gabapentin at reducing opioid use in these patients at our institution.

METHODS

A retrospective study of patients receiving radiation was performed, using patients from our previous study as controls. Risk factors for opioid use at 3 and 6 months were determined using univariate and multivariate analyses.

RESULTS

In total, 53/185 patients were treated with gabapentin, 39.6% of which took opioids at 3 months vs. 58.3% in the non-gabapentin cohort (p = 0.021). Gabapentin was independently associated with less opioid use on multivariate analysis at 3 months (OR 0.47, 95% CI 0.24-0.9). Gastrostomy tube dependence and pretreatment opioid use were associated with chronic opioid use despite gabapentin.

CONCLUSIONS

Gabapentin is effective at expediting opioid tapering in head and neck cancer patients who are not gastrostomy tube dependent or taking opioids pretreatment.

Impacts of an Opioid Safety Initiative on US Veterans Undergoing Cancer Treatment

BACKGROUND

There is limited research on how the opioid epidemic and consequent risk reduction policies have affected pain management among cancer patients. The purpose of this study was to analyze how the Opioid Safety Initiative (OSI) implemented at the Veterans Health Administration affected opioid prescribing patterns and opioid-related toxicity.

METHODS

We performed an interrupted time series analysis of 42 064 opioid-naïve patients treated at the Veterans Health Administration for prostate, lung, breast, and colorectal cancer from 2011 to 2016. Segmented regression was used to evaluate the impact of the OSI on the incidence of any new opioid prescriptions, high-risk prescriptions, persistent use, and pain-related emergency department (ED) visits. We compared the cumulative incidence of adverse opioid events including an opioid-related admission or diagnosis of misuse before and after the OSI. All statistical tests were 2-sided.

RESULTS

The incidence of new opioid prescriptions was 26.7% (95% confidence interval [CI] = 25.0% to 28.4%) in 2011 and increased to 50.6% (95% CI = 48.3% to 53.0%) by 2013 before OSI implementation (monthly rate of change: +3.3%, 95% CI = 1.3% to 4.2%, P < .001). After the OSI, there was a decrease in the monthly rate of change for new prescriptions (-3.4%, 95% CI = -3.9 to -2.9%, P < .001). The implementation of the OSI was associated with a decrease in the monthly rate of change of concomitant benzodiazepines and opioid prescriptions (-2.5%, 95% CI = -3.2% to -1.8%, P < .001), no statistically significant change in high-dose opioids (-1.2%, 95% CI = -3.2% to 0.9%, P = .26), a decrease in persistent opioid use (-5.7%, 95% CI = -6.8% to -4.7%, P < .001), and an increase in pain-related ED visits (+3.0%, 95% CI = 1.0% to 5.0%, P = .003). The OSI was associated with a decreased incidence of opioid-related admissions (3-year cumulative incidence: 0.9% [95% CI = 0.7% to 1.0%] vs 0.5% [95% CI = 0.4% to 0.6%], P < .001) and no statistically significant change in the incidence of opioid misuse (3-year cumulative incidence: 1.2% [95% CI = 1.0% to 1.3%] vs 1.2% [95% CI = 1.1% to 1.4%], P = .77).

CONCLUSIONS

The OSI was associated with a relative decline in the rate of new, persistent, and certain high-risk opioid prescribing as well as a slight increase in the rate of pain-related ED visits. Further research on patient-centered outcomes is required to optimize opioid prescribing policies for patients with cancer.

Tibetan Herbal Pain-Relieving Plaster for Chronic Musculoskeletal Pain Among Cancer Survivors: Study Protocol of a Randomized, Double-Blind, Placebo-Controlled Trial

Chronic pain is common and debilitating in cancer survivors. Tibetan herbal pain-relieving plaster is used as an external analgesic to treat musculoskeletal pain in China; however, its safety and efficacy have not been evaluated via clinical trials in cancer survivors. We designed this Phase II randomized, double-blind, placebo-controlled trial (ClinicalTrials.gov Identifier: NCT04916249) to assess the efficacy and safety of the pain-relieving plaster for temporary pain relief among cancer survivors with chronic musculoskeletal pain. Under ethical approval from the Institutional Review Board at the Memorial Sloan Kettering Cancer Center, we will enroll eligible cancer survivors who have a clinical diagnosis of moderate to severe chronic musculoskeletal pain in this study. We use a central randomization system to allocate the eligible participants to either the treatment or the control group in a 1:1 ratio, with stratification by baseline opioid use. We will instruct the participants to apply the herbal patch (Tibetree Pain-Relieving Plaster, Tibet Cheezheng Tibetan Medicine Co. Ltd., Tibet, China) or placebo patch daily at the focal area with worst pain for 14 consecutive days. Study physician, participant, outcome assessor, and biostatistician are blinded to the group allocation. The primary outcome is pain severity measured by the Brief Pain Inventory on Days 2–7. Secondary outcomes include changes in insomnia, anxiety, depression, fatigue, pressure pain threshold, pain medication use, and global impression of change. We will also monitor the adverse events throughout the study period. Statistical analysis will follow the intention-to-treat principle and linear mixed modeling will be used. With rigorous design and implementation, this randomized, placebo-controlled trial will provide the initial evidence on the efficacy and safety of the pain-relieving plaster for pain relief among cancer survivors with chronic musculoskeletal pain.

When Management of Cancer-Related Pain Is Complicated by Coexisting Opioid Use Disorder: A Case Review

Patients with cancer are living longer, and many experience pain secondary to tumor invasion or as a consequence of cancer-directed therapies. Opioid use disorders and associated morbidity and mortality have increased with dramatic rise during the SARS-CoV-2 pandemic. National and international stakeholders have developed clinical practice guidelines in an effort to curb opioid misuse and overdose-related death. However, to ensure that patients with cancer do not experience barriers to adequate pain management, most of these guidelines are not intended for patients with cancer-related pain or for those receiving palliative or hospice care. Oncology, palliative, and hospice care providers are increasingly tasked with the management of severe disease-related pain in the setting of coexisting opioid use disorder without research on the most effective risk and harm reduction strategies to guide care. Clinicians should be familiar with addiction medicine and chronic pain literature and be able to incorporate some of these best practices. This case study reviews the management of severe cancer-related pain in a patient with co-occurring opioid use disorder, utilizing many of the best practices in available clinical practice guidelines for the management of chronic non-cancer-related pain.

Opioid Prescribing and Use Among Cancer Survivors: A Mapping Review of Observational and Intervention Studies

CONTEXT

Recent years show a sharp increase in research on opioid use among cancer survivors, but evidence syntheses are lacking, leaving knowledge gaps. Corresponding research needs are unclear.

OBJECTIVES

To provide an evidence synthesis.

METHODS

We searched PubMed and Embase, identifying articles related to cancer, and opioid prescribing/use published through September 2020. We screened resulting titles/abstracts. Relevant studies underwent full-text review. Inclusion criteria were quantitative examination of and primary focus on opioid prescribing or use, and explicit inclusion of cancer survivors. Exclusion criteria included end-of-life opioid use and opioid use as a secondary or downstream outcome (for intervention studies). We extracted information on the opioid-related outcome(s) examined (including definitions and terminology used), study design, and methods.

RESULTS

Research returned 16,591 articles; 296 were included. Only 22 of 296 studies evaluated an intervention. There were 105 studies evaluating outcomes indicative of potentially high-risk, nonrecommended, or avoidable opioid use, e.g., continuous use-described as chronic use, prolonged use, and persistent use (n = 17); use after completion of curative-intent treatment-described as chronic opioid use, long-term opioid use, persistent opioid use, prolonged opioid use, continued opioid use, late opioid use, post-treatment opioid use (n = 27); use of opioids concurrent with other potentially high-risk medications (n = 13), and opioid misuse (n = 14).

CONCLUSIONS

We found lack of consistency in the measurement of and terms used to describe similar opioid use outcomes, and a lack of interventional research targeting well-documented patterns of potentially nonrecommended, potentially avoidable, or potentially high-risk opioid prescribing or use.

'They say you can get addicted': Exploring factors that fuel the fear of addiction to prescription opioids among cancer survivors

OBJECTIVES

To explore misconceptions regarding addiction potential of prescription opioids among cancer survivors.

METHODS

A qualitative study using semi-structured interviews were conducted with a purposive sample of cancer survivors (N = 25) treated with prescription opioids for pain management. Interviews were audio recorded, transcribed and coded using Atlas.ti version 8. Inductive applied thematic analysis techniques were employed to identify emergent themes.

RESULTS

The majority of participants were breast cancer survivors (88%) who underwent a combination of surgery, chemotherapy and radiation (72%). Thematic analysis revealed that (1) cancer survivors view opioids as an illicit drug, (2) media narrative of the opioid epidemic increased negative perception of opioid use for cancer-related pain, (3) perceptions of opioids were also informed by experiences of friends and family with an opioid use disorder, (4) poor understanding of terminology resulted in misconceptions of opioid use and addiction and (5) fear of opioid addiction resulted in unrelieved cancer pain and poor quality of life.

CONCLUSION

Our findings support previously identified concerns among cancer patients about fear of addiction to opioids, a barrier to effective pain management. It highlights the importance for health care providers caring for cancer survivors to continue to address misconceptions about prescribed opioids.

Development and Validation of Prediction Models for Hypertensive Nephropathy, the PANDORA Study

Importance

Hypertension is a leading cause of end-stage renal disease (ESRD), but currently, those at risk are poorly identified.

Objective

To develop and validate a prediction model for the development of hypertensive nephropathy (HN).

Design, Setting, and Participants

Individual data of cohorts of hypertensive patients from Kailuan, China served to derive and validate a multivariable prediction model of HN from 12, 656 individuals enrolled from January 2006 to August 2007, with a median follow-up of 6.5 years. The developed model was subsequently tested in both derivation and external validation cohorts.

Variables

Demographics, physical examination, laboratory, and comorbidity variables.

Main Outcomes and Measures

Hypertensive nephropathy was defined as hypertension with an estimated glomerular filtration rate (eGFR) &lt; 60 ml/min/1.73 m2 and/or proteinuria.

Results

About 8.5% of patients in the derivation cohort developed HN after a median follow-up of 6.5 years that was similar in the validation cohort. Eight variables in the derivation cohort were found to contribute to the risk of HN: salt intake, diabetes mellitus, stroke, serum low-density lipoprotein, pulse pressure, age, hypertension duration, and serum uric acid. The discrimination by concordance statistics (C-statistics) was 0.785 (IQR, 0.770-0.800); the calibration slope was 1.129, the intercept was –0.117; and the overall accuracy by adjusted R2 was 0.998 with similar results in the validation cohort. A simple points scale developed from these data (0, low to 40, high) detected a low morbidity of 7% in the low-risk group (0–10 points) compared with &gt;40% in the high-risk group (&gt;20 points).

Conclusions and Relevance

A prediction model of HN over 8 years had high discrimination and calibration, but this model requires prospective evaluation in other cohorts, to confirm its potential to improve patient care.

Patterns and Trends in Receipt of Opioids Among Patients Receiving Treatment for Cancer in a Large Health System

BACKGROUND

Given limited evidence on opioid prescribing among patients receiving treatment for cancer during the ongoing opioid epidemic, our objective was to assess predictors of and trends in opioid receipt during cancer treatment, including how patterns differ by type of cancer.

METHODS

Using cancer registry data, we identified patients with a first lifetime primary diagnosis of breast, colorectal, or lung cancer from 2013 to 2017 who underwent treatment within a large cancer center network. Cancer registry data were linked to electronic health record information on opioid prescriptions. We examined predictors of and trends in receipt of any opioid prescription within 12 months of cancer diagnosis.

RESULTS

The percentage of patients receiving opioids varied by cancer type: breast cancer, 35% (1,996/5,649); colorectal, 37% (776/2,083); lung, 47% (1,259/2,654). In multivariable analysis, opioid use in the year before cancer diagnosis was the factor most strongly associated with receipt of opioids after cancer diagnosis, with 4.90 (95% CI, 4.10-5.86), 5.09 (95% CI, 3.88-6.69), and 3.31 (95% CI, 2.68-4.10) higher odds for breast, colorectal, and lung cancers, respectively. We did not observe a consistent decline in opioid prescribing over time, and trends differed by cancer type.

CONCLUSIONS

Our findings suggest that prescription of opioids to patients with cancer varies by cancer type and other factors. In particular, patients are more likely to receive opioids after cancer diagnosis if they were previously exposed before diagnosis, suggesting that pain among patients with cancer may commonly include non-cancer-related pain. Heterogeneity and complexity among patients with cancer must be accounted for in developing policies and guidelines aimed at addressing pain management while minimizing the risk of opioid misuse.

Risk of an Opioid-Related Emergency Department Visit or Hospitalization Among Older Breast, Colorectal, Lung, and Prostate Cancer Survivors

OBJECTIVE

To assess whether long-term cancer survivors (≥5 years after diagnosis) are at an increased risk of experiencing an opioid-related emergency department (ED) visit or hospitalization compared with persons without cancer.

METHODS

A 1:1 matched retrospective cohort study was performed using the Surveillance, Epidemiology, and End Results-Medicare linked data sets. The analysis was conducted from October 2020 to December 2020 in persons who lived 5 years or more after a breast, colorectal, lung, or prostate cancer diagnosis matched to noncancer controls on the basis of age, sex, race, pain conditions, and previous opioid use. Fine-Gray regression models were used to assess the relationship between cancer survivorship status and opioid-related ED visit or hospitalization.

RESULTS

The incidence of opioid-related ED visits and hospitalizations was 51.2 (95% CI, 43.5 to 59.8) and 62.2 (95% CI, 53.4 to 72.1) per 100,000 person-years among cancer survivors and matched noncancer controls, respectively. No significant association was observed between survivorship and opioid-related adverse event among opioid naive (hazard ratio, 0.79; 95% CI, 0.61 to 1.02) and non-naive (hazard ratio, 1.26; 95% CI, 0.84 to 1.89) cohorts.

CONCLUSION

Cancer survivors and noncancer controls had a similar risk of an ED visit or inpatient admission. Guidelines and policies should promote nonopioid pain management approaches especially to opioid non-naive older adults, a population at high risk for an opioid-related ED visit or hospitalization.

Temporal Trends and Predictors of Opioid Use Among Older Patients With Cancer

OBJECTIVES

While opioids represent a cornerstone of cancer pain management, the timing and patterns of opioid use in the cancer population have not been well studied. This study sought to explore longitudinal trends in opioid use among Medicare beneficiaries with nonmetastatic cancer.

MATERIALS AND METHODS

Within a cohort of 16,072 Medicare beneficiaries ≥66 years old diagnosed with nonmetastatic cancer between 2007 and 2013, we determined the likelihood of receiving a short-term (0 to 6 mo postdiagnosis), intermediate-term (6 to 12 mo postdiagnosis), long-term (1 to 2 y postdiagnosis), and high-risk (morphine equivalent dose ≥90 mg/day) opioid prescription after cancer diagnosis. Multivariable logistic regression models were used to identify patient and cancer risk factors associated with these opioid use endpoints.

RESULTS

During the study period, 74.6% of patients received an opioid prescription, while only 2.66% of patients received a high-risk prescription. Factors associated with use varied somewhat between short-term, intermediate-term, and long-term use, though in general, patients at higher risk of receiving an opioid prescription after their cancer diagnosis were younger, had higher stage disease, lived in regions of higher poverty, and had a history of prior opioid use. Prescriptions for high-risk opioids were associated with individuals living in regions with lower poverty.

CONCLUSIONS

Temporal trends in opioid use in cancer patients depend on patient, demographic, and tumor characteristics. Overall, understanding these correlations may help physicians better identify patient-specific risks of opioid use and could help better inform future evidence-based, cancer-specific opioid prescription guidelines.

Safety of opioid prescribing among older cancer survivors

BACKGROUND

Cancer survivors receive more long-term opioid therapy (LTOT) than people without cancer, but the safety of LTOT prescribing is unknown.

METHODS

Opioid-naive adults aged ≥66 years who had been diagnosed in 2008-2015 with breast, lung, head and neck, or colorectal cancer were identified with data from Surveillance, Epidemiology, and End Results cancer registries linked with Medicare claims. Survivors with 1 or more LTOT episodes (≥90 consecutive days) occurring ≥1 year after their cancer diagnosis and before censoring at hospice entry, another cancer diagnosis, 6 months before death, or December 2016 were included. The safety of prescribing during the first 90 days of the first LTOT episode was measured during follow-up. As a positive safety indicator, the proportion of survivors with concurrent nonopioid pain management was measured. Indicators of less safe prescribing were the proportion of survivors with a high average daily opioid dose (≥90 morphine milligram equivalents) and the proportion of survivors with concurrent benzodiazepine dispensing. Multivariable logistic regression analyses were conducted to identify clinical predictors of each safety outcome.

RESULTS

In all, 3628 cancer survivors received LTOT during follow-up (median duration, 4.9 months; interquartile range, 3.5-8.0 months). Seventy-two percent of the survivors received multimodal pain management concurrently with LTOT. Eight percent of the survivors had high-dose opioid prescriptions; 25% of the survivors received benzodiazepines during LTOT. Multivariable analyses identified variations in safety measures by multiple clinical factors, although none were consistently significant across outcomes.

CONCLUSIONS

To improve safe LTOT prescribing for survivors, efforts should focus on increasing multimodal pain management and reducing inappropriate benzodiazepine prescribing. Different clinical predictors of each outcome suggest different drivers of safe prescribing.

Association between initial opioid prescription diagnosis type and subsequent chronic prescription opioid use in Rhode Island: a population-based cohort study

OBJECTIVE

To identify initial diagnoses associated with elevated risk of chronic prescription opioid use.

DESIGN

Population-based, retrospective cohort study.

SETTING

State of Rhode Island.

PARTICIPANTS

Rhode Island residents with an initial opioid prescription dispensed between 1 April 2019 and 31 March 2020.

PRIMARY OUTCOME MEASURE

Subsequent chronic prescription opioid use, defined as receiving 60 or more days' supply of opioids in the 90 days following an initial opioid prescription.

RESULTS

Among the 87 055 patients with an initial opioid prescription, 3199 (3.7%) subsequently became chronic users. Patients who become chronic users tended to receive a longer days' supply, greater quantity dispensed, but a lower morphine milligram equivalents on the initial opioid prescription. Patients prescribed an initial opioid prescription for diseases of the musculoskeletal system and connective tissue (adjusted OR (aOR): 5.9, 95% CI: 4.7 to 7.6), diseases of the nervous system (aOR: 6.3, 95% CI: 4.9 to 8.0) and neoplasms (aOR: 5.6, 95% CI: 4.2 to 7.5) had higher odds of subsequent chronic prescription opioid use, compared with a referent group that included all diagnosis types with fewer than 15 chronic opioid users, after adjusting for confounders.

CONCLUSIONS

By focusing interventions and prescribing guidelines on specific types of diagnoses that carry a high risk of chronic prescription opioid use and diagnoses that would benefit equally or more from alternative management approaches, states and healthcare organisations may more efficiently decrease inappropriate opioid prescribing while improving the quality of patient care.

Abuse-Deterrent Opioids: A Survey of Physician Beliefs, Behaviors, and Psychology

Objective

Evaluate beliefs and behaviors pertaining to abuse-deterrent opioids (ADFs).

Design

Survey in 2019 by invitation to all licensed physicians.

Setting

Commonwealth of Kentucky.

Participants

374 physicians.

Methods

Descriptive statistics, and hypothesis test that early adopter prescribers would have greater endorsement of opioid risk management.

Results

Of all prescribers, 55% believed all opioid analgesics should have ADF requirements (15% were unsure); 74% supported mandating insurance coverage. Only one-third considered whether an opioid was ADF when prescribing, motivated by patient family diversion (94%) and societal supply reduction (88%). About half believed ADFs were equally effective in preventing abuse by intact swallowing, injection, chewing, snorting, smoking routes. Only 4% of OxyContin prescribers chose it primarily because of ADF properties. Instead, the most common reason (33%) was being started by another prescriber. A quarter of physicians chose not to prescribe ADFs because of heroin switching potential. Early adopters strongly believed ADFs were effective in reducing abuse (PR 3.2; 95% CI 1.5, 6.6) compared to mainstream physicians. Early-adopter risk-management practices more often included tools increasing agency and measurement: urine drug screens (PR 2.0; 1.3, 3.1), risk screening (PR 1.3; 0.94, 1.9). While nearly all respondents (96%) felt that opioid abuse was a problem in the community, only 57% believed it was a problem among patients in their practice. Attribution theory revealed an externalization of opioid abuse problems that deflected blame from patients on to family members.

Conclusions

The primary motivator for prescribing ADFs was preventing diversion by family members, not patient-level abuse concerns.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40122-021-00343-z.

Implicit Bias Training: Improving Outcomes for Patients With Cancer Who Have Substance Use Disorders

Being mindful of one's implicit bias in the treatment of patients with cancer who have substance use disorders is fundamental to quality of care and good patient outcomes. Implicit bias held by healthcare professionals could negatively affect patient assessment, diagnosis and treatment decisions, and follow-ups at discharge.

Racial, Ethnic, and Socioeconomic Discrepancies in Opioid Prescriptions Among Older Patients With Cancer

PURPOSE

Minority race and lower socioeconomic status are associated with lower rates of opioid prescription and undertreatment of pain in multiple noncancer healthcare settings. It is not known whether these differences in opioid prescribing exist among patients undergoing cancer treatment.

METHODS AND MATERIALS

This observational cohort study involved 33,872 opioid-naive patients of age > 65 years undergoing definitive cancer treatment. We compared rates of new opioid prescriptions by race or ethnicity and socioeconomic status controlling for differences in baseline patient, cancer, and treatment factors. To evaluate downstream impacts of opioid prescribing and pain management, we also compared rates of persistent opioid use and pain-related emergency department (ED) visits.

RESULTS

Compared with non-Hispanic White patients, the covariate-adjusted odds of receiving an opioid prescription were 24.9% (95% CI, 16.0 to 33.9, P < .001) lower for non-Hispanic Blacks, 115.0% (84.7 to 150.3, P < .001) higher for Asian-Pacific Islanders, and not statistically different for Hispanics (-1.0 to 14.0, P = .06). There was no significant association between race or ethnicity and persistent opioid use or pain-related ED visits. Patients living in a high-poverty area had higher odds (53.9% [25.4 to 88.8, P < .001]) of developing persistent use and having a pain-related ED visit (39.4% [16.4 to 66.9, P < .001]).

CONCLUSION

For older patients with cancer, rates of opioid prescriptions and pain-related outcomes significantly differed by race and area-level poverty. Non-Hispanic Black patients were associated with a significantly decreased likelihood of receiving an opioid prescription. Patients from high-poverty areas were more likely to develop persistent opioid use and have a pain-related ED visit.

Chronic Opioid Therapy in Cancer Survivors at a Specialty Oncology Pain Clinic: Opioid Dosing, Efficacy, and Safety During Five Years of Pain Management

There are limited data regarding long-term safety and efficacy in cancer survivors receiving chronic opioid therapy. With conflicting recommendations on opioid-prescribing practices and lack of available outcome data, this study aimed to provide a longitudinal perspective on opioid prescribing in cancer survivors. A retrospective chart review at a comprehensive cancer care center pain clinic used data from pain clinic provider notes from 2013 to 2018. Inclusion criteria were patients in clinical remission not receiving active chemotherapy or immunotherapy and receiving opioids during the study period. Opioid dosing changes and outcomes between zero and five years were evaluated by standard statistical analysis. Thirty-two patients met inclusion criteria. Solid malignancies were more common than hematologic malignancies (72% vs. 28%). Common pain complaints were related to postsurgical changes (43%), postradiation (32%), and chemotherapy-induced pain syndromes (25%). There were no serious adverse events. One patient exhibited possible aberrant behavior. At the initial visit, the median morphine milligram equivalent per day (MME/day) was 130. Median MME/day at Year 0 (study start) and Year 5 was 135 and 159, respectively (P = 0.475). Functional status was satisfactory in 58% at Year 0 and increased to 91% of patients meeting their functional goals at Year 5. In a carefully monitored group of cancer survivors with persistent pain, chronic opioid therapy was safely managed during extended periods without significant opioid escalation or evidence of serious adverse events including aberrant behaviors. This population benefited when opioid therapy was managed with a focus on function rather than reduction of pain intensity scores.

Predictors of Chronic Opioid Use: A Population-level Analysis of North Carolina Cancer Survivors Using Multi-Payer Claims

Background

No population-based studies have examined chronic opioid use among cancer survivors who are diverse with respect to diagnosis, age group, and insurance status.

Methods

We conducted a retrospective cohort study using North Carolina cancer registry data linked with claims from public and private insurance (2006-2016). We included adults with nonmetastatic cancer who had no prior chronic opioid use (n = 38 366). We used modified Poisson regression to assess the adjusted relative risk of chronic opioid use in survivorship (>90-day continuous supply of opioids in the 13-24 months following diagnosis) associated with patient characteristics.

Results

Only 3.0% of cancer survivors in our cohort used opioids chronically in survivorship. Predictors included younger age (adjusted risk ratio [aRR] 50-59 vs 60-69 = 1.23, 95% confidence interval [CI] = 1.05 to 1.43), baseline depression (aRR = 1.22, 95% CI = 1.06 to 1.41) or substance use (aRR = 1.43, 95% CI = 1.15 to 1.78) and Medicaid (aRR vs private = 1.93, 95% CI = 1.56 to 2.40). Survivors who used opioids intermittently (vs not at all) before diagnosis were twice as likely to use opioids chronically in survivorship (aRR = 2.62, 95% CI = 2.28 to 3.02). Those who used opioids chronically (vs intermittently or not at all) during active treatment had a nearly 17-fold increased likelihood of chronic use in survivorship (aRR = 16.65, 95% CI = 14.30 to 19.40).

Conclusions

Younger and low-income survivors, those with baseline depression or substance use, and those who require chronic opioid therapy during treatment are at increased risk for chronic opioid use in survivorship. Our findings point to opportunities to improve assessment of psychosocial histories and to engage patients in shared decision-making around long-term pain management, when chronic opioid therapy is required during treatment.

Opioid use by cancer status and time since diagnosis among older adults enrolled in the Prostate, Lung, Colorectal, and Ovarian screening trial in the United States

BACKGROUND

Dosing limits in opioid clinical practice guidelines in the United States are likely misapplied to cancer patients, however, opioid use may be difficult to ascertain as they are largely excluded from opioid use studies.

METHODS

The primary objective was to determine whether cancer patients were more likely to be chronic opioid users after diagnosis. We described prescription opioid use among U.S. older adult cancer patients during two time periods, within 2 years of diagnosis (short-term) and at least 2 years beyond diagnosis (long-term), compared to those without cancer (controls). Among participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) screening trial with linkages to Medicare Part D data during 2011-2015, we used multivariable logistic regression to estimate the association between cancer diagnosis and opioid use outcomes controlling for demographics. The primary outcome of opioid use was measured with the following metrics: Any opioid use, chronic use (90 consecutive days supply of opioid use while allowing for a 7-day gap between refills), high use (average daily morphine equivalent (MME) ≥120 mg for any 90-day period), and total MME dose above 2,000 mg (MME₂₀₀₀ ).

RESULTS

The short-term cohort included 1,491 cancer patients and 24,930 controls. Any use in the 2-year post-diagnosis period was higher among cancer patients OR 3.3 (95% CI: 3.0-3.7). Chronic use rates were similar by cancer status (4.6% vs. 3.8% for cases and controls, respectively). The long-term cohort included 4,377 cancer patients and 27,545 controls. Rates of any use were similar among cancer patients and controls (63% vs. 59%).

CONCLUSIONS

Any opioid use was similar among long-term cancer survivors compared to controls, but differed among short-term survivors for any opioid use and marginally for chronic opioid use.

Exploring Factors Associated With Long-Term Opioid Therapy in Cancer Survivors: An Integrative Review

CONTEXT

The prevalence of chronic pain in cancer survivors is double that of the general U.S.

POPULATION

Opioids have been the foundation of cancer pain management for decades; however, there is a paucity of literature on long-term opioid therapy (LTOT) in cancer survivors. An understanding of factors related to LTOT use in cancer survivors is needed to address chronic pain and balance opioid harms in the expanding population of cancer survivors.

OBJECTIVES

To analyze the research of LTOT utilization and factors associated with persistent opioid use in cancer survivors.

METHODS

A five-stage integrative review process was adapted from Whittemore and Knafl. Data sources searched included Web of Science, PubMed, Embase, Cochrane, and Google Scholar. Quantitative research studies from 2010 to present related to cancer survivors managed on LTOT were included. Editorials, reviews, or abstracts were excluded.

RESULTS

After reviewing 315 articles, 21 articles were included. We found that there were several definitions of LTOT in the reviewed studies, but the duration of opioid use (i.e., more than three months after completion of curative treatment) was the most common. The reviewed literature describes a relationship between LTOT and important biopsychosocial factors (cancer type, socioeconomic factors, and comorbidities).

CONCLUSION

The studies in this review shed light on the factors associated with LTOT in cancer survivors. LTOT was common in certain populations of cancer survivors and those with a collection of patient-specific characteristics. This review suggests that there is a critical need for specialized research on chronic cancer pain and opioid safety in cancer survivors.

Perceptions of prescription opioid medication within the context of cancer survivorship and the opioid epidemic

PURPOSE

Prescription opioid medication can be of great benefit for cancer patients and survivors who suffer from cancer-related pain throughout their cancer care trajectory. However, the current opioid epidemic has influenced how such medications are perceived. The purpose of this study was to explore the perceptions of opioid use and misuse in cancer survivorship within the context of the opioid epidemic.

METHODS

pt?>A qualitative study using a semi-structured interview was conducted with a purposive sample of health care professionals (n = 24), community-level stakeholders (n = 6), and cancer survivors (n = 25) using applied thematic analysis techniques.

RESULTS

Crosscutting themes include (1) fear of addiction and living with poorly managed pain, (2) the importance of good patient/provider communication and the need for education around the use/handling/disposal of prescription opioid medication, (3) preference for nonopioid alternatives for pain management, (4) cancer survivors perceived to be low risk for developing opioid use disorder (include inconsistent screening), and (5) impact of policies aimed at curbing the opioid epidemic on cancer survivors.

CONCLUSION

This study illustrates the intersecting and sometimes conflicting assumptions surrounding the use of opioids analgesics in the management of cancer pain among survivors embedded within the national discourse of the opioid epidemic.

IMPLICATIONS FOR CANCER SURVIVORS

A system of integrated cancer care using psychosocial screening, opioid risk mitigation tools, opioid treatment agreements, and specialist expertise that cancer care providers can rely on to monitor POM use in conjunction with patient-centered communication to empower patients informed decision making in managing their cancer pain could address this critical gap in survivorship care.

Validation of an oncology-specific opioid risk calculator in cancer survivors

BACKGROUND

Clinical guidelines recommend that providers risk-stratify patients with cancer before prescribing opioids. Prior research has demonstrated that a simple cancer opioid risk score might help identify to patients with cancer at the time of diagnosis with a high likelihood of long-term posttreatment opioid use. This current project validates this cancer opioid risk score in a generalizable, population-based cohort of elderly cancer survivors.

METHODS

This study identified 44,932 Medicare beneficiaries with cancer who had received local therapy. Longitudinal opioid use was ascertained from Medicare Part D data. A risk score was calculated for each patient, and patients were categorized into low-, moderate-, and high-risk groups on the basis of the predicted probability of persistent opioid use. Model discrimination was assessed with receiver operating characteristic curves.

RESULTS

In the study cohort, 5.2% of the patients were chronic opioid users 1 to 2 years after the initiation of cancer treatment. The majority of the patients (64%) were at low risk and had a 1.2% probability of long-term opioid use. Moderate-risk patients (33% of the cohort) had a 5.6% probability of long-term opioid use. High-risk patients (3.5% of the cohort) had a 75% probability of long-term opioid use. The opioid risk score had an area under the receiver operating characteristic curve of 0.869.

CONCLUSIONS

This study found that a cancer opioid risk score could accurately identify individuals with a high likelihood of long-term opioid use in a large, generalizable cohort of cancer survivors. Future research should focus on the implementation of these scores into clinical practice and how this could affect prescriber behavior and patient outcomes.

LAY SUMMARY

A novel 5-question clinical decision tool allows physicians treating patients with cancer to accurately predict which patients will persistently be using opioid medications after completing therapy.

Implications of Treatment Modality on Chronic Opioid Use Following Treatment for Head and Neck Cancer

Objective

To investigate the relationship between treatment modality and chronic opioid use in a large cohort of patients with head and neck cancer.

Study Design

Retrospective cohort study.

Setting

Single academic center.

Methods

There were 388 patients with head and neck cancer treated between January 2011 and December 2017 who met inclusion criteria. Clinical risk factors for opioid use at 3 and 6 months were determined with univariate and multivariate analyses.

Results

The prevalence of opioid use was 43.0% at 3 months and 33.2% at 6 months. On multivariate analysis, primary chemoradiation (odds ratio [OR], 4.04; 95% CI, 1.91-8.55) and surgery with adjuvant chemoradiation (OR, 2.39; 95% CI, 1.09-5.26) were associated with opioid use at 3 months. Additional risk factors at that time point included pretreatment opioid use (OR, 7.63; 95% CI, 4.09-14.21) and decreasing age (OR, 1.03; 95% CI, 1.01-1.06). At 6 months, primary chemoradiation (OR, 2.40; 95% CI, 1.34-4.28), pretreatment opioid use (OR, 5.86; 95% CI, 3.30-10.38), current tobacco use (OR, 2.00; 95% CI, 1.18-3.40), and psychiatric disorder (OR, 1.79; 95% CI, 1.02-3.14) were associated with opioid use.

Conclusion

Of the patients who receive different treatment modalities, those receiving primary chemoradiation are independently at highest risk for chronic opioid use. Other risk factors include pretreatment opioid use, tobacco use, and a psychiatric disorder. In an effort to reduce their risk of chronic opioid use, preventative strategies should be especially directed to these patients.

National Patterns in Prescription Opioid Use and Misuse Among Cancer Survivors in the United States

IMPORTANCE

Prescription opioids are frequently prescribed to treat cancer-related pain. However, limited information exists regarding rates of prescription opioid use and misuse in populations with cancer.

OBJECTIVES

To estimate the prevalence and likelihood of prescription opioid use and misuse in adult cancer survivors compared with respondents without cancer and to identify characteristics associated with prescription opioid use and misuse in adult cancer survivors.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study is a retrospective, population-based study using data from 169 162 respondents to the National Survey on Drug Use and Health from January 2015 to December 2018. Survey data sets were queried for all respondents aged 18 years or older. Those with a reported history of cancer were termed cancer survivors and further divided into more recent (had cancer within 12 months of survey) and less recent (had cancer more than 12 months prior to survey) cohorts. Respondents with nonmelanoma skin cancer were excluded.

MAIN OUTCOMES AND MEASURES

Prescription opioid use and misuse within the past 12 months.

RESULTS

Among 169 162 respondents, 5139 (5.2%) were cancer survivors, with 1243 (1.2%) and 3896 (4.0%) reporting having more recent and less recent cancer histories, respectively. Higher rates of prescription opioid use were observed among more recent cancer survivors (54.3%; 95% CI, 50.2%-58.4%; odds ratio [OR], 1.86; 95% CI, 1.57-2.20; P < .001) and less recent cancer survivors (39.2%; 95% CI, 37.3%-41.2%; OR, 1.18; 95% CI, 1.08-1.28; P < .001) compared with respondents without cancer (30.5%, reference group). Rates of prescription opioid misuse were similar among more recent (3.5%; 95% CI, 2.4%-5.2%; OR, 1.27; 95% CI, 0.82-1.96; P = .36) and less recent (3.0%; 95% CI, 2.4%-3.6%; OR, 1.03; 95% CI, 0.83-1.28; P = .76) survivors compared with respondents without cancer (4.3%, reference group). Younger age (aged 18-34 years vs ≥65 years: OR, 7.06; 95% CI, 3.03-16.41; P < .001), alcohol use disorder (OR, 3.22; 95% CI, 1.45-7.14; P = .005), and nonopioid drug use disorder (OR, 14.76; 95% CI, 7.40-29.44; P < .001) were associated with prescription opioid misuse among cancer survivors.

CONCLUSIONS AND RELEVANCE

In this study, prescription opioid use was higher among more and less recent cancer survivors compared with the population without a history of cancer. Rates of prescription opioid misuse were low and similar among all 3 cohorts. These findings suggest that higher prescription opioid use among cancer survivors may not correspond to increased short-term or long-term misuse.