How I treat pain in hematologic malignancies safely with opioid therapy

Perceptions of prescription opioids among marginalized patients with hematologic malignancies in the context of the opioid epidemic: a qualitative study

PURPOSE

Opioids are essential for treating pain in hematologic malignancies (HM), yet are heavily stigmatized in the era of the opioid epidemic. Stigma and negative attitudes towards opioids may contribute to poorly managed cancer pain. We aimed to understand patient attitudes towards opioids for HM pain management, particularly among historically marginalized populations.

METHODS

We interviewed a convenience sample of 20 adult patients with HM during outpatient visits at an urban academic medical center. Semi-structured interviews were audio-recorded, transcribed, and qualitatively analyzed using the framework method.

RESULTS

Among 20 participants, 12 were female and half were Black. Median age was 62 (interquartile range = 54-68). HM diagnoses included multiple myeloma (n = 10), leukemia (n = 5), lymphoma (n = 4), and myelofibrosis (n = 1). Eight themes emerged from interviews that seemed to influence HM-related pain self-management, including (1) fear of opioid-related harms, (2) opioid side effects and harms to health, (3) fatalism and stoicism, (4) perceived value of opioids for HM-related pain, (5) low perceived susceptibility to opioid-related harms and externalizing blame, (6) preferences for non-opioid pain management approaches, (7) trust in providers and opioid accessibility, and (8) external sources of pain management support and information.

CONCLUSIONS

This qualitative study demonstrates that fears and stigmatized views of opioids can conflict with marginalized patients' needs to manage debilitating HM-related pain. Negative attitudes towards opioids were shaped by the opioid epidemic and reduced willingness to seek out or use analgesics.

IMPLICATIONS FOR CANCER SURVIVORS

These findings help expose patient-level barriers to optimal HM pain management, revealing attitudes, and knowledge to be targeted by future pain management interventions in HM.

Integrative Approaches in the Treatment of Patients Affected by Lymphoma

PURPOSE OF REVIEW

Lymphoma is the most frequent hematological malignancy with wide disease spectrum of watchful waiting period, active treatment, survivorship, and palliative care. All these steps impose unmet needs in terms of prevention, symptom alleviation, or prognosis. Complementary and integrative medicine (CIM) is widely used by patients with lymphoma to cope with such issues. Here, we describe the different CIM modalities that may be effective and safe for the management of patients with lymphoma.

RECENT FINDINGS

Low inflammatory diet and ginseng seem effective for lymphoma prevention. Pain and neuropathy may be improved using acupuncture, touch therapy and specific dietary supplements. Nausea/vomiting, fatigue, and insomnia may be relieved by acupuncture, mind-body, touch therapy, and certain dietary supplements. Vitamin D, curcumin, and some traditional medicine herbs may positively impact lymphoma prognosis. Finally, safety issues should be considered especially for the concomitant use of dietary supplements and lymphoma-directed therapies. CIM may be beneficial along the continuum of lymphoma management although safety concerns should be considered when used concomitantly with conventional therapy.

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.

Clinical relevance of deep learning models in predicting the onset timing of cancer pain exacerbation

Cancer pain is a challenging clinical problem that is encountered in the management of cancer pain. We aimed to investigate the clinical relevance of deep learning models that predict the onset of cancer pain exacerbation in hospitalized patients. We defined cancer pain exacerbation (CPE) as the pain with a numerical rating scale (NRS) score of ≥ 4. We investigated the performance of the deep learning models using the Matthews correlation coefficient (MCC) with different input lengths and time binning. All the pain records were obtained from the electronic medical records of the hematology-oncology wards in a Samsung Medical Center between July 2016 and February 2020. The model was externally validated using the holdout method with 20% of the datasets. The most common type of cancer was lung cancer (n = 745, 21.7%), and the median CPE per day was 1.01. The NRS pain records showed circadian patterns that correlated with NRS pain patterns of the previous days. The correlation of the NRS scores showed a positive association with the closeness of the NRS pattern of the day with forecast date and size of time binning. The long short-term memory-based model exhibited a good performance by demonstrating 9 times the best performance and 8 times the second-best performance among 21 different settings. The best performance was achieved with 120 h input and 12 h bin lengths (MCC: 0.4927). Our study demonstrated the possibility of predicting CPE using deep learning models, thereby suggesting that preemptive cancer pain management using deep learning could potentially improve patients' daily life.

Patient-centered quality measurement for opioid use disorder: Development of a taxonomy to address gaps in research and practice

Background: Evidence-based treatment is provided infrequently and inconsistently to patients with opioid use disorder (OUD). Treatment guidelines call for high-quality, patient-centered care that meets individual preferences and needs, but it is unclear whether current quality measures address individualized aspects of care and whether measures of patient-centered OUD care are supported by evidence. Methods: We conducted an environmental scan of OUD care quality to (1) evaluate patient-centeredness in current OUD quality measures endorsed by national agencies and in national OUD treatment guidelines; and (2) review literature evidence for patient-centered care in OUD diagnosis and management, including gaps in current guidelines, performance data, and quality measures. We then synthesized these findings to develop a new quality measurement taxonomy that incorporates patient-centered aspects of care and identifies priority areas for future research and quality measure development. Results: Across 31 endorsed OUD quality measures, only two measures of patient experience incorporated patient preferences and needs, while national guidelines emphasized providing patient-centered care. Among 689 articles reviewed, evidence varied for practices of patient-centered care. Many practices were supported by guidelines and substantial evidence, while others lacked evidence despite guideline support. Our synthesis of findings resulted in EQuIITable Care, a taxonomy comprised of six classifications: (1) patient Experience and engagement, (2) Quality of life; (3) Identification of patient risks; (4) Interventions to mitigate patient risks; (5) Treatment; and (6) Care coordination and navigation. Conclusions: Current quality measurement for OUD lacks patient-centeredness. EQuIITable Care for OUD provides a roadmap to develop measures of patient-centered care for OUD.