Pain medication adherence in patients with cancer: a pragmatic review

Assessing the Validity of the Centers for Medicare & Medicaid Services Measure in Identifying Potentially Preventable Emergency Department Visits by Patients With Cancer

PURPOSE

The Centers for Medicare & Medicaid Services (CMS) implemented chemotherapy measures (OP-35) to reduce potentially preventable emergency department visits (PPEDVs) and hospitalizations. This study evaluated the validity of the OP-35 measure in identifying PPEDVs among patients with cancer.

METHODS

This is a cross-sectional study, which used data from the 2012-2022 National Hospital Ambulatory Medical Care Survey. ED visits are assessed and compared on the basis of three measures: immediacy using Emergency Severity Index (ESI), disposition (discharge v hospitalization), and OP-35 criteria.

RESULTS

Between 2012 and 2022, a weighted sample of 46,723,524 ED visits were made by patients with cancer. Among reported ESI cases, 25.2% (8,346,443) was high urgency. In addition, 30.3% (14,135,496) of ED visits among patients with cancer led to hospitalizations. Using the OP-35 measure, it was found that 20.85% (9,743,977) was PPEDVs. A 21.9% (10,232,102) discrepancy between discharge diagnosis (CMS billing codes) and chief complaints was identified. Further analysis showed that 19.2% (1,872,556) of potentially preventable ED visits (CMS OP-35) were high urgency and 32.6% (3,181,280) resulted in hospitalization.

CONCLUSION

The CMS approach to identifying PPEDVs has limitations. First, it may overcount preventable visits by including high-urgency or hospitalization-requiring cases. Second, relying on final diagnoses for retrospective preventability judgment can be misleading as they may not reflect the initial reason for the visit. In addition, differentiating causes for ED visits in patients with cancer undergoing various treatments is challenging as the approach does not distinguish between chemotherapy-related complications and others. Identification inconsistencies arise because of varying coding practices and chosen preventable conditions, lacking consensus and alignment with specific hospital or patient needs. Finally, the model fails to consider crucial nonclinical factors like social support, economic barriers, and alternative care access, potentially unfairly penalizing hospitals serving underserved populations.

Translation, Cultural Adaptation and Validation of the Medication Adherence Report Scale (MARS-5) in Nepalese Cancer Patients Experiencing Pain

Background

Adherence to pain medication is crucial for cancer patients, since non-adherence can lead to increased suffering, reduced quality of life and increased healthcare costs. Although the five-item Medication Adherence Report Scale (MARS-5) is a validated tool for assessing medication adherence, but it has not been translated and validated into the Nepalese language. This study aimed to translate, culturally adapt and validate the MARS-5 in Nepalese language for Nepalese cancer patients who were experiencing pain.

Materials and Methods

The cross-sectional validation study utilized a convenience sampling method. Initially, a pre-test was conducted with 25 patients. The MARS-5 was then forward and backward translated following the EORTC QLG translation procedure. The final translated version was reviewed by experts and subjected to a second pre-test. Construct validity was assessed through principal component analysis, and internal consistency was measured using Cronbach's alpha coefficient. Inter-rater reliability was evaluated using the Intra-Class Correlation coefficient (ICC).

Results

The study included 204 cancer patients (ages 18-86, 55% female). The Nepalese version of the MARS-5 was translated without significant issues and underwent pre-testing with participants. Participants discussed the scale during these pre-tests, providing feedback on its clarity and comprehensibility. While formal assessment tools were not employed, the iterative nature of the pre-testing process allowed for the refinement of the translation based on participant feedback, indicating a robust understanding of the scale among participants. The ICC of test-retest reliability was found to be 0.860. The Kaiser Meyer Olkin's value was 0.690, and Cronbach's alpha was 0.72, indicating good construct validity and high internal consistency. The medication non-adherence rate was 11.3%.

Conclusion

The MARS-5 was successfully translated, culturally adapted, and validated in Nepalese for use among Nepalese cancer patients experiencing pain. The Nepalese version of MARS-5 is a reliable tool for evaluating medication adherence in this population.

Comprehensive assessment of pain characteristics, quality of life, and pain management in cancer patients: a multi-center cross-sectional study

INTRODUCTION

Pain is the most common complaint among cancer patients, significantly impairing their health-related quality of life (HRQOL). There is limited evidence on the characteristics of pain among cancer patients in Nepal with low-resource settings.

OBJECTIVES

The primary objective of this study was to evaluate the clinical characteristics of pain, factors influencing pain intensity, and the association of pain severity with quality of life (QoL) among cancer patients. Secondary objectives included investigating perceived barriers to pain management and medication adherence among these patients.

METHODS

This multi-center, cross-sectional study enrolled adult patients (over 18 years old) with reported cancer diagnoses experiencing pain. Socio-demographic characteristics (e.g., age, gender, educational status), clinical characteristics (e.g. cancer diagnosis, staging), and pain characteristics (e.g., duration, type, location, medicines used for pain management, etc.) were recorded. Outcomes were assessed using the Numeric rating scale (NRS), Pain management Index, European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire, Barriers Questionnaire II, Medication Adherence Rating Scale, and Hospital Anxiety and Depression Scale.

RESULTS

Four hundred and eight patients participated in the study. The mean ± SD age was 54.87 ± 15.65, with 226 patients (55.4%) being female. The most common cancer diagnoses were cervical (17.6%), lung (11.8%), and colon/rectum (12.0%) cancers. The most common pain locations were the head and neck (27.0%); a majority (55.6%) reported pain duration of more than 3 months. Nociceptive pain was reported by 42.4% of patients; the mean ± SD of NRS was 4.31 ± 2.69, with 32.4% of patients experiencing moderate pain. Patients with mixed pain type (B = 1.458, p < 0.001) or pain in multiple sites (B = 1.175, p < 0.001), lower Karnofsky Performance Status (KPS) (B = -1.308, p < 0.001), and specific cancer diagnoses such as prostate (B = -2.045, p = 0.002), pancreatic (B = 1.852, p = 0.004), oesophageal (B = 1.674, p = 0.012), and ovarian cancer (B = 1.967, p = 0.047), experienced varying degrees of increased NRS score. The combined chemotherapy and radiotherapy treatment modality was associated with a lower NRS score (B = -0.583, p = 0.017). A significant inverse relationship was observed between pain severity and global health status/QoL (B = -37.36, p < 0.001. Key barriers to pain management included moderate perceptions of physiological effects, communication issues between doctors and patients, and concerns about the harmful effects of pain medicine. The prevalence of non-adherence to pain medications was 13.97%.

CONCLUSION

In conclusion, this study highlights the multi-faceted nature of pain management and QoL for cancer patients in Nepal with low-resource settings. These findings underscore the multifactorial nature of pain perception in cancer patients, with mixed pain types, pain in multiple sites, lower KPS, and specific cancer diagnoses, all contributing significantly to pain severity. Additionally, pain severity was associated with declining QoL. These findings contribute valuable insights into the complex aspects of cancer pain and its broader implications for the well-being of patients, offering a foundation for targeted interventions and improved pain management strategies in the context of cancer care in low-resource settings.

Opioid Nonadherence Risk Prediction of Patients with Cancer-Related Pain Based on Five Machine Learning Algorithms

Objectives

Opioid nonadherence represents a significant barrier to cancer pain treatment efficacy. However, there is currently no effective prediction method for opioid adherence in patients with cancer pain. We aimed to develop and validate a machine learning (ML) model and evaluate its feasibility to predict opioid nonadherence in patients with cancer pain.

Methods

This was a secondary analysis from a cross-sectional study that included 1195 patients from March 1, 2018, to October 31, 2019. Five ML algorithms, such as logistic regression (LR), random forest, eXtreme Gradient Boosting, multilayer perceptron, and support vector machine, were used to predict opioid nonadherence in patients with cancer pain using 43 demographic and clinical factors as predictors. The predictive effects of the models were compared by the area under the receiver operating characteristic curve (AUC_ROC), accuracy, precision, sensitivity, specificity, and F1 scores. The value of the best model for clinical application was assessed using decision curve analysis (DCA).

Results

The best model obtained in this study, the LR model, had an AUC_ROC of 0.82, accuracy of 0.82, and specificity of 0.71. The DCA showed that clinical interventions for patients at high risk of opioid nonadherence based on the LR model can benefit patients. The strongest predictors for adherence were, in order of importance, beliefs about medicines questionnaire (BMQ)-harm, time since the start of opioid, and BMQ-necessity. Discussion. ML algorithms can be used as an effective means of predicting adherence to opioids in patients with cancer pain, which allows for proactive clinical intervention to optimize cancer pain management. This trial is registered with ChiCTR2000033576.

Managing Severe Cancer Pain with Oxycodone/Naloxone Treatment: A Literature Review Update

Severe cancer pain substantially affects patients' quality of life, increasing the burden of the disease and reducing the disability-adjusted life years. Although opioid analgesics are effective, they may induce opioid-induced bowel dysfunction (OIBD). Oxycodone/naloxone combination therapy has emerged as a promising approach to mitigate opioid-induced constipation (OIC) while providing effective pain relief. This review provides an updated analysis of the literature of the last decade regarding the use of oxycodone/naloxone in the management of severe cancer pain. Through a comprehensive search of databases, studies focusing on the efficacy, safety, and patient experience of oxycodone/naloxone's prolonged release in severe cancer pain management were identified. Furthermore, the literature discusses the mechanism of action of naloxone in mitigating OIC without compromising opioid analgesia. Overall, the evidence suggests that oxycodone/naloxone combination therapy offers a valuable option for effectively managing severe cancer pain while minimizing opioid-induced constipation, thereby improving patients' quality of life. However, further research is needed to optimize dosing regimens, evaluate long-term safety, and assess patient outcomes in diverse cancer populations.

Investigating the risk factors for nonadherence to analgesic medications in cancer patients: Establishing a nomogram model

Objective

The substantial prevalence of nonadherence to analgesic medication among individuals diagnosed with cancer imposes a significant strain on both patients and healthcare resources. The objective of this study is to develop and authenticate a nomogram model for assessing nonadherence to analgesic medication in cancer patients.

Methods

Clinical information, demographic data, and medication adherence records of cancer pain patients were gathered from the Affiliated Hospital of Chengde Medical University between April 2020 and March 2023. The risk factors associated with analgesic medication nonadherence in cancer patients were analyzed using the least absolute selection operator (LASSO) regression model and multivariate logistic regression. Additionally, a nomogram model was developed. The bootstrap method was employed to internally verify the model. Discrimination and accuracy of the nomogram model were evaluated using the Concordance index (C-index), area under the receiver Operating characteristic (ROC) curve (AUC), and calibration curve. The potential clinical value of the nomogram model was established through decision curve analysis (DCA) and clinical impact curve.

Results

The study included a total of 450 patients, with a nonadherence rate of 43.33%. The model incorporated seven factors: age, address, smoking history, number of comorbidities, use of nonsteroidal antiinflammatory drugs (NSAIDs), use of opioids, and PHQ-8. The C-index of the model was found to be 0.93 (95% CI: 0.907-0.953), and the ROC curve demonstrated an AUC of 0.929. Furthermore, the DCA and clinical impact curves indicate that the built model can accurately predict cancer pain patients' medication adherence performance.

Conclusions

A nomogram model based on 7 risk factors has been successfully developed and validated for long-term analgesic management of cancer patients.

Patient Experiences After Aborted Cancer Surgery: A Qualitative Study

BACKGROUND

Surgical resection is a necessary component of curative-intent treatment for most solid-organ cancers but is occasionally aborted, most often due to occult metastatic disease or unanticipated unresectability. Despite its frequency, little research has been performed on the experiences, care needs, and treatment preferences of patients who experience an aborted cancer surgery.

METHODS

Semistructured interviews of patients who had previously experienced an aborted cancer surgery were conducted, focusing on their recalled experiences and stated preferences. All interviews were audio recorded, transcribed, and coded by two independent researchers by using NVivo 12. An integrative approach to qualitative analysis was used-both inductive and deductive methods-and iteratively identifying themes until saturation was reached.

RESULTS

Fifteen patients with an aborted cancer surgery participated in the interviews. Cancer types included pancreatic (n = 9), cholangiocarcinoma (n = 3), hepatocellular carcinoma (n = 1), gallbladder (n = 1), and neuroendocrine (n = 1). The most common reasons for aborting surgery included local tumor unresectability (n = 8) and occult metastatic disease (n = 7). Five subthemes that characterized the patient experience following an aborted cancer surgery emerged, including physical symptoms, emotional responses, impact on social and life factors, coping mechanisms, and support received.

CONCLUSIONS

This qualitative study characterizes the impact of aborted cancer surgery on multiple domains of quality of life: physical, emotional, social, and existential. These results highlight the importance of developing patient-centered interventions that focus on enhancing quality of life after aborted cancer surgery.