Patterns of analgesic adherence predict health care utilization among outpatients with cancer pain

Electronic Real-Time Monitoring Reveals Limited Adherence to Long-Term Opioid Prescriptions in Pain Patients

Background

Pain management physicians are increasingly focused on limiting prescription opioid abuse, yet existing tools for monitoring adherence have limited accuracy. Medication event monitoring system (MEMS) is an emerging technology for tracking medication usage in real-time but has not been tested in chronic pain patients on long-term opioid regimens.

Objective

We conducted a pilot clinical trial to investigate the utility of MEMS for monitoring opioid adherence and compared to traditional methods including self-report diaries, urine drug screen (UDS), and physicians' opinions.

Methods

Opioid-maintained chronic pain patients were recruited from a pain management clinic. Participants (n=28) were randomly assigned to either receive MEMS bottles containing their opioid medication for a 90-day period or to continue using standard medication bottles. MEMS bottles were configured to record and timestamp all bottle openings and the number of pills that were removed from the bottle (via measurement of weight change).

Results

Participants who received MEMS demonstrated highly heterogenous dosing patterns, with a substantial number of patients rapidly removing excessive amounts of medication and/or "stockpiling" medication. By comparison, physicians rated all participants as either "totally compliant" or "mostly compliant". UDS results did not reveal any illicit drug use, but 25% of participants (n=7) tested negative for their prescribed opioid metabolite. MEMS data did not correlate with physician-rated adherence (P=0.24) and UDS results (P=0.77). MEMS data consistently revealed greater non-adherence than self-report data (P<0.001).

Conclusion

These results highlight the limits in our understanding of naturalistic patterns of daily opioid use in chronic pain patients as well as support the use of MEMS for detecting potential misuse as compared to routine adherence monitoring methods. Future research directions include the need to determine how MEMS could be used to improve patient outcomes, minimize harm, and aid in clinical decision-making.

Trial Registration

This study was preregistered on ClinicalTrials.gov (NCT03752411).

Trajectories and predictors of high-occurrence pain flares in ambulatory cancer patients on opioids

BACKGROUND

Pain flares have a substantive impact on the quality of life and well-being of patients with cancer. We identified longitudinal trajectories (clusters) of cancer pain flares in ambulatory patients and sociodemographic and clinical predictors of these trajectories.

METHODS

In a prospective cohort study using ecological momentary assessment (mEMA), we collected patient-reported daily pain flare ratings data over 5 months and identified predictors and correlates using validated measures.

RESULTS

The mean age of the sample (N = 270) was 60.9 years (SD = 11.2), 64.8% were female, and 32.6% self-identified as African American. Four pain flare clusters were identified. The "high-occurrence" cluster (23% of patients) experienced 5.5 (SD = 5.47) daily flares, whereas low-moderate clusters (77%) reported 2.4 (SD = 2.74) daily flares (P < .000). Those in the high-occurrence cluster reported higher pain scores (P = .000), increased pain-related interference (P = .000), depressive symptoms (P = .023), lower quality of life (P = .001), and reduced pain self-efficacy (P = .006). Notably, 67.2% of those prescribed opioids as needed (PRN only) were in the high-occurrence pain flare cluster, compared with 27.9% with PRN and around-the-clock opioid prescriptions (P = .024). Individual predictors of high-occurrence pain flares were income below $30 000, unemployment, being African American, lower education level, Medicaid insurance, current opioid misuse (COMM), baseline inpatient hospital stay duration, and PRN-only opioid regimen. In the multiple predictor model, lower education level, unemployment, COMM score, extended inpatient duration, and PRN-only opioid regimen remained significant.

CONCLUSION

In ambulatory patients with cancer, high occurrence of pain flares may be mitigated by attention to opioid prescription factors and addressing social determinants of health needs of underserved patients.

The Effect of Remote-Based Monitoring and Education Program on Cancer Pain Management in an Outpatient Pain Clinic

BACKGROUND

Pain is one of the most feared consequences of cancer for patients and their families. Many barriers may hinder optimal pain management.

AIM

Examine the effect of remote-based monitoring and education program on cancer pain management, patient-related barriers, and level of adherence to pain medication.

METHODS

A sample of 134 patients was assigned to two groups; 68 in the intervention group and 66 in the control. The intervention group received three educational sessions by telephone. Both groups completed questionnaires at baseline and one month after the initial visit.

RESULTS

Significant differences were found between the groups in the levels of pain right now (p = .030), pain at its least (p = .016), and in the percentage of achieved pain relief (p = .048). Moreover, the intervention group experienced lower levels of interference with their general activity (p = < .001), mood (p = .011), and normal work (p = .004) post-intervention. The Attitudinal Barriers differences were statistically significant in the total mean (p = < .001), and the subscales of physiological effects (p = < .001), fatalism (p = < .001), communication (p = < .001), harmful effects (p = < .001). Participants in the intervention group exhibited higher adherence levels (p = .001).

CONCLUSIONS

Patients suffering from cancer-related pain can benefit from remote-based monitoring and education programs to improve pain management outcomes, overcome barriers, and increase adherence. Further research is needed to investigate the different available educational methods and long-term effects.

Cultural dimensions of individualism and collectivism and risk of opioid misuse: A test of Social Cognitive Theory

BACKGROUND

Despite the critical role social and cultural contexts play in pain experience, limited theoretical and empirical attention has been devoted to the interplay between social, cognitive, cultural, and psychological factors in chronic pain management and the risk of opioid misuse.

METHODS

Using structural equation modeling, the present study tested the Social Cognitive Theory (SCT) of chronic pain management and risk of opioid misuse in the context of intraindividual cultural dimensions of individualism and collectivism among 316 ethnically diverse adults with chronic pain in the United States.

RESULTS

Social cognitive predictors account for a significant amount of variance in pain dysfunction and risk of opioid misuse in adults with chronic pain. Satisfaction with pain support was positively associated with both greater pain acceptance and greater pain self-efficacy. Individualism was found to be positively associated with satisfaction with pain support, pain self-efficacy, and pain acceptance but negatively associated with the risk of opioid misuse. Collectivism was positively associated with the risk of opioid misuse.

CONCLUSIONS

The study findings not only empirically support using SCT for adults with chronic pain, but also provide a more thorough conceptual framework that highlights the intracultural diversity and interplay among social, cognitive, and psychological factors that affect pain experience and the risk of opioid misuse among adults with chronic pain.

Impact of Cannabis Use on Least Pain Scores Among African American and White Patients with Cancer Pain: A Moderation Analysis

INTRODUCTION

Based on many published reports, African American patients with cancer experience higher pain severity scores and lower pain relief than White patients. This disparity results from undertreatment of pain and is compounded by low adherence to prescribed non-opioid and opioid analgesics among African American patients with cancer. While nearly one in four patients use cannabis to manage cancer-related symptoms, less is known about how cannabis use influences pain relief in this patient population.

METHODS

This study is based on preliminary data from an ongoing study of longitudinal outcomes of opioid therapy among African American and White patients with cancer. Linear mixed-effects models were utilized to assess the interaction of race and cannabis use on pain relief using "least pain" item scores from the Brief Pain Inventory (BPI) averaged across three time points. Models were adjusted for sociodemographic and clinical variables.

RESULTS

This analysis included 136 patients (49 African American, 87 White). Overall, 30.1% of the sample reported cannabis use for cancer pain. The mean "least pain" score on BPI was 3.3 (SD=2.42) on a scale of 0-10. African American patients had a mean "least pain" score 1.32±0.48 units higher (indicating lower pain relief) than White patients (p=0.006). Cannabis use did not have a significant main effect (p=0.28). However, cannabis use was a significant moderator of the relationship between race and "least pain" (p=0.03). In the absence of cannabis use, African Americans reported higher "least pain" scores compared to Whites (mean difference=1.631±0.5, p=0.001). However, this disparity was no longer observed in African American patients reporting cannabis use (mean "least pain" difference=0.587±0.59, p=0.32).

CONCLUSION

These findings point to the possible role of cannabis in cancer pain management and its potential to reduce racial disparities. These findings are preliminary and further research into the role of cannabis in cancer pain outcomes is needed.

Gaps in the Use of Long-Acting Opioids Within Intervals of Consecutive Days Among Cancer Outpatients Using Electronic Pill Caps

OBJECTIVE

This study describes individual cancer patients' nonuse of extended-release or long-acting (ER/LA) opioids, including periods of gap between opioid doses taken.

DESIGN

Secondary analysis of a three-month observational study of prescribed ER/LA opioids monitored using electronic pill caps.

SETTING

Two outpatient oncology clinics of a large health system in the Mid-Atlantic region.

PARTICIPANTS

Inclusion was based on self-identified African Americans and whites, at least 18 years old, diagnosed with solid tumors or multiple myeloma. For the current analysis, the additional inclusion criterion was prescription of an oral ER/LA opioid for cancer pain to be taken around the clock.

METHODS

The electronic monitoring period for each study participant was partitioned into intervals of days between days with one or more openings (using medication event monitoring systems) representing rates of ER/LA opioid nonuse over consecutive days and over time.

RESULTS

Of the sample (N = 109), two-thirds of the cancer patients had some nonuse of prescribed ER/LA opioids, with one in four having nonuse during 31.5-87.5% of their electronic-monitoring periods. Nonuse over periods of five or more, six or more, and seven or more consecutive days occurred for 37.6%, 34.9%, and 30.3% of the participants, respectively.

CONCLUSIONS

About one in three ambulatory cancer patients in this study had substantial gaps between days of ER/LA opioid use, potentially resulting in risk of overdose depending upon the prescribed ER/LA opioid type, dose, and length of the time the opioid was stopped and resumed at the previous dose. This phenomenon has received little to no attention in the opioid safety discourse.

Pain medication adherence in patients with cancer: a pragmatic review

OBJECTIVE

Adherence to pain medication in patients with cancer is crucial for successful pain therapy. This review aimed to investigate: the rate of adherence, which factors influence adherence, whether adherence differs in diverse patient populations, whether there are methods to improve adherence, and the relationship between adherence and pain relief.

METHODS

This review was performed following the PRISMA guidelines. MEDLINE/Pubmed, Embase, Web Of Science, Cochrane and ClinicalTrials.gov were searched. All types of studies investigating adherence of patients with cancer, factors influencing adherence, and methods to improve adherence to pain medication were included. They were first screened on title and abstract and thereafter on full text. Selected articles were subjected to a quality assessment according to the PRISMA checklist. From included articles, study characteristics and outcomes were extracted.

RESULTS

Out of 795 articles, 18 were included. Different methods were used to measure adherence, which led to adherence rates ranging from 8.9% to 82.0%. White Americans and men were found to be more adherent than African Americans and women. Due to various barriers, adherence is often suboptimal. Fear of addiction, physiological and harmful effects, tolerance, and disease progression are common concerns. Interventions, such as pain education booklets, pain consults, and specialised nurses, may be beneficial to increase the adherence. Lower adherence rates were associated with lower pain relief.

CONCLUSION

Adherence of cancer patients to pain medication is suboptimal. Health care workers should focus on barriers to increase the adherence in order to obtain a better pain relief.

The Association Between Analgesic Treatment Beliefs and Electronically Monitored Adherence for Cancer Pain

OBJECTIVES

To determine whether clusters based on analgesic treatment beliefs among patients with cancer predict objective analgesic adherence.

SAMPLE & SETTING

207 patients with cancer in the outpatient setting who were aged 18 years or older, self-identified as White or African American, were diagnosed with solid tumor or multiple myeloma, and were prescribed at least one around-the-clock analgesic prescription for reported cancer pain.

METHODS & VARIABLES

This study is a secondary analysis of an existing dataset. General linear modeling with a backward elimination approach was applied to determine whether previously identified analgesic treatment belief clusters, as well as sociodemographic, clinical, and pain variables, were associated with adherence behaviors.

RESULTS

Significant explanatory factors were experiential in nature and included sociodemographic, clinical, and pain-related variables, explaining 21% of the variance in analgesic adherence. Analgesic belief clusters were not predictive of adherence.

IMPLICATIONS FOR NURSING

Future research should examine sociodemographic and other clinical factors, as well as the influence of analgesic treatment beliefs, to better understand adherence behaviors among patients with cancer.

Modeling Individual Patient Count/Rate Data over Time with Applications to Cancer Pain Flares and Cancer Pain Medication Usage

The purpose of this article is to investigate approaches for modeling individual patient count/rate data over time accounting for temporal correlation and non-constant dispersions while requiring reasonable amounts of time to search over alternative models for those data. This research addresses formulations for two approaches for extending generalized estimating equations (GEE) modeling. These approaches use a likelihood-like function based on the multivariate normal density. The first approach augments standard GEE equations to include equations for estimation of dispersion parameters. The second approach is based on estimating equations determined by partial derivatives of the likelihood-like function with respect to all model parameters and so extends linear mixed modeling. Three correlation structures are considered including independent, exchangeable, and spatial autoregressive of order 1 correlations. The likelihood-like function is used to formulate a likelihood-like cross-validation (LCV) score for use in evaluating models. Example analyses are presented using these two modeling approaches applied to three data sets of counts/rates over time for individual cancer patients including pain flares per day, as needed pain medications taken per day, and around the clock pain medications taken per day per dose. Means and dispersions are modeled as possibly nonlinear functions of time using adaptive regression modeling methods to search through alternative models compared using LCV scores. The results of these analyses demonstrate that extended linear mixed modeling is preferable for modeling individual patient count/rate data over time, because in example analyses, it either generates better LCV scores or more parsimonious models and requires substantially less time.

Patient Trade-Offs Related to Analgesic Use for Cancer Pain: A MaxDiff Analysis Study

PURPOSE

Many patients with cancer pain deviate from prescribed analgesic regimens. Our aim was to elicit the trade-offs patients make based on their beliefs about analgesic use and rank utilities (importance scores) using maximum difference (MaxDiff) scaling. We also investigated if there were unique clusters of patients based on their analgesic beliefs.

METHODS

This was a secondary analysis of a three-month, prospective observational study. Patients (N = 207) were self-identified African Americans and Whites, >18 years, diagnosed with multiple myeloma or solid tumor, and were prescribed at least one around-the-clock analgesic for cancer pain. MaxDiff analysis allowed us to identify patients utilities. Second, a cluster analysis assisted in ranking how analgesic beliefs differed by groups. Third, clusters were described by comparing key sociodemographic and clinical variables.

RESULTS

Participants' beliefs were a significant factor in choices related to analgesic use (chi-square = 498.145, p < .0001). The belief, 'Pain meds keep you from knowing what is going on in your body', had the highest patient endorsement. Two distinct clusters of patients based on analgesic beliefs were identified; 'knowing body' was ranked as top priority for both clusters. The belief that cancer patients become addicted to analgesics was moderately important for both clusters. Severity of side effects was the only key variable significantly different between clusters (p = .043).

CONCLUSIONS

Our findings support tailored pain management interventions that attend to individual beliefs about cancer pain and analgesic use. Future research should explore the relationship between analgesic utilities, actual analgesic taking behaviors, and how they impact patients' cancer pain outcomes.

When Patients Take Charge of Opioids: Self-Management Concerns and Practices Among Cancer Outpatients in the Context of Opioid Crisis

CONTEXT

With concerns about opioid prescribing practices prominent in the professional and lay literature, there is less focus on patients' self-management of opioids for cancer pain and potential safety risks.

OBJECTIVES

To investigate reports of opioid self-management practices and concerns among patients undergoing active cancer treatments-a group excluded from the scope of most policy initiatives on prescription opioids.

METHODS

This sequential multimethod study used freelisting (n = 65) and open-ended semistructured interviews with a racially diverse subgroup (n = 32). Adult ambulatory patients with solid malignancies or multiple myeloma and pain (≥4 on a scale of 0-10) were recruited from an urban National Cancer Institute-designated cancer center in Philadelphia. Freelists were analyzed using consensus analysis and semistructured interview data were analyzed using thematic analysis.

RESULTS

In freelisting, "pain relief" emerged as the primary term in relation to taking pain medications preceding "addiction" concerns. In interviews, patients described several heuristics and some potentially unsafe practices to minimize opioid use to a self-defined "normal." These included reducing opioid dose by cutting pills; self-tapering off opioids; using extended-release/long-acting opioids on an as-needed basis; mixing over-the-counter, nonopioid analgesics; and using illicit drugs to avoid "harder medicines" (opioids). Many patients preferred nonopioid treatments for pain but invariably faced access barriers. Some described assuming stewardship of their prescribed opioids and felt that oncology clinicians are quick to prescribe opioids without providing workable alternatives.

CONCLUSIONS

Risks related to self-management of opioids among cancer outpatients, including potential overdose risks, need urgent attention. Interventions are needed for improving clinician-patient communication, patient education, safety, and access to effective nonopioid alternatives.

Both Race and Insurance Type Independently Predict the Selection of Oral Opioids Prescribed to Cancer Outpatients

BACKGROUND

Previous research suggests that racial disparities in patients' reported analgesic adverse effects are partially mediated by the type of opioid prescribed to African Americans despite the presence of certain comorbidities, such as renal disease.

AIMS

We aimed to identify independent predictors of the type of opioid prescribed to cancer outpatients and determine if race and chronic kidney disease independently predict prescription type, adjusting for relevant sociodemographic and clinical confounders.

DESIGN

We conducted a secondary analysis of a 3-month observational study.

SETTING

Outpatient oncology clinics of an academic medical center.

PARTICIPANTS/SUBJECTS

Patients were older than 18 years of age, self-identified as African American or White, and had an analgesic prescription for cancer pain.

METHODS

Cancer patients (N = 241) were recruited from outpatient oncology clinics within a large mid-Atlantic healthcare system.

RESULTS

Consistent with published literature, most patients (75.5%) were prescribed either morphine or oxycodone preparations as oral opioid therapy for cancer pain. When compared with Whites, African Americans were significantly more likely to be prescribed morphine (33% vs 14%) and less likely to be prescribed oxycodone (38% vs 64%) (p < .001). The estimated odds for African Americans to receive morphine were 2.573 times that for Whites (95% confidence interval 1.077-6.134) after controlling for insurance type, income, and pain levels. In addition, the presence of private health insurance was negatively associated with the prescription of morphine and positively associated with prescription of oxycodone in separate multivariable models. The presence of chronic kidney disease did not predict type of analgesic prescribed.

CONCLUSIONS

Both race and insurance type independently predict type of opioid selection for cancer outpatients. Larger clinical studies are needed to fully understand the sources and clinical consequences of racial differences in opioid selection for cancer pain.

Discontinuation of angiotensin-converting enzyme inhibitors or beta-blockers and the impact on heart failure hospitalization rates

BACKGROUND

Adherence to evidence-based therapy is essential for optimal management of heart failure. Yet, medication adherence is poor in heart failure patients. The Ascertaining Barriers to Compliance Project decomposed the medication adherence process into initiation, implementation, and discontinuation stages, but electronic monitoring-based adherence analyses usually do not consider this process.

AIMS

The aim of this study was to describe individual-patient patterns of medication adherence from electronic monitoring data among adults with chronic heart failure, adherence types, and risk factors for increased all-cause hospitalization including measures of poor adherence such as discontinuation.

METHODS

Data from two prospective studies of adherence measured with electronic monitoring for heart failure patients were combined and restricted to monitoring of angiotensin-converting enzyme inhibitors and beta-blockers over an initial three-month period. Hospitalizations were recorded for this period as well as for a three-month follow-up period. Analyses were conducted using adaptive modeling methods to identify individual-patient adherence patterns, adherence types, and risk factors for an increased hospitalization rate.

RESULTS

Using electronic monitoring data for 254 heart failure patients, four adherence types were identified: highly consistent, consistent but variable, moderately consistent, and poorly consistent. Sixteen individually significant risk factors for increased hospitalization rates were identified and used to generate a multiple risk factors model. Medication discontinuation was the most important individual risk factor and most important in the multiple risk factors model.

CONCLUSION

Discontinuation of angiotensin-converting enzyme inhibitors or beta-blockers increases hospitalization rates for heart failure patients. Interventions that effectively address this problem are urgently needed.

Patient Patterns and Perspectives on Using Opioid Regimens for Chronic Cancer Pain

CONTEXT

With increasing attention to the undertreatment of cancer pain in parallel with concerns about opioid misuse, little is known about how patients with advanced cancer adhere to opioid regimens for chronic cancer pain.

OBJECTIVES

We explored patient approaches to managing chronic cancer pain with long-acting opioids.

METHODS

In a multimethods study at an academic medical center, adult patients with chronic cancer pain (n = 17) used electronic pill caps to record adherence to prescribed long-acting opioid regimens. After eight weeks, patients viewed their adherence records and completed a semistructured interview about their opioid use. With a framework approach, we coded interview data (Kappa >0.95) and identified themes in how patients perceived and used opioids to manage cancer pain.

RESULTS

Patients (59% female; 94% non-Hispanic white; median age = 65 years) felt grateful about pain benefit from opioids yet concerned about opioid side effects and addiction/tolerance. Main reasons for nonadherence included both intentional decisions (e.g., skipping doses) and unintentional barriers (e.g., missing doses due to inconsistent sleep schedules). Overall, patients set their own opioid adherence goals and developed routines to achieve them. Residual pain varied and was not consistently linked with opioid adherence.

CONCLUSION

Patients commonly felt conflicted about using prescribed long-acting opioids to manage cancer pain due to concurrent perceptions of their risks and benefits, and they set their own parameters for opioid-taking practices. Intentional and unintentional deviations from prescribed opioid schedules highlight the need to enhance adherence communication, education, and counseling, to optimize the use of long-acting opioids as a component of cancer pain management.

Factors Related to Adherence to Opioids in Black Patients With Cancer Pain

CONTEXT

Cancer pain relief is often inadequate because of poor adherence to pain medication, especially for black patients.

OBJECTIVES

The purpose of this study is to describe factors related to adherence to around-the-clock opioids among 110 black patients being treated for cancer pain.

METHODS

Sociodemographic, clinical, symptoms, and social support data were collected at baseline; pain and adherence data were collected at 30 days. Associations between these variables and opioid adherence measured by Medication Event Monitoring System were estimated using multiple regression.

RESULTS

Mean age was 56 (±10.1), the majority were women (63%) and college educated (56%). Mean pain severity at baseline equaled 4.6 (±2.3). Mean dose adherence was 60% (±28.5), while mean schedule adherence was 33.0% (±31.0). In adjusted analysis, 26% of the variance in dose adherence was explained by recent chemotherapy, changes in pain, concerns about nausea, and doctors' focus on cure versus pain control (P<0.001); 27% of the variance in schedule adherence was explained by recent chemotherapy, changes in pain, symptom burden, and concerns about doctors focus on cure versus pain control (P<0.001).

CONCLUSION

Findings confirm pain medication adherence is poor and pain was not well relieved. Multiple factors influence adherence to around-the-clock opioids. Clinicians need to partner with patients by providing a personalized pain treatment plan including an in-depth assessment of treatment choices and adherence.

Tube feeding during treatment for head and neck cancer - Adherence and patient reported barriers

OBJECTIVES

The main aim was to investigate the incidence of patient adherence to nutritional tube feeding recommendations in patients with head and neck cancer and to determine patient barriers to meeting tube feeding prescription.

MATERIALS AND METHODS

This was an observational study from a randomised controlled trial in patients with head and neck cancer deemed at high nutritional risk with prophylactic gastrostomy (n=125). Patients were randomised to receive early tube feeding prior to treatment (intervention group) or standard care. All patients in the intervention and standard care groups then commenced clinical tube feeding as required during treatment. Patients maintained a daily record of gastrostomy intake, main nutrition impact symptom necessitating gastrostomy use, and reasons for not meeting nutrition prescription. Adherence was defined as meeting ≥75% of total prescribed intake.

RESULTS

Patients were predominantly male (89%), median age 60, with oropharyngeal tumours (78%), stage IV disease (87%) treated with chemoradiotherapy (87%). Primary reasons for gastrostomy use were poor appetite/dysgeusia (week 2-3) and odynophagia/mucositis (week 4-7). Early tube feeding adherence was 51%. Clinical tube feeding adherence was significantly higher in the intervention group (58% vs 38%, p=0.037). Key barriers to both phases of tube feeding were; nausea, early satiety and treatment factors (related to hospital healthcare processes).

CONCLUSIONS

Early tube feeding can improve patient adherence to clinically indicated tube feeding during treatment. Low adherence overall is a likely explanation for clinically significant weight loss despite intensive nutrition interventions. Optimising symptom management and strategies to overcome other barriers are key to improving adherence.

CLINICAL TRIAL REGISTRATION

This trial has been registered in the Australian New Zealand Clinical Trials registry as ACTRN12612000579897.

Self-management research of asthma and good drug use (SMARAGD study): a pilot trial

Background Community pharmacists play an important role in supporting patients for optimal drug use. Objective To assess the effectiveness of monitoring in asthma patients with inhaled corticosteroids (ICS) on disease control. Setting Asthma patients using ICS were invited from two intervention (IG) and two control pharmacies (CG). Method Participating patients completed questionnaires at the study start and at 6-month follow-up, including the Control of Allergic Rhinitis and Asthma Test (CARAT) questionnaire. IG patients completed the CARAT questionnaire every 2 weeks and received counselling on disease management, ICS adherence, and inhalation technique when scores were suboptimal, deteriorating, or absent. For Turbuhaler users, additional electronic monitoring (EMI) was available, with daily alerts for ICS intake. Main outcome measure As the primary outcome, CARAT scores at follow-up were compared between IG and CG using linear regression. As secondary outcome, refill adherence was compared using logistic regression. Results From March to July 2015, we enrolled 39 IG and 41 CG patients. At follow-up, CARAT scores did not differ between IG and CG (−0.19; 95% confidence interval [CI], −2.57 to 2.20), neither did patient numbers with ICS adherence >80% (0.82; 95% CI, 0.28–2.37). Among EMI users, CARAT scores did not differ, but ICS adherence >80% showed a 4.52-fold increase (95% CI, 1.56–13.1) compared with EMI nonusers. Conclusion Among community-dwelling asthma patients, pharmacist monitoring did not affect CARAT scores, but EMI use showed improved ICS refill adherence.

Incorporating nonlinearity into mediation analyses

Background

Mediation is an important issue considered in the behavioral, medical, and social sciences. It addresses situations where the effect of a predictor variable X on an outcome variable Y is explained to some extent by an intervening, mediator variable M. Methods for addressing mediation have been available for some time. While these methods continue to undergo refinement, the relationships underlying mediation are commonly treated as linear in the outcome Y, the predictor X, and the mediator M. These relationships, however, can be nonlinear. Methods are needed for assessing when mediation relationships can be treated as linear and for estimating them when they are nonlinear.

Methods

Existing adaptive regression methods based on fractional polynomials are extended here to address nonlinearity in mediation relationships, but assuming those relationships are monotonic as would be consistent with theories about directionality of such relationships.

Results

Example monotonic mediation analyses are provided assessing linear and monotonic mediation of the effect of family functioning (X) on a child’s adaptation (Y) to a chronic condition by the difficulty (M) for the family in managing the child's condition. Example moderated monotonic mediation and simulation analyses are also presented.

Conclusions

Adaptive methods provide an effective way to incorporate possibly nonlinear monotonicity into mediation relationships.

Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study

AIM

To identify unique clusters of patients based on their concerns in using analgesia for cancer pain and predictors of the cluster membership.

METHODS

This was a 3-mo prospective observational study (n = 207). Patients were included if they were adults (≥ 18 years), diagnosed with solid tumors or multiple myelomas, and had at least one prescription of around-the-clock pain medication for cancer or cancer-treatment-related pain. Patients were recruited from two outpatient medical oncology clinics within a large health system in Philadelphia. A choice-based conjoint (CBC) analysis experiment was used to elicit analgesic treatment preferences (utilities). Patients employed trade-offs based on five analgesic attributes (percent relief from analgesics, type of analgesic, type of side-effects, severity of side-effects, out of pocket cost). Patients were clustered based on CBC utilities using novel adaptive statistical methods. Multiple logistic regression was used to identify predictors of cluster membership.

RESULTS

The analyses found 4 unique clusters: Most patients made trade-offs based on the expectation of pain relief (cluster 1, 41%). For a subset, the main underlying concern was type of analgesic prescribed, i.e., opioid vs non-opioid (cluster 2, 11%) and type of analgesic side effects (cluster 4, 21%), respectively. About one in four made trade-offs based on multiple concerns simultaneously including pain relief, type of side effects, and severity of side effects (cluster 3, 28%). In multivariable analysis, to identify predictors of cluster membership, clinical and socioeconomic factors (education, health literacy, income, social support) rather than analgesic attitudes and beliefs were found important; only the belief, i.e., pain medications can mask changes in health or keep you from knowing what is going on in your body was found significant in predicting two of the four clusters [cluster 1 (-); cluster 4 (+)].

CONCLUSION

Most patients appear to be driven by a single salient concern in using analgesia for cancer pain. Addressing these concerns, perhaps through real time clinical assessments, may improve patients’ analgesic adherence patterns and cancer pain outcomes.