Chronic Pain: How Challenging Are DDIs in the Analgesic Treatment of Inpatients with Multiple Chronic Conditions?

Abstract

Background

Chronic pain is common in multimorbid patients. However, little is known about the implications of chronic pain and analgesic treatment on multimorbid patients. This study aimed to assess chronic pain therapy with regard to the interaction potential in a sample of inpatients with multiple chronic conditions.

Methods and Findings

We conducted a retrospective study with all multimorbid inpatients aged ≥18 years admitted to the Department of Internal Medicine of University Hospital Zurich in 2011 (n = 1,039 patients). Data were extracted from the electronic health records and reviewed. We identified 433 hospitalizations of patients with chronic pain and analyzed their combinations of chronic conditions (multimorbidity). We then classified all analgesic prescriptions according to the World Health Organization (WHO) analgesic ladder. Furthermore, we used a Swiss drug-drug interactions knowledge base to identify potential interactions between opioids and other drug classes, in particular coanalgesics and other concomitant drugs. Chronic pain was present in 38% of patients with multimorbidity. On average, patients with chronic pain were aged 65.7 years and had a mean number of 6.6 diagnoses. Hypertension was the most common chronic condition. Chronic back pain was the most common painful condition. Almost 90% of patients were exposed to polypharmacotherapy. Of the chronic pain patients, 71.1% received opioids for moderate to severe pain, 43.4% received coanalgesics. We identified 3,186 potential drug-drug interactions, with 17% classified between analgesics (without coanalgesics).

Conclusions

Analgesic drugs-related DDIs, in particular opioids, in multimorbid patients are often complex and difficult to assess by using DDI knowledge bases alone. Drug-multimorbidity interactions are not sufficiently investigated and understood. Today, the scientific literature is scarce for chronic pain in combination with multiple coexisting medical conditions and medication regimens. Our work may provide useful information to enable further investigations in multimorbidity research within the scope of potential interactions and chronic pain.

About the Authors:

Klarissa Siebenhuener

Affiliations Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland, Center of Competence Multimorbidity, University of Zurich, Zurich, Switzerland

Emmanuel Eschmann

Affiliation: Research Center for Medical Informatics, Directorate of Research and Education, University Hospital Zurich, Zurich, Switzerland

Alexander Kienast

Affiliation: Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland

Dominik Schneider

Affiliation: Maennedorf Hospital, Department of Internal Medicine, Canton Zurich, Switzerland

Christoph E. Minder

Affiliation: Horten Center, University Hospital Zurich, Zurich, Switzerland

Reinhard Saller

Affiliations Center of Competence Multimorbidity, University of Zurich, Zurich, Switzerland, Institute of Complementary and Integrative Medicine, University Hospital Zurich, Zurich, Switzerland

Lukas Zimmerli

Affiliations Center of Competence Multimorbidity, University of Zurich, Zurich, Switzerland, Cantonal Hospital, Internal Medicine, Olten, Switzerland

Jürg Blaser

Affiliation: Research Center for Medical Informatics, Directorate of Research and Education, University Hospital Zurich, Zurich, Switzerland

Edouard Battegay

Affiliations Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland, Center of Competence Multimorbidity, University of Zurich, Zurich, Switzerland, University Research Priority Program ‘Dynamics of Healthy Aging,’ University of Zurich, Zurich, Switzerland

Barbara M. Holzer

* E-mail: [email protected]

Affiliations Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland, Center of Competence Multimorbidity, University of Zurich, Zurich, Switzerland

ORCID http://orcid.org/0000-0001-6929-3145

Introduction

Pain is a medical condition listed among the most common diseases worldwide. The most common causes of chronic pain relate to musculoskeletal disorders [1]. Prevalence estimates for musculoskeletal pain in elderly patients vary widely, from 32.9% to 60% in Europe [2, 3]. Typically, many people with musculoskeletal pain are multimorbid and receive polypharmacotherapy [4, 5]. Previous, studies on multimorbidity have reported chronic pain diagnoses and treatments as an outcome of only secondary interest—for instance, as a medical condition co-occurring with somatic and mental health disorders [6–9]. Opioids are a mainstay of chronic pain treatment according to the World Health Organization (WHO) three-step analgesic ladder, which was developed in the mid-1980s as a scheme for patients with cancer pain [10]. Meanwhile, opioids have become increasingly popular as a treatment option for patients with chronic non-cancer pain [11, 12], and the range of applications of the WHO analgesic ladder has been extended accordingly.

The WHO scheme also introduced the term “adjuvant drugs”; originally, a small number of drugs (e.g., anxiolytics) was described as adjuvants, to enhance the analgesic “three-step” sequence from non-opioids, to weak opioids, and finally to strong opioids [13]. Later, the scope of these drugs was extended [14]. Key recommendations for adjuvant drugs, as described in the WHO analgesic ladder approach, were to treat adverse effects of analgesics (e.g., antiemetics or laxatives), to enhance pain relief (e.g., corticosteroids in spinal nerve compression), and to treat concomitant psychological comorbidities (e.g., psychotropic drugs).

Today, adjuvant or coanalgesic drugs have become established in the treatment of cancer pain and non-cancer pain. As a consequence, the broad range of alternative analgesic strategies increases the risk of polypharmacotherapy. From this perspective, chronic pain therapy in patients with multiple chronic conditions can be challenging [15]. Little is known, on the one hand, about the clinical impact of opioids and potential adverse drug-drug interactions (DDIs) in multimorbid patients [16], and, on the other hand, about the clinical impact of drug-disease interactions in combination with coanalgesics in patients with chronic pain and multimorbidity.

The primary aim of this study was to assess drugs used to treat pain in multimorbid patients at a tertiary teaching hospital. The secondary aim was to examine the potential of DDIs by using an electronic DDI knowledge base.

We undertook the following steps:

1. We explored the current literature on common chronic conditions and their potential to modify chronic pain.

2. We identified and characterized the target population from patients’ electronic medical chart reviews;

3. We examined and described analgesic prescriptions corresponding to the WHO analgesic pain ladder;

4. We examined and described coanalgesic and concomitant drugs of the target population;

5. We reviewed the potential for DDIs; and

Material and Methods

Data Collection

The University Hospital Zurich is a tertiary teaching hospital with 850 beds and about 38,000 inpatient admissions per year. We used a retrospective data set of all multimorbid inpatients admitted to the Department of Internal Medicine in 2011 (n = 1,139 hospitalizations). We included all adult inpatients discharged between January 1 and December 31, 2011, aged 18 years and older, and with more than one chronic medical condition. Patients in a methadone program, pregnant women, and palliative care patients were excluded. This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [17].

Data were extracted from the hospital’s electronic health records by the hospital’s Research Center for Medical Informatics. The following variables were extracted and transferred to a spreadsheet (Microsoft Excel® 2010, www.microsoft.com): date of admission, gender, age (years), length of hospital stay (days), all chronic pain diagnoses, all diagnoses of other chronic conditions, and all medications prescribed during hospitalization. Two physicians reviewed each case with regard to the inclusion and exclusion criteria and completed a list of diagnoses, using the patient’s care and discharge report. Patients were categorized as ‘with’ or ‘without’ a painful chronic condition. The diagnoses identified were marked as active if the painful condition required the prescription of analgesics during the patient’s hospital stay. In addition, all analgesic prescriptions were assessed in accordance with the WHO analgesic ladder approach [14]. All chronic conditions were transformed from the ICD-10 to ICPC-2 standard based on the list of chronic conditions provided by O’Halloran et al. [18]. Some ICPC-2 codes were grouped together—for example, the diagnosis of cancer (including solid malignant tumors of different types). All relevant patient charts were individually reviewed and completed by members of the research team. Unclear information about a patient record was reviewed by the study group and agreed on before coding. In a first step we looked at our patient population with regard to multimorbidity and the most frequent combinations of single diseases (triplets), including the drugs prescribed during their hospital stay. In a second step, we classified all prescribed analgesics according to the single steps of the WHO analgesic ladder.

Drug-drug interaction knowledge base.

Potential interactions between opioids, coanalgesics and other drug classes were identified using the Swiss drug-drug interaction knowledge base galdat/hospINDEX® (distributed by e-mediat AG, Berne, Switzerland; derived from ABDATA Pharma-Daten, Eschborn, Germany), The knowledge base is used at the University Hospital Zurich (at present hospINDEX 2016–05)[19]. This knowledge base categorizes DDIs by severity from level 1 (contraindicated) to level 6 (no action required), according to the ORCA criteria (operational classification of drug interactions, with a focus on clinically relevant interacting drug pairs) [20]. The treatment recommendations presented are collected from clinical practice guidelines, pharmaceutical drug information, or case reports, and they include country-specific information. The frequency of potential DDIs was calculated as the total number of overlapping drug orders identified as interacting according to the knowledge base. In detail, potential DDIs were described separately for opioid-related DDIs and for coanalgesic or concomitant drugs.

Definitions

Multimorbidity.

Multimorbidity was defined as the co-occurrence of two or more chronic medical conditions [21, 22]. Chronic conditions were defined following O’Halloran et al. [18], based on the International Classification of Primary Care, second edition (ICPC-2) disease classification system.

Chronic pain.

The International Association for the Study of Pain defined chronic pain as “pain that persists beyond the normal time of healing” [23]. We defined the persistence of pain for more than three months as chronic. We defined DDIs as a modification of the effect of a drug or as an adverse effect resulting from concomitant administration of one or more other drugs. We refer to potential DDIs only, as actual adverse drug events were not considered in this study. Drug-disease interactions were defined as a modification in the endogenous regulatory system, either in an already pathologically altered or in a hitherto unaffected regulatory system.

Adjuvants/coanalgesics.

The terms ‘adjuvant drugs,’ ‘adjuvants,’ ‘adjuvant analgesics’ [24–26], ‘coanalgesics,’ or ‘concomitant medication’ in persistent opioid use [27, 28] have been used simultaneously and interchangeably over the past two decades. To date, there is still no consensus in the literature on how to classify the growing number of such agents [29]. Criteria for a meaningful classification have been recommended by Lussier et al. [30]; however, these are applied mainly in the context of cancer pain: adjuvant analgesics were defined as drugs with a primary indication other than pain but having analgesic properties in some painful conditions. From this perspective, adjuvants are potentially beneficial as analgesics, and as a result, the categorization is based on how they are used in clinical practice. Coanalgesics have since become established for the treatment of cancer pain as well as non-cancer pain.

Chronic Pain Treatment and the WHO Analgesic Ladder

Patients’ pain medications were specified by trade name, using the Anatomical Therapeutic Chemical Classification System code; the duration (in days) of the prescription was also determined. Analgesic prescriptions were assigned to the steps of the WHO analgesic ladder [14]: non-opioid analgesics (step I), weak opioids (step II), and strong opioids (step III). This classification of analgesics is conventionally based on their activity at opioid receptors as either non-opioid or opioid. To characterize all relevant groups with an analgesic effect we used three terms to distinguish between these groups: (1) analgesics–drugs for pain relief based on the WHO analgesic ladder (non-opioids, weak and strong opioids) ‒ i.e., paracetamol (acetaminophen) as a non-opioid; (2) coanalgesics–drugs that are distinctly prescribed in the specific context of pain relief; i.e., pregabalin approved for the treatment of neuropathic pain; and (3) concomitant medication–concurrent use of any drugs that are given in the context of multimorbidity. In some cases nevertheless they may have a modifying effect on pain ‒ i.e., antidepressants for coexisting depression.

Data Management and Statistical Analysis

For the statistical analyses, we used Stata® statistical software (Version 13, Stata Corporation, College Station, TX; www.stata.com). Continuous data were presented as means with standard deviations, categorical data as counts and proportions. We used t-tests to compare continuous data and chi square tests to compare categorical data. The significance level was set at 0.05.

Ethics Approval

Ethics approval for this study was obtained from the Research Ethics Committee of the Canton of Zurich, KEK-ZH-No. 2012–0237, which waived the requirement for obtaining informed consent for this retrospective review of electronic medical records. All patient records and information were anonymized and de-identified before the analysis.

Results

Study Population and Diagnoses

The prevalence of chronic pain found among the 1039 multimorbid inpatients was 38% (n = 393). On average, these patients were 66 years old, with no significant difference in age between multimorbid patients with and without chronic pain (p = 0.318; Table 1). Multimorbid patients with chronic pain (CP) had significantly more chronic diagnoses (with a mean of 6.6 chronic diagnoses, with 4.4 different organ systems involved) compared with multimorbid patients without chronic pain (mean of 5.0 conditions and 3.1 organ systems involved) (p < 0.00005). Moreover, patients with CP had significantly longer hospital stays than multimorbid patients without CP (15.5 vs. 12.5 days, p = 0.0007).

[Figure omitted. See PDF.]

Table 1. Sociodemographic characteristics of the study population (n = 1039): Comparison of multimorbid patients with and without chronic pain in a population of inpatients in a department of internal medicine in a tertiary care hospital.

https://doi.org/10.1371/journal.pone.0168987.t001

Hypertension, chronic kidney disease, and diabetes were the most frequent single chronic conditions in both groups, with prevalence estimates for the group with CP of 58.7% for hypertension, 29.1% for chronic kidney disease, and 23.1% for diabetes (data not shown). When only patients with chronic pain diagnoses were considered (Table 2), the most common triple combination was hypertension, chronic back pain, and chronic kidney disease (Table 3). Further, 15.3% of the patients with CP had depressive disorders, which is almost twice as many as the multimorbid patients without CP who had depressive disorders (p < 0.00005). Logistic regression showed that this difference in the prevalence of depression was not explained by either different numbers of chronic conditions or differences in the duration of hospitalization. After adjustment, the difference in the probability of depression between pain and non-pain patients remained significant (p = 0.008).

[Figure omitted. See PDF.]

Table 2. Top 10 chronic pain conditions/chronic conditions associated with chronic pain respectively in a population of inpatients at a department of internal medicine in a tertiary care hospital (n = 433 hospitalizations).

Multiple counts were allowed.

https://doi.org/10.1371/journal.pone.0168987.t002

[Figure omitted. See PDF.]

Table 3. The most common triplets of chronic conditions including chronic pain diagnoses in a population of inpatients at a tertiary department of internal medicine (n = 433 hospitalizations).

https://doi.org/10.1371/journal.pone.0168987.t003

Of all patients with CP, 60% had one, 27% had two, and 13% had three or more pain diagnoses, respectively. The most common chronic pain diagnosis was chronic back pain (38.6%; Table 2), followed by chronic pain diagnoses, such as osteoarthrosis (17.6%), and painful conditions subsequent to cancer (16.6%). Of the 10 most frequent pain diagnoses, seven were related to chronic musculoskeletal diseases.

Pain Treatment and WHO Analgesic Ladder

The most frequent mode of prescription in terms of assignment to the WHO analgesic ladder was a combination of step I analgesics (non-opioids) with step III analgesics (strong opioids) in 35% of all CP hospitalizations with no step II analgesics (weak opioids). The second most frequent mode was a prescription of step I analgesics only (29%), followed by (third) concurrent prescription of all three steps (19%). Step I analgesics were prescribed to 98.6% of all inpatients with CP, with paracetamol (acetaminophen) or metamizole (novaminsulfone) the most often prescribed (Table 4). In total, 71.1% of these CP patients received opioids, in different combinations, for moderate to severe pain. The most frequent combination with a longer (more than a day) simultaneous prescription of weak and strong opioids was tramadol and morphine. All of these 58 prescriptions were additionally complemented with step I analgesics. In 21 of these 58 simultaneous opioid medications, an upward change took place (stronger medications were required over time), and consequently only strong opioids were prescribed.

[Figure omitted. See PDF.]

Table 4. Drug prescriptions in multimorbid patients with chronic pain corresponding to the classification by the WHO analgesic ladder.

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Coanalgesic and Concomitant Drugs

Overall, 43.4% (188) of all patients with chronic pain received drugs prescribed as coanalgesics. In addition, quite a number of these patients received drugs that were not primarily prescribed as analgesics but that have analgesic properties in some painful conditions (concomitant drugs) (Table 5).

[Figure omitted. See PDF.]

Table 5. Classification of coanalgesics and concomitant drugs.

https://doi.org/10.1371/journal.pone.0168987.t005

Antidepressants were assigned to both categories (coanalgesic and concomitant drugs). Potentially, antidepressants could be considered for the treatment of chronic pain and for the treatment of depressive disorders (66 cases). Alpha-2 adrenergic agonists, antidepressants, and corticosteroids have been categorized as multipurpose analgesics (multipurpose drugs have a various range of indications). Almost all patients received laxatives and antiemetic drugs. Most laxative agents were those that predominantly soften the stool (liquid paraffin). In addition to prokinetic agents/anti-emetics (domperidone and metoclopramide), other drugs ‒for example, corticosteroids ‒may enhance an antiemetic strategy. Pregabalin has been identified as a coanalgesic in the management of neuropathic pain (32 cases). All other antiepileptic drugs should be considered in patients with epilepsy or pain relief.

Drug-Drug Interactions

With an average mean of 10.4 medications (SD = 4.9) prescribed per inpatient hospitalization with chronic pain, the amount of polypharmacotherapy (five or more drugs) was high, at 89% of all cases. We identified 3,186 potential DDIs (overlapping drug orders of drug pairs listed as interacting in the drug-drug interaction knowledge base), with 551 (17%) potential interactions between analgesics (without coanalgesics); 175 (5.5%) were with opioids. None of the interactions were classified as severity level 1 interactions (“contraindicated”). The DDIs knowledge base classified most potential interactions with opioids in our inpatients as severity level 3 (“monitoring or adaption required”); the only exception were the DDIs between buprenorphine and opioid agonists, as severity level 2 (“contraindicated as a precaution”) (Table 6). In a later version of this DDIs knowledge base, hospINDEX (2016–05), the interaction with buprenorphine is classified as severity level 3.

[Figure omitted. See PDF.]

Table 6. Potential opioid related drug-drug interactions (DDIs) in multimorbid patients with chronic pain (n = 433), identified by using the galdat/hospINDEX® database.

Multiple counts were allowed.

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Table 7 shows an overview of DDIs between analgesics, coanalgesics, concomitant drugs, and other drugs (e.g., antihypertensive drugs) prescribed to the study population of multimorbid inpatients with CP. All potential DDIs listed here were identified in the data set accordingly. This table is based on the recommendations in the drug-drug interactions knowledge base used in this study (galdat/hospINDEX®).

[Figure omitted. See PDF.]

Table 7. Overview of the relevant drug interaction potential of analgesics (categorized into analgesics, coanalgesics, and concomitant drugs), identified by galdat/hospINDEX® database in the sample of chronic pain patients (n = 433).

Antidepressants are included here as coanalgesics.

https://doi.org/10.1371/journal.pone.0168987.t007

Discussion

This study provides a general overview of the most common chronic pain diagnoses and combinations of chronic diseases (triplets) and the prescribed medications, respectively, in the multimorbid population under study. We discuss possible consequences of these data in regard to the impact of pain treatment on different multiple disease combinations found and vice versa. Furthermore, we discuss potential DDIs related to pain treatment with a focus on opioids and some selected coanalgesic or concomitant drugs.

In our study, 38% of all multimorbid inpatients had chronic pain. On average, these CP patients were 65.7 years old, had 6.6 chronic diagnoses, and were exposed to a high degree of polypharmacotherapy (10.4 drugs). The most common chronic pain diagnoses were musculoskeletal diseases (see Table 2). The most common triple disease combination was hypertension, chronic kidney disease, and chronic back pain (see Table 3). Opioids were prescribed in more than two thirds of CP patients for moderate to severe pain. Coanalgesic drugs were prescribed for 43% of these patients. The DDIs knowledge base classified most DDIs for these multimorbid patients with CP as severity level 3 (“monitoring or adaption required”).

According to the WHO analgesic ladder, non-opioids should be combined with opioids, but opioids should not necessarily be combined with other opioids. Some experts [32, 33] have recommended omitting the intermediate step of weak opioids completely and using low doses of strong opioids in combination with non-opioid analgesics instead. They argue in favor of this adaptation (a modified two-step approach) of the original WHO analgesic ladder mainly on the basis that it would establish more effective and simple pain therapy, in particular for patients with cancer. Omitting step II medication is likely to permit using only one single (strong) opioid, with modification in doses, and titration according to the patient’s individual pain level. In general, the use of opioids in combination with other opioids seems to be largely based on empirical evidence and depends on the physician’s clinical experience [34]. Furthermore, new formulations of analgesics have been developed in the past 10 years—for example, to prevent the most common side effect of opioid-induced constipation. Meanwhile, the co-administration of oral naloxone together with oxycodone (prolonged release) is a well-known regimen [35].

Tramadol in combination with other analgesics (in total 147 cases with tramadol prescriptions) was one of the most frequently prescribed analgesics. Tramadol has a specific dual mode of action relating to its affinities to the opioid receptors (modest affinity with μ-receptor, weak affinity to δ and κ) and/or the inhibition of the uptake of noradrenaline and serotonin [36]. Accordingly, tramadol may cause less constipation and respiratory depression than other strong opioids (e.g., morphine) and might therefore be an alternative choice in patients with multiple chronic conditions before more potent opioid analgesics are used. Tramadol can be especially useful in older patients who do not tolerate more potent opioids [37].

The common use of NSAIDs has been identified as critical, especially in terms of adverse drug events in elderly patients [38, 39]. NSAIDs pose three major risks: they may interfere with blood pressure control, aggravate renal impairment, or cause gastrointestinal bleeding. In this study, NSAIDs were found to be rarely used (only in 16%), probably to avoid such well-known interactions. In our study population chronic kidney disease was a common chronic condition, 29.1%. This may have been another reason for the low prescription rate of NSAIDs. At different stages of chronic kidney disease some opioids should be used with caution (risk of accumulation) possibly at reduced and less frequent doses [40]. However, buprenorphine seems to be a safe choice in patients with chronic kidney disease [40].

To date, the potential interaction risk of metamizole has not been sufficiently addressed in research [41]. The same is true for the impact of paracetamol on diagnosed hypertension [42]. But there is some evidence that paracetamol may lessen the effect of antihypertensive drugs [43]. By contrast, corticosteroids can have a particular impact in combination with diabetes, osteoporosis, and hypertension (e.g. increased blood pressure). Aggravations of diabetes mellitus, as a result of corticosteroid intake as an additional risk factor for osteoporosis are well-documented. Moreover, administering high doses of corticosteroids may trigger neuropsychiatric reactions [44], which may lead to an interaction with a coexisting mental health problem (e.g. psychosis caused by steroids).

In our study, 17% of total potential DDIs were identified as DDIs with analgesic prescriptions by galdat/hospINDEX®. In particular, this knowledge base put the main focus on drugs involved in the opioid-cytochrome P450 isoenzymes metabolism and multiple drug transporters (e.g., P-glycoprotein). These well-known DDIs are classified as inhibitors, inducers, or substrate accordingly (see Table 6; drugs as inducers/inhibitors). Some specific properties have to be noted here, in addition to the recommendation of this knowledge base, such as the fact that St. John’s Wort (SJW) preparations vary greatly and have different effects on CYP3A4 induction or in the drug transporter systems. SJW medicinal products with hyperforin-low Hypericum perforatum extracts are usually not considered to be of clinical relevance as inducers [45, 46]. A clinical pharmacokinetic study showed that treatment with rich-hyperforin SJW extracts decreases the plasma concentration of oxycodone [47].

For most clinical interactions with opioids identified in our study, galdat/hospINDEX® resulted in the following advice: “monitoring or adaptation required” (severity level 3). Still, for the use of the knowledge base a daily review of current medications is recommended (e.g., correct applications of drugs and dosing), as well as an individual risk assessment to enhance patient safety. However, the risk of interactions and adverse events may increase with every additional medical condition and every additional drug prescribed (polypharmacotherapy) [48, 49]. Table 5 (overview of coanalgesic and concomitant drugs), shows that concomitant drugs (laxatives, prokinetic/anti-emetics or neuroleptics) contribute to a high amount of polypharmacotherapy in this study. Potential DDIs are typically analyzed as drug-drug interaction pairs. For multimorbid patients with multiple drug and disease combinations, the analyses of two-way drug combinations are certainly not sufficient (see Table 7 for an overview of drug-drug interactions related to opioid prescriptions). For example, antidepressants (concomitant or even coanalgesic drugs) can imply an additive interaction risk, as these drugs, identified as having the most frequent DDIs with opioids in this study, have the potential for numerous drug interactions [50]. Mental disorders, such as depression, are common comorbid conditions in multimorbid patients. It is well known that the prevalence of depression doubles in patients with pain [51]. SSRIs (selective serotonin reuptake inhibitors) might interfere to various degrees with opioids but also with oral anticoagulation drugs (atrial fibrillation had a prevalence of 16.2% in this study) or even NSAIDs, resulting in a cumulative risk for adverse events [52].

Pain management is usually multimodal and in the first instance aims at reducing pain sufficiently and quickly. Beyond the desired effects of opioids, exogenous opioids can affect a number of the body’s own regulation systems, especially cardiac and vascular regulation [53].

Table 3 shows the most common chronic pain diagnoses and triplets of chronic conditions in our multimorbid inpatients. Musculoskeletal pain is not only a common chronic condition in elderly patients in primary care [54] but also an important coexisting condition in medical inpatients with multimorbidity, as shown by our study results. Overall, hypertension was the most common condition (57.7%). This was also reported, for multimorbid patients, with similar prevalence estimates, in a study of the most common disease combinations [55]. Other relationships may exist between hypertension and pain perception. Some studies suggest that chronic pain-related opioid changes (e.g., opioid receptor downregulation) such as hypoalgesia (i.e., decreased sensitivity to pain) are associated with elevated resting blood pressure [56]. These findings raise questions about potential modifying effects of opioids on pain sensitivity in patients with untreated hypertension or insufficiently lowered blood pressure. Similar considerations apply to other common disease combinations in multimorbid patients with CP, such as the treatment of diabetes mellitus (23.1% in this study) and its effect on chronic neuropathic pain. Endogenous opioids also have a role in the regulation of blood glucose and hyperinsulinemia [57], and it is conceivable that exogenous opioids, such as morphine, may affect this regulation.

Implications for Research

Intensified research is needed on relevant interactions in clinical practice (e.g. pragmatic trials), which simultaneously includes multimorbid patients with polypharmacotherapy receiving analgesics, coanalgesics, and a substantial number of concomitant drugs. Research of this kind is scarce, and precise data on the interplay of interactions and polypharmacotherapy (on all sorts of modifying effects) are lacking. Furthermore, it is unclear how the interaction potential changes in the case of polypharmacotherapy and a reduction of drugs (deprescribing) [58]. A great need for research exists in this setting (e.g., increasing or decreasing drug dosages and omitting drugs or adding additional drugs, respectively). Reliable knowledge bases should be enlarged (interface options) with patient-specific static information (e.g., demographics, concurrent diseases) and dynamic information (e.g., lab results, vital signs), as well as relevant pharmacodynamic and pharmacokinetic aspects of co-medication and the time course of therapy (start, end, maintenance treatment) [59].

The implementation of a comprehensive tool for the assessment of potential DDIs and drug-disease interactions in multimorbidity, with a multimorbidity score to estimate the severity of potential interactions, is probably essential for well-structured, evidence-based clinical decision making. More research is needed to gain insights into harmful and beneficial effects of various interactions. In the context of this study, future research could shed light on the (positive and negative) effects of pain management on the body’s regulation systems—for example, in terms of possible drug-endogenous opioid activity interactions (e.g., exogenous opioids as possible ligands of the endogenous opioidergic regulation systems). Critically, the present findings indicate that multimorbidity is insufficiently well-managed by exclusively considering and treating the individual diseases of a patient with multiple chronic conditions. The potential interactions (DDIs, drug-multimorbidity interactions) have yet to be investigated.

Our study provides the basis for a deeper understanding of important interaction potential of patients with chronic pain. As a next step, frequent disease- and drug-combinations in multimorbidity should be investigated in pragmatic clinical trials.

Limitations

Our study has several limitations. First, we examined a highly specific study population at a tertiary hospital. Our results are based on a retrospective medical chart review; with potential underreporting. Second, owing to the retrospective study design, chronic pain diagnoses had to be taken from medical health records without accompanying self-reports from patients—for example, by using the Visual Analog Scale for Pain [60, 61]. Third, we used the galdat/hospINDEX® knowledge base with country-specific information to identify potential DDIs. Fourth, we analyzed analgesic prescriptions and not medication intake. The interactions with opioids reported in this study will therefore have to be interpreted as potential medical conflicts and not as actual adverse events. A particular strength of our study was the use of detailed electronic health records for each patient, to review and complete the clinical administrative data.

Conclusions

Our study explored retrospective data of multimorbid patients with chronic pain at a tertiary teaching hospital. To our knowledge this is the first study examining complex treatment situations in multimorbid patients with chronic pain. The following conclusions can be drawn:

Analgesics and analgesia-related drugs are often prescribed in combination with a large variety of other drugs, accompanied by a great potential of risks for multimorbid patients. Analgesic-related DDIs, in particular opioids, in multimorbid patients are often complex and difficult to assess by using DDI knowledge bases alone. Drug-multimorbidity interactions are not sufficiently investigated and understood. Currently, the scientific literature is scarce for chronic pain in combination with multiple coexisting medical conditions and medication regimens. Our work may provide useful information to enable further investigations in multimorbidity research within the scope of potential interactions and chronic pain.

Acknowledgments

We thank Marcus Cheetham for comments on a previous version of this paper. We further thank Ellen Russon for editorial assistance with the manuscript.

Author Contributions

1. Conceptualization: BMH CEM EE KS RS LZ EB JB DS.

2. Data curation: EE JB.

3. Formal analysis: BMH CEM EE KS.

4. Funding acquisition: EB LZ.

5. Investigation: BMH CEM EE RS KS AK DS.

6. Methodology: BMH CEM EE RS KS DS.

7. Project administration: BMH KS.

8. Resources: BMH CEM EE RS KS AK DS.

9. Software: BMH CEM.

10. Supervision: DS JB LZ EB.

11. Validation: DS LZ.

12. Visualization: KS BMH RS EE CEM.

13. Writing – original draft: KS BMH RS EE CEM.

14. Writing – review & editing: DS JB LZ EB BMH CEM EE KS RS AK.

Citation: Siebenhuener K, Eschmann E, Kienast A, Schneider D, Minder CE, Saller R, et al. (2017) Chronic Pain: How Challenging Are DDIs in the Analgesic Treatment of Inpatients with Multiple Chronic Conditions? PLoS ONE 12(1): e0168987. https://doi.org/10.1371/journal.pone.0168987

References

1. Muller-Schwefe GH. European survey of chronic pain patients: results for Germany. Curr Med Res Opin. 2011;27(11):2099–106. Epub 2011/09/22. pmid:21933101

2. Brochet B, Michel P, Barberger-Gateau P, Dartigues JF. Population-based study of pain in elderly people: a descriptive survey. Age and Ageing. 1998;27(3):279–84.

3. Grimby C, Fastbom J, Forsell Y, Thorslund M, Claesson CB, Winblad B. Musculoskeletal pain and analgesic therapy in a very old population. Arch Gerontol Geriatr. 1999;29(1):29–43. pmid:15374075

4. Payne RA, Avery AJ, Duerden M, Saunders CL, Simpson CR, Abel GA. Prevalence of polypharmacy in a Scottish primary care population. Eur J Clin Pharmacol. 2014;70(5):575–81. pmid:24487416

5. Schafer I. Does multimorbidity influence the occurrence rates of chronic conditions? A claims data based comparison of expected and observed prevalence rates. PLoS One. 2012;7(9):e45390. PubMed Central PMCID: PMCPMC3444489. pmid:23028979

6. van den Bussche H, Schon G, Kolonko T, Hansen H, Wegscheider K, Glaeske G, et al. Patterns of ambulatory medical care utilization in elderly patients with special reference to chronic diseases and multimorbidity—results from a claims data based observational study in Germany. BMC Geriatr. 2011;11(1):54. PubMed Central PMCID: PMCPMC3180370.

7. Gunn JM, Ayton DR, Densley K, Pallant JF, Chondros P, Herrman HE, et al. The association between chronic illness, multimorbidity and depressive symptoms in an Australian primary care cohort. Soc Psychiatry Psychiatr Epidemiol. 2012. Epub 2010/12/25.

8. van Oostrom SH, Picavet HS, van Gelder BM, Lemmens LC, Hoeymans N, van Dijk CE, et al. Multimorbidity and comorbidity in the Dutch population—data from general practices. BMC Public Health. 2012;12(1):715. PubMed Central PMCID: PMCPMC3490727.

9. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380(9836):37–43. Epub 2012/05/15. pmid:22579043

10. World Health Organization. Cancer Pain Relief Geneva:World Health Organization. 1986.

11. Chou R, Fanciullo GJ, Fine PG, Adler JA, Ballantyne JC, Davies P, et al. Clinical guidelines for the use of chronic opioid therapy in chronic noncancer pain. J Pain. 2009;10(2):113–30. PubMed Central PMCID: PMCPMC4043401. pmid:19187889

12. Pergolizzi J, Boger RH, Budd K, Dahan A, Erdine S, Hans G, et al. Opioids and the management of chronic severe pain in the elderly: consensus statement of an International Expert Panel with focus on the six clinically most often used World Health Organization Step III opioids (buprenorphine, fentanyl, hydromorphone, methadone, morphine, oxycodone). Pain Pract. 2008;8(4):287–313. Epub 2008/05/28. pmid:18503626

13. Ventafridda V, Tamburini M, Caraceni A, De Conno F, Naldi F. A validation study of the WHO method for cancer pain relief. Cancer. 1987;59(4):850–6. Epub 1987/02/15. pmid:3802043

14. World Health Organization. Cancer pain relief, with a guide to opioid availability. Geneva: WHO. 1996.:2nd edition.

15. Smith H, Bruckenthal P. Implications of opioid analgesia for medically complicated patients. Drugs Aging. 2010;27(5):417–33. pmid:20450239

16. Overholser BR, Foster DR. Opioid pharmacokinetic drug-drug interactions. Am J Manag Care. 2011;17 Suppl 11:S276–87.

17. Vandenbroucke JP, von Elm E, Altman DG, Gotzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Epidemiology. 2007;18(6):805–35. Epub 2007/12/01. pmid:18049195

18. O'Halloran J, Miller GC, Britt H. Defining chronic conditions for primary care with ICPC-2. Fam Pract. 2004;21(4):381–6. Epub 2004/07/14. pmid:15249526

19. galdat/hospINDEX® distributed by e-mediat AG Berne Switzerland. derived from ABDATA Pharma-Daten-Service, Werbe- und Vertriebsgesellschaft Deutscher Apotheker, Eschborn, Germany.

20. Hansten PD, Horn JR, Hazlet TK. ORCA: OpeRational ClassificAtion of drug interactions. Journal of the American Pharmaceutical Association. 2001;41(2):161–5. pmid:11297327

21. Boyd CM, Fortin M. Future of Multimordibity Research: How should Understandung of Multimorbidity Inform Health System Design? Public Health Reviews. 2010;32(2):451–74.

22. van den Akker M, Buntinx F, Metsemakers JF, Roos S, Knottnerus JA. Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases. J Clin Epidemiol. 1998;51(5):367–75. Epub 1998/06/10. pmid:9619963

23. IASP. Classification of chronic pain. Descriptions of chronic pain snydromes and definitions of pain terms. Pain Suppl. 1986;3(S1–226). pmid:3461421

24. Russo CM, Brose WG. Chronic pain. Annu Rev Med. 1998;49:123–33. Epub 1998/03/24. pmid:9509254

25. Samer CF, Desmeules JA, Dayer P. Individualizing analgesic prescription. Part II: pharmacogenetics of anti-inflammatory analgesics and co-analgesics. Personaflzed Medicine. 2006;3(3):271–97.

26. Bair MJ, Sanderson TR. Coanalgesics for chronic pain therapy: a narrative review. Postgrad Med. 2011;123(6):140–50. Epub 2011/11/23. pmid:22104463

27. Mitra R, Jones S. Adjuvant analgesics in cancer pain: a review. Am J Hosp Palliat Care. 2012;29(1):70–9. Epub 2011/06/30. pmid:21712306

28. Mellbye A, Svendsen K, Borchgrevink PC, Skurtveit S, Fredheim OM. Concomitant medication among persistent opioid users with chronic non-malignant pain. Acta Anaesthesiol Scand. 2012;56(10):1267–76. pmid:22946822

29. Portenoy RK, Ahmed E, Keilson YY. Cancer pain management: Adjuvant analgesics (coanalgesics). In: UpToDate. (Accessed on April 25, 2016.).

30. Lussier D, Huskey AG, Portenoy RK. Adjuvant analgesics in cancer pain management. The oncologist. 2004;9(5):571–91. Epub 2004/10/13. pmid:15477643

31. Frechen S, Zoeller A, Ruberg K, Voltz R, Gaertner J. Drug interactions in dying patients: a retrospective analysis of hospice inpatients in Germany. Drug Saf. 2012;35(9):745–58. pmid:22809376

32. Maltoni M, Scarpi E, Modonesi C, Passardi A, Calpona S, Turriziani A, et al. A validation study of the WHO analgesic ladder: a two-step vs three-step strategy. Support Care Cancer. 2005;13(11):888–94. Epub 2005/04/09. pmid:15818486

33. Eisenberg A, Shifrin A. Reassessing the Need for Step 2 of the WHO Analgesic Ladder. Journal of Pain & Palliative Care Pharmacotherapy. 2011;25:288–90.

34. Davis MP, Walsh D, Lagman R, LeGrand SB. Controversies in pharmacotherapy of pain management. The lancet oncology. 2005;6(9):696–704. pmid:16129370

35. Burness CB, Keating GM. Oxycodone/Naloxone prolonged-release: a review of its use in the management of chronic pain while counteracting opioid-induced constipation. Drugs. 2014;74(3):353–75. pmid:24452879

36. Grond S, Sablotzki A. Clinical pharmacology of tramadol. Clinical pharmacokinetics. 2004;43(13):879–923. pmid:15509185

37. Fitzcharles MA, Lussier D, Shir Y. Management of chronic arthritis pain in the elderly. Drugs Aging. 2010;27(6):471–90. pmid:20524707

38. Vandraas KF, Spigset O, Mahic M, Slordal L. Non-steroidal anti-inflammatory drugs: use and co-treatment with potentially interacting medications in the elderly. Eur J Clin Pharmacol. 2010;66(8):823–9. Epub 2010/04/21. pmid:20405110

39. Guthrie B, McCowan C, Davey P, Simpson CR, Dreischulte T, Barnett K. High risk prescribing in primary care patients particularly vulnerable to adverse drug events: cross sectional population database analysis in Scottish general practice. BMJ. 2011;342:d3514. pmid:21693525

40. Ripamonti CI, Santini D, Maranzano E, Berti M, Roila F, Group EGW. Management of cancer pain: ESMO Clinical Practice Guidelines. Ann Oncol. 2012;23 Suppl 7:vii139–54.

41. Gosch M. [Analgesics in geriatric patients. Adverse side effects and interactions]. Z Gerontol Geriatr. 2015;48(5):483–92; quiz 93. pmid:26152872

42. Turtle EJ, Dear JW, Webb DJ. A systematic review of the effect of paracetamol on blood pressure in hypertensive and non-hypertensive subjects. Br J Clin Pharmacol. 2013;75(6):1396–405. PubMed Central PMCID: PMCPMC3690099. pmid:23145789

43. Gualtierotti R, Zoppi A, Mugellini A, Derosa G, D'Angelo A, Fogari R. Effect of naproxen and acetaminophen on blood pressure lowering by ramipril, valsartan and aliskiren in hypertensive patients. Expert Opin Pharmacother. 2013;14(14):1875–84. pmid:23883161

44. Dubovsky AN, Arvikar S, Stern TA, Axelrod L. The neuropsychiatric complications of glucocorticoid use: steroid psychosis revisited. Psychosomatics. 2012;53(2):103–15. pmid:22424158

45. Mueller SC, Majcher-Peszynska J, Mundkowski RG, Uehleke B, Klammt S, Sievers H, et al. No clinically relevant CYP3A induction after St. John's wort with low hyperforin content in healthy volunteers. Eur J Clin Pharmacol. 2009;65(1):81–7. pmid:18762932

46. Russo E, Scicchitano F, Whalley BJ, Mazzitello C, Ciriaco M, Esposito S, et al. Hypericum perforatum: pharmacokinetic, mechanism of action, tolerability, and clinical drug-drug interactions. Phytother Res. 2014;28(5):643–55. Epub 2013/07/31. pmid:23897801

47. Nieminen TH, Hagelberg NM, Saari TI, Neuvonen M, Laine K, Neuvonen PJ, et al. St John's wort greatly reduces the concentrations of oral oxycodone. Eur J Pain. 2010;14(8):854–9. pmid:20106684

48. Nobili A, Pasina L, Tettamanti M, Lucca U, Riva E, Marzona I, et al. Potentially severe drug interactions in elderly outpatients: results of an observational study of an administrative prescription database. Journal of clinical pharmacy and therapeutics. 2009;34(4):377–86. pmid:19583670

49. Guthrie B, Makubate B, Hernandez-Santiago V, Dreischulte T. The rising tide of polypharmacy and drug-drug interactions: population database analysis 1995–2010. BMC Med. 2015;13:74. PubMed Central PMCID: PMCPMC4417329. pmid:25889849

50. Nieuwstraten C, Labiris NR, Holbrook A. Systematic overview of drug interactions with antidepressant medications. Can J Psychiatry. 2006;51(5):300–16. pmid:16986820

51. Guthrie B, Payne K, Alderson P, McMurdo ME, Mercer SW. Adapting clinical guidelines to take account of multimorbidity. BMJ. 2012;345:e6341. pmid:23036829

52. Jiang HY, Chen HZ, Hu XJ, Yu ZH, Yang W, Deng M, et al. Use of selective serotonin reuptake inhibitors and risk of upper gastrointestinal bleeding: a systematic review and meta-analysis. Clin Gastroenterol Hepatol. 2015;13(1):42–50 e3. Epub 2014/07/06. pmid:24993365

53. Feuerstein G, Siren AL. The opioid system in cardiac and vascular regulation of normal and hypertensive states. Circulation. 1987;75(1 Pt 2):I125–9.

54. Scherer M, Hansen H, Gensichen J, Mergenthal K, Riedel-Heller S, Weyerer S, et al. Association between multimorbidity patterns and chronic pain in elderly primary care patients: a cross-sectional observational study. BMC Fam Pract. 2016;17(1):68. PubMed Central PMCID: PMCPMC4895952.

55. Violan C, Foguet-Boreu Q, Hermosilla-Perez E, Valderas JM, Bolibar B, Fabregas-Escurriola M, et al. Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity. BMC Public Health. 2013;13:251. PubMed Central PMCID: PMCPMC3659017. pmid:23517342

56. Bruehl S, Burns JW, Chung OY, Magid E, Chont M, Gilliam W, et al. Hypoalgesia associated with elevated resting blood pressure: evidence for endogenous opioid involvement. J Behav Med. 2010;33(2):168–76. PubMed Central PMCID: PMCPMC2844461. pmid:20039197

57. Guido M, Romualdi D, Lanzone A. Role of opioid antagonists in the treatment of women with glucoregulation abnormalities. Curr Pharm Des. 2006;12(8):1001–12. Epub 2006/03/15. pmid:16533167

58. Hafner V, Jager M, Matthee AK, Ding R, Burhenne J, Haefeli WE, et al. Effect of simultaneous induction and inhibition of CYP3A by St John's Wort and ritonavir on CYP3A activity. Clin Pharmacol Ther. 2010;87(2):191–6. pmid:19924124

59. Seidling HM, Klein U, Schaier M, Czock D, Theile D, Pruszydlo MG, et al. What, if all alerts were specific—estimating the potential impact on drug interaction alert burden. Int J Med Inform. 2014;83(4):285–91. Epub 2014/02/04. pmid:24484781

60. ten Klooster PM, Drossaers-Bakker KW, Taal E, van de Laar MA. Patient-perceived satisfactory improvement (PPSI): interpreting meaningful change in pain from the patient's perspective. Pain. 2006;121(1–2):151–7. pmid:16472915

61. Todd KH, Funk KG, Funk JP, Bonacci R. Clinical significance of reported changes in pain severity. Annals of emergency medicine. 1996;27(4):485–9. pmid:8604867