Abstract
Objective:
To examine treatment patterns and costs among patients with fibromyalgia prescribed pregabalin or tricyclic antidepressants (TCAs).
Methods:
Using the LifeLink™ Health Plan Claims Database, patients with fibromyalgia (International Classification of Diseases, Ninth Revision, Clinical Modification code 729.1X) newly prescribed (index date) TCAs (n = 898) were identified and propensity score-matched (PSM) with patients newly prescribed pregabalin (n = 898). Pain-related pharmacotherapy, comorbidities, and healthcare resource use/costs were examined during the 12 months, pre-index, and follow-up periods.
Results:
Both patient groups reported multiple comorbidities and received pain medications in the pre-index and follow-up periods. Among patients prescribed pregabalin, use of non-selective non-steroidal anti-inflammatory drugs (43.3% vs 39.8%), other anticonvulsants (28.6% vs 23.3%), and tetracyclic/miscellaneous antidepressants (28.5% vs 25.8%) significantly decreased, and cyclooxygenase 2 (COX-2) inhibitors (7.7% vs 10.4%), TCAs (4.8% vs 7.9%), and topical agents (10.8% vs 15.1%) increased in the follow-up period (p < 0.05). Among patients prescribed TCAs, there were significant decreases in muscle relaxants (42.0% vs 38.4%) and sedative hypnotics (27.4% vs 23.9%), and increases in COX-2 inhibitors (5.8% vs 7.9%) and anticonvulsants (25.1% vs 33.7%; p < 0.05). There were increases (p < 0.0001) in pharmacy costs in both cohorts and total healthcare costs in the pregabalin cohort from pre-index to follow-up. Median total costs were higher (p < 0.05) in the pregabalin group vs TCAs in the pre-index ($9935 vs $8771) and follow-up ($10,689 vs $8379) periods.
Limitations:
Despite attempts to address bias through PSM, the higher pre-index costs in the pregabalin cohort suggest a channeling of patients with more severe fibromyalgia to pregabalin.
Conclusions:
Patients with fibromyalgia prescribed pregabalin or TCAs had multiple comorbidities and a sizeable pain medication burden, which increased in the follow-up period for both cohorts. Only 5% of pregabalin initiators had been treated with concomitant TCAs at baseline, suggesting that TCAs were inappropriate for these patients owing to their contraindications.
Introduction
Fibromyalgia (FM) affects between 2–4% of the US populationCitation1. Although chronic musculoskeletal pain, tenderness, and fatigue are the cardinal symptoms of FM, patients also report comorbid sleep and mood disturbancesCitation2–4, which result in impaired patient functioning, diminished quality-of-life, and increased healthcare costsCitation5. FM is diagnosed symptomatically based on the American College of Rheumatology (ACR) classification criteriaCitation6. These criteria emphasize the coexistence of both pain (widespread pain including in the axial, plus upper and lower body segments, and left- and right-sided pain) and tenderness (at ≥ 11 of the 18 specific tender point sites). The symptomatic diagnostic criteria, coupled with the fact that FM frequently resembles other pain syndromes, can cause significant delays in establishing an appropriate FM diagnosis and causes patients with FM to consume significant healthcare resources even prior to their diagnosisCitation7,Citation8.
FM is associated with a substantial socioeconomic burden. Studies have reported that FM is characterized by an increased prevalence of myriad conditions including depression, anxiety, sleep disorders, chronic fatigue, cardiovascular disorders, gastrointestinal disorders, and musculoskeletal and neuropathic pain conditions relative to non-FM controls and patients with other chronic pain conditionsCitation4,Citation9–15. Regardless of whether these comorbidities are part of FM or separate illnesses, their coprevalence magnifies the burden of FMCitation16,Citation17. The estimated direct costs of FM are substantialCitation8–11,Citation15,Citation18–23, and patients with FM have significantly higher healthcare resource use compared with non-FM reference groupsCitation9–11,Citation15–19,Citation21. Further, the symptomatic nature of FM has a serious impact on disability and work productivity, and the resulting indirect costs associated with absenteeism and employment status compound the total costs of FMCitation2,Citation15,Citation22,Citation24,Citation25.
Appropriate management of FM is challenging; however, many of the symptoms of FM are potentially amenable to pharmacologic therapy. Current treatment recommendations and management strategies are aimed at alleviating pain and improving functional status and sleep impairment. Evidence-based treatment guidelines developed by the American Pain Society and the European League Against Rheumatism uniformly recommend the use of anticonvulsants, low-dose tricyclic antidepressants (TCAs), selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), benzodiazepines, dopaminergic agonists, tramadol, and opioids (when other therapies have failed) along with non-pharmacologic therapies such as cardiovascular fitness and/or cognitive-behavioral therapyCitation26–28.
Only three drugs, pregabalin (Lyrica)Citation29, duloxetine (Cymbalta)Citation30, and milnacipran (Savella)Citation31, have received approval from the US Food and Drug Administration for the treatment of FM. (Lyrica is a registered trademark of Pfizer Inc., Cymbalta is a registered trademark of Lilly USA, LLC, and Savella is a registered trademark of Forest Laboratories, Inc.) Although not specifically approved for FM, TCAs are recommended and used in clinical practiceCitation8,Citation11–13,Citation26–28 and their generic status makes them an attractive low-cost treatment option. Additionally, since the prescribing of new branded therapies (including pregabalin) often requires prior authorization or step edits, use of recommended generically available drugs such as TCAs may be an attractive treatment alternative for pharmacy benefit managers concerned with rising costs. Although several studies have documented the costs of FMCitation2,Citation9–11,Citation15–25, there is limited information on the costs associated with FM treatment in community-based settings. Moreover, while studies have both evaluated the comparative efficacy of approved treatments for FMCitation32,Citation33 and the use of pregabalin or duloxetine in patients with FM in community-based settingsCitation12,Citation13,Citation34, there is a lack of information on patients initiated on TCAs. Results of a previous study that entailed a descriptive evaluation of the treatment patterns and costs of patients with FM initiated on pregabalin or gabapentin suggested a channeling bias, where patients with more severe disease were more frequently prescribed pregabalin (the newer and branded drug) rather than gabapentin (the older and generic option)Citation13.
Accordingly, in the present study, we used propensity-score matching (PSM) to evaluate the treatment patterns and costs of patients with FM initiating treatment with pregabalin or TCAs in clinical practice. The PSM methodology was employed to address potential selection bias and to allow a fair comparison of treatment patterns and costs.
Materials and methods
Data source
Data from the LifeLink™ (formerly PharMetrics) Health Plan Claims Database (IMS, Inc., Watertown, MA) were used in this study. The LifeLink database is composed of adjudicated medical and pharmaceutical claims for enrollees of more than 98 commercial managed care health plans throughout the US, which includes more than 61 million unique individuals and ∼16 million covered lives per year. Data submitted by participating plans undergo rigorous quality and consistency reviews, and all patient identifiers are encrypted to ensure full compliance with the Health Insurance Portability and Accountability Act of 1996. All available claims for each individual can be linked using a unique encrypted identifier to facilitate a longitudinal evaluation of each enrollee’s claims records over a specified time period. Claims records include information on patient demographics (age, gender, and region), enrollment details (coverage start and stop dates), inpatient and outpatient diagnoses (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] format), surgeries and procedures (Current Procedural Terminology, 4th Edition and Healthcare Common Procedural Coding System formats), and retail and mail order prescriptions including National Drug Code numbers, days’ supply, and quantity dispensed.
Sample selection
All patients aged 18 years and older with one or more healthcare encounters and an associated diagnosis of FM (ICD-9-CM codes 729.1X) during each of the 2 years starting July 1, 2005 through June 30, 2006 and July 1, 2006 through June 30, 2007 were identified, and those initiated on pregabalin or TCAs on or after July 1, 2007 (index date) were selected. In addition, these patients had to be continuously enrolled for 12 months before (pre-index) and 12 months after (follow-up) the index date (the study period), had to be naïve to pregabalin and TCAs for at least 6 months preceding the index date, could not have received a prescription for both pregabalin and a TCA on the index date, and could not be enrolled in a Medicare risk/supplemental plan if they were aged 65 years and older. Pregabalin and TCA initiators who satisfied the above-stated study entry criteria were then matched using PSMCitation35,Citation36.
PSM is generally used when, in the absence of randomization, it may not be clear whether a difference in outcomes between comparators results from the treatment itself or because of prior differences between the cohorts. This methodology, which was developed to generate matched cohorts in observational studies, enables control of bias by accounting for other potential confounding factors, i.e., a set of observed predictors (covariates). In the current analysis, logistic regression was used to estimate the conditional probability, or the propensity score of each patient in the pregabalin and TCA cohorts after controlling for the following covariates: age, gender, pre-index Charlson Comorbidity Index score (i.e., severity of the comorbidity burden)Citation37, pre-index pain comorbidity count, and total pre-index healthcare costs. Patients in the TCAs cohort were matched 1:1 (within 0.01 units) to patients in the pregabalin cohort based on their respective propensity scores. PSM was done using the Greedy matching algorithm.
Measures and analyses
Patient demographics (e.g., age and gender) and the prevalence of select chronic conditions (e.g., cardiovascular, gastrointestinal, and sleep disorders, and musculoskeletal and neuropathic pain conditions) were evaluated in patients prescribed pregabalin or TCAs. Comorbidities were selected based on their documented prevalence in patients with rheumatic diseases (e.g., cardiovascular disorders)Citation38 or in patients with FM (e.g., other pain conditions, gastrointestinal disorders, depression, anxiety, and sleep disorders)Citation4,Citation9–15. The presence of each comorbidity was defined as one or more healthcare encounters with the ICD-9-CM diagnoses codes for that comorbidity during the pre-index period (see ).
Table 1. Diagnostic codes used to identify relevant comorbidities.
Medication exposure was defined as the proportions of patients receiving pregabalin or TCAs who had one or more prescription claims for the various medication classes recommended and/or used for the treatment of FM or for the treatment of pain-related anxiety, depression, and sleep impairment in the pre-index and follow-up periods. The average number of prescriptions that patients received for these medications during the pre-index and follow-up periods also was assessed. Evaluated medications included opioids, non-selective non-steroidal anti-inflammatory drugs (NSAIDs), cyclooxygenase 2 (COX-2) inhibitors, SSRIs, SNRIs, TCAs, anticonvulsants, salicylates, tramadol, tetracyclic and miscellaneous antidepressants, miscellaneous agents (e.g., acetaminophen, butorphanol, nalbuphine, pentazocine), topical agents (e.g., capsaicin, lidocaine 5% dermal patch), topical corticosteroids, systemic corticosteroids, triptans and other antimigraines, attention-deficit/hyperactivity disorder (ADHD) drugs, intra-articular injections (IA; with hyaluronic acid or corticosteroids), disease-modifying anti-rheumatic drugs (DMARDs), benzodiazepines, sedatives/hypnotics, and muscle relaxants. For patients receiving pregabalin, only the use of anticonvulsants other than pregabalin were evaluated.
Use and costs of healthcare resources including physician office visits, emergency department (ED) visits, hospitalizations, other outpatient services (e.g., radiology, imaging, and pathology), and total direct healthcare costs were examined during the pre-index and follow-up periods for patients prescribed pregabalin or TCAs.
Statistics
Demographic characteristics and comorbidities were summarized using descriptive statistics, and Chi-square, Fisher exact tests, or analysis of variance models were used to determine the statistical significance of differences between the pregabalin and TCA cohorts for categorical and continuous variables, respectively. McNemar tests were used to assess the statistical significance of within-group changes (pre- vs post-index) in proportions of pregabalin and TCA patients who used the various study medications, and Wilcoxon signed rank tests were used to assess within-group changes in the magnitude of medication and healthcare resource use. Chi-square or Fisher exact tests, logistic regressions, Wilcoxon rank sum tests, and generalized linear models with log-links were used to assess the statistical significance of between-group (pregabalin vs TCAs) differences in medication and healthcare resource use and costs during the pre-index and follow-up periods. The SAS software system, PC version 8.0 (SAS Institute Inc., Cary, NC), was used to conduct all study analyses and an alpha value of <0.05 was used to establish statistical significance.
Results
In total, 898 patients initiated on TCAs matched with 898 patients initiated on pregabalin were included in this study. Patients in the two cohorts were similar in age (mean [standard deviation]: pregabalin 47.9 [9.6] years, TCAs 48.5 [9.9] years); 87.6% of patients were women in the pregabalin cohort and 84.6% in the TCAs cohort (see ). The prevalence of several comorbidities was significantly different (p < 0.05) between the matched pregabalin and TCA cohorts. Rheumatic disease, depression, sleep apnea, rheumatoid arthritis, and arthritis and other arthropathies were higher in the pregabalin cohort. Disease of the digestive system, low back pain, back and neck pain other than low back pain, other musculoskeletal pain conditions, headache, and abdominal pain were higher in the TCAs cohort.
Table 2. Demographic and clinical characteristics of the study cohorts.
Depression was the most prevalent mental disorder in each cohort (pregabalin 33.4%, TCAs 28.6%; p = 0.0283), and more than 20% of patients in each cohort had insomnia/sleep disorders (pregabalin 23.3%, TCAs 24.5%; not significant). Hyperlipidemia was the most common cardiovascular comorbidity, occurring in 35.8% of patients prescribed pregabalin and 37.5% of patients prescribed TCAs (not significant). More than 90% of patients in each cohort had at least one of the evaluated musculoskeletal pain conditions including arthritis and other arthropathies (pregabalin 55.0%, TCAs 49.8%; p = 0.0264), low back pain (pregabalin 55.6%, TCAs 62.9%; p = 0.0015), back and neck pain (pregabalin 46.8%, TCAs 52.4%, p = 0.0161), and rheumatism (pregabalin 55.0%, TCAs 52.8%; not significant). Approximately 40% of patients in each cohort had neuropathic pain conditions, with neuropathic back and neck pain being the most prevalent in each cohort (pregabalin 29.5%, TCAs 28.6%; not significant).
Exposure to and magnitude of use of the evaluated medications are presented in and . In the pre-index period, exposure to pain-related and adjuvant medications was substantial in patients prescribed both pregabalin and TCAs. Compared with TCAs, significantly higher proportions (p < 0.01) of patients in the pregabalin cohort were prescribed opioids, NSAIDs, SNRIs, anticonvulsants, muscle relaxants, benzodiazepines, sedative/hypnotics, tramadol, tetracyclic and miscellaneous antidepressants, topical agents, and DMARDs. Medication use continued to be substantially higher in the follow-up period in both cohorts; in addition to the medication classes previously noted (except DMARDs), significantly higher (p < 0.05) proportions of patients in the pregabalin cohort were prescribed ADHD drugs and IA injections.
Table 3. Number of patients prescribed pregabalin and TCAs who had ≥ 1 claims for pain-related medications in the pre-index and follow-up periods.
Table 4. Medication use (among users) for pain-related medications in the pre-index and follow-up periods.
In the pregabalin cohort, the proportions of patients who received COX-2 inhibitors (7.7% vs 10.4%; p = 0.0088), TCAs (4.8% vs 7.9%; p = 0.0047), topical agents (10.8% vs 15.1%; p = 0.0008), and ADHD drugs (6.0% vs 7.6%; p = 0.0433) increased significantly from the pre-index to the follow-up periods. Conversely, the proportions of patients who received non-selective NSAIDs (43.3% vs 39.8%; p = 0.0405), tetracyclic and miscellaneous antidepressants (28.5% vs 25.8%; p = 0.0285), and other anticonvulsants (28.6% vs 23.3%; p = 0.0009) decreased significantly. There was no change in opioid use on an overall basis or when opioid use was stratified by the number of pregabalin prescriptions.
In the TCAs cohort, there were significant increases in the proportions of patients who received COX-2 inhibitors (5.8% vs 7.9%; p = 0.0167) and anticonvulsants (25.1% vs 33.7%; p < 0.0001), and significant decreases in the proportions of patients who received muscle relaxants (42.0% vs 38.4%; p = 0.0381), sedative/hypnotics (27.4% vs 23.9%; p = 0.0164), and IA injections (14.9% vs 12.2%; p = 0.0455) from the pre-index to the follow-up periods. Similar to the pregabalin cohort, there was no change in opioid use on an overall basis or when opioid use was stratified by the number of TCA prescriptions.
Among users of the various study medications, the number of prescriptions for opioids (i.e., long-acting opioids, short-acting opioids, weak opioids, strong opioids, any opioids), non-selective NSAIDs, any NSAIDs, SSRIs, muscle relaxants, benzodiazepines, sedative/hypnotics, tramadol, and tetracyclic and miscellaneous antidepressants were significantly higher (p < 0.05) in the pregabalin cohort compared with the TCAs cohort in the pre-index period. Pregabalin-treated patients also received a significantly higher number of prescriptions for short-acting opioids, strong opioids, any opioids, SNRIs, anticonvulsants, muscle relaxants, other anti-migraines, and tetracyclic and miscellaneous antidepressants (p < 0.05) in the follow-up period. After controlling for relevant covariates in regression analyses, except for SNRIs and muscle relaxants, the differences in the number of prescriptions between the pregabalin and TCA cohorts for all other classes of medications in the follow-up period remained significant. When holding other covariates constant, the number of prescriptions for each respective medication class in the pre-index period was a significant predictor of the number of prescriptions in the follow-up period.
There were significant increases (p < 0.05) in the number of prescriptions for strong opioids, any opioids, TCAs, and topical agents from the pre-index to the follow-up periods among patients prescribed pregabalin. In the TCAs cohort, there were significant increases (p < 0.01) in the number of prescriptions for COX-2 inhibitors, any NSAIDs, and anticonvulsants, and significant decreases (p < 0.05) in the number of prescriptions for other anti-migraines and IA injections from the pre-index to the follow-up periods.
Healthcare resource use data are presented in . Most patients in both the pregabalin and TCAs groups had physician office and other outpatient visits, ∼30% had ED visits, and between 10–15% had hospitalizations during the pre-index and follow-up periods. Except for hospitalizations, which were higher in the pregabalin group during the follow-up period (13.1% vs 10.0%; p = 0.0390), there were no other significant differences in the proportions of patients using healthcare resources between the two medication cohorts.
Table 5. Healthcare resource use among patients prescribed pregabalin and TCAs in the pre-index and follow-up periods.
Among patients prescribed pregabalin, there was a decrease (p < 0.0028) in the proportion of patients with other outpatient visits in the follow-up period; among patients prescribed TCAs, there were decreases (p < 0.05) in the proportions of patients with hospitalizations, physician office visits, and other outpatient visits in the follow-up period.
The number of physician office visits and total outpatient visits were higher (p < 0.01) in the pre-index period among patients prescribed TCAs compared with pregabalin; however, there were no significant differences in visits between the two drug groups in the follow-up period. There were no changes in the number of healthcare visits in the pregabalin group from the pre-index to follow-up periods, whereas there were decreases (p < 0.001) in physician office visits and total outpatient visits in the TCA group. There was a significant decrease (both p < 0.01) in both the proportion of patients who had visits to a chiropractor and the number of visits to chiropractors; a decrease (p = 0.0426) in the number of visits to general practitioners; and an increase (p < 0.05) in the proportion of patients and number of visits to psychiatrists from the pre-index to the follow-up periods among patients prescribed pregabalin. There was also an increase (p < 0.05) in the magnitude of cognitive-behavioral therapy in the follow-up period. In the TCAs cohort, there was a significant decrease (p = 0.0002) in the proportion of patients with visits to chiropractors, a decrease (p = 0.0028) in the number of visits to chiropractors, and a decrease in the number of visits to physical therapists (p = 0.0372) in the follow-up period.
Direct healthcare costs of patients prescribed pregabalin or TCAs are presented in . During the pre-index period, costs of physician office visits (median $1376.9 [interquartile range (IQR) $831.0–$2412.8] vs median $1208.1 [IQR $757.4–$2042.0]) and total outpatient visits (median $5228.0 [IQR $2564.7–$9820.2] vs median $4784.2 [IQR $2145.0–$8990.9]) were higher in patients prescribed TCAs compared with those prescribed pregabalin, respectively. Total medication costs (median $3258.4 [IQR $1480.9–$6698.2] vs median $2054.6 [IQR $867.9–$4427.4]) and total healthcare costs (median $9934.7 [IQR $5386.7–$17,531.1] vs median $8771.2 [IQR $4379.7–$16,679.0]) were higher in the pregabalin cohort compared with the TCAs cohort, respectively. Total medication costs (median $4422.0 [IQR $2050.5–$7523.3] vs $2395.3 [IQR $950.9–$5043.2]) and total healthcare costs (median $10,689.1 [IQR $6131.3–$18,491.2] vs $8379.3 [IQR $4291.0–$16,433.6]), were each significantly higher (p < 0.0001 for both comparisons) in the pregabalin group compared with TCAs in the follow-up period. Medication and total healthcare costs remained significantly higher in the follow-up period in the pregabalin cohort relative to the TCAs cohort, after controlling for relevant covariates in regression analyses. There were significant increases in total medication costs and total healthcare costs in the pregabalin cohort, and a significant increase in total medication costs from the pre-index to the follow-up periods in the TCAs cohort (p < 0.0001).
Table 6. Direct healthcare costs among patients prescribed pregabalin and TCAs in the pre-index and follow-up periods.
Discussion
Results of the present study suggest that patients with FM who are prescribed pregabalin or TCAs have a considerable comorbidity and pain medication burden. The rates of comorbidities observed in this study are higher than those previously reported in a study of a prevalent cohort of 33,176 patients with FMCitation9 and in a study of patients with FM initiated on pregabalin or gabapentin in usual care settingsCitation13. The high prevalence of comorbid illnesses observed in patients with FM often complicates the recognition, treatment, and costs of this syndrome.
Consistent with previous studies, patients in this study had myriad comorbid illnesses including cardiovascular, sleep, and gastrointestinal disorders as well as musculoskeletal and neuropathic pain conditionsCitation4,Citation9–15. The prevalence of pain conditions in this study was significantly higher than reported in previous studiesCitation9,Citation13, which suggests that patients in the present study may have more severe disease. In addition, one of the previous studiesCitation13 evaluated clinical comorbidities in a prevalent FM cohort, whereas the present study included patients with FM who were prescribed recommended treatments for FM-related pain. Accordingly, since this study included “treatment seekers”, it follows that patients in this study potentially had more severe pain. The mood and sleep disturbances reported in previous studiesCitation2–4 also were confirmed in the present study, with nearly one-third of patients in the pregabalin and TCA cohorts reporting depression and one in four patients in both groups reporting sleep disorders.
Importantly, the observation of a wide range of comorbidities, as well as the proportions of patients with these conditions highlights the differences between FM populations in clinical practice and clinical trials. Several of the conditions observed among substantial proportions of the patients in the current study have been used as reasons for exclusion in FM clinical trials, including depression, musculoskeletal conditions, and neuropathic pain conditionsCitation39–44. Also, clinical trials often exclude patients based on baseline use of other pain medications that may confound evaluation of the analgesic effect of the study medication. These differences suggest that FM clinical trial populations may not necessarily be representative of patients in clinical practice, with the additional implication that there remains a need for the design of trials that more accurately reflect the clinical setting.
Consistent with previous studies in patients with FMCitation8–13,Citation15,Citation23, both study cohorts had a considerable pain-related and adjuvant medication burden in the pre-index and follow-up periods. However, medication burden was significantly higher in the pregabalin group in both the pre-index and follow-up periods in terms of both proportions of patients receiving various medications and the magnitude of the number of prescriptions among users. The finding of a higher pain medication burden in the pregabalin cohort could be attributed to a channeling bias, where patients with more severe disease are being initiated on pregabalin. Although we used PSM to address selection bias in this study, the PSM model could not directly account for pain severity owing to limitations inherent in a retrospective claims database. Thus, it is possible that, despite our attempts to control potential bias, patients with more severe FM pain were initiated on pregabalin. The channeling of patients with more severe disease is common after the launch of a new treatment for any indication. Further, owing to the generic availability of TCAs, it is conceivable that the more expensive branded pregabalin was preferentially used in patients with more severe FM pain. However, it should be noted that the higher use of SNRIs in the pregabalin group could also suggest that patients who were on concomitant SNRIs were prescribed pregabalin as opposed to a TCA, because prescribing two concurrent antidepressants may not be an optimal choice.
There were no notable differences in physician office visits, ED visits, hospitalizations, or outpatient visits between the pregabalin and TCA groups in the pre-index and follow-up periods or within groups from pre-index to follow-up; there was a decrease in the number of visits to chiropractors in both groups. Owing to database limitations, it cannot be ascertained whether this decrease in use of chiropractors was related to improved pain control that resulted from the initiation of pregabalin or TCA treatment. There were significant increases in medication costs in both cohorts and increases in total healthcare costs in the pregabalin cohort from the pre-index to the follow-up periods. Median total healthcare costs were higher in the pregabalin cohort relative to the TCAs cohort in both the pre-index and follow-up periods. Following the supposition that potentially sicker patients were prescribed pregabalin, these findings are consistent with a previous studyCitation8, which noted that costs associated with FM increase as the disease progresses from a milder to a more established stage. If patients prescribed pregabalin were sicker to begin with, this could explain why their costs remained high in the 12-month follow-up period.
Differences between patients prescribed pregabalin and patients prescribed TCAs could have been driven by specific patient characteristics and clinical judgment about appropriate treatment with either medication. Only 5% of patients initiated on pregabalin had been treated with concomitant TCAs at baseline, which could suggest that most patients prescribed pregabalin were not suitable candidates for TCAs. While TCAs have shown effectiveness in managing pain from various origins, they are older drugs with multiple contraindications and warnings, such as use by patients with cardiovascular conditions and long-term use in the elderlyCitation45–47. Further research on patient sub-types and responder characteristics is necessary to inform individualized, more targeted treatment of patients with fibromyalgia.
Several limitations of our study are worth noting. As is the case with all studies using retrospective claims data, such data are subject to potential miscoding of diagnoses that results in a fraction of patients who did not have FM potentially being included in our study samples. However, given the rigorous data quality reviews performed by the database provider before releasing the data, such errors are likely to be negligible. In addition, since there is no simple diagnostic test or an ICD-9-CM code specifically for FM, it is possible that patients with other diffuse types of myalgias were misclassified as having FM. However, to minimize this possibility and improve specificity, we required that all patients in our study have a diagnosis of FM in each of two consecutive years. Further, owing to the unavailability of physicians’ prescribing instructions or notes in retrospective claims databases, whether or not the index medications (pregabalin or TCAs) were actually prescribed for FM cannot be determined. In a population such as FM, in which patients have multiple chronic pain comorbidities, it is possible that pregabalin, TCAs, or any other pain or adjuvant medication evaluated in this study were actually being prescribed for chronic pain conditions other than FM.
Since the database essentially reflects a compilation of medical and pharmacy claims paid by insurance providers, use of over-the-counter medications, vitamins, supplements, and alternative treatments (e.g., acupuncture, cognitive-behavioral therapy, and chiropractic care) are likely to be under-represented in our study, as they are not reimbursed by all health plans. Moreover, it is not possible to know if the use of pregabalin or TCAs had any effect on the concomitant use of such therapies in patients with FM. Another limitation is related to the inability to truly assess patient compliance when using retrospective claims data. Although we were able to determine what medications were prescribed to patients with FM, whether patients actually took these medications is not known. Finally, information on clinical parameters such as patients’ pain severity is not recorded in claims databases, and, therefore, any conclusions regarding the effectiveness of either pregabalin or TCAs in alleviating FM pain cannot be drawn. For all these reasons, the results reported here should be interpreted with the appropriate caveats in mind.
Conclusions
Results indicate patients with FM who were prescribed pregabalin or TCAs had a significant number of other chronic pain and non-pain conditions and these patients were using a number of different medications. Medication use in both groups was substantial both before and after the prescribing of index medications, and moderate increases were observed in medication use in both cohorts in the follow-up period. Consistent with increases in medication use, medication costs also increased in both cohorts in the follow-up period, and total healthcare costs were higher in the pregabalin group both before and after treatment initiation. Despite our attempts to control potential bias through PSM, the higher pre-index medication use and costs in the pregabalin cohort suggest a channeling of more severe patients to pregabalin. As only 5% of patients initiated on pregabalin had been treated with concomitant TCAs at baseline, the patients prescribed pregabalin had likely been unsuitable candidates for TCAs based on their contraindications.
Transparency
Declaration of funding
This research was funded by Pfizer Inc. All authors contributed to the concept design of the study and to data preparation and analysis. All authors drafted, reviewed, and revised the manuscript.
Declaration of financial/other relationships
Dr Gore is Principal Consultant and Mr Kei-Sing Tai is Principal Statistician at Avalon Health Solutions, Inc., and they were paid consultants to Pfizer Inc in connection with the development and execution of both this article and the research it describes. Dr Gore also owns stock in Pfizer. Dr Zlateva and Ms Chandran are employees and stockholders of Pfizer. Dr Leslie was paid an honorarium by Avalon Health Solutions, Inc. for his participation in this research and for his review of, and input for this article. Dr Leslie has also performed consulting for Kurron Bermuda Ltd.
Acknowledgments
The authors would like to thank Christopher Rice for editorial assistance in the preparation of this article. Christopher Rice is an employee of Avalon Health Solutions, Inc. Editorial support to prepare this manuscript for journal submission was provided by UBC Scientific Solutions and funded by Pfizer Inc.
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