Background: The 2019 American College of Rheumatology (ACR) guidelines strongly recommend oral nonsteroidal anti-inflammatory drugs (NSAIDs) for management of hip and knee osteoarthritis (OA) and strongly recommend topical NSAIDs for knee OA. There are, however, important safety considerations with NSAIDs in terms of increased rates of gastrointestinal, cardiovascular, and renal events. Given these risks, it is important to understand the characteristics and drug utilization of the patients who start treatment on these different treatments (i.e., traditional NSAIDs [tNSAIDs] and cyclooxygenase-2 inhibitors [COX-2s]). Objectives: The goal of this research was to describe and compare baseline characteristics of commercially-insured patients diagnosed with OA of the hip and/or knee who started treatment on different types of NSAIDs (i.e., oral tNSAIDs, topical tNSAIDs, and COX-2s). Methods: The Optum Healthcare Solutions, Inc. claims database (1/2012-3/2017) was used to identify patients ≥18 years old, with ≥2 diagnoses of hip and/or knee OA, and ≥90 days supply of oral tNSAIDs, topical tNSAIDs, or COX-2s during the one-year follow up period. The index date was defined as the first prescription after the first OA diagnosis. Patients were assigned to cohorts based on the type of NSAID prescribed on index date. Patients were required to be continuously-enrolled six months before (baseline period) and 36 months after (follow-up period) the index date. Demographic and clinical characteristics including age, sex, comorbidities, and healthcare resource use (HRU) were summarized during baseline. Drug utilization characteristics including days supply and number of prescriptions for the different NSAIDs types were summarized during follow-up period. Results: Data for 23,796 patients were analyzed: 18,100 patients received oral tNSAIDs, 4,825 received COX-2s, and 871 topical tNSAIDs. Patients who initiated treatment on oral tNSAIDs were the youngest (mean age of 60.6 vs. 64.6 for COX-2s and 65.0 for topical tNSAIDs) and topical tNSAIDs had the highest proportion of female patients (71% vs. 62% for oral tNSAIDs and 63% for COX-2s). The topical tNSAIDs cohort had the highest presence of chronic kidney disease (2.6% vs. 1.0% and 1.5% for oral tNSAIDs and COX-2s, respectively) and congestive heart failure (2.5% vs. 0.8% and 1.7% for oral tNSAIDs and COX-2s, respectively) at baseline. In terms of HRU during baseline, topical tNSAIDs had the most patients with emergency department visits (20.8% vs. 16.7% in both COX-2s and oral tNSAIDs), and COX-2 had the most patients with inpatient visits (18.1% vs. 15.4% for topical tNSAIDs and 11.8% for oral tNSAIDs). Oral tNSAIDs had the lowest total all-cause cost ($6,504), and the topical tNSAIDs cohort had the highest costs ($8,455), but fairly comparable with COX-2s ($8,289). During follow-up, oral tNSAIDs patients stayed mostly on oral tNSAIDs as less than 15% of oral tNSAIDs patients later had a prescription for COX-2s or topical tNSAIDs. 37% of COX-2 patients and 56% of topical tNSAIDs patients later took oral tNSAIDs. Topical tNSAIDs patients had an average of 184.4 days of supply for topical tNSAIDs yet also extensively used oral NSAIDs during follow-up (average days of supply for oral tNSAIDs was 315.5 days and for COX-2s was 383.5 days). Conclusion: This study suggests that patients with more complex comorbidity profiles, including higher rates of adverse effects, often start pharmacological treatment with topical tNSAIDs. However, patients who start treatment with topical tNSAIDs switch to other types of NSAIDs; oral tNSAIDs were the most frequently prescribed treatment across the cohorts. Thus, despite the safety concerns with oral tNSAIDs and COX-2s, patients are still placed on these treatments to manage their OA pain. There is a need for new innovative treatments as there is currently a lack of other options. Disclosure of Interests: Stuart Silverman Consultant of: Stuart Silverman is a paid consultant to Pfizer and Eli Lilly and Company in connection with this study, Patricia Schepman Shareholder of: Patricia Schepman is an employee of Pfizer with stock and/or stock options, Employee of: Pfizer, James B Rice Consultant of: Brad Rice is an employee of Analysis Group, who were paid consultants to Pfizer and Eli Lilly and Company for this study, Craig Beck Shareholder of: Craig Beck is an employee of Pfizer with stock and/or stock options, Employee of: Pfizer, Alan White Consultant of: Alan White is an employee of Analysis Group, who were paid consultants to Pfizer and Eli Lilly and Company for this study, Sheena Thakkar Shareholder of: Sheena Thakkar is an employee of Pfizer with stock and/or stock options, Employee of: Pfizer, Michaela Johnson Consultant of: Michaela Johnson is an employee of Analysis Group, who were paid consultants to Pfizer and Eli Lilly and Company for this study, Rebecca Robinson Shareholder of: Rebecca Robinson is an employee and minor stockholder of Eli Lilly and Company, Employee of: Eli Lilly and Company, Birol Emir Shareholder of: Birol Emir is an employee of Pfizer with stock and/or stock options, Employee of: Pfizer
Objectives: Examine short-term disability (STD) and workers’ compensation (WC) associated leave and wage replacements, and overall direct healthcare payments, among employees with osteoarthritis (OA) versus other chronically painful conditions; quantifying the impact of opioid use. Methods: Analysis of employees with more than or equal to two STD or WC claims for OA or pre-specified chronically painful conditions (control) in the IBM MarketScan Research Databases (2014 to 2017). Results: The OA cohort ( n = 144,355) had an estimated +1.2 STD days, +$152 STD payments, and +$1410 healthcare payments relative to the control cohort ( n = 392,639; P < 0.001). WC days/payments were similar. Differences were partially driven by an association between opioid use, increased STD days/payments, and healthcare payments observed in pooled cohorts ( P < 0.001). Conclusions: OA is associated with high STD days/payments and healthcare payments. Opioid use significantly contributes to these and this should be considered when choosing treatment.
Osteoarthritis (OA) is one of the most common causes of chronic pain and a leading cause of disability in the US. The objective of this study was to examine the clinical and economic burden of OA by pain severity.We used nationally representative survey data. Adults ≥18 years with self-reported physician-diagnosed OA and experiencing OA pain were included in the study. OA pain severity was measured using the Short Form McGill Pain Questionnaire Visual Analog Scale (SF-MPQ-VAS). Data were collected for demographics, clinical characteristics, health-related quality of life (HRQoL), productivity, OA treatment, adherence to pain medication, and healthcare resource utilization. Univariate analysis was performed to examine differences between respondents with moderate-to-severe OA pain vs those with mild OA pain.Higher proportions of respondents with moderate-to-severe OA pain (n=3798) compared with mild OA pain (n=2038) were female (69.4% vs 57.3%), <65 years of age (54.8% vs 43.4%), and not employed (70.6% vs 64.5%). Respondents with moderate-to-severe OA pain experienced OA pain daily (80.8% vs 48.8%), were obese (53.0% vs 40.5%), had more comorbidities (sleep disturbance, insomnia, depression, and anxiety), and reported significantly poorer health status and HRQoL, and greater productivity and activity impairment (all P<0.05). Moderate-to-severe OA pain respondents were prescribed significantly more pain medications than mild OA pain respondents (41.0% vs 17.0%) and had higher adherence (75.9% vs 64.1%) yet were less satisfied with their pain medications (all P<0.001). Outpatient and emergency room visits, and hospitalizations in the 6 months prior to the survey were significantly higher in moderate-to-severe OA pain respondents vs those with mild OA pain (all P<0.05).Patient and clinical burden was significantly greater in moderate-to-severe OA pain respondents vs mild OA pain respondents and may inform decision-making for appropriate resource allocation and effective management strategies that target specific subgroups.
Background: The development of new therapies to treat symptomatic osteoarthritis (OA) often requires targeting patient subgroups such as mild and/or moderate and/or severe. Multiple assessments for pain are used in clinical and research settings, yet to quantify patient burden with increasing pain severity it is important to understand the potential variability in outcomes based on definitions of severity used 1 . Objectives: The objective of this study was to examine studies in the published literature that report the burden of OA pain by severity to assess similarities and/or differences across study methodologies and outcomes. Methods: A targeted literature review of PubMed and Google Scholar was conducted January 2021 and included search terms: osteoarthritis, severity, United States (US), burden, quality of life, medication/treatment, and healthcare resource utilization. The search was limited to the English language, full-text articles, and no restriction on publication date. Results included a recent study of the burden of symptomatic OA pain respondents by severity level in the US 2,3 . Over 100 publication titles were reviewed. Comparison of findings was descriptive in nature. Results: Nine publications were identified representing 7 unique studies, 6 being patient and/or healthcare provider surveys. Two studies focused on OA severity: the remaining 5 stratified patients by pain severity, and all but 2 of the 5 identified and confirmed pain as OA-related. Pain measures included numeric rating scales (generic 0-10, Western Ontario and McMaster Universities Arthritis Index [WOMAC] NRS 3.1), visual analog scales (generic 0-100, Short-Form McGill Pain Questionnaire Visual Analog Scale [SF-MPQ-VAS]) or Pain Interference with Activities (PIA) scale derived from the 12-Item Short Form Health Survey [SF-12v2] developed for the Medical Outcomes Study, with recall periods varying from 48 hours to 7 days to 4 weeks. Only one study exclusively assessed symptomatic patients only i.e., patients with pain scores of 0 were excluded; the remainder compared cohorts of no/mild pain with increasing severity cohorts. Four of the 7 studies examined pairwise differences among mild, moderate, and severe patients (1 study vs. a non-OA cohort); 2 compared no/mild vs. moderate-to-severe OA pain and 1 study compared mild to moderate-to-severe OA pain. For most outcomes examined like clinical comorbidities, quality of life, and healthcare resource utilization, increasing burden was observed with increasing OA and/or pain severity despite study variability. Conclusion: Pain severity levels represent an important and distinguishing factor that contributes to health outcomes in OA patients in the US. Considerable heterogeneity across studies may impact how OA pain is defined, perceived by patients, and treated. Selecting appropriate OA pain severity assessments, including cut-points, may contribute to the successful monitoring of outcomes or comparisons of therapies to manage symptomatic OA pain, especially those that target specific pain severity subgroups. References: [1]Hawker GA, Mian S, Kendzerska T et al. Arthritis Care and Research. 2011; 63(11):S240-S252. [2]Schepman P, Robinson RL, Thakkar S, et al. International Society of Pharmacoeconomics and Outcomes Research (ISPOR) Virtual Annual Meeting; May 2020. [3]Schepman P, Thakkar S, Robinson RL, et al. PAINWeek 2020 Virtual Meeting; September 2020. Disclosure of Interests: Alesia Sadosky Shareholder of: Own stock in Pfizer Inc, Consultant of: I am an employee with the consulting firm Apperture Health, Employee of: I am retired from Pfizer Inc, Patricia Schepman Shareholder of: Owns shares in Pfizer Inc, Employee of: Employee of Pfizer Inc, Sheena Thakkar Shareholder of: Owns shares of Pfizer Inc, Employee of: Employee of Pfizer Inc, Rebecca Robinson Shareholder of: Owns shares of Eli Lilly and Company, Employee of: Employee of Eli Lilly and Company, Craig Beck Shareholder of: Owns shares of Pfizer Inc, Employee of: Employee of Pfizer Inc
Abstract Background No algorithms exist to identify important osteoarthritis (OA) patient subgroups (i.e., moderate-to-severe disease, inadequate response to pain treatments) in electronic healthcare data, possibly due to the complexity in defining these characteristics as well as the lack of relevant measures in these data sources. We developed and validated algorithms intended for use with claims and/or electronic medical records (EMR) to identify these patient subgroups. Methods We obtained claims, EMR, and chart data from two integrated delivery networks. Chart data were used to identify the presence or absence of the three relevant OA-related characteristics (OA of the hip and/or knee, moderate-to-severe disease, inadequate/intolerable response to at least two pain-related medications); the resulting classification served as the benchmark for algorithm validation. We developed two sets of case-identification algorithms: one based on a literature review and clinical input (predefined algorithms), and another using machine learning (ML) methods (logistic regression, classification and regression tree, random forest). Patient classifications based on these algorithms were compared and validated against the chart data. Results We sampled and analyzed 571 adult patients, of whom 519 had OA of hip and/or knee, 489 had moderate-to-severe OA, and 431 had inadequate response to at least two pain medications. Individual predefined algorithms had high positive predictive values (all PPVs ≥ 0.83) for identifying each of these OA characteristics, but low negative predictive values (all NPVs between 0.16–0.54) and sometimes low sensitivity; their sensitivity and specificity for identifying patients with all three characteristics was 0.95 and 0.26, respectively (NPV 0.65, PPV 0.78, accuracy 0.77). ML-derived algorithms performed better in identifying this patient subgroup (range: sensitivity 0.77–0.86, specificity 0.66–0.75, PPV 0.88–0.92, NPV 0.47–0.62, accuracy 0.75–0.83). Conclusions Predefined algorithms adequately identified OA characteristics of interest, but more sophisticated ML-based methods better differentiated between levels of disease severity and identified patients with inadequate response to analgesics. The ML methods performed well, yielding high PPV, NPV, sensitivity, specificity, and accuracy using either claims or EMR data. Use of these algorithms may expand the ability of real-world data to address questions of interest in this underserved patient population.
Background: While prior research has shown that patients with osteoarthritis (OA) who are prescribed opioids have higher rates of falls and fractures following drug initiation, there is a limited body of work establishing a comprehensive model of factors that influence the risk of falls or fractures among these patients. Objective: Opioids are associated with negative clinical outcomes, including increased risk of falls and fractures. This study assessed the frequency, treatment characteristics, and risk factors associated with falls or fractures among patients with OA taking opioids. Methods: Optum Healthcare Solutions, Inc data (January 2012–March 2017) were used to identify patients over 18 with at least 2 diagnoses of hip and/or knee OA, and at least 90 days’ supply of opioids. Patients with cancer were excluded. Falls or fractures outcomes were assessed in the 36-month follow-up period after the date of the first opioid prescription after first OA diagnosis. Demographic, treatment, and clinical characteristics associated with falls or fractures were assessed using logistic regression. Results: Of 16 663 patients meeting inclusion criteria, 3886 (23%) had at least 1 fall or fracture during follow-up. Of these 3886 patients, 1349 (35%) had at least 1 fall with an average of 3 fall claims, and 3299 (85%) patients had at least 1 fracture with an average of 8 claims during follow-up. Spine (15.8%) and hip (12.5%) fractures were most common. Median time to fall or fracture was 18.6 and 13.9 months, respectively. Significant (P<.05) risk factors associated with at least 1 fall or fracture during the follow-up period included alcohol use (odds ratio [OR], 3.41), history of falling (OR, 2.19), non-tramadol opioid use (OR, 1.31), age (OR, 1.03), benzodiazepine use (OR, 1.21), and at least 1 osteoporosis diagnosis (OR, 2.06). Discussion: This study is among only a few that clearly identifies the substantial impact and frequency of falls and fractures associated with prescribing non-tramadol opioids to patients with OA. Findings suggest that fall or fracture risks need to be considered when managing OA pain with opioids. Conclusion: Falls and fractures impose a major clinical burden on patients prescribed opioids for OA-related pain management. Falls or fracture risks should be an important consideration in the ongoing treatment of patients with OA.
465 Background: The JAVELIN Bladder 100 clinical trial demonstrated a significant overall survival and progression-free survival benefit with avelumab 1LM + best supportive care (BSC) vs BSC alone for la/mUC not progressing on platinum-based chemotherapy (PBC). PATRIOT-II aims to describe RW data for avelumab 1LM treatment (tx) of patients (pts) with la/mUC. Methods: PATRIOT-II collected data from pts with la/mUC treated in 37 geographically dispersed oncology practices/communities and academic centers in the US. Pts who initiated avelumab 1LM following PBC were retrospectively enrolled and will be followed up via medical record review for 52 weeks post avelumab 1LM initiation. This analysis focused on pt characteristics and tx data from la/mUC diagnosis through the PBC period and at avelumab 1LM initiation. Disease and PBC tx characteristics, as well as response to PBC, were assessed. All analyses were descriptive. Results: A total of 160 pts were enrolled (Table), 118 (74%) were white, non-Hispanic, 16 (10%), were Black, Asian, or Hispanic, and the rest unknown; 102 (64%) were current or former smokers. 77 (48%) were tested for PD-L1 via various assays, with 44 (57%) of those tumor samples reported as positive. 1L PBC was cisplatin-based in 100 (63%) of pts and carboplatin-based in 60 (38%). Pts received a median of 4 PBC cycles (interquartile range [IQR], 3-6) for a median of 13 weeks (IQR, 10-17). 31 (19%) discontinued PBC due to unacceptable side effects/toxicity. Best observed response was complete response in 21 (13%), partial response in 109 (68%), and stable disease in 17 (11%), with the remainder unknown. Median time to first imaging was 10 weeks (IQR, 5-14) after PBC initiation. 23 (14%) were hospitalized while receiving PBC, and 25 (16%) were seen in the emergency department. Pts proceeded to avelumab 1LM at a median of 4 weeks (IQR, 3-6) following PBC completion. Avelumab was administered at 800 mg every 2 weeks in 130 (81%), 10 mg/kg in 15 (9%), <800 mg in 8 (5%), and >800 mg in 7 (4%) pts. Conclusions: This ‘RW’ study offers valuable insights into characteristics and outcomes of pts with la/mUC treated in the US. Baseline factors, tx patterns and response to PBC were consistent with usual therapy paradigms in the 1L induction setting. Ongoing trials are evaluating the optimal number of PBC cycles and predictive biomarkers. Limitations include the retrospective nature, lack of randomization and central review, potential selection and confounding biases. [Table: see text]
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