Linked Patient-Reported Outcomes Data From Patients With Multiple Sclerosis Recruited on an Open Internet Platform to Health Care Claims Databases Identifies a Representative Population for Real-Life Data Analysis in Multiple Sclerosis.

BACKGROUND: An enormous amount of information relevant to public health is being generated directly by online communities. OBJECTIVE: To explore the feasibility of creating a dataset that links patient-reported outcomes data, from a Web-based survey of US patients with multiple sclerosis (MS) recruited on open Internet platforms, to health care utilization information from health care claims databases. The dataset was generated by linkage analysis to a broader MS population in the United States using both pharmacy and medical claims data sources. METHODS: US Facebook users with an interest in MS were alerted to a patient-reported survey by targeted advertisements. Eligibility criteria were diagnosis of MS by a specialist (primary progressive, relapsing-remitting, or secondary progressive), ≥12-month history of disease, age 18-65 years, and commercial health insurance. Participants completed a questionnaire including data on demographic and disease characteristics, current and earlier therapies, relapses, disability, health-related quality of life, and employment status and productivity. A unique anonymous profile was generated for each survey respondent. Each anonymous profile was linked to a number of medical and pharmacy claims datasets in the United States. Linkage rates were assessed and survey respondents' representativeness was evaluated based on differences in the distribution of characteristics between the linked survey population and the general MS population in the claims databases. RESULTS: The advertisement was placed on 1,063,973 Facebook users' pages generating 68,674 clicks, 3719 survey attempts, and 651 successfully completed surveys, of which 440 could be linked to any of the claims databases for 2014 or 2015 (67.6% linkage rate). Overall, no significant differences were found between patients who were linked and not linked for educational status, ethnicity, current or prior disease-modifying therapy (DMT) treatment, or presence of a relapse in the last 12 months. The frequencies of the most common MS symptoms did not differ significantly between linked patients and the general MS population in the databases. Linked patients were slightly younger and less likely to be men than those who were not linkable. CONCLUSIONS: Linking patient-reported outcomes data, from a Web-based survey of US patients with MS recruited on open Internet platforms, to health care utilization information from claims databases may enable rapid generation of a large population of representative patients with MS suitable for outcomes analysis.

Medical care costs and survival associated with hepatocellular carcinoma among the elderly.

BACKGROUND & AIMS: We assessed the burden of hepatocellular carcinoma (HCC), in terms of mortality and medical care costs, based on analysis of the Surveillance, Epidemiology and End Results (SEER)-Medicare database. METHODS: We analyzed data from the SEER-Medicare database on patients 66 years or older who were diagnosed with primary HCC from 1991 to 2007, entitled for Medicare Parts A and B, and not enrolled in health maintenance organizations (n = 5712). Controls were individuals without HCC, identified from a 5% sample of Medicare beneficiaries residing in SEER areas; they were matched 1:1 with individuals with HCC (cases) for age, sex, race, and geographic region (average age, 75 y; 34.7% female). Kaplan-Meier analysis was used to estimate survival distributions. Costs were reported in 2009 dollars; per-patient-per-month (PPPM) costs were compared between cases and controls using the Wilcoxon rank sum test. RESULTS: The largest proportion of cases had localized disease (38.2%), followed by regional (24.0%), unstaged (20.4%), and distant (17.3%) disease. The median survival times were 5 months for cases and 60 months for controls; they were 3 months for patients with distant disease, 4 months for patients with regional disease, and 9 months for those with localized disease. The mean PPPM costs were $7863 for cases and $1243 for controls (P < .001). These costs were primarily driven by inpatient (mean, $5439 vs $682 without HCC; P < .001) and hospice (mean $554 vs $42 without HCC; P < .001) care. Mean PPPM costs by stage were $7265 for localized disease, $8072 for regional disease, and $9585 for distant disease (P < .001 for trend). CONCLUSIONS: Based on analysis of the SEER-Medicare database, costs for patients with HCC are approximately 6- to 8-fold higher than for those without this cancer. Patients with distant HCC had the greatest costs. These findings highlight that HCC is a substantial medical cost burden for elderly patients.

Incidence of venous thromboembolism among chemotherapy-treated patients with lung cancer and its association with mortality: a retrospective database study.

Cancer patients, especially those with lung cancer and undergoing chemotherapy, have an elevated risk for venous thromboembolism (VTE). This study assessed incidence, timing, and risk factors for VTE (specifically receipt of chemotherapy), along with the association between VTE and survival among lung cancer patients receiving chemotherapy. Using Florida Medicaid administrative claims data (2000-2008), patients with any diagnosis of primary lung cancer were selected. Patients with recent prior VTE and those enrolled in Medicare or an HMO were excluded. Crude rates of VTE per 100 person years were estimated, and Cox proportional hazards models were developed to assess risk factors for VTE in the lung cancer population, and the association between VTE and survival among patients undergoing chemotherapy. Of 15,749 lung cancer patients, 7,052 (2,242 receiving chemotherapy and 4,810 not receiving chemotherapy) met cohort selection criteria. The incidence of VTE was 10.8 per 100 person-years (PYs) in the chemotherapy cohort and 6.8 per 100 PYs in the non-chemotherapy cohort. Among patients on chemotherapy developing VTE, median time to occurrence was 109 days, with 61 and 82 % of patients experiencing an event within six and 12 months, respectively. In multivariate analyses, the adjusted risk of VTE was 30 % higher among patients undergoing chemotherapy. Comorbidity and the presence of a central venous catheter also were significantly associated with a greater risk of developing VTE. Moreover, patients in the chemotherapy cohort who developed VTE had a significantly faster time-to-death (adjusted hazard ratio [HR] = 1.97; 95 % CI 1.69-2.29).VTE was common among lung cancer patients, especially among patients receiving chemotherapy, with the majority of VTE events occurring within 6 months of initiation of chemotherapy. The presence of a VTE event was significantly associated with an increased risk of mortality.

Relationship between glycemic control and diabetes-related hospital costs in patients with type 1 or type 2 diabetes mellitus.

BACKGROUND: Diabetes mellitus requires continuous medical care and patient self-management in order to prevent short-term complications and decrease the risk of long-term complications, which can result in substantial increases in the total economic burden of the disease. Findings from randomized clinical trials have shown that improved glycemic control may reduce the risk of long-term complications as long as a target for hemoglobin A1c is not set below 7% for intensive glycemic control. However, limited data from clinical practice are available regarding the relationship between glycemic control and medical costs associated with diabetes care. OBJECTIVE: To assess the potential relationships between glycemic levels, diabetes-related hospitalizations, and hospital costs among adult patients with either type 1 or type 2 diabetes mellitus who were assigned to a primary care provider (PCP) in a clinic that was affiliated with a managed care organization (MCO). METHODS: A retrospective cohort analysis was conducted using data from approximately 200,000 members of the Fallon Clinic Health Plan who were assigned to a clinic PCP at any time during a 5-year study period beginning January 1, 2002, and ending December 31, 2006. Patients aged 30 years or older with at least 2 medical claims with any listed diagnosis of diabetes mellitus (ICD-9-CM code 250.xx) during the study period and 2 or more A1c values within 1 year of each other during the study period (mean 7.6 tests over 39 months; median=6.8), were identified and stratified into 1 of 5 groups defined by 1% increments of A1c, based on their mean A1c values during the entire study period. A1c data were available only for tests ordered by a clinic provider; tests ordered by other specialists in the MCO's network were absent from the database. The study follow-up period started with each patient's first A1c test (index date) and continued until plan disenrollment, death, or December 31, 2006, whichever was earlier (end date), regardless of when the diagnosis of diabetes mellitus was made. Study measures included the proportion of patients with 1 or more diabetes-related hospitalizations, number of diabetes-related inpatient stays, and the associated estimated hospitalization costs over the follow-up period. Diabetes-related hospitalizations were identified based on a diagnosis, in any of 10 diagnosis fields, for 1 of 16 selected complications of diabetes identified by the authors. Hospital costs were estimated using discharge data (diagnoses and costs calculated from cost-to-charge ratios) contained in the 2004 Healthcare Cost and Utilization Project (HCUP) database and inflated to 2007 dollars using the medical care component of the Consumer Price Index. Multivariate models controlled for age, sex, number of A1c tests, diagnosis of cancer, and follow-up time. A multivariate logistic regression analysis was conducted with the occurrence of at least 1 diabetes-related hospital admission as the dependent variable. In the logistic regression analysis, follow-up time was defined as time from the index date to the date of the first diabetes-related hospitalization, plan disenrollment, death, or the study end date, whichever occurred first. A generalized linear model with a Poisson distribution and a log link was employed to estimate the rate of hospital admissions. In the Poisson regression analysis, follow-up time was defined as duration of the entire study follow-up period and was an offset variable. Costs were estimated using a 2-part model: first, we calculated the probability of having a hospitalization, as determined by the logistic regression above; second, a generalized linear model with a negative binomial distribution and a log link was used to predict the mean cost of diabetes-related hospitalizations only for patients with an inpatient stay, with the duration of the entire study follow-up period as an offset variable. We calculated the mean per patient cost of diabetes-related hospitalizations by multiplying the probability of having a hospitalization (as determined by the first part of the model) by the mean costs for patients who had such admissions (as determined by the second part of the model). RESULTS: 9,887 patients met study selection criteria. Mean A1c level was < 7% for 5,649 (57.1%) patients, 7% to < 8% for 2,747 (27.8%), 8% to < 9% for 1,002 (10.1%), 9% to < 10% for 312 (3.2%), and 10% or more for 177 (1.8%). Over a mean (median) 40 (40) months of follow-up (interquartile range = 30-50 months), 28.7% (n = 2,838) of patients had 1 or more diabetes- related hospital admissions. In the logistic regression analysis, odds of having at least 1 diabetes-related hospital stay did not significantly differ for patients with mean A1c of < 7% compared with patients in most higher mean A1c categories (7% to < 8%, 8% to < 9%, or 9% to < 10%); however, odds of having a diabetes-related hospitalization were significantly higher for patients with mean A1c of 10% or more compared with patients with mean A1c of < 7% (odds ratio = 2.13, 95% confidence interval = 1.36-3.33). In the negative binomial regression analysis of those with at least 1 hospital admission, estimated costs per hospitalized patient increased by mean A1c level. In the Poisson regression analysis, the rate of diabetes-related hospitalizations significantly increased by A1c level (13 per 100 patient-years for patients with mean A1c of < 7% vs. 30 per 100 patient-years for mean A1c of 10% or more when covariates were held at mean levels, P<0.001). In the 2-part model results, adjusted mean estimated costs of diabetes-related hospitalizations per study patient were $2,792 among those with mean A1c of < 7% and $6,759 among those with mean A1c of 10% or more. CONCLUSIONS: In this managed-care plan, the odds of having at least 1 diabetes-related hospitalization were not significantly associated with higher mean A1c except for patients with mean A1c of at least 10%. However, higher mean A1c levels were associated with significantly higher estimated hospitalization costs among those with at least 1 hospitalization and with higher rates of diabetes-related hospital utilization per 100 patient-years.

Lifetime and treatment-phase costs associated with colorectal cancer: evidence from SEER-Medicare data.

BACKGROUND & AIMS: This study provides detailed estimates of lifetime and phase-specific colorectal cancer (CRC) treatment costs. METHODS: This retrospective cohort study included patients aged 66 years and older, newly diagnosed with CRC in a Surveillance Epidemiology and End Results (SEER) registry (1996-2002), matched 1:1 (by age, sex, and geographic region) to patients without cancer from a 5% sample of Medicare beneficiaries. The Kaplan-Meier sample average estimator was used to estimate observed 10-year costs, which then were extrapolated to 25 years. A secondary analysis computed costs on a per-survival-year basis to adjust for differences in mortality by stage and age. Costs were expressed in 2006 US$, with future costs discounted 3% per year. RESULTS: Our sample included 56,838 CRC patients (41,256 colon cancer [CC] patients and 15,582 rectal cancer [RC] patients; mean +/- SD age, 77.7 +/- 7.1 y; 55% women; and 86% white). Lifetime excess costs were $29,500 for CC and $26,500 for RC patients. Per survival year, stage IV CRC patients incurred $31,000 in excess costs compared with $3000 for stage 0 patients. CRC patients incurred excess costs of $33,500 in the initial phase, $4500/y in the continuing phase, and $14,500 in the terminal phase. RC patients had lower costs than CC patients in the initial phase, but higher costs in both the continuing and terminal phases. CONCLUSIONS: Excess costs associated with CRC are striking and vary considerably by treatment phase, cancer subsite, and stage at diagnosis. Interventions aimed at earlier diagnosis and prevention have the potential to reduce cancer-related health care costs.

Factors associated with improved survival among older colorectal cancer patients in the US: a population-based analysis.

BACKGROUND: The purpose of this study was to estimate the relative impact of changes in demographics, stage at detection, treatment mix, and medical technology on 5-year survival among older colorectal cancer (CRC) patients. METHODS: We selected older patients diagnosed with CRC between 1992 and 2000 from the SEER-Medicare database and followed them through 2005. Trends in demographic characteristics, stage at detection and initial treatment mix were evaluated descriptively. Separate multivariate logistic regression models for colon (CC) and rectal cancer (RC) patients were estimated to isolate the independent effects of these factors along with technological change (proxied by cohort year) on 5-year survival. RESULTS: Our sample included 37,808 CC and 13,619 RC patients (combined mean +/- SD age: 77.2 +/- 7.0 years; 55% female; 87% white). In recent years, more CC patients were diagnosed at Stage I and fewer at Stages II and IV, and more RC patients were diagnosed at Stage I and fewer at Stages II and III. CC and RC patients diagnosed in later years were slightly older with somewhat better Charlson scores and were more likely to be female, from the Northeast, and from areas with higher average education levels. Surgery alone was more common in later years for CC patients while combined surgery, chemotherapy, and radiotherapy was more common for RC patients. Between 1992 and 2000, 5-year observed survival improved from 43.0% to 46.3% for CC patients and from 39.4% to 42.2% for RC patients. Multivariate logistic regressions indicate that patients diagnosed in 2000 had significantly greater odds of 5-year survival than those diagnosed in 1992 (OR: 1.35 for CC, 1.38 for RC). Our decomposition suggests that early detection had little impact on survival; rather, technological improvements (e.g., new medical technologies or more effective use of existing technologies) and changing demographics were responsible for the largest share of the change in 5-year survival in CC and RC between 1992 and 2000. CONCLUSION: Technological advances and changes in patient demographics had the largest impact on improved colorectal cancer survival during the study period.

Trends in healthcare utilization among older Americans with colorectal cancer: a retrospective database analysis.

BACKGROUND: Analyses of utilization trends (cost drivers) allow us to understand changes in colorectal cancer (CRC) costs over time, better predict future costs, identify changes in the use of specific types of care (eg, hospice), and provide inputs for cost-effectiveness models. This retrospective cohort study evaluated healthcare resource use among US Medicare beneficiaries diagnosed with CRC between 1992 and 2002. METHODS: Cohorts included patients aged 66+ newly diagnosed with adenocarcinoma of the colon (n = 52,371) or rectum (n = 18,619) between 1992 and 2002 and matched patients from the general Medicare population, followed until death or December 31, 2005. Demographic and clinical characteristics were evaluated by cancer subsite. Resource use, including the percentage that used each type of resource, number of hospitalizations, and number of hospital and skilled nursing facility days, was evaluated by stage and subsite. The number of office, outpatient, and inpatient visits per person-year was calculated for each cohort, and was described by year of service, subsite, and treatment phase. Hospice use rates in the last year of life were calculated by year of service, stage, and subsite for CRC patients who died of CRC. RESULTS: CRC patients (mean age: 77.3 years; 44.9% male) used more resources than controls in every category (P < .001), with the largest differences seen in hospital days and home health use. Most resource use (except hospice) remained relatively steady over time. The initial phase was the most resource intense in terms of office and outpatient visits. Hospice use among patients who died of CRC increased from 20.0% in 1992 to 70.5% in 2004, and age-related differences appear to have evened out in later years. CONCLUSION: Use of hospice care among CRC decedents increased substantially over the study period, while other resource use remained generally steady. Our findings may be useful for understanding CRC cost drivers, tracking trends, and forecasting resource needs for CRC patients in the future.

Impact of fingolimod on clinical and magnetic resonance imaging outcomes in routine clinical practice: A retrospective analysis of the multiple sclerosis, clinical and MRI outcomes in the USA (MS-MRIUS) study.

BACKGROUND: The effectiveness of fingolimod on clinical and magnetic resonance imaging (MRI) outcomes in patients with multiple sclerosis (MS) has been well established in trials and, to a lesser extent, in the real world. OBJECTIVE: To evaluate clinical and MRI outcomes in patients with relapsing MS receiving fingolimod in US clinical practice. METHODS: Clinical and MRI data from 590 patients initiating fingolimod treatment at 33 MS centers in the USA were retrospectively analyzed. Clinical data were obtained from medical records. MRI data were systematically quantified at a centralized imaging facility. Patients had an index (within 6 months before and 1 month after starting fingolimod) and post-index (9-24 months after starting fingolimod) MRI scan; 184 individuals had a pre-index scan (9-24 months before starting fingolimod). RESULTS: In the index to post-index period, mean annualized relapse rates decreased from 0.36 to 0.13 and disability progression occurred in 18.5% of patients. Median T2, T1 and gadolinium-enhancing lesion volume changed by 1.15%, 2.36%, and -100% between the index and post-index scans, respectively, and median annualized percentage changes in brain volume and lateral ventricular volume were -0.32% and +0.66%, respectively. For patients with pre-index scans, MRI outcomes were unchanged or improved during treatment. Outcomes were generally comparable with those in fingolimod phase 3 trials. CONCLUSION: This real-world study highlights the effectiveness of fingolimod and the feasibility of quantifying clinical and MRI data collected from multiple centers during routine clinical practice on a group level using a systematic, quantitative methodology.

Establishing pathological cut-offs for lateral ventricular volume expansion rates.

Background: A percent brain volume change (PBVC) cut-off of -0.4% per year has been proposed to distinguish between pathological and physiological changes in multiple sclerosis (MS). Unfortunately, standardized PBVC measurement is not always feasible on scans acquired outside research studies or academic centers. Percent lateral ventricular volume change (PLVVC) is a strong surrogate measure of PBVC, and may be more feasible for atrophy assessment on real-world scans. However, the PLVVC rate corresponding to the established PBVC cut-off of -0.4% is unknown. Objective: To establish a pathological PLVVC expansion rate cut-off analogous to -0.4% PBVC. Methods: We used three complementary approaches. First, the original follow-up-length-weighted receiver operating characteristic (ROC) analysis method establishing whole brain atrophy rates was adapted to a longitudinal ventricular atrophy dataset of 177 relapsing-remitting MS (RRMS) patients and 48 healthy controls. Second, in the same dataset, SIENA PBVCs were used with non-linear regression to directly predict the PLVVC value corresponding to -0.4% PBVC. Third, in an unstandardized, real world dataset of 590 RRMS patients from 33 centers, the cut-off maximizing correspondence to PBVC was found. Finally, correspondences to clinical outcomes were evaluated in both datasets. Results: ROC analysis suggested a cut-off of 3.09% (AUC = 0.83, p < 0.001). Non-linear regression R2 was 0.71 (p < 0.001) and a - 0.4% PBVC corresponded to a PLVVC of 3.51%. A peak in accuracy in the real-world dataset was found at a 3.51% PLVVC cut-off. Accuracy of a 3.5% cut-off in predicting clinical progression was 0.62 (compared to 0.68 for PBVC). Conclusions: Ventricular expansion of between 3.09% and 3.51% on T2-FLAIR corresponds to the pathological whole brain atrophy rate of 0.4% for RRMS. A conservative cut-off of 3.5% performs comparably to PBVC for clinical outcomes.

Assessing 'No Evidence of Disease Activity' Status in Patients with Relapsing-Remitting Multiple Sclerosis Receiving Fingolimod in Routine Clinical Practice: A Retrospective Analysis of the Multiple Sclerosis Clinical and Magnetic Resonance Imaging Outcomes in the USA (MS-MRIUS) Study.

BACKGROUND: 'No evidence of disease activity' (NEDA), a composite measure of clinical and magnetic resonance imaging outcomes, provides a comprehensive assessment of disease activity, but is not extensively reported in clinical practice. NEDA-3 is defined as patients with no new/enlarged T2 or gadolinium-enhancing lesions, no relapses, and no disability progression (according to Expanded Disability Status Scale scores). NEDA-4 comprises the components of NEDA-3 and a fourth criterion of ≤ 0.4% annualized brain volume loss. OBJECTIVE: The objective of this study was to assess NEDA status among patients with relapsing-remitting multiple sclerosis receiving fingolimod in clinical practice. METHODS: Clinical and magnetic resonance imaging data were retrospectively collected from 590 patients who initiated fingolimod at 33 multiple sclerosis centers in the USA. Patients were required to have a magnetic resonance imaging scan in the 6 months before or 1 month after fingolimod initiation (index period) and in the 9-24 months after fingolimod initiation (post-index period). Magnetic resonance imaging data were systematically quantified at a centralized reading facility. The proportions of patients with NEDA-3 or NEDA-4 status during fingolimod treatment were assessed. RESULTS: During the follow-up period (median: 16 months), data to assess NEDA-3 and NEDA-4 were available for 586 and 325 patients, respectively. In the post-index period, 58.7% of patients achieved NEDA-3 status (no relapses, 85.2%; no new/enlarged T2/gadolinium-enhancing lesions, 76.3%; no disability progression, 87.9%) and 37.2% achieved NEDA-4 status (no relapses, 86.5%; no new/enlarged T2/gadolinium-enhancing lesions, 78.8%; no disability progression, 91.1%; brain volume loss ≤ 0.4, 58.2%). CONCLUSION: Among patients receiving fingolimod, over half achieved NEDA-3 status and over one-third achieved NEDA-4 status.

No evidence of disease activity in patients receiving fingolimod at private or academic centers in clinical practice: a retrospective analysis of the multiple sclerosis, clinical, and magnetic resonance imaging outcomes in the USA (MS-MRIUS) study.

OBJECTIVE: The impact of multiple sclerosis (MS) center type on outcomes has not been investigated. This study aimed to evaluate baseline characteristics and clinical and magnetic resonance imaging (MRI) outcomes in patients with MS receiving fingolimod over 16 months' follow-up at private or academic centers in the USA. METHODS: Clinical and MRI data collected in clinical practice from patients initiating fingolimod were stratified by center type and retrospectively analyzed. No evidence of disease activity (NEDA-3) was defined as patients with no new/enlarged T2/gadolinium-enhancing lesions, no relapses, and no disability progression (Expanded Disability Status Scale scores). RESULTS: Data were collected for 398 patients from 25 private centers and 192 patients from eight academic centers. Patients were older (median age = 43 vs 41 years; p = .0047) and had a numerically shorter median disease duration (7.0 vs 8.5 years; p = .0985) at private vs academic centers. Annualized relapse rate (ARR) was higher in patients at private than academic centers in the pre-index (0.40 vs 0.29; p = .0127) and post-index (0.16 vs 0.08; p = .0334) periods. The opposite was true for T2 lesion volume in the pre-index (2.86 vs 5.23 mL; p = .0002) and post-index (2.86 vs 5.11 mL; p = .0016) periods; other MRI outcomes were similar between center types. After initiating fingolimod, ARRs were reduced, disability and most MRI outcomes remained stable, and a similar proportion of patients achieved NEDA-3 at private and academic centers (64.1% vs 56.1%; p = .0659). CONCLUSION: Patient characteristics differ between private and academic centers. Over 55% of patients achieved NEDA-3 during fingolimod treatment at both center types.

Fingolimod's Impact on MRI Brain Volume Measures in Multiple Sclerosis: Results from MS-MRIUS.

BACKGROUND AND PURPOSE: Evidence is needed to understand the effect of fingolimod on slowing down brain atrophy progression in multiple sclerosis (MS) patients in clinical practice. We investigated the effect of fingolimod on brain atrophy in MS patients with active disease (clinically and/or magnetic resonance imaging [MRI]) versus no evidence of active disease (NEAD). METHODS: MS and clinical outcome and MRI in the United States (MS-MRIUS) is a multicenter, retrospective study that included 590 relapsing-remitting MS patients, who initiated fingolimod, and were followed for a median of 16 months. Patients with active disease at baseline (245, 41.5%) were defined as those who had one or more relapses in the year previous starting fingolimod, and/or displayed gadolinium enhancing lesions(s) at baseline MRI scan, whereas patients with NEAD at baseline (345, 58.5%) did not fulfill these criteria. Annualized percentage brain volume change (PBVC) and percentage lateral ventricle volume change (PLVVC) over the follow-up were analyzed in both groups. RESULTS: Over the follow-up, the rate of PBVC was -.38% in active disease and -.25% in NEAD patients (P = .076), whereas PLLVC was 1.76% in active disease and .28% in NEAD patients (P = .046). No changes in timed 25-foot walk (P = .619) and Expanded Disability Status Scale (P = .275) scores or MRI lesion accumulation (P > 0.08) were detected, although the active disease group had a higher proportion of relapses during the follow-up period (P = .02). CONCLUSIONS: The study provides real-world evidence that rate of brain atrophy in MS patients with underlying active disease and NEAD in fingolimod treated patients is below the established pathological cutoff for loss of whole brain volume (>-.4%) or expansion of lateral ventricles (> 3.5%).

Angioedema Among Hypertensive Patients Treated with Aliskiren or Other Antihypertensive Medications in the United States.

BACKGROUND: A non-interventional study suggested that use of angiotensin-converting enzyme inhibitors (ACEIs) or aliskiren was associated with an angioedema risk three times that of beta-blockers (BBs). OBJECTIVE: The aim was to assess angioedema incidence rates (IRs) and the relative angioedema risk of aliskiren compared to other antihypertensive drugs (AHDs). METHODS: A cohort study in hypertensive patients with an AHD prescription between 2007 and 2012 was conducted using data from the US PharMetrics Plus™ claims database. Angioedema was identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9CM) code 995.1. Additionally, a nested case-control analysis was conducted to assess the relative angioedema risk of aliskiren or other AHDs versus BBs. RESULTS: A total of 3,090,114 patients were included (aliskiren n = 30,720). There were 15,744 angioedema events (IR 2.28/1000 person-years; 95% confidence interval (CI) 2.24-2.32). Aliskiren IRs were: any aliskiren 2.58 (2.08-3.17), aliskiren monotherapy 1.71 (0.74-3.37), aliskiren fixed-dose combination (FDC) 1.27 (0.41-2.96), and aliskiren free-standing combination (FSC) 2.93 (2.31-3.66). The case-control analysis included 15,100 angioedema cases and 60,400 controls; the angioedema risk for both aliskiren monotherapy and FDC was not significantly different from BBs [adjusted odds ratio (adjOR) 0.99 (95% CI 0.45-2.20) and 1.06 (0.40-2.76)]; aliskiren FSC was associated with an increased angioedema risk [adjOR 3.29 (2.42-4.48)], mainly driven by concomitant ACEI use [adjOR 7.03 (4.10-12.05)]. CONCLUSIONS: The IR and risk of angioedema in patients with aliskiren monotherapy or FDC are comparable to BBs. The higher IR and risk of angioedema identified in the aliskiren FSC group may largely be driven by the concomitant use of ACEIs.

An Observational Study to Assess Brain MRI Change and Disease Progression in Multiple Sclerosis Clinical Practice-The MS-MRIUS Study.

BACKGROUND & PURPOSE: To describe methodology, interim baseline, and longitudinal magnetic resonance imaging (MRI) acquisition parameter characteristics of the multiple sclerosis clinical outcome and MRI in the United States (MS-MRIUS). MATERIAL & METHODS: The MS-MRIUS is an ongoing longitudinal and retrospective study of MS patients on fingolimod. Clinical and brain MRI image scan data were collected from 600 patients across 33 MS centers in the United States. MRI brain outcomes included change in whole-brain volume, lateral ventricle volume, T2- and T1-lesion volumes, and new/enlarging T2 and gadolinium-enhancing lesions. RESULTS: Interim baseline and longitudinal MRI acquisition parameters results are presented for 252 patients. Mean age was 44 years and 81% were female. Forty percent of scans had 3-dimensional (3D) T1 sequence in the preindex period, increasing to 50% in the postindex period. Use of 2-dimensional (2D) T1 sequence decreased over time from 85% in the preindex period to 65% in the postindex. About 95% of the scans with FLAIR and 2D T1-WI were considered acceptable or good quality compared to 99-100% with 3D T1-WI. There were notable changes in MRI hardware, software, and coil (39.5% in preindex to index and 50% in index to postindex). MRI sequence parameters (orientation, thickness, or protocol) differed for 36%, 29%, and 20% of index/postindex scans for FLAIR, 2D T1-WI, and 3D T1-WI, respectively. CONCLUSIONS: The MS-MRIUS study linked the clinical and brain MRI outcomes into an integrated database to create a cohort of fingolimod patients in real-world practice. Variability was observed in MRI acquisition protocols overtime.

Expanding the use of administrative claims databases in conducting clinical real-world evidence studies in multiple sclerosis.

OBJECTIVE: Administrative claims databases provide a wealth of data for assessing the effect of treatments in clinical practice. Our aim was to propose methodology for real-world studies in multiple sclerosis (MS) using these databases. RESEARCH DESIGN AND METHODS: In three large US administrative claims databases: MarketScan, PharMetrics Plus and Department of Defense (DoD), patients with MS were selected using an algorithm identified in the published literature and refined for accuracy. Algorithms for detecting newly diagnosed ('incident') MS cases were also refined and tested. Methodology based on resource and treatment use was developed to differentiate between relapses with and without hospitalization. RESULTS: When various patient selection criteria were applied to the MarketScan database, an algorithm requiring two MS diagnoses at least 30 days apart was identified as the preferred method of selecting patient cohorts. Attempts to detect incident MS cases were confounded by the limited continuous enrollment of patients in these databases. Relapse detection algorithms identified similar proportions of patients in the MarketScan and PharMetrics Plus databases experiencing relapses with (2% in both databases) and without (15-20%) hospitalization in the 1 year follow-up period, providing findings in the range of those in the published literature. LIMITATION: Additional validation of the algorithms proposed here would increase their credibility. CONCLUSIONS: The methods suggested in this study offer a good foundation for performing real-world research in MS using administrative claims databases, potentially allowing evidence from different studies to be compared and combined more systematically than in current research practice.

Healthcare resource use and relapses with fingolimod versus natalizumab for treating multiple sclerosis: a retrospective US claims database analysis.

OBJECTIVE: Healthcare resource utilization in patients with multiple sclerosis (MS) is linked to relapses and disease progression. This retrospective cohort database analysis compared healthcare resource use and proxy measures of relapse outcomes in patients with active disease who switched to fingolimod or natalizumab. METHODS: Using administrative claims data from the US PharMetrics Plus database, we identified patients with an MS diagnosis and a claim for fingolimod or natalizumab between 1 October 2010 and 30 June 2012 (index period) who had experienced a relapse (identified using a claims-based algorithm) and used other disease-modifying therapies (DMTs) in the previous year. Patients in the fingolimod and natalizumab cohorts were propensity score matched (1:1). MS-related inpatient stays, corticosteroid use and the proportion of patients experiencing claims-based relapses were assessed in the pre-index and post-index persistence periods. Time to first claims-based relapse in the post-index persistence period was assessed using a Kaplan-Meier curve. RESULTS: The study included 623 unmatched patients (299 and 324 patients in the fingolimod and natalizumab cohorts, respectively) and 370 matched patients (185 in each cohort). In the matched analysis, MS-related inpatient stays and corticosteroid use were similar in the fingolimod and natalizumab cohorts during the post-index persistence period, and were significantly reduced versus the pre-index period (p < 0.01). A similar proportion of patients in the fingolimod and natalizumab cohorts were free from claims-based relapses in the persistence period (68.1% and 68.6%, respectively). There was no significant difference in the likelihood of experiencing a claims-based relapse (p = 0.8696). LIMITATION: Identification of relapses is based on database claims rather than on clinical assessment. CONCLUSIONS: In analyses of patients with MS with a history of relapse and DMT use, fingolimod and natalizumab reduce healthcare resource utilization and have similar effectiveness in a real-world setting.

Relapse rates in patients with multiple sclerosis switching from interferon to fingolimod or glatiramer acetate: a US claims database study.

BACKGROUND: Approximately one-third of patients with multiple sclerosis (MS) are unresponsive to, or intolerant of, interferon (IFN) therapy, prompting a switch to other disease-modifying therapies. Clinical outcomes of switching therapy are unknown. This retrospective study assessed differences in relapse rates among patients with MS switching from IFN to fingolimod or glatiramer acetate (GA) in a real-world setting. METHODS: US administrative claims data from the PharMetrics Plus™ database were used to identify patients with MS who switched from IFN to fingolimod or GA between October 1, 2010 and March 31, 2012. Patients were matched 1∶1 using propensity scores within strata (number of pre-index relapses) on demographic (e.g. age and gender) and disease (e.g. timing of pre-index relapse, comorbidities and symptoms) characteristics. A claims-based algorithm was used to identify relapses while patients were persistent with therapy over 360 days post-switch. Differences in both the probability of experiencing a relapse and the annualized relapse rate (ARR) while persistent with therapy were assessed. RESULTS: The matched sample population contained 264 patients (n = 132 in each cohort). Before switching, 33.3% of patients in both cohorts had experienced at least one relapse. During the post-index persistence period, the proportion of patients with at least one relapse was lower in the fingolimod cohort (12.9%) than in the GA cohort (25.0%), and ARRs were lower with fingolimod (0.19) than with GA (0.51). Patients treated with fingolimod had a 59% lower probability of relapse (odds ratio, 0.41; 95% confidence interval [CI], 0.21-0.80; p = 0.0091) and 62% fewer relapses per year (rate ratio, 0.38; 95% CI, 0.21-0.68; p = 0.0013) compared with those treated with GA. CONCLUSIONS: In a real-world setting, patients with MS who switched from IFNs to fingolimod were significantly less likely to experience relapses than those who switched to GA.

Estimating effectiveness and cost of biologics for rheumatoid arthritis: application of a validated algorithm to commercial insurance claims.

PURPOSE: The aim of this analysis was to implement a claims-based algorithm to estimate biologic cost per effectively treated patient for biologics approved for moderate to severe rheumatoid arthritis (RA). METHODS: This retrospective analysis included commercially insured adults (aged 18-63 years) with RA in a commercial database, who initiated biologic treatment with abatacept, adalimumab, etanercept, golimumab, or infliximab between 2007 and 2010. The algorithm defined effectiveness as having all of the following: high adherence, no biologic dose increase, no biologic switching, no new nonbiologic disease-modifying antirheumatic drug, no increased or new oral glucocorticoid use, and no more than 1 glucocorticoid injection. For each biologic, cost per effectively treated patient was defined as total drug and administration costs (from allowed amounts on claims), divided by the number of patients categorized as effectively treated. FINDINGS: Of 15,351 patients, 12,018 (78.3%) were women, and the mean (SD) age was 49.7 (9.6) years. The algorithm categorized treatment as effective in the first year for 30% (1899/6374) of etanercept, 30% (1396/4661) of adalimumab, 20% (560/2765) of infliximab, 27% (361/1338) of abatacept, and 29% (62/213) of golimumab treated patients. The 1-year biologic cost per effectively treated patient, as defined by the algorithm, was nominally lower for subcutaneously injected biologics than for infused biologics. The 1-year biologic cost per effectively treated patient, as defined by the algorithm, was lowest for etanercept ($49,952), followed by golimumab ($50,189), adalimumab ($52,858), abatacept ($71,866), and infliximab ($104,333). IMPLICATIONS: Algorithm-defined effectiveness was similar for biologics other than infliximab. The 1-year biologic cost per effectively treated patient, as defined by the algorithm, was nominally lower for subcutaneously injected biologics than for infused biologics.

Persistence with and adherence to fingolimod compared with other disease-modifying therapies for the treatment of multiple sclerosis: a retrospective US claims database analysis.

OBJECTIVE: Achieving therapeutic goals in multiple sclerosis (MS) requires strict adherence to treatment schedules. This retrospective study analyzed persistence with, and adherence to, fingolimod compared with injectable/infusible disease-modifying therapies (DMTs) in patients with MS. METHODS: Patients in the PharMetrics Plus™ US administrative claims database with at least one prescription for, or administration of, fingolimod, glatiramer acetate (GA), interferon (IFN), or natalizumab (index DMT) between October 1, 2010 and September 30, 2011 were included. Patients were naïve to index DMT (no claim in the previous 360 days) and had an MS diagnosis code within 360 days of the first index DMT prescription. Outcomes were persistence, risk of discontinuing index DMT (evaluated by a Cox proportional hazards model), adherence (measured using the medication possession ratio [MPR] and proportion of days covered [PDC] in patients with at least two index DMT prescriptions), and the risk of being non-adherent (MPR <80% and PDC <80%, assessed using a logistic regression model). RESULTS: The study included 3750 patients (fingolimod, n = 889; GA, n = 1233; any IFN, n = 1341; natalizumab, n = 287). Discontinuation rates (fingolimod, 27.9%; GA, 39.5%; IFN, 43.7%; natalizumab, 39.5%; all p < 0.001) and risk of discontinuation were significantly higher (hazard ratios vs fingolimod [95% confidence interval]: GA, 1.75 [1.49-2.07]; IFN, 2.01 [1.71-2.37]; natalizumab, 1.53 [1.22-1.91]) for patients receiving other DMTs compared with fingolimod. The risk of being non-adherent was also lower for patients in the fingolimod cohort than the other treatment cohorts, irrespective of whether non-adherence was defined as MPR <80% (p < 0.05 for all) or PDC <80% (p < 0.05 for GA and IFN). LIMITATIONS: As with all studies assessing real-world treatment patterns it is unclear if medications were used as prescribed. CONCLUSIONS: In a real-world setting, persistence with, and adherence to, oral fingolimod was higher than for injectable and infusible DMTs.

Use of a validated algorithm to estimate the annual cost of effective biologic treatment for rheumatoid arthritis.

OBJECTIVES: To estimate biologic cost per effectively treated patient with rheumatoid arthritis (RA) using a claims-based algorithm for effectiveness. METHODS: Patients with RA aged 18-63 years in the IMS PharMetrics Plus database were categorized as effectively treated if they met all six criteria: (1) a medication possession ratio ≥80% (subcutaneous) or at least as many infusions as specified in US labeling (intravenous); (2) no biologic dose increase; (3) no biologic switch; (4) no new non-biologic disease-modifying anti-rheumatic drug; (5) no new or increased oral glucocorticoid; and (6) ≤1 glucocorticoid injection. Biologic cost per effectively treated patient was defined as total cost of the index biologic (drug plus intravenous administration) divided by the number of patients categorized by the algorithm as effectively treated. Similar methods were used for the index biologic in the second year and for a second biologic after a switch. RESULTS: Rates that the index biologic was categorized as effective in the first year were 31.0% etanercept (2243/7247), 28.6% adalimumab (1426/4991), 28.6% abatacept (332/1160), 27.2% golimumab (71/261), and 20.2% infliximab (474/2352). Mean biologic cost per effectively treated patient, per the algorithm, was $50,141 etanercept, $53,386 golimumab, $56,942 adalimumab, $73,516 abatacept, and $114,089 infliximab. Biologic cost per effectively treated patient, using this algorithm, was lower for patients who continued the index biologic in the second year and higher after switching. CONCLUSIONS: When a claims-based algorithm was applied to a large commercial claims database, etanercept was categorized as the most effective and had the lowest estimated 1-year biologic cost per effectively treated patient. This proxy for effectiveness from claims databases was validated against a clinical effectiveness scale, but analyses of the second year or the year after a biologic switch were not included in the validation. Costs of other medications were not included in cost calculations.