The clinical and economic burdens of metabolic dysfunction-associated steatohepatitis.

AIMS: This study aimed to assess and compare the health care resource utilization (HCRU) and medical cost of metabolic dysfunction-associated steatohepatitis (MASH) by disease severity based on Fibrosis-4 Index (FIB-4) score among US adults in a real-world setting. MATERIALS AND METHODS: This observational cohort study used claims data from the Healthcare Integrated Research Database (HIRD) to compare all-cause, cardiovascular (CV)-related, and liver-related HCRU, including hospitalization, and medical costs stratified by FIB-4 score among patients with MASH (identified by International Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] code K75.81). Hospitalization and medical costs were compared by FIB-4 score using generalized linear regression with negative binomial and gamma distribution models, respectively, while controlling for confounders. RESULTS: The cohort included a total of 5,104 patients with MASH and comprised 3,162, 1,343, and 599 patients with low, indeterminate, and high FIB-4 scores, respectively. All-cause hospitalization was significantly higher in the high FIB-4 cohort when compared with the low FIB-4 reference after covariate adjustment (rate ratio, 1.63; 95% CI, 1.32-2.02; p < .0001). CV-related hospitalization was similar across all cohorts; however, CV-related costs were 1.26 times higher (95% CI, 1.11-1.45; p < .001) in the indeterminate cohort and 2.15 times higher (95% CI, 1.77-2.62; p < .0001) in the high FIB-4 cohort when compared with the low FIB-4 cohort. Patients with indeterminate and high FIB-4 scores had 2.97 (95% CI, 1.78-4.95) and 12.08 (95% CI, 7.35-19.88) times the rate of liver-related hospitalization and were 3.68 (95% CI, 3.11-4.34) and 33.73 (95% CI, 27.39-41.55) times more likely to incur liver-related costs, respectively (p < .0001 for all). LIMITATIONS: This claims-based analysis relied on diagnostic coding accuracy, which may not capture the presence of all diseases or all care received. CONCLUSIONS: High and indeterminate FIB-4 scores were associated with significantly higher liver-related clinical and economic burdens than low FIB-4 scores among patients with MASH.

MASH is a serious liver disease that can lead to fibrosis, cirrhosis, and other complications. There is a need to understand the impact of disease severity on the burden of MASH. Health care claims data were used to assess the use of medical resources, including hospitalization, and medical costs among patients with 3 different levels of severity of MASH, as assessed via FIB-4 score. FIB-4 is a widely available non-invasive marker of severity. Rates of all-cause, cardiovascular-related and liver-related hospitalization and medical costs were several-fold higher in patients with high disease severity of MASH than those with low disease severity of MASH.

Cardiovascular risk prediction model and stratification in patients with type 2 diabetes enrolled in a Medicare Advantage plan.

BACKGROUND: Cardiovascular (CV) risk tools have been developed both nationally and internationally to identify patients at risk for developing CV disease or experiencing a CV event. However, these tools vary widely in the definitions of endpoints, the time at which the endpoints are measured, patient populations, and their validity. The primary limitation of some of the most commonly utilized tools is the lack of specificity for a type 2 diabetes (T2D) population and/or among older patients. OBJECTIVE: To develop a predictive model within an older population of patients with T2D to identify patients at risk for CV events. METHODS: This retrospective cohort study used claims, laboratory, and enrollment data during the 2011-2018 study period. Patients with T2D were identified based on diagnoses and/or medications from 2012-2013. The patient cohort was split into 3 different datasets. The holdout dataset included only those patients residing in the northeastern United States. The rest of the sample was then randomly split: 70% for the training dataset, which were used to fit the predictive model, and 30% for the test dataset to assess internal validity. The primary outcome was the first composite CV event defined as at least 1 of the following: inpatient hospitalization for myocardial infarction, ischemic stroke, unstable angina, or heart failure; or any evidence of revascularization. A survival model for the composite outcome was fitted with baseline demographic and clinical characteristics prognostic for the dependent variable utilizing augmented backwards elimination. For assessing model performance, accuracy, sensitivity, specificity, and the c-statistic were used. Patients were ranked as having a low, moderate, or high probability of a future CV event. RESULTS: A total of 362,791 patients were identified. The holdout dataset included only those patients residing in the northeastern United States (n = 8,303). There were 248,142 patients included in the training dataset and 106,346 patients in the test dataset. The proportion with at least 1 observed composite CV event was 20.9%. The final model included 42 variables. The c-statistic was 0.68, and the accuracy, sensitivity, and specificity were approximately 63%. Results were consistent across the training, test, and holdout samples. The optimal cut points minimizing the difference in sensitivity and specificity for low-, moderate-, and high-risk future CV events were determined to be less than 0.18, 0.18-0.63, and greater than 0.63, respectively, in the training dataset at 5 years. The 5-year observed event risk was 11%, 27%, and 51% for patients classified as low, moderate, and high risk of a future CV event, respectively. CONCLUSIONS: A model predicting CV events among older patients with T2D using administrative claims to identify those at risk may be used for focusing interventions to prevent future events. DISCLOSURES: This study was funded by Boehringer Ingelheim (BI) and conducted as part of the BI-Humana Research Collaboration. Caplan is employed by Humana Healthcare Research, Inc., a wholly owned subsidiary of Humana Inc., which received fees to conduct the study from the sponsor BI. At the time of the study, Hayden and Harvey were employees of Humana Healthcare Research, Inc. Additionally, Prewitt, who owns stock in Humana Inc, and Chiguluri are employees of Humana Inc. Kattan, associated with the Cleveland Clinic in Ohio, served as a consultant to BI, and Pimple and Goss are employees of BI. Luthra was employed by BI for the duration of the study. Portions of this work were accepted as an abstract and presented as a poster at the American Diabetes Association 2020 virtual meeting, June 12-16, 2020.

Assessing risk of future cardiovascular events, healthcare resource utilization and costs in patients with type 2 diabetes, prior cardiovascular disease and both.

BACKGROUND: Description of risk of cardiovascular (CV) events associated with diabetes is evolving. This US-based real-world study estimated risk of future CV events and heart failure (HF) from type 2 diabetes (T2DM) only, prior CV events only or T2DM plus prior CV events, versus controls, and evaluated healthcare resource utilization (HCRU) and costs. METHODS AND MATERIALS: This retrospective cohort study queried claims and mortality data for 638,301 patients: T2DM only (377,205); prior CV events only (130,964); both T2DM and prior CV events (130,132); and matched (1:1) controls, during 1 January 2012-31 December 2012. Cardiovascular diagnoses/events and death were assessed individually, and as composite endpoint (myocardial infarction [MI], stroke, transient ischemic attack [TIA], peripheral artery disease [PAD]), during follow-up, ending 31 July 2018. RESULTS: Adjusting for age and gender, patients with T2DM only were 1.6, prior CV events only 2.5 and T2DM plus prior CV events 3.8 times likelier to have primary composite CV events relative to controls, p < .001. HF development was elevated across all three cohorts. Adjusted results showed inpatient admissions for T2DM only, CV events only and T2DM plus prior CV events were 1.37, 2.76 and 3.63 times greater than controls, respectively. All-cause healthcare costs were highest in the T2DM plus prior CV events cohort ($2783 per patient per month [PPPM]) followed by the prior CV events only ($1910 PPPM) and T2DM only cohorts ($1343 PPPM), and controls ($825 PPPM). Adjusted all-cause total costs were 1.48 for T2DM only, 1.49 for prior CV events only and 1.93 for T2DM plus prior CV events times higher compared to controls. CONCLUSION: In this large and geographically broad US based cohort, CV risk for T2DM patients was elevated, as was the risk for patients with prior CV events, while patients with T2DM plus prior CV events had the highest risk of future CV events. The substantial clinical and economic burden of CV events and HF in patients with both T2DM and prior CV events suggest a need for an integrated treatment and targeted intervention across both conditions.

Spirometry evaluation to assess performance of a claims-based predictive model identifying patients with undiagnosed COPD.

BACKGROUND: A claims-based model to predict patients likely to have undiagnosed COPD was developed by Moretz et al in 2015. This study aims to assess the performance of the aforementioned model using prospectively collected spirometry data. METHODS: A study population aged 40-89 years enrolled in a Medicare Advantage plan with prescription drug coverage or commercial health plan and without a claim for COPD diagnosis was identified from April 1, 2012 to March 31, 2016 in the Humana claims database. This population was stratified into subjects likely or unlikely to have undiagnosed COPD using the claims-based predictive model. Subjects were randomly selected for spirometry evaluation of FEV1 and FVC. The predictive model was validated using airflow limitation ratio (FEV1/FVC <0.70). RESULTS: A total of 218 subjects classified by the predictive model as likely and 331 not likely to have undiagnosed COPD completed spirometry evaluation. Those predicted to have undiagnosed COPD had a higher mean age (70.2 vs 67.9 years, P=0.0012) and a lower mean FEV1/FVC ratio (0.724 vs 0.753, P=0.0002) compared to those predicted not to have undiagnosed COPD. Performance metrics for the predictive model were: area under the curve =0.61, sensitivity =52.5%, specificity =64.6%, positive predictive value =33.5%, and negative predictive value =80.1%. CONCLUSION: The claims-based predictive model identifies those not at risk of having COPD eight out of ten times, and those who are likely to have COPD one out of three times.

Initiation of triple therapy maintenance treatment among patients with COPD in the US.

BACKGROUND: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommends triple therapy (long-acting muscarinic receptor antagonists, long-acting beta-2 agonists, and inhaled corticosteroids) for patients with only the most severe COPD. Data on the proportion of COPD patients on triple therapy and their characteristics are sparse and dated. Objective 1 of this study was to estimate the proportion of all, and all treated, COPD patients receiving triple therapy. Objective 2 was to characterize those on triple therapy and assess the concordance of triple therapy use with GOLD guidelines. PATIENTS AND METHODS: This retrospective study used claims from the IMS PharMetrics Plus database from 2009 to 2013. Cohort 1 was selected to assess Objective 1 only; descriptive analyses were conducted in Cohort 2 to answer Objective 2. A validated claims-based algorithm and severity and frequency of exacerbations were used as proxies for COPD severity. RESULTS: Of all 199,678 patients with COPD in Cohort 1, 7.5% received triple therapy after diagnosis, and 25.5% of all treated patients received triple therapy. In Cohort 2, 30,493 COPD patients (mean age =64.7 years) who initiated triple therapy were identified. Using the claims-based algorithm, 34.5% of Cohort 2 patients were classified as having mild disease (GOLD 1), 40.8% moderate (GOLD 2), 22.5% severe (GOLD 3), and 2.3% very severe (GOLD 4). Using exacerbation severity and frequency, 60.6% of patients were classified as GOLD 1/2 and 39.4% as GOLD 3/4. CONCLUSION: In this large US claims database study, one-quarter of all treated COPD patients received triple therapy. Although triple therapy is recommended for the most severe COPD patients, spirometry is infrequently assessed, and a majority of the patients who receive triple therapy may have only mild/moderate disease. Any potential overprescribing of triple therapy may lead to unnecessary costs to the patient and health care system.

Differences in Health Care Use and Costs Among Patients With Cancer Receiving Intravenous Chemotherapy in Physician Offices Versus in Hospital Outpatient Settings.

PURPOSE: The current shift in site of care from community oncology practices to the hospital outpatient department to deliver oncology services may have significant implications for the economic and clinical outcomes of cancer care. Therefore, this study compares health care use and costs among patients with cancer receiving intravenous (IV) chemotherapy in physician offices (PO) versus in hospital outpatient settings (HOP). METHODS: This retrospective study, which was based on medical and pharmacy claims data, included patients (age, 18 to 64 years) initiating IV chemotherapy/biologic treatment between January 1, 2006, and August 31, 2012, who were diagnosed with early or metastatic breast cancer, metastatic lung cancer, metastatic colorectal cancer, or non-Hodgkin lymphoma or chronic lymphocytic leukemia. Patients were assigned to PO or HOP groups on the basis of where they received > 95% of their IV cancer therapy. RESULTS: The study sample included 18,740 patients (12,899 PO; 5,841 HOP) who had a mean age of 51.6 years and a Deyo-Charlson Comorbidity Index score of 5.37. Overall office visits (21.8 ± 13.8 PO v 21.2 ± 12.9, P < .005) and outpatient services (50.8 ± 35.5 PO v 48.5 ± 33.6, P < .001) were higher in the PO group than in the HOP group. Cancer-related inpatient hospitalizations (0.6 ± 1.2 PO v 0.7 ± 1.4 HOP, P = .002) were lower in the PO group than in the HOP group. Although quality-of-care metrics were similar between the HOP and PO groups, follow-up all-cause costs ($82,773 PO v $122,473 HOP) and cancer-related health care costs ($69,037 PO v $108,177 HOP) were higher in the HOP group than in the PO group. CONCLUSION: Despite similar resource use, all-cause and cancer-related health care costs in HOP were significantly higher compared with those in PO settings.