A machine-learning algorithm using claims data to identify patients with homozygous familial hypercholesterolemia.

Homozygous familial hypercholesterolemia (HoFH) is an underdiagnosed and undertreated ultra-rare disease. We utilized claims data from the Komodo Healthcare Map database to develop a machine-learning model to identify potential HoFH patients. We tokenized patients enrolled in MyRARE (patient support program for those prescribed evinacumab-dgnb in the United States) and linked them with their Komodo claims. A true positive HoFH cohort (n = 331) was formed by including patients from MyRARE and patients with prescriptions for evinacumab-dgnb or lomitapide. The negative cohort (n = 1423) comprised patients with or at risk for cardiovascular disease. We divided the cohort into an 80% training and 20% testing set. Overall, 10,616 candidate features were investigated; 87 were selected due to clinical relevance and importance on prediction performance. Different machine-learning algorithms were explored, with fast interpretable greedy-tree sums selected as the final machine-learning tool. This selection was based on its satisfactory performance and its easily interpretable nature. The model identified four useful features and yielded precision (positive predicted value) of 0.98, recall (sensitivity) of 0.88, area under the receiver operating characteristic curve of 0.98, and accuracy of 0.97. The model performed well in identifying HoFH patients in the testing set, providing a useful tool to facilitate HoFH screening and diagnosis via healthcare claims data.

Serum cholesterol and the risk of developing hormonally driven cancers: A narrative review.

Although cholesterol has been hypothesized to promote cancer development through several potential pathways, its role in the risk of developing hormonally driven cancer is controversial. This literature review summarizes evidence from the highest quality studies to examine the consistency and strength of the relationship between serum cholesterol parameters and incidence of hormonally driven cancer. Articles were identified using EMBASE. Longitudinal observational studies published between January 2000 and December 2020 were considered for inclusion. The endpoint of interest was incident prostate, ovary, breast, endometrium, and uterine cancers. In total, 2732 reports were identified and screened; 41 studies were included in the review. No associations were found for ovarian cancer. Most endometrial cancer studies were null. The majority (76.9%) of studies reported no association between cholesterol and prostate cancer. Data on breast cancer were conflicting, associations limited, and effect sizes modest. Our results do not provide evidence for a clear association between cholesterol and different types of incident, hormonally driven reproductive cancers. Future studies should investigate the impact of lipid-lowering therapy.

The prevalence of low muscle mass associated with obesity in the USA.

BACKGROUND: Sarcopenia is defined as age-related low muscle mass and function, and can also describe the loss of muscle mass in certain medical conditions, such as sarcopenic obesity. Sarcopenic obesity describes loss of muscle and function in obese individuals; however, as sarcopenia is an age-related condition and obesity can occur in any age group, a more accurate term is obesity with low lean muscle mass (OLLMM). Given limited data on OLLMM (particularly in those aged < 65 years), the purpose of this study was to estimate the prevalence of OLLMM in adults aged ≥ 20 years in the USA. METHODS: Data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 and 1999-2006 were used. OLLMM was defined as an appendicular lean mass, adjusted for body mass index (BMI), cut-off point < 0.789 for males and < 0.512 for females, measured by dual-energy X-ray absorptiometry (DXA). DXA was only measured in individuals 20-59 years old in NHANES 2017-2018; we therefore utilized logistic regression models to predict OLLMM from NHANES 1999-2006 for those aged ≥ 60 years. The prevalence of OLLMM was estimated overall, and by sex, age, race/ethnicity, and clinical subgroup (high BMI, prediabetes, type 2 diabetes mellitus [T2DM], non-alcoholic fatty liver disease [NAFLD] with fibrosis, or post-bariatric surgery). Prevalence estimates were extrapolated to the USA population using NHANES sampling weights. RESULTS: We estimated that, during 2017-2018, 28.7 million or 15.9% of the USA population had OLLMM. The prevalence of OLLMM was greater in older individuals (8.1%, aged 20-59 years vs 28.3%, aged ≥ 60 years), highest (66.6%) in Mexican-American females aged ≥ 60 years, and lowest (2.6%) in non-Hispanic Black males aged 20-59 years. There was a higher prevalence of OLLMM in adults with prediabetes (19.7%), T2DM (34.5%), NAFLD with fibrosis (25.4%), or post-bariatric surgery (21.8%), compared with those without each condition. CONCLUSIONS: Overall, the burden of OLLMM in the USA is substantial, affecting almost 30 million adults. The prevalence of OLLMM increased with age, and among those with prediabetes, T2DM, NAFLD with fibrosis, or post-bariatric surgery. A unified definition of OLLMM will aid diagnosis and treatment strategies.

Quantifying Importance of Major Risk Factors for Coronary Heart Disease.

BACKGROUND: To optimize preventive strategies for coronary heart disease (CHD), it is essential to understand and appropriately quantify the contribution of its key risk factors. Our objective was to compare the associations of key modifiable CHD risk factors-specifically lipids, systolic blood pressure (SBP), diabetes mellitus, and smoking-with incident CHD events based on their prognostic performance, attributable risk fractions, and treatment benefits, overall and by age. METHODS: Pooled participant-level data from 4 observational cohort studies sponsored by the National Heart, Lung, and Blood Institute were used to create a cohort of 22 626 individuals aged 45 to 84 years who were initially free of cardiovascular disease. Individuals were followed for 10 years from baseline evaluation for incident CHD. Proportional hazards regression was used to estimate metrics of prognostic model performance (likelihood ratio, C index, net reclassification, discrimination slope), hazard ratios, and population attributable fractions for SBP, non-high-density lipoprotein cholesterol (non-HDL-C), diabetes mellitus, and smoking. Expected absolute risk reductions for antihypertensive and lipid-lowering treatment were assessed. RESULTS: Age, sex, and race capture 63% to 80% of the prognostic performance of cardiovascular risk models. In contrast, adding either SBP, non-HDL-C, diabetes mellitus, or smoking to a model with other risk factors increases the C index by only 0.004 to 0.013. However, primordial prevention could have a substantial effect as demonstrated by population attributable fractions of 28% for SBP≥130 mm Hg and 17% for non-HDL-C≥130 mg/dL. Similarly, lowering the SBP of all individuals to <130 mm Hg or lowering low-density lipoprotein cholesterol by 30% would be expected to lower a baseline 10-year CHD risk of 10.7% to 7.0 and 8.0, respectively (absolute risk reductions: 3.7% and 2.7%, respectively). Prognostic performance decreases with age (C indices for age groups 45-54, 55-64, 65-74, 75-84 are 0.75, 0.72, 0.66, and 0.62, respectively), whereas absolute risk reductions increase (SBP: 1.1%, 2.3%, 5.4%, 10.3%, respectively; non-HDL-C: 1.1%, 2.0%, 3.7%, 5.9%, respectively). CONCLUSIONS: Although individual modifiable CHD risk factors contribute only modestly to prognostic performance, our models indicate that eliminating or controlling these individual factors would lead to substantial reductions in total population CHD events. Metrics used to judge importance of risk factors should be tailored to the research objectives.

Use of Lipid-modifying Therapy and LDL-C Goal Attainment in a High-Cardiovascular-Risk Population in the Netherlands.

PURPOSE: This study investigates lipid-modifying therapy (LMT) and LDL-C goal attainment in a real-world, high-cardiovascular-risk population in the Netherlands. METHODS: From the PHARMO Database Network, patients aged ≥18 years with an LDL-C measurement in 2012 (index date) were selected and hierarchically classified into the following mutually exclusive high-cardiovascular-risk categories: familial hypercholesterolemia (FH), recent acute coronary syndrome (ACS), coronary heart disease, ischemic stroke, peripheral arterial disease, and diabetes mellitus. LMT use and LDL-C goal attainment at the index date was assessed. FINDINGS: Of 61 839 patients who met the inclusion criteria, 1132 (2%) had FH, 2431 (4%) had recent ACS, 6292 (10%) had coronary heart disease, 2868 (5%) had ischemic stroke, 3017 (5%) had peripheral arterial disease, and 46 099 (75%) had diabetes mellitus. Overall, 67% of patients were receiving LMT. Use of LMT ranged from 77% for recent ACS to 53% for FH, and standard-potency statins were the most prescribed. The percentage attaining an LDL-C goal of <100 mg/dL was 55%, ranging from 23% (FH) to 58% (recent ACS). Among LMT users, 69% taking high-potency statins, 70% taking standard-potency statins, and 20% receiving nonstatin LMTs attained an LDL-C goal of <100 mg/dL. IMPLICATIONS: LMT use among high-cardiovascular-risk patients was modest, which contributed to 46% of the cohort failing to reach LDL-C goals <100 mg/dL. Underuse and suboptimal use of LMTs in this cohort represent opportunities for quality improvement programs aimed at reducing the risk of cardiovascular events.

Healthcare Utilization and Costs of Knee or Hip Replacements versus Pain-Relief Injections.

BACKGROUND: Given the dramatic increase in total knee and hip replacement procedures among the US population aged 45 years and older, there is a need to compare the downstream healthcare utilization and costs between patients who undergo joint replacement and those who receive intraarticular injections as a low-cost alternative. OBJECTIVE: To compare changes in osteoarthritis (OA)-related healthcare utilization and costs for Medicare members with OA who underwent knee or hip replacement versus those receiving steroid or viscosupplementation injections. METHODS: Medicare members aged ≥45 years diagnosed with OA were identified for this retrospective longitudinal study. Data were compared for patients who underwent primary knee or hip replacement surgery between July 1, 2007, and June 30, 2012, and those receiving injection of pain-relief medication during the same period. The date of joint replacement surgery was considered the index date. For the comparison cohort, the index date was 180 days postinjection of the first intraarticular injection. Medical and pharmacy claims were examined longitudinally in 90-day increments, from 180 days preindex until 360 days postindex. Difference-in-difference analyses were conducted to compare the change in OA-related healthcare costs, postindex versus preindex, between the study cohorts. Time-to-event analyses were used to measure rates of readmissions and venous thromboembolism (VTE). RESULTS: The mean age was 70.7 years for patients with knee replacement, 71.7 years for those with hip replacement, and 71.1 years for those receiving pain-relief injection (P <.0001). The RxRisk-V comorbidity index scores were 4.7, 4.4, and 4.8, respectively (P <.0001). Difference-in-difference analyses indicated that decreases in OA-related costs were greater for the joint replacement cohorts (coefficient for knee replacement*time: -0.603; hip replacement*time: -0.438; P <.001 for both) than for the comparison cohort. The VTE rates were 5.6% (knee) and 5.1% (hip) postsurgery versus 1.4% (knee) and 1.3% (hip) presurgery. CONCLUSION: The overall difference-in-difference results showed a greater decrease in healthcare utilization and costs for the members with joint replacement than for those receiving injection.

Patterns of health care utilization for low back pain.

BACKGROUND: The purpose of this study was to determine if primary care patients with low back pain (LBP) cluster into definable care utilization subgroups that can be explained by patient and provider characteristics. MATERIALS AND METHODS: Adult primary care patients with an incident LBP encounter were identified from Geisinger Clinic electronic health records over 5 years. Two-thirds of the cohort had only one to two encounters. Principal component analysis was applied to the data from the remaining one-third on use of ambulatory, inpatient, emergency department, and surgery care and use of magnetic resonance imaging, injections, and opioids in 12 months following the incident encounter. Groups were compared on demographics, health behaviors, chronic and symptomatic disease burden, and a measure of physician efficiency. RESULTS: Six factors with eigenvalues >1.5 explained 71% of the utilization variance. Patient subgroups were defined as: 1-2 LBP encounters; 2+ surgeries; one surgery; specialty care without primary care; 3+ opioid prescriptions; laboratory dominant care; and others. The surgery and 3+ opioid subgroups, while accounting for only 10.4% of the cohort, had used disproportionately more magnetic resonance imaging, emergency department, inpatient, and injectable resources. The specialty care subgroup was characterized by heavy use of inpatient care and the lowest use of injectables. Anxiety disorder and depression were not more prevalent among the surgery patients than in the others. Surgery patients had features in common with specialty care patients, but were older, had higher prevalence of Fibromyalgia, and were associated primary care physicians with worse efficiency scores. CONCLUSION: LBP care utilization is highly variable and concentrated in small subgroups using disproportionate amounts of potentially avoidable care that reflect both patient and provider characteristics.

Health care costs in patients with fibromyalgia on pregabalin vs. duloxetine.

BACKGROUND: The economic burden associated with fibromyalgia in the U.S. is substantial. The objective of this study was to compare changes in health care costs in fibromyalgia patients initiated on pregabalin and duloxetine in real-world settings. METHODS: Patients (≥ 18 years old) initiating pregabalin or duloxetine between June 1, 2007 and December 31, 2008 were identified using a U.S. managed care database. Patients were selected if they had ≥ 2 medical claims for fibromyalgia (ICD-9-CM, 729.1) at least 90 days apart or ≥ 1 claim for fibromyalgia followed within 30 days by a pharmacy claim for pregabalin. The date of the first pregabalin or duloxetine prescription was defined as the index date, and continuous enrollment for 6-month pre- and postindex periods was required. RESULTS: A total of 1,616 pregabalin and 207 duloxetine patients were identified. Treatment differences between pregabalin and duloxetine in the pre-/postindex change in mean [SD] all-cause total health care costs ($1,307 [16,747] vs. -$158 [17,337]; P = 0.24) or fibromyalgia-related total health care costs ($584 [3,834] vs. $759 [2,133]; P = 0.32) were not significant. Multivariate analysis using difference-in-differences models showed no significant difference in all-cause costs (mean cost ratio = 1.05, 95% CI: 0.84 to 1.31) or fibromyalgia-related costs (0.85, 95% CI: 0.61 to 1.18) between treatments during the postindex period. CONCLUSION: No significant differences were found between pregabalin and duloxetine in the pre- to postindex change in mean all-cause or fibromyalgia-related total health care costs.

Health outcomes and costs among employees with fibromyalgia treated with pregabalin vs. standard of care.

OBJECTIVE: To compare comorbidities, drug use, benefit costs, absences, medication persistence/adherence between employees with fibromyalgia initiating treatment with pregabalin (PGB) vs. antidepressant Standard of Care ([SOC] amitriptyline, duloxetine, or venlafaxine). METHODS: Retrospective study of 240 adults initiating PGB or SOC after 7/1/2007. Multivariate regression models on propensity-score-matched cohorts compared postindex costs, absences, and adherence between cohorts. RESULTS: Pregabalin users had significantly more preindex muscle pain and dizziness and less depression than SOC (each P < 0.05). Use of some non-PBG/SOC drugs differed. No differences were found in total medical, drug, or absenteeism cost. PGB had more sick leave (9.8 vs. 6.8 days, P = 0.04), but other absence types were similar. All adherence metrics were nonsignificantly greater for PGB vs. SOC. CONCLUSION: Despite several comorbidity and drug use differences, most employee benefit outcomes and adherence did not differ between the cohorts.

Real-world evaluation of health-care resource utilization and costs in employees with fibromyalgia treated with pregabalin or duloxetine.

OBJECTIVE: To evaluate changes in health-care resource use and costs after initiating pregabalin or duloxetine in employees with fibromyalgia (FM). METHODS: Employees (18 to 64 years old) with at least one claim for an FM-attributable medication within 60 days following an FM diagnosis were identified using the Thomson Reuters MarketScan(®) Commercial Database (2006 to 2008). Patients newly initiated on pregabalin were propensity score matched to patients newly initiated on duloxetine. These treatment cohorts were evaluated for changes between the 6-month pre- and post-initiation periods in health-care utilization including prescriptions, imputed medically related work loss and expenditures. Pre- to post-initiation changes were compared between pregabalin and duloxetine using a difference-in-difference approach based on univariate statistics and multivariable models. RESULTS: A total of 731 employees with FM initiated on pregabalin (89.9% female, mean age 47.1±9.7 years) were matched with 731 employees initiated on duloxetine (89.5% female, mean age 47.1±9.8 years); other demographic and clinical characteristics were also comparable between cohorts. The adjusted marginal effects were not statistically significant for pre- to post-changes in opioid utilization (P=0.856), number of FM-attributable (P=0.151) or FM-related medications (P=0.462), and all-cause (P=0.323) or FM-attributable (P=0.991) expenditures. Pregabalin was associated with a significantly lower probability of any medically related work loss of 3.2 percentage points (P=0.030) compared with duloxetine, but changes in indirect costs were not significantly different (P=0.600). CONCLUSIONS: The changes in health resource utilization and costs after initiation of pregabalin were not significantly different than the changes observed after initiation of duloxetine. These results not only demonstrate an overall similarity of resource utilization, but also suggest cost neutrality between pregabalin and duloxetine.

Badger Heart Program: health screenings targeted to increase cardiovascular awareness in women at four northern sites in Wisconsin.

PURPOSE: This study reports the results of initial statewide health screenings of the Badger Heart Program (BHP), which aims to increase the cardiovascular health awareness and health status of women living in Wisconsin. METHODS: In May 2004, the BHP provided cardiovascular disease risk screenings to women in 4 geographic areas throughout Wisconsin. Screening participants were informed of their results and counseled on issues concerning diet, exercise, smoking cessation, medications, and/or visiting their primary health care professional. Data collected included total cholesterol, high-density lipoproteins, low-density lipoproteins (LDL), triglycerides, blood pressure (BP), blood glucose measurements, height and weight, along with a brief survey of medical history, family history, smoking status, and current medication use. After the screening, participants were asked to volunteer for an opt-in 6-month educational program. RESULTS: A total of 318 women participated. The majority screened were Caucasian (95.9%) with an average age of 58 years (standard deviation [SD] = 13.2). Participants' blood pressure and LDL goals were determined from the risk profile assessment. According to national guidelines, an optimal blood pressure goal of < 140/90 was recommended for the majority of the participants (294 [92.5%]), while an optimal blood pressure goal of < 120/80 was recommended for only 24 (7.5%) participants. An optimal LDL value <100 was recommended for 48 (15.4%) participants, an LDL goal of <130 was recommended for 106 (33.3%), and an LDL goal of less than <160 was recommended for 157 (50.5%) participants. Of screened participants, 35% were not at BP goal, 32.4% were not at LDL goal, and 53.5% were not at both goals. CONCLUSION: While the number of participants who were at BP and/or LDL goal is higher than what is generally reported in the literature, there is still opportunity for significant improvement. A follow-up analysis including re-screening of individuals aimed at measuring the improvements in CVD profile post educational interventions will occur in November.