Identification of Patients with Statin Intolerance in a Managed Care Plan: A Comparison of 2 Claims-Based Algorithms.

BACKGROUND: While statins are safe and efficacious, some patients may experience statin intolerance or treatment-limiting adverse events. Identifying patients with statin intolerance may allow optimal management of cardiovascular event risk through other strategies. Recently, an administrative claims data (ACD) algorithm was developed to identify patients with statin intolerance and validated against electronic medical records. However, how this algorithm compared with perceptions of statin intolerance by integrated delivery networks remains largely unknown. OBJECTIVE: To determine the concurrent validity of an algorithm developed by a regional integrated delivery network multidisciplinary panel (MP) and a published ACD algorithm in identifying patients with statin intolerance. METHODS: The MP consisted of 3 physicians and 2 pharmacists with expertise in cardiology, internal medicine, and formulary management. The MP algorithm used pharmacy and medical claims to identify patients with statin intolerance, classifying them as having statin intolerance if they met any of the following criteria: (a) medical claim for rhabdomyolysis, (b) medical claim for muscle weakness, (c) an outpatient medical claim for creatinine kinase assay, (d) fills for ≥ 2 different statins excluding dose increases, (e) decrease in statin dose, or (f) discontinuation of a statin with a subsequent fill for a nonstatin lipid-lowering therapy. The validated ACD algorithm identified statin intolerance as absolute intolerance with rhabdomyolysis; absolute intolerance without rhabdomyolysis (i.e., other adverse events); or as dose titration intolerance. Adult patients (aged ≥ 18 years) from the integrated delivery network with at least 1 prescription fill for a statin between January 1, 2011, and December 31, 2012 (first fill defined the index date) were identified. Patients with ≥ 1 year pre- and ≥ 2 years post-index continuous enrollment and no statin prescription fills in the pre-index period were included. The MP and ACD algorithms were applied to the population, and concordance was examined using individual (i.e., sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) and overall performance measures (i.e., accuracy, Cohen's kappa coefficient, balanced accuracy, F-1 score, and phi coefficient). RESULTS: After applying the inclusion criteria, 7,490 patients were evaluated for statin intolerance. The mean (SD) age of the population was 51.1 (8.5) years, and 55.7% were male. The MP and ACD algorithms classified 11.3% and 5.4% of patients as having statin intolerance, respectively. The concordance of the MP algorithm was mixed, with negative classification of statin intolerance measures having high concordance (specificity 0.91, NPV 0.97) and positive classification of statin intolerance measures having poor concordance (sensitivity 0.45, PPV 0.21). Overall performance measures showed mixed agreement between the algorithms. CONCLUSIONS: Both algorithms used a mix of pharmacy and medical claims and may be useful for organizations interested in identifying patients with statin intolerance. By identifying patients with statin intolerance, organizations may consider a variety of options, including using nonstatin lipid-lowering therapies, to manage cardiovascular event risk in these patients. DISCLOSURES: This study was funded by Regeneron Pharmaceuticals and Sanofi US. Boklage is employed by, and owns stock in, Regeneron, and Charland is employed by Sanofi. Bellows has received fees from Avenir for advisory board membership and grants from Myriad Genetics, Biogen, Janssen, and National Institutes of Health. Brixner reports advisory board and consultancy fees and grants from Sanofi. Mitchell reports consultancy fees from Sanofi. Study concept and design were contributed by Bellows, Boklage, Charland, and Brixner. Bellows, Sainski-Nguyen, and Olsen took the lead in data collection, along with Mitchell. Data interpretation was performed by Mitchell, along with the other authors. The manuscript was written by Bellows, Sainski-Nguyen, and Olsen and revised by all the authors.

Maintenance of the HIV Reservoir Is Antagonized by Selective BCL2 Inhibition.

Decay of the HIV reservoir is slowed over time in part by expansion of the pool of HIV-infected cells. This expansion reflects homeostatic proliferation of infected cells by interleukin-7 (IL-7) or antigenic stimulation, as well as new rounds of infection of susceptible target cells. As novel therapies are being developed to accelerate the decay of the latent HIV reservoir, it will be important to identify interventions that prevent expansion and/or repopulation of the latent HIV reservoir. Our previous studies showed that HIV protease cleaves the host protein procaspase 8 to generate Casp8p41, which can bind and activate Bak to induce apoptosis of infected cells. In circumstances where expression of the anti-apoptotic protein BCL2 is high, Casp8p41 instead binds BCL2, and cell death does not occur. This effect can be overcome by treating cells with the clinically approved BCL2 antagonist venetoclax, which prevents Casp8p41 from binding BCL2, thereby allowing Casp8p41 to bind Bak and kill the infected cell. Here we assess whether the events that maintain the HIV reservoir are also antagonized by venetoclax. Using the J-Lat 10.6 model of persistent infection, we demonstrate that proliferation and HIV expression are countered by the use of venetoclax, which causes preferential killing of the HIV-expressing cells. Similarly, during new rounds of infection of primary CD4 T cells, venetoclax causes selective killing of HIV-infected cells, resulting in decreased numbers of HIV DNA-containing cells.IMPORTANCE Cure of HIV infection requires an intervention that reduces the HIV reservoir size. A variety of approaches are being tested for their ability to impact HIV reservoir size. Even if successful, however, these approaches will need to be combined with additional complementary approaches that prevent replenishment or repopulation of the HIV reservoir. Our previous studies have shown that the FDA-approved BCL2 antagonist venetoclax has a beneficial effect on the HIV reservoir size following HIV reactivation. Here we demonstrate that venetoclax also has a beneficial effect on HIV reservoir size in a model of homeostatic proliferation of HIV as well as in acute spreading infection of HIV in primary CD4 T cells. These results suggest that venetoclax, either alone or in combination with other approaches to reducing HIV reservoir size, is a compound worthy of further study for its effects on HIV reservoir size.

Office-Based Buprenorphine Versus Clinic-Based Methadone: A Cost-Effectiveness Analysis.

The objective of this analysis was to compare the cost-effectiveness of clinic-based methadone maintenance therapy (MMT) and office-based buprenorphine maintenance therapy (BMT) from the perspective of third-party payers in the United States. The authors used a Markov cost-effectiveness model. A hypothetical cohort of 1000 adult, opioid-dependent patients was modeled over a 1-year time horizon. Patients were allowed to transition between the health states of in opioid dependence treatment and either abusing or not abusing opioids, or to have dropped out of treatment. Probabilities were derived from randomized clinical trials comparing methadone and buprenorphine. Costs included drug and administration, clinic visits, and therapy sessions. Effectiveness outcomes examined were (1) retention in the treatment program and (2) opioid abuse-free weeks. For retention in treatment at 1 year, MMT was more costly ($4,613 vs. $4,155) and more effective (20.3% vs. 15.9%) than BMT, resulting in an incremental cost-effectiveness ratio (ICER) of $10,437 per additional patient retained in treatment. MMT was also more effective than BMT in terms of opioid abuse-free weeks (9.2 vs. 9.1 weeks), resulting in an ICER of $8,515 per opioid abuse-free week gained. One-way sensitivity analyses found costs per week of MMT to have the largest impact on the retention-in-treatment outcome, whereas the probability of dropping out with MMT had the greatest impact on opioid abuse-free weeks. The authors conclude that MMT is cost-effective compared with BMT for the treatment of patients with opioid dependence. However, the treatment of substance abuse is complex, and decision makers should also consider individual patient characteristics when making coverage decisions.