The American journal of managed care
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Although clinical trial data have quantified patient survival gains associated with tyrosine kinase inhibitors in chronic myeloid leukemia, the overall value of these benefits is unknown. ⋯ These estimates indicate that the introduction of TKI drugs to treat CML has generated significant social value as a result of survival gains, the vast majority of which has accrued to patients.
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To test the validity of the adapted Diabetes Complications Severity Index (aDCSI), which does not include laboratory test results, as an indicator of diabetes severity. ⋯ The aDCSI is a good measure of diabetes severity, given its ability to explain hospitalizations and its similar performance to the DCSI.
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This study was designed to assess the effect of tyrosine kinase inhibitor (TKI) use on nonpharmaceutical medical spending for patients with chronic myeloid leukemia (CML), and estimate the association between cost-sharing and the TKI medication possession ratio (MPR). ⋯ Use of TKIs was associated with a 30% reduction in non-pharmaceutical medical spending for CML patients. This difference is approximately equal to 40% of the incremental pharmaceutical cost associated with using TKI therapy. The net annual cost of TKI therapy is roughly $15,000. An informal calculation suggests that this is well within the range of conventional cost-effectiveness thresholds. On balance, coverage of TKIs is relatively generous, with the vast majority of patients exhibiting high levels of adherence to therapy.
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The management of type 2 diabetes mellitus (T2DM) remains challenging. Limitations associated with many current therapies include hypoglycemia and weight gain. An increased understanding of the pathophysiology of T2DM has led to the development of incretin-related antihyperglycemic therapies. ⋯ As a result, they can lower blood glucose levels with a low risk of hypoglycemia or weight gain. Incretin-based therapies, the dipeptidyl peptidase 4 inhibitors and the glucagonlike peptide-1 receptor agonists, are now integrated into T2DM treatment algorithms. Trial data and clinical experience have shown that these agents are efficacious and generally well tolerated.
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Eleven classes of antidiabetic medicines are now available to help the 25.8 million Americans with type 2 diabetes control their blood sugar levels when diet and lifestyle modifications are not sufficient. Although patients benefit from the myriad of treatment options, there are little comparative data to effectively differentiate the products and predict their relative utility. ⋯ In addition to traditional CER approaches such as systematic reviews, meta-analyses, and retrospective claims analyses, Markov modeling and Bayesian analysis can be applied to predict patient outcomes in scenarios in which clinical trials are not feasible. CER may be the best way to consolidate and interpret data on the many agents involved and thereby guide rational treatment decisions.