Mean cost per number needed to treat with tocilizumab plus methotrexate versus abatacept plus methotrexate in the treatment of rheumatoid arthritis in patients previously treated with methotrexate

Pharmacoeconomic analysis of biologics and methotrexate for rheumatoid arthritis from the standpoint of the number needed to treat concept under the Japanese health insurance system

OBJECTIVES

To evaluate the cost-effectiveness of biologics and methotrexate (MTX) for rheumatoid arthritis (RA) using the number needed to treat (NNT) concept and total actual health care cost.

METHODS

This study included 121 RA patients with newly prescribed biologics and/or MTX between 2012 and 2017. The NNT was calculated based on the 24 week remission rate of Disease Activity Score in 28 joints using erythrocyte sedimentation rate (DAS28-ESR) and Clinical Disease Activity Index (CDAI).

RESULTS

Remission rates were 76.4% for DAS28-ESR and 45.4% for CDAI in the biologics group and 63.6% and 24.2%, respectively, in the MTX group. The NNT was calculated as 6.4 and 4.2 in the biologics group and 34.2 and 35.2 in the MTX group, respectively. Mean total actual health care costs were 1,044,066 JPY (9835 US$)/24 weeks per treated patient in the biologics group and 75,860 JPY (715 US$)/24 weeks in the MTX group. Although the effectiveness of biologics was superior to MTX from the standpoint of NNT, the mean total health care cost and mean cost per NNT were much higher in the biologics group.

CONCLUSIONS

Cost-effectiveness is clearly higher for MTX than biologics from the standpoint of mean total health care cost per adjusted NNT under the Japanese health insurance system.

Cost-effectiveness of long-acting insulin analogues vs intermediate/long-acting human insulin for type 1 diabetes: A population-based cohort followed over 10 years

AIMS

This study assessed the cost-effectiveness of long-acting insulin analogues (LAIAs) vs intermediate/long-acting human insulin (ILAHI) for patients with type 1 diabetes (T1D) in real-world clinical practice.

METHODS

Individual-level analyses were conducted within a longitudinal population-based cohort of 540 propensity score-matched T1D patients (LAIAs, n = 270; ILAHI, n = 270) with over 10 years of follow-up using Taiwan's National Health Insurance Research Database, 2004-2013, from third-party payer and healthcare sector perspectives. The study outcomes included the number needed to treat (NNT) to prevent one case of clinical events (eg, hypoglycaemia, diabetes-related complications), medical costs, and cost per case of events prevented. Cost estimates are presented in 2013 British pounds (GBP, £).

RESULTS

The NNTs using LAIAs vs ILAHI to avoid one case of hypoglycaemia requiring medical assistance, outpatient hypoglycaemia and any diabetes-related complications were 12, 9 and 10 for mean follow-up periods of 5.84, 6.02 and 3.62 years, respectively. From third-party payer and healthcare sector perspectives, using LAIAs instead of ILAHI saved GBP6924-GBP7116 per case of hypoglycaemia requiring medical assistance prevented, GBP5346-GBP5508 per case of outpatient hypoglycaemia prevented, and GBP3570-GBP3680 per case of any diabetes-related complications prevented. Sensitivity analyses considering sampling uncertainty showed that using LAIAs over ILAHI yields at least a 76% probability of cost-saving for avoiding one case of hypoglycaemia requiring medical assistance, outpatient hypoglycaemia or any diabetes-related complications.

CONCLUSIONS

This real-world evidence reveals that compared with ILAHI, the greater pharmaceutical costs associated with LAIAs for patients with T1D could be substantially offset by savings from averted hypoglycaemia or diabetes-related complications.

K Nearest Neighbor Algorithm Coupled with Metabonomics to Study the Therapeutic Mechanism of Sendeng-4 in Adjuvant-Induced Rheumatoid Arthritis Rat

As a traditional Mongolian medicine, Sendeng-4 (SD) has been widely used to treat rheumatoid arthritis (RA) in Inner Mongolia and exhibits a good curative effect. Unfortunately, due to geographical factors, it is difficult to popularize this drug throughout the whole country, and the mechanism of action of SD has been unclear. In this study, a serum metabolite profile analysis was performed to identify potential biomarkers associated with adjuvant-induced RA and investigate the mechanism of action of SD. Ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was performed for the metabonomics analysis. K nearest neighbor (KNN) models were established in both positive and negative spectra for classifying data from the control, model, and SD administration groups. Accuracy rate for classification was 95.8% in positive ion mode and 91.7% in negative ion mode. Orthogonal partial least squares discriminant analysis (OPLS-DA) enabled the identification of 12 metabolites as potential biomarkers of adjuvant-induced RA. After treatment with SD, the levels of uridine triphosphate, calcitroic acid, dynorphin B (6-9), and docosahexaenoic acid were restored to normal, indicating that SD likely ameliorated RA by regulating the levels of these biomarkers. This study identified early biomarkers of RA and elucidated the underlying mechanism of action of SD, which is worth further investigation for development as a clinical therapy.