The increased level of formation is similar in patients who were either TN or had lower bone turnover initially due to previous ALN therapy. Elevated bone formation in postmenopausal women with osteoporosis was sustained over a 24-month period by TPTD. Biochemical markers of bone formation are a good surrogate for the assessment of TPTD effects.
Our findings demonstrate that SOST KO mice were protected from the major sublesional bone loss that invariably follows SCI. The evidence indicates that sclerostin is an important mediator of the marked sublesional bone loss after SCI, and that pharmacological inhibition of sclerostin may represent a promising novel approach to this challenging clinical problem.
Data from electronic dosing monitors may be used in conjunction with the pharmacokinetics (PK) of a monitored drug and could predict health outcomes. We derived an adherence metric modeling the estimated mean serum concentration of metoprolol Cp (Cpave) from standard PK parameter values of the study drug (ka and k) and times of administration from electronic dosing monitors. A target serum concentration (Cṕave) was determined using the same model assuming perfect adherence to the prescribed dose and administration schedule i.e. perfect adherence. The difference Δ= Cṕave −Cpave represented the deviation from the target Cp and was used as the new kinetic‐derived adherence measure with a larger Δ representing a greater gap between prescribed and actual serum concentrations resulting from poorer adherence. We analyzed the electronic monitor records of 80 older heart failure patients who had been prescribed metoprolol. The mean of Δ was 8.2 ng/ml (SD=9.9). Δ correlated negatively with the percentage of dose taken (ρ=−0.5075) and the percentage dose taken on schedule (ρ= −0.3813). Log‐linear models adjusted for functional severity indicated that Δ strongly predicted the numbers of patient hospitalizations and emergency visits (p<0.0001). The new adherence measure summarizes gaps between the targeted and actual metoprolol serum concentration using data from electronic dosing monitors and predicts health outcomes of older adult patients with heart failure.
Clinical Pharmacology & Therapeutics (2004) 75, P76–P76; doi:
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