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1.  The Degree of Bone Mineralization is Maintained with Single Intravenous Bisphosphonates in Aged Estrogen Deficient Rats and is a Strong Predictor of Bone Strength 
Bone  2007;41(5):10.1016/j.bone.2007.06.021.
The treatment of osteoporotic women with bisphosphonates significantly reduces the incidence of bone fractures to a degree greater than can be explained by an increase in bone mineral density. In this Study, 18 month Fischer 344 rats were ovariectomized and treated with a single dose of risedronate (intravenous, iv, 500μg), zoledronic acid (iv, 100μg) or continuous raloxifene (2mg/kg, po., 3x/wk). High resolution microCT was used to measure lumbar vertebral bone microarchitecture, the degree of bone mineralization (DBM) and the distribution of mineral. Small angle x-ray scattering was used to investigate mineral crystallinity. We found prolonged estrogen deficiency, reduced trabecular bone volume, and increased micro architecture bone compression strength. lowered the degree of mineralization. Treatment with resorptive agents (bisphosphonates > raloxifene) prevented the loss of mineralization, trabecular bone volume and bone compression strength. Crystal size was not changed with OVX or with anti-resorptive treatments. In conclusion, in the aged estrogen deficient rat model, single intravenous doses of two bisphosphonates were effective in maintaining the compressive bone strength for 180 days by reducing bone turnover, and maintaining the DBM to a greater degree than with raloxifene.
doi:10.1016/j.bone.2007.06.021
PMCID: PMC3883569  PMID: 17825637
intravenous bisphosphonates; bone mineralization; compression strength; rat; OVX
2.  African American patients with gout: efficacy and safety of febuxostat vs allopurinol 
Background
African Americans are twice as likely as Caucasians to develop gout, but they are less likely to be treated with urate-lowering therapy (ULT). Furthermore, African Americans typically present with more comorbidities associated with gout, such as hypertension, obesity, and renal impairment. We determined the efficacy and safety of ULT with febuxostat or allopurinol in African American subjects with gout and associated comorbidities and in comparison to Caucasian gout subjects.
Methods
This is a secondary analysis of the 6-month Phase 3 CONFIRMS trial. Eligible gouty subjects with baseline serum urate (sUA) ≥ 8.0 mg/dL were randomized 1:1:1 to receive febuxostat 40 mg, febuxostat 80 mg, or allopurinol (300 mg or 200 mg depending on renal function) daily. All subjects received gout flare prophylaxis. Primary efficacy endpoint was the proportion of subjects in each treatment group with sUA < 6.0 mg/dL at the final visit. Additional endpoints included the proportion of subjects with mild or with moderate renal impairment who achieved a target sUA < 6.0 mg/dL at final visit. Adverse events (AEs) were recorded throughout the study.
Results
Of the 2,269 subjects enrolled, 10.0% were African American and 82.1% were Caucasian. African American subjects were mostly male (89.5%), obese (BMI ≥ 30 kg/m2; 67.1%), with mean baseline sUA of 9.8 mg/dL and mean duration of gout of 10.4 years. The proportions of African American subjects with a baseline history of diabetes, renal impairment, or cardiovascular disease were significantly higher compared to Caucasians (p < 0.001). ULT with febuxostat 80 mg was superior to both febuxostat 40 mg (p < 0.001) and allopurinol (p = 0.004). Febuxostat 40 mg was comparable in efficacy to allopurinol. Significantly more African American subjects with mild or moderate renal impairment achieved sUA < 6.0 mg/dL in the febuxostat 80 group than in either the febuxostat 40 mg or allopurinol group (p < 0.05). Efficacy rates in all treatment groups regardless of renal function were comparable between African American and Caucasian subjects, as were AE rates.
Conclusions
In African American subjects with significant comorbidities, febuxostat 80 mg is significantly more efficacious than either febuxostat 40 mg or allopurinol 200/300 mg. Febuxostat was well tolerated in this African American population.
Please see related article: http://www.biomedcentral.com/1741-7015/10/15
doi:10.1186/1471-2474-13-15
PMCID: PMC3317813  PMID: 22316106
3.  Stage-specific cancer incidence 
Statistics in medicine  2009;28(15):2054-2076.
SUMMARY
Early detection of prostate cancer using the prostate-specific antigen test led to a sharp spike in the incidence of the disease accompanied by an equally sharp improvement in patient prognoses as evaluated at the point of advanced diagnosis. Observed outcomes represent age at diagnosis and stage, a categorical prognostic variable combining the actual stage and the grade of tumor. The picture is summarized by the stage-specific cancer incidence that represents a joint survival-multinomial response regressed on factors affecting the unobserved history of the disease before diagnosis (mixture). Fitting the complex joint mixed model to large population data is a challenge. We develop a stable and structured MLE approach to the problem allowing for the estimates to be obtained iteratively. Factorization of the likelihood achieved by our method allows us to work with only a fraction of the model dimension at a time. The approach is based on generalized self-consistency and the quasi-EM algorithm used to handle the mixed multinomial part of the response through Poisson likelihood. The model provides a causal link between the screening policy in the population and the stage-specific incidence.
doi:10.1002/sim.3615
PMCID: PMC2779845  PMID: 19452568
incidence; joint modeling; mixed multinomial logit model; screening; generalized self-consistency
4.  Generalized Self-Consistency: Multinomial logit model and Poisson likelihood 
A generalized self-consistency approach to maximum likelihood estimation (MLE) and model building was developed in (Tsodikov, 2003) and applied to a survival analysis problem. We extend the framework to obtain second-order results such as information matrix and properties of the variance. Multinomial model motivates the paper and is used throughout as an example. Computational challenges with the multinomial likelihood motivated Baker (1994) to develop the Multinomial-Poisson (MP) transformation for a large variety of regression models with multinomial likelihood kernel. Multinomial regression is transformed into a Poisson regression at the cost of augmenting model parameters and restricting the problem to discrete covariates. Imposing normalization restrictions by means of Lagrange multipliers (Lang, 1996) justifies the approach. Using the self-consistency framework we develop an alternative solution to multinomial model fitting that does not require augmenting parameters while allowing for a Poisson likelihood and arbitrary covariate structures. Normalization restrictions are imposed by averaging over artificial “missing data” (fake mixture). Lack of probabilistic interpretation at the “complete-data” level makes the use of the generalized self-consistency machinery essential.
doi:10.1016/j.jspi.2007.10.004
PMCID: PMC2516948  PMID: 18709183

Results 1-4 (4)