Preclinical Evaluation of AMG 337, a Highly Selective Small Molecule MET Inhibitor, in Hepatocellular Carcinoma.

Aberrant hepatocyte growth factor (HGF)/MET signaling has been implicated in hepatocarcinogenesis, suggesting that MET may serve as an attractive therapeutic target in hepatocellular carcinoma. We sought to investigate the in vitro and in vivo antitumor activity of AMG 337, a potent and highly selective small molecule MET kinase inhibitor, in preclinical models of hepatocellular carcinoma. The antiproliferative activity of AMG 337 was evaluated across a panel of hepatocellular carcinoma cell lines in a viability assay. Daily oral administration was used to evaluate the in vivo antitumor activity of AMG 337 in two patient-derived xenograft (PDX) models of hepatocellular carcinoma (LI0612 and LI1078). AMG 337 exerted potent antiproliferative activity against 2 of 40 hepatocellular carcinoma cell lines, namely, MHCC97H (IC50, 0.015 µmol/L) and HCCLM3 (IC50, 0.025 µmol/L). Both sensitive cell lines showed MET amplification (MET/CEN-7 >2.0) assessed by FISH, and high MET expression (3+ IHC) assessed by IHC. AMG 337 potently inhibited p-MET in all cell lines with detectable levels of total MET. However, the dose-dependent inhibition of downstream effectors of HGF/MET signaling, including p-GAB1, p-AKT, and p-ERK, was limited to those cell lines sensitive to AMG 337 in a viability assay (MHCC97H and HCCLM3). AMG 337 significantly inhibited tumor growth at all doses tested in the MET-amplified and MET-high-expressing hepatocellular carcinoma PDX model LI0612 and had no effect on tumor growth in the non-MET-amplified and MET-low-expressing hepatocellular carcinoma PDX model LI1078. AMG 337 represents a promising and novel therapeutic strategy for targeting hepatocellular carcinomas with a dependence on HGF/MET signaling. Mol Cancer Ther; 15(6); 1227-37. ©2016 AACR.

Clinical trials in "emerging markets": regulatory considerations and other factors.

Clinical studies are being placed in emerging markets as part of global drug development programs to access large pool of eligible patients and to benefit from a cost effective structure. However, over the last few years, the definition of "emerging markets" is being revisited, especially from a regulatory perspective. For purposes of this article, countries outside US, EU and the traditional "western countries" are discussed. Multiple factors are considered for placement of clinical studies such as adherence to Good Clinical Practice (GCP), medical infrastructure & standard of care, number of eligible patients, etc. This article also discusses other quantitative factors such as country's GDP, patent applications, healthcare expenditure, healthcare infrastructure, corruption, innovation, etc. These different factors and indexes are correlated to the number of clinical studies ongoing in the "emerging markets". R&D, healthcare expenditure, technology infrastructure, transparency, and level of innovation, show a significant correlation with the number of clinical trials being conducted in these countries. This is the first analysis of its kind to evaluate and correlate the various other factors to the number of clinical studies in a country.

Comparison of several imputation methods for missing baseline data in propensity scores analysis of binary outcome.

We performed a simulation study comparing the statistical properties of the estimated log odds ratio from propensity scores analyses of a binary response variable, in which missing baseline data had been imputed using a simple imputation scheme (Treatment Mean Imputation), compared with three ways of performing multiple imputation (MI) and with a Complete Case analysis. MI that included treatment (treated/untreated) and outcome (for our analyses, outcome was adverse event [yes/no]) in the imputer's model had the best statistical properties of the imputation schemes we studied. MI is feasible to use in situations where one has just a few outcomes to analyze. We also found that Treatment Mean Imputation performed quite well and is a reasonable alternative to MI in situations where it is not feasible to use MI. Treatment Mean Imputation performed better than MI methods that did not include both the treatment and outcome in the imputer's model.

Relationship between epoetin alfa dose and mortality: findings from a marginal structural model.

BACKGROUND AND OBJECTIVES: Observational studies relating epoetin alfa (EPO) dose and mortality frequently use analytic methods that do not control time-dependent confounding by indication (CBI). The relationship between EPO dose and 1-year mortality, adjusting for the effects of time-dependent CBI, was examined using a marginal structural model. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This retrospective cohort study included 27,791 hemodialysis patients between July 2000 and June 2002. Patients were grouped at successive 2-wk intervals into a zero-dose category or four nonzero-dose categories. Ordinal regression was used to calculate inverse probability of treatment weights of patients receiving their own dose level given their covariate and treatment history. Three treatment models with an increasing number of treatment predictors were evaluated to assess the effect of model specification. A small number of excessively large patient weights were truncated. Relative hazards for higher-dose groups compared with the lowest nonzero-dose group varied by treatment model specification and by level of weight truncation. RESULTS: Results differed appreciably between the simplest treatment model, which incorporated only hemoglobin and EPO dosing history with 2% weight truncation (hazard ratio: 1.51; 95% confidence interval: 1.09, 1.89 for highest-dose patients), and the most comprehensive treatment model with 1% weight truncation (hazard ratio: 0.98; 95% confidence interval: 0.76, 1.74). CONCLUSIONS: There is appreciable CBI at higher EPO doses, and EPO dose was not associated with increased mortality in marginal structural model analyses that more completely addressed this confounding.

Evolving statistical methods to facilitate evaluation of the causal association between erythropoiesis-stimulating agent dose and mortality in nonexperimental research: strengths and limitations.

Findings from randomized controlled trials examining the efficacy of therapy with erythropoiesis-stimulating agents (ESAs) to normalize hemoglobin levels in patients with chronic kidney disease or kidney failure have raised questions regarding the safety of this class of drugs. However, no trial to date has specifically assessed the safety of ESA-dosing algorithms used to achieve the lower hemoglobin targets typically using in clinical practice. Although a wealth of nonexperimental data is available for dialysis patients, analyses based on these data are more susceptible to confounding bias than randomized controlled trials. Conducting valid pharmacoepidemiologic studies of drug effects in hemodialysis patients is complicated by the extent of their comorbidities, frequent hospitalizations, various concomitant medications, and an exceedingly high mortality rate. The need for greater ESA doses for the treatment of anemia in sicker patients potentially and plausibly generates confounding by indication, the control of which is complicated by the presence of time-dependent confounding. Here, we describe sources of bias in nonexperimental studies of ESA therapy in hemodialysis patients and critically appraise analytical methods that may help minimize bias in such studies.

Exploring relative mortality and epoetin alfa dose among hemodialysis patients.

BACKGROUND: Confounding-by-indication is a bias in nonexperimental studies that occurs when outcomes are compared for treated and untreated patients and the treatment or medication dose is related to predictors of the outcome. Two recent publications reported that greater epoetin alfa (EPO) doses were associated with increased mortality rates. We assessed whether confounding-by-indication might account for these results. STUDY DESIGN: We used a retrospective cohort study design. SETTING & PARTICIPANTS: Hemodialysis patients were randomly selected from a large dialysis organization from July 2000 to June 2002 and were required to have completed a 9-month baseline period. PREDICTOR: EPO dose assessed during months 7 to 9 of the baseline period and monthly throughout the follow-up period. Hemoglobin (Hb) was assessed as average value during months 4 to 6 of the baseline period and monthly throughout the follow-up period. All other covariates were assessed during months 1 to 6 of the baseline period. OUTCOME: All-cause mortality during the 1 year of follow-up. Baseline Cox models were fitted with log EPO and Hb with and without adjustment for baseline patient characteristics. Time-dependent models were fitted with time-varying log EPO and Hb and, separately, lagged log EPO and Hb, with adjustment for baseline patient characteristics. RESULTS: 22,955 patients met our inclusion criteria. In the unadjusted model, we observed increased mortality risk with increasing EPO dose (hazard ratio [HR], 1.31 per log unit increase; 95% confidence interval [CI], 1.26 to 1.36). Adjustment for baseline patient characteristics resulted in an appreciably decreased HR (HR, 1.21; 95% CI, 1.15 to 1.28). In the lagged time-dependent analyses, estimates ranged from HR of 0.93 (95% CI, 0.92 to 0.95) to HR of 1.01 (95% CI, 0.99 to 1.03) for the 1- and 2-month lagged models, respectively. LIMITATIONS: This analysis was limited to prevalent hemodialysis patients, and inhospital EPO dosing information was unavailable. CONCLUSIONS: The observed mortality risk estimates associated with EPO dose in nonexperimental studies in dialysis patients may be highly sensitive to the analytic method used. This highlights the complexity of evaluating the association between EPO dose, Hb level, and mortality in these studies.

Gatekeeping procedures in dose-response clinical trials based on the Dunnett test.

This paper discusses multiple testing procedures in dose-response clinical trials with primary and secondary endpoints. A general gatekeeping framework for constructing multiple tests is proposed, which extends the Dunnett test [Journal of the American Statistical Association 1955; 50: 1096-1121] and Bonferroni-based gatekeeping tests developed by Dmitrienko et al. [Statistics in Medicine 2003; 22:2387-2400]. The proposed procedure accounts for the hierarchical structure of the testing problem; for example, it restricts testing of secondary endpoints to the doses for which the primary endpoint is significant. The multiple testing approach is illustrated using a dose-response clinical trial in patients with diabetes. Monte-Carlo simulations demonstrate that the proposed procedure provides a power advantage over the Bonferroni gatekeeping procedure. The power gain generally increases with increasing correlation among the endpoints, especially when all primary dose-control comparisons are significant.

Recombinant human parathyroid hormone (1-34) [teriparatide] improves both cortical and cancellous bone structure.

UNLABELLED: Histomorphometry and microCT of 51 paired iliac crest biopsy specimens from women treated with teriparatide revealed significant increases in cancellous bone volume, cancellous bone connectivity density, cancellous bone plate-like structure, and cortical thickness, and a reduction in marrow star volume. INTRODUCTION: We studied the ability of teriparatide (rDNA origin) injection [rhPTH(1-34), TPTD] to improve both cancellous and cortical bone in a subset of women enrolled in the Fracture Prevention Trial of postmenopausal women with osteoporosis after a mean treatment time of 19 months. This is the first report of a biopsy study after treatment with teriparatide having a sufficient number of paired biopsy samples to provide quantitative structural data. METHODS: Fifty-one paired iliac crest bone biopsy specimens (placebo [n = 19], 20 microg teriparatide [n = 18], and 40 microg teriparatide [n = 14]) were analyzed using both two-dimensional (2D) histomorphometry and three-dimensional (3D) microcomputed tomography (microCT). Data for both teriparatide treatment groups were pooled for analysis. RESULTS AND CONCLUSIONS: By 2D histomorphometric analyses, teriparatide significantly increased cancellous bone volume (median percent change: teriparatide, 14%; placebo, -24%; p = 0.001) and reduced marrow star volume (teriparatide, -16%; placebo, 112%; p = 0.004). Teriparatide administration was not associated with osteomalacia or woven bone, and there were no significant changes in mineral appositional rate or wall thickness. By 3D cancellous and cortical bone structural analyses, teriparatide significantly decreased the cancellous structure model index (teriparatide, -12%; placebo, 7%; p = 0.025), increased cancellous connectivity density (teriparatide, 19%; placebo, - 14%; p = 0.034), and increased cortical thickness (teriparatide, 22%; placebo, 3%; p = 0.012). These data show that teriparatide treatment of postmenopausal women with osteoporosis significantly increased cancellous bone volume and connectivity, improved trabecular morphology with a shift toward a more plate-like structure, and increased cortical bone thickness. These changes in cancellous and cortical bone morphology should improve biomechanical competence and are consistent with the substantially reduced incidences of vertebral and nonvertebral fractures during administration of teriparatide.

The skeletal response to teriparatide is largely independent of age, initial bone mineral density, and prevalent vertebral fractures in postmenopausal women with osteoporosis.

In a recent study of women with postmenopausal osteoporosis, treatment with teriparatide for a median of 19 months increased bone mineral density and decreased the risk of vertebral and nonvertebral fractures. Using the same cohort, the current study evaluated the relationship between these therapeutic effects and the patient's baseline age, vertebral bone mineral density, and prevalent vertebral fractures. In women over 65 years of age, treatment resulted in a greater increase in vertebral bone mineral density than in younger women (treatment-by-age interaction, p = 0.037), but baseline age had no effect on the relative risk reduction for vertebral fractures (treatment-by-age interaction, p = 0.558). In women receiving placebo (with calcium and vitamin D), there was an inverse relationship between baseline vertebral bone mineral density and vertebral fracture risk. When compared across bone mineral density tertiles, the effects of teriparatide on the relative risk for developing new vertebral fractures and increase in vertebral bone mineral density did not differ significantly (p = 0.817 and p = 0.615, respectively). Teriparatide treatment significantly decreased vertebral fracture risk in patients with a vertebral bone mineral density T score of less than -33 or a score between -2.1 and -3.3 (p < 0.001 and p = 0.027, respectively) and showed a trend toward reduced fracture risk in the group with a T score greater than -2.1 (p = 0.115). Placebo-treated women with two or more prevalent vertebral fractures had a significantly greater risk of developing new vertebral fractures than women with zero or one prevalent vertebral fracture (p < 0.001). When compared within prevalent vertebral fracture subgroups, the effects of teriparatide on the relative risk for developing new vertebral fractures were similar. The results of this study indicate that teriparatide offers clinical benefit to patients across a broad range of age and disease severity.