No description available.

No description available.

No / Background: AQ4N (1,4-bis[[2-(dimethylamino)ethyl] amino]-5,8-dihydroxyanthracene-9, 10-dione bis-N-oxide dihydrochloride) is a prodrug which is selectively activated within hypoxic tissues to AQ4, a topoisomerase II inhibitor and DNA intercalator. Patients and methods: In the phase I study, 22 patients with oesophageal carcinoma received an i.v. infusion of AQ4N (22.5¿447 mg/m2) followed, 2 weeks later, by further infusion and radiotherapy. Pharmacokinetics and lymphocyte AQ4N and AQ4 levels were measured after the first dose. At 447 mg/m2, biopsies of tumour and normal tissue were taken after AQ4N administration. Results: Drug-related adverse events were blue discolouration of skin and urine, grade 2¿3 lymphopenia, grade 1¿3 fatigue, grade 1¿2 anaemia, leucopenia and nausea. There were no drug-related serious adverse events (SAEs). Three patients had reductions in tumour volume >50%, nine had stable disease. Pharmacokinetics indicated predictable clearance. Plasma area under the curve (AUC) at 447 mg/m2 exceeded AQ4N concentrations in mice at therapeutic doses and tumour biopsies contained concentrations of AQ4 greater than those in normal tissue. Tumour concentrations of AQ4 exceeded in vitro IC50 values for most cell lines investigated. Conclusions: No dose-limiting toxic effects were observed and a maximum tolerated dose was not established. Tumour AQ4 concentrations and plasma AUC at 447 mg/m2 exceeded active levels in preclinical models. This dose was chosen for future studies with radiotherapy.

This work presents an investigation of the potential development of phenoxodiol, a novel isoflavone, for the treatment of prostate cancer. The literature concerning isoflavone epidemiology, pharmacology, clinical use and their effect on prostate cancer is reviewed. Isoflavone impact on signal transduction pathways is also reviewed with a particular focus on the Akt / mTOR signal transduction pathway, a key signaling pathway in prostate cancer cells. In vitro experiments and xenograft nude mice studies show that phenoxodiol inhibits the growth of DU145 and PC3 prostate cancer cells, when used alone and in combination with cisplatin or carboplatin. Phenoxodiol in combination with cisplatin is highly synergistic when inhibiting the growth of DU145 cells in particular. We show for the first time, that phenoxodiol and cisplatin or carboplatin, inhibits phosphorylation of Akt and mTOR in DU145 and PC3 cells. A first-in-human study of single dose phenoxodiol investigating its pharmacokinetic properties in cancer patient volunteers was performed. Extensive conjugation of phenoxodiol and a short half-life was noted in this study. A Phase I study of intravenous phenoxodiol administered weekly to patients with advanced cancer was then performed to assess toxicity of a repeated dose schedule, as well as the maximum tolerated dose. This schedule was well tolerated in patients, with lymphocytopenia noted as the main toxicity. Given the short half-life of phenoxodiol and our preclinical studies suggesting that combination with cisplatin and carboplatin synergistically inhibited prostate cancer cell growth, we also undertook a Phase I dose escalation study of oral phenoxodiol administered in combination with cisplatin or carboplatin to patients with advanced cancer. The main adverse events include hyperglycemia, hypocalcemia, mild transaminase rises, as well as nausea, constipation, infusion site reactions and lethargy. Three patients with ovarian cancer responded to treatment according to CA125 criteria, and there was a 45% reduction in prostate specific antigen level in one man with androgen independent prostate cancer. The bioavailability of the oral formulation of phenoxodiol was calculated to be 17.5%. Phenoxodiol shows promise for further development in the potential treatment of prostate cancer.

This work presents an investigation of the potential development of phenoxodiol, a novel isoflavone, for the treatment of prostate cancer. The literature concerning isoflavone epidemiology, pharmacology, clinical use and their effect on prostate cancer is reviewed. Isoflavone impact on signal transduction pathways is also reviewed with a particular focus on the Akt / mTOR signal transduction pathway, a key signaling pathway in prostate cancer cells. In vitro experiments and xenograft nude mice studies show that phenoxodiol inhibits the growth of DU145 and PC3 prostate cancer cells, when used alone and in combination with cisplatin or carboplatin. Phenoxodiol in combination with cisplatin is highly synergistic when inhibiting the growth of DU145 cells in particular. We show for the first time, that phenoxodiol and cisplatin or carboplatin, inhibits phosphorylation of Akt and mTOR in DU145 and PC3 cells. A first-in-human study of single dose phenoxodiol investigating its pharmacokinetic properties in cancer patient volunteers was performed. Extensive conjugation of phenoxodiol and a short half-life was noted in this study. A Phase I study of intravenous phenoxodiol administered weekly to patients with advanced cancer was then performed to assess toxicity of a repeated dose schedule, as well as the maximum tolerated dose. This schedule was well tolerated in patients, with lymphocytopenia noted as the main toxicity. Given the short half-life of phenoxodiol and our preclinical studies suggesting that combination with cisplatin and carboplatin synergistically inhibited prostate cancer cell growth, we also undertook a Phase I dose escalation study of oral phenoxodiol administered in combination with cisplatin or carboplatin to patients with advanced cancer. The main adverse events include hyperglycemia, hypocalcemia, mild transaminase rises, as well as nausea, constipation, infusion site reactions and lethargy. Three patients with ovarian cancer responded to treatment according to CA125 criteria, and there was a 45% reduction in prostate specific antigen level in one man with androgen independent prostate cancer. The bioavailability of the oral formulation of phenoxodiol was calculated to be 17.5%. Phenoxodiol shows promise for further development in the potential treatment of prostate cancer.

Thesis (Ph. D.)--Virginia Commonwealth University, 2007. / Prepared for: Dept. of Biostatistics. Bibliography: leaves 179-181. Also available online via the Internet.

OBJECTIVE: The aim of this study was to investigate the safety and tolerability of a novel anti-folate drug, pemetrexed, in the setting of a phase I clinical trial in patients with non-HIV related central nervous system lymphoma (CNSL). METHODS: In this multicenter, open-label, phase I dose finding clinical trial, pemetrexed was investigated as a single agent treatment for primary or secondary CNSL. RESULTS: A total of 18 patients were enrolled between January 2009 and November 2014. The mean age was 64.6 years old (range: 47-79). The ratio of male to female was 1:1. One out of six patients experienced a dose limiting toxicity (DLT) at dose level 1 (600mg/m2). There were no DLTs among the four patients enrolled at dose level 2 (900m/m2). Two of six patients experienced a DLT at dose level 3 (1200mg/m2). The MTD was therefore determined to be 900mg/m2. Overall, pemetrexed was well tolerated but toxicities were seen and need to be monitored. All patients experienced at least one type of toxicity of any grade. Most patients (92.9%) experienced at least one type of neurological toxicity. Grade-3 toxicities included confusion, speech impairment, and psychosis. Twelve patients (85.7%) experienced at least one bone marrow type of toxicity of any grade. These toxicities included anemia (78.6%), thrombocytopenia (57.1%), neutropenia (50%), leukocytopenia (42.9%), and lymphopenia (42.9%). Four patients experienced either grade-3 (14.3%) or grade-4 (14.3%) neutropenia. Three patients experienced grade-3 leukopenia (21.4%). One patient experienced grade-3 lymphopenia (7.1%) and two patients experienced grade-4 lymphopenia (14.3%). Twelve patients (85.7%) experienced at least one metabolic type of toxicity of any grade. A majority of these were also grade-1 or 2, with the exception of hypophosphatemia (grade-4), hyperglycemia (grade-3) and increased ALT (grade-3), increased AST (grade-3) and increased creatinine phosphokinase (CPK) (grade-4). Constitutional and gastrointestinal symptoms were seen in >60% of patients. These consisted mainly of fatigue, constipation, nausea, and anorexia. Musculoskeletal symptoms were seen in greater than 60% of patients. Less common adverse events included pain (<60%), infection (<40%), dermatologic, ocular/visual, and pulmonary/upper respiratory (<30%). The average number of cycles on treatment for all patients was 5.5 cycles. 14 patients were evaluated for response to treatment by neuroimaging (MRI) while on treatment. Of these, four patients (28.6%) showed a complete response (CR). Of those patients, 2 patients achieved this response after only 2 doses, and 2 patients after a total of 8 doses. 5 patients (35.7%) showed a partial response (PR) and four patients (28.6%) achieved stable disease (SD). The overall response rate (ORR) was determined at 92.9% (SD, PR and CR combined). CONCLUSIONS: Given this data, pemetrexed is a powerful drug and feasible alternative to existing treatment options; however, certain toxicities need to be closely monitored. Further studies are needed to assess the efficacy of pemetrexed in a larger cohort of patients with CNSL.

No description available.

No description available.

Profile monitoring is a well-known approach used in statistical process control where the quality of the product or process is characterized by a profile or a relationship between a response variable and one or more explanatory variables. Profile monitoring is conducted over two phases, labeled as Phase I and Phase II. In Phase I profile monitoring, regression methods are used to model each profile and to detect the possible presence of out-of-control profiles in the historical data set (HDS). The out-of-control profiles can be detected by using the statis-tic. However, previous methods of calculating the statistic are based on using all the data in the HDS including the data from the out-of-control process. Consequently, the ability of using this method can be distorted if the HDS contains data from the out-of-control process. This work provides a new profile monitoring methodology for Phase I analysis. The proposed method, referred to as the cluster-based profile monitoring method, incorporates a cluster analysis phase before calculating the statistic. Before introducing our proposed cluster-based method in profile monitoring, this cluster-based method is demonstrated to work efficiently in robust regression, referred to as cluster-based bounded influence regression or CBI. It will be demonstrated that the CBI method provides a robust, efficient and high breakdown regression parameter estimator. The CBI method first represents the data space via a special set of points, referred to as anchor points. Then a collection of single-point-added ordinary least squares regression estimators forms the basis of a metric used in defining the similarity between any two observations. Cluster analysis then yields a main cluster containing at least half the observations, with the remaining observations comprising one or more minor clusters. An initial regression estimator arises from the main cluster, with a group-additive DFFITS argument used to carefully activate the minor clusters through a bounded influence regression frame work. CBI achieves a 50% breakdown point, is regression equivariant, scale and affine equivariant and distributionally is asymptotically normal. Case studies and Monte Carlo results demonstrate the performance advantage of CBI over other popular robust regression procedures regarding coefficient stabil-ity, scale estimation and standard errors. The cluster-based method in Phase I profile monitoring first replaces the data from each sampled unit with an estimated profile, using some appropriate regression method. The estimated parameters for the parametric profiles are obtained from parametric models while the estimated parameters for the nonparametric profiles are obtained from the p-spline model. The cluster phase clusters the profiles based on their estimated parameters and this yields an initial main cluster which contains at least half the profiles. The initial estimated parameters for the population average (PA) profile are obtained by fitting a mixed model (parametric or nonparametric) to those profiles in the main cluster. Profiles that are not contained in the initial main cluster are iteratively added to the main cluster provided their statistics are "small" and the mixed model (parametric or nonparametric) is used to update the estimated parameters for the PA profile. Those profiles contained in the final main cluster are considered as resulting from the in-control process while those not included are considered as resulting from an out-of-control process. This cluster-based method has been applied to monitor both parametric and nonparametric profiles. A simulated example, a Monte Carlo study and an application to a real data set demonstrates the detail of the algorithm and the performance advantage of this proposed method over a non-cluster-based method is demonstrated with respect to more accurate estimates of the PA parameters and improved classification performance criteria. When the profiles can be represented by vectors, the profile monitoring process is equivalent to the detection of multivariate outliers. For this reason, we also compared our proposed method to a popular method used to identify outliers when dealing with a multivariate response. Our study demonstrated that when the out-of-control process corresponds to a sustained shift, the cluster-based method using the successive difference estimator is clearly the superior method, among those methods we considered, based on all performance criteria. In addition, the influence of accurate Phase I estimates on the performance of Phase II control charts is presented to show the further advantage of the proposed method. A simple example and Monte Carlo results show that more accurate estimates from Phase I would provide more efficient Phase II control charts. / Ph. D.