Biomedical subjects

Guosheng Yin

Publications and source records attributed to Guosheng Yin.

15 recordsLinked to original sources

PubMed2006

Phase I study of capecitabine in combination with temozolomide in the treatment of patients with brain metastases from breast carcinoma.

BACKGROUND: A single-institution Phase I clinical trial was conducted to determine the maximum tolerated dose (MTD) and define the safety profile of temozolomide and capecitabine when used in combination to treat brain metastases from breast cancer. METHODS: Patients were eligible if they had bidimensionally measurable supratentorial or infratentorial brain metastasis from histologically confirmed breast carcinoma. Patients could have received up to 3 prior chemotherapy regimens. Temozolomide and capecitabine were administered concomitantly to 4 sequential cohorts at different dosing levels on Days 1-5 and Days 8-12, with cycles repeated every 21 days until disease progression. RESULTS: Twenty-four patients with multiple brain lesions were treated, including 14 patients with newly diagnosed brain metastases and 10 patients with recurrent brain metastases. Only 1 patient was chemotherapy-naive. Fatigue and nausea were the most commonly observed toxicities observed at any dose levels. Significant antitumor activity was observed, with a total of 1 complete and 3 partial responses (18% objective response rate) in the brain. The median response duration was 8 weeks (range, 6-64 weeks) and the median time to progression in the brain was 12 weeks (range, 3-70 weeks). Neurocognitive function improved or remained stable in patients with a response or stable disease. CONCLUSIONS: The combination of temozolomide and capecitabine is an active, well-tolerated regimen. The observed antitumor activity warrants further evaluation of this combination as an alternative to or in combination with whole-brain radiation therapy for the treatment of multiple brain metastases.

Adult↗

PubMed2006

ErbB2 increases vascular endothelial growth factor protein synthesis via activation of mammalian target of rapamycin/p70S6K leading to increased angiogenesis and spontaneous metastasis of human breast cancer cells.

ErbB2 overexpression in breast tumors results in increased metastasis and angiogenesis and reduced survival. To study ErbB2 signaling mechanisms in metastasis and angiogenesis, we did a spontaneous metastasis assay using MDA-MB-435 human breast cancer cells stably transfected with constitutively active ErbB2 kinase (V659E), a kinase-dead mutant of ErbB2 (K753M), or vector control (neo). Mice injected with V659E had increased metastasis incidence and tumor microvessel density than mice injected with K753M or control. Increased angiogenesis in vivo from the V659E transfectants paralleled increased angiogenic potential in vitro. V659E produced increased vascular endothelial growth factor (VEGF) through increased VEGF protein synthesis. This was mediated through signaling events involving extracellular signal-regulated kinase, phosphatidylinositol 3-kinase/Akt, mammalian target of rapamycin (mTOR), and p70S6K. The V659E xenografts also had significantly increased phosphorylated Akt, phosphorylated p70S6K, and VEGF compared with controls. To validate the clinical relevance of these findings, we examined 155 human breast tumor samples. Human tumors that overexpressed ErbB2, which have been previously shown to have higher VEGF expression, showed significantly higher p70S6K phosphorylation as well. Increased VEGF expression also significantly correlated with higher levels of Akt and mTOR phosphorylation. Additionally, patients with tumors having increased p70S6K phosphorylation showed a trend for worse disease-free survival and increased metastasis. Our findings show that ErbB2 increases VEGF protein production by activating p70S6K in cell lines, xenografts, and in human cancers and suggest that these signaling molecules may serve as targets for antiangiogenic and antimetastatic therapies.

Animals↗

PubMed2006

Correlation of cytologic findings and chromosomal instability detected by fluorescence in situ hybridization in breast fine-needle aspiration specimens from women at high risk for breast cancer.

Cytologic evaluation of ductal lavage or random periareolar fine-needle aspiration (FNA) specimens has been proposed to improve risk stratification of women at high risk for breast cancer. However, cytologic assessment of morphologic changes is subjective. To assess the utility of fluorescence in situ hybridization (FISH) in the categorization of breast lesions, we prospectively evaluated 32 random periareolar FNA specimens from 27 women at high risk for breast cancer. Cytologic specimens were prepared using the thin preparation technique, and diagnoses were made on the basis of previously published criteria. Specimens were also evaluated by FISH for chromosomes 1, 8, 11, and 17. Monosomy was defined as the loss of one signal or both signals in >20% of cells, and polysomy was defined as the presence of > or = 3 signals in >6% of cells. Cytologic smears from seven invasive ductal carcinomas and nine benign breast specimens from women at low risk for breast cancer were included for comparison. In the high-risk group, cytologic findings were nonproliferative epithelium (NPE) in 16 cases and hyperplasia in 16 cases. Chromosomal aberrations were detected in 11 (69%) of 16 NPE cases, 14 (89%) of 16 hyperplasia cases, seven (100%) of seven carcinoma cases, and none of the low-risk cases. High-risk cases had significantly more monosomy of chromosomes 1, 11, and 17 and polysomy of chromosome 8 compared to low-risk cases and significantly less polysomy of chromosomes 1, 8, 11, and 17 compared to patients with cancer. There were no significant differences in monosomy or polysomy of individual chromosomes or a combination of chromosomes between the NPE and hyperplasia groups. This study shows that aberrations of chromosome number are common in high-risk women irrespective of cytologic findings. Studies evaluating the association between specific patterns of chromosomal polysomy and progression to malignancy may be warranted.

Adult↗

PubMed2006

Bayesian dose-finding in phase I/II clinical trials using toxicity and efficacy odds ratios.

A Bayesian adaptive design is proposed for dose-finding in phase I/II clinical trials to incorporate the bivariate outcomes, toxicity and efficacy, of a new treatment. Without specifying any parametric functional form for the drug dose-response curve, we jointly model the bivariate binary data to account for the correlation between toxicity and efficacy. After observing all the responses of each cohort of patients, the dosage for the next cohort is escalated, deescalated, or unchanged according to the proposed odds ratio criteria constructed from the posterior toxicity and efficacy probabilities. A novel class of prior distributions is proposed through logit transformations which implicitly imposes a monotonic constraint on dose toxicity probabilities and correlates the probabilities of the bivariate outcomes. We conduct simulation studies to evaluate the operating characteristics of the proposed method. Under various scenarios, the new Bayesian design based on the toxicity-efficacy odds ratio trade-offs exhibits good properties and treats most patients at the desirable dose levels. The method is illustrated with a real trial design for a breast medical oncology study.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2005

Combined-modality treatment for isolated recurrences of breast carcinoma: update on 30 years of experience at the University of Texas M.D. Anderson Cancer Center and assessment of prognostic factors.

BACKGROUND: In three prospective, single-arm studies, the authors previously showed an improved outcome for anthracycline-naïve patients with isolated sites of recurrent breast carcinoma (BC) who were treated with doxorubicin-based chemotherapy after local therapy (surgery and/or radiotherapy). In the current report, the initial results are presented from a Phase II trial of docetaxel (100 mg/m(2) every 21 days for 6 cycles) given after local therapy for recurrent BC (Stage IV BC with no evidence of clinically measurable disease) in patients who received prior adjuvant anthracycline-based chemotherapy, and the authors provide an update of the 3 previous studies. An analysis of prognostic factors for these patients also is presented. METHODS: Eligibility criteria for all studies included histologic proof of recurrent BC that had been resected and/or irradiated with curative intent. Survival was calculated using the Kaplan-Meier method. Univariate survival analyses were performed to test for associations between patient characteristics and outcome (log-rank test). Cox proportional hazards models were used to determine the multivariable correlations between patient characteristics and outcome. RESULTS: The median follow-up for the docetaxel-based trial (n = 26 patients) was 45 months. Early outcomes for this study are promising. The median disease-free survival (DFS) was 44 months, and the 3-year DFS and overall survival (OS) rates were 58% and 87%, respectively. In the 3 doxorubicin-based studies, the median follow-up was 121.5 months for all living patients, and the estimated 20-year DFS and OS rates were both 26%. On multivariable analysis of patients from all 4 studies, the only significant prognostic factor for DFS and OS (P = 0.0006) was the number of involved axillary lymph nodes at initial diagnosis. CONCLUSIONS: A proportion of patients with isolated BC recurrences achieved prolonged DFS with combined-modality treatment. Patients who receive anthracycline-based chemotherapy at primary diagnosis may benefit from local treatment followed by docetaxel-based chemotherapy for isolated recurrences. The only significant independent prognostic factor was the number of involved axillary lymph nodes at initial diagnosis.

Adult↗

PubMed2005

Pair chart test for an early survival difference.

The log-rank test is commonly used in comparing survival distributions between treatment and control groups in clinical trials. However, in many studies, the treatment is only effective at the early stage of the trial. Especially when the two survival curves cross, the log-rank test has a low statistical power to show the survival difference. We propose a test statistic for detecting such an early difference between the two treatment arms. The new test has an intuitive geometric interpretation based on a pair chart and is shown to have more power than the log-rank test when the treatment effect only appears in the early phase of the study. This advantage is evaluated for finite sample sizes in simulation studies. Finally, the proposed method is illustrated with a real data example of patients with gastric cancer.

Biometry↗

PubMed2005

Self-designing trial combined with classical group sequential monitoring.

At the interim analyses of a clinical trial, it is appealing to modify the originally planned sample size in order to achieve an adequate power to detect a meaningful treatment effect. We propose a flexible sequential monitoring scheme through combining the self-designing and classical group sequential methods. The maximum sample size does not have to be specified in advance and one efficacy interim analysis is conducted for the purpose of possible early termination after the first block of data is observed. At the interim analysis for efficacy, the usual sufficient test statistic is used and the type I error rate is adjusted to maintain the overall nominal level. At the final analysis, the test is constructed from a weighted average of the blockwise test statistics based on the sequentially collected data. The weight function at each stage is determined by the observed data prior to that stage. The futility stopping rule allows the trial to be terminated when there is no beneficial treatment effect. We conduct simulation studies to evaluate the performance of the proposed design.

Algorithms↗

PubMed2005

Quantile regression models with multivariate failure time data.

As an alternative to the mean regression model, the quantile regression model has been studied extensively with independent failure time data. However, due to natural or artificial clustering, it is common to encounter multivariate failure time data in biomedical research where the intracluster correlation needs to be accounted for appropriately. For right-censored correlated survival data, we investigate the quantile regression model and adapt an estimating equation approach for parameter estimation under the working independence assumption, as well as a weighted version for enhancing the efficiency. We show that the parameter estimates are consistent and asymptotically follow normal distributions. The variance estimation using asymptotic approximation involves nonparametric functional density estimation. We employ the bootstrap and perturbation resampling methods for the estimation of the variance-covariance matrix. We examine the proposed method for finite sample sizes through simulation studies, and illustrate it with data from a clinical trial on otitis media.

Biometry↗

PubMed2005

A class of Bayesian shared gamma frailty models with multivariate failure time data.

For multivariate failure time data, we propose a new class of shared gamma frailty models by imposing the Box-Cox transformation on the hazard function, and the product of the baseline hazard and the frailty. This novel class of models allows for a very broad range of shapes and relationships between the hazard and baseline hazard functions. It includes the well-known Cox gamma frailty model and a new additive gamma frailty model as two special cases. Due to the nonnegative hazard constraint, this shared gamma frailty model is computationally challenging in the Bayesian paradigm. The joint priors are constructed through a conditional-marginal specification, in which the conditional distribution is univariate, and it absorbs the nonlinear parameter constraints. The marginal part of the prior specification is free of constraints. The prior distributions allow us to easily compute the full conditionals needed for Gibbs sampling, while incorporating the constraints. This class of shared gamma frailty models is illustrated with a real dataset.

Adolescent↗

PubMed2005

A general class of Bayesian survival models with zero and nonzero cure fractions.

We propose a new class of survival models which naturally links a family of proper and improper population survival functions. The models resulting in improper survival functions are often referred to as cure rate models. This class of regression models is formulated through the Box-Cox transformation on the population hazard function and a proper density function. By adding an extra transformation parameter into the cure rate model, we are able to generate models with a zero cure rate, thus leading to a proper population survival function. A graphical illustration of the behavior and the influence of the transformation parameter on the regression model is provided. We consider a Bayesian approach which is motivated by the complexity of the model. Prior specification needs to accommodate parameter constraints due to the non-negativity of the survival function. Moreover, the likelihood function involves a complicated integral on the survival function, which may not have an analytical closed form, and thus makes the implementation of Gibbs sampling more difficult. We propose an efficient Markov chain Monte Carlo computational scheme based on Gaussian quadrature. The proposed method is illustrated with an example involving a melanoma clinical trial.

Adult↗

PubMed2005

Adaptive design and estimation in randomized clinical trials with correlated observations.

Clinical trial designs involving correlated data often arise in biomedical research. The intracluster correlation needs to be taken into account to ensure the validity of sample size and power calculations. In contrast to the fixed-sample designs, we propose a flexible trial design with adaptive monitoring and inference procedures. The total sample size is not predetermined, but adaptively re-estimated using observed data via a systematic mechanism. The final inference is based on a weighted average of the block-wise test statistics using generalized estimating equations, where the weight for each block depends on cumulated data from the ongoing trial. When there are no significant treatment effects, the devised stopping rule allows for early termination of the trial and acceptance of the null hypothesis. The proposed design updates information regarding both the effect size and within-cluster correlation based on the cumulated data in order to achieve a desired power. Estimation of the parameter of interest and its confidence interval are proposed. We conduct simulation studies to examine the operating characteristics and illustrate the proposed method with an example.

Biometry↗

PubMed2005

Bayesian cure rate frailty models with application to a root canal therapy study.

Due to natural or artificial clustering, multivariate survival data often arise in biomedical studies, for example, a dental study involving multiple teeth from each subject. A certain proportion of subjects in the population who are not expected to experience the event of interest are considered to be "cured" or insusceptible. To model correlated or clustered failure time data incorporating a surviving fraction, we propose two forms of cure rate frailty models. One model naturally introduces frailty based on biological considerations while the other is motivated from the Cox proportional hazards frailty model. We formulate the likelihood functions based on piecewise constant hazards and derive the full conditional distributions for Gibbs sampling in the Bayesian paradigm. As opposed to the Cox frailty model, the proposed methods demonstrate great potential in modeling multivariate survival data with a cure fraction. We illustrate the cure rate frailty models with a root canal therapy data set.

Bayes Theorem↗

PubMed2005

Root canal filled versus non-root canal filled teeth: a retrospective comparison of survival times.

OBJECTIVE: This matched cohort study used data from a large dental HMO in the Pacific Northwest to evaluate the degree to which pulpal involvement and subsequent endodontic therapy affects tooth survival. Root canal filled (RCF) teeth were used as an indicator of pulpal involvement. Our hypothesis was that RCF teeth would be extracted sooner than non-RCF teeth matched within subjects, controlling for tooth-level variables of interest. METHODS: The HMO's treatment databases and a subsequent chart audit were used to identify 202 eligible subjects, each of whom had one tooth endodontically treated in 1987-88 and a similar contralateral tooth that was non-RCF at that time. Both teeth were followed from the endodontic access date through the extraction date, the endodontic access date (for initially non-RCF teeth), or 12/31/94, whichever was earliest. Time-to-event analyses were carried out, with Kaplan-Meier curves generated and multivariable marginal proportional hazards regression models fitted to describe the effect of RCF status on tooth survival. All statistical analyses accounted for the complex sampling strategy used in generating the dataset. RESULTS: Teeth were followed for up to eight (median = 6.7) years. RCF teeth had substantially worse survival than their non-RCF counterparts (p < 0.001), with a greater effect of RCF status evident among molars than non-molars. Adjusted hazard ratios (95% confidence intervals) for loss of RCF versus non-RCF molars and non-molars were 7.4 (3.2-15.1) and 1.8 (0.7-4.6), respectively. CONCLUSION: Though endodontic therapy can prolong tooth survival, pulpal involvement still may hasten tooth loss, underscoring the importance of caries prevention and prompt restorative care.

Adult↗

PubMed2004

Two simulation methods for constructing confidence bands under the additive risk model.

With right-censored failure time data, we propose procedures to construct simultaneous confidence bands for the survival curve of a given subject under the additive risk model. The distribution of the subject-specific cumulative hazard function can be approximated with a zero-mean Gaussian process, which can be generated through simulation methods. We propose two different simulation schemes to obtain the distribution of the supremum of the cumulative hazard process over the entire time range. The two simulation approaches are asymptotically equivalent, whereas the numerical forms are different. We construct two types of confidence bands, namely the equal precision band and the Hall-Wellner type band, through choosing suitable weight functions. Monte Carlo simulation studies show that both of the proposed confidence bands are appropriate for finite sample sizes. We illustrate the new proposal with a real example.

Computer Simulation↗

PubMedDate not supplied

Novel clinical trial designs for treatment of ductal carcinoma in situ of the breast with trastuzumab (herceptin).

Because ductal carcinoma in situ (DCIS) avidly expresses Her2/neu, the target of the monoclonal antibody trastuzumab, and because trastuzumab has been shown to be effective against invasive breast cancer, trastuzumab may be effective for reducing the tumor burden and abrogating or reversing the hypothesized transition from in situ to invasive disease in patients with DCIS. To test this hypothesis, a trial of neoadjuvant trastuzumab for DCIS has been opened at our institution. Because trastuzumab has been shown to act as a radiosensitizing agent for Her2/neu-overexpressing cancer and because there are currently no systemic treatments for estrogen-receptor-negative DCIS, it makes sense to investigate whether use of trastuzumab concurrently with postoperative radiation therapy improves local control of DCIS. The National Surgical Adjuvant Breast and Bowel Project (NSABP) is planning a trial to test this hypothesis. The risk of cardiac toxicity associated with the doses of trastuzumab planned for these trials (cumulative doses of 8 mg/kg for our trial and 14 mg/kg in the NSABP trial) is believed to be minimal, but the safety profile of these approaches will need to be closely monitored.

Antibodies, Monoclonal↗