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Results for “NEOPLASM STATISTICS”

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PubMed1988

[Statistical analysis of pathological factors influencing prognosis of colorectal carcinoma].

The pathological and follow-up data of 503 patients with colorectal carcinoma have been analysed to assess quantitatively prognostic values of 16 pathological factors and their sub-categories with aid of computer. Besides the routine procedure, Cox's proportional hazards model, Hayashi's quantification theory II, III, Akaike's information criteria, Kendall's rank correlation, relative risk, and linear trend test were used. Regardless of methods used, liver metastasis, peritoneal dissemination, lymph nodes metastasis, depth of penetration, venous and lymphatic invasion emerged as powerful prognostic variables. Most of the analyses indicated that venous invasion contained the largest amount of prognostic information including that of long-term survival. When venous invasion is graded not only by the number of veins involved but also by the depth of invasion, its prognostic capability was comparable with that of staging systems. The values of relative risks calculated for the factors' sub-category were more closely associated with prognosis than five-year survival rates or median survival rates, thus permitting detailed comparison of different categories. We conclude the modern statistical methods are indispensable tool for prognostic factor analysis.

Colonic Neoplasms↗
PubMed2001

Multiple imputation methods for estimating regression coefficients in the competing risks model with missing cause of failure.

We propose a method to estimate the regression coefficients in a competing risks model where the cause-specific hazard for the cause of interest is related to covariates through a proportional hazards relationship and when cause of failure is missing for some individuals. We use multiple imputation procedures to impute missing cause of failure, where the probability that a missing cause is the cause of interest may depend on auxiliary covariates, and combine the maximum partial likelihood estimators computed from several imputed data sets into an estimator that is consistent and asymptotically normal. A consistent estimator for the asymptotic variance is also derived. Simulation results suggest the relevance of the theory in finite samples. Results are also illustrated with data from a breast cancer study.

Breast Neoplasms↗
PubMed2004

In vivo assessment of antiangiogenic activity of SU6668 in an experimental colon carcinoma model.

PURPOSE: The purpose of this research was to assess in vivo by dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) the antiangiogenic effect of SU6668, an oral, small molecule inhibitor of the angiogenic receptor tyrosine kinases vascular endothelial growth factor receptor 2 (Flk-1/KDR), platelet-derived growth factor receptor, and fibroblast growth factor receptor 1. EXPERIMENTAL DESIGN: A s.c. tumor model of HT29 human colon carcinoma in athymic mice was used. DCE-MRI with a macromolecular contrast agent was used to measure transendothelial permeability and fractional plasma volume, accepted surrogate markers of tumor angiogenesis. CD31 immunohistochemical staining was used for assessing microvessels density and vessels area. Experiments were performed after 24 h, and 3, 7, and 14 days of treatment. RESULTS: DCE-MRI clearly detected the early effect (after 24 h of treatment) of SU6668 on tumor vasculature as a 51% and 26% decrease in the average vessel permeability measured in the tumor rim and core (respectively). A substantial decrease was also observed in average fractional plasma volume in the rim (59%) and core (35%) of the tumor. Histological results confirmed magnetic resonance imaging findings. After 3, 7, and 14 days of treatment, postcontrast magnetic resonant images presented a thin strip of strongly enhanced tissue at the tumor periphery; histology examination showed that this hyperenhanced ring corresponded to strongly vascularized tissue adjacent but external to the tumor. Histology also revealed a strong decrease in the thickness of peripheral viable tissue, with a greatly reduced vessel count. SU6668 greatly inhibited tumor growth, with 60% inhibition at 14 days of treatment. CONCLUSIONS: DCE-MRI detected in vivo the antiangiogenic efficacy of SU6668.

Angiogenesis Inhibitors↗
PubMed2005

Skeletal retention of bisphosphonate (pamidronate) and its relation to the rate of bone resorption in patients with breast cancer and bone metastases.

UNLABELLED: Bisphosphonate pharmacokinetics may affect individual responses. Skeletal retention of pamidronate infused monthly to patients with bone metastases was highly variable (12-98%) and did not diminish with time, showing the capacity of the skeleton to retain large amounts of bisphosphonate. Relationships between skeletal retention of pamidronate and rate of bone resorption are complex and depend on previous treatment and the total amount of retained bisphosphonate. INTRODUCTION: Bisphosphonates (BPs) given intravenously every 3-4 weeks are effective in the management of metastatic bone disease from breast cancer, but responses among patients vary, and it is not known whether current dose and dose intervals are appropriate for an individual patient. An influence of pharmacokinetics of BPs on antiresorptive action may contribute to this variation in response. To test this hypothesis, we determined the skeletal retention of intravenous pamidronate and its association to the rate of bone resorption in patients with bone metastases from breast cancer. MATERIALS AND METHODS: In a cross-sectional study, 24-h urinary excretion of pamidronate and the biochemical marker of bone resorption N-terminal telopeptide of type 1 collagen and serum alkaline phosphatase were measured in 40 patients with bone metastases from breast cancer at the beginning, after 3-6 months, and after 1 year of treatment with intravenous pamidronate 90 mg every 3-4 weeks. RESULTS AND CONCLUSIONS: Skeletal retention (dose--amount excreted into urine) 2 days after infusion varied between 12% and 98% (mean, 62%) of the administered dose, but there were no differences in retention between patients receiving pamidronate for the first time or after 3-6 months or after 1 year of treatment. Retention of pamidronate was related to the prevalent rate of bone turnover in previously untreated patients, whereas no such relationship was found in previously treated patients. Rate of bone resorption after treatment seemed to be related to the amount of pamidronate retained. During 1 year of treatment, retention of pamidronate remained constant, indicating no saturation of skeletal binding sites with treatment. The variability in retention among individual patients can be attributed to the number of available binding sites. This is related, however, to bone turnover only before the start of treatment. The apparent relationships between skeletal retention and antiresorptive effect could have implications for the design of optimal therapeutic regimens with BPs in patients with bone metastases from breast cancer.

Aged↗
PubMed2002

Singular value decomposition regression models for classification of tumors from microarray experiments.

An important problem in the analysis of microarray data is correlating the high-dimensional measurements with clinical phenotypes. In this paper, we develop predictive models for associating gene expression data from microarray experiments with such outcomes. They are based on the singular value decomposition. We propose new algorithms for performing gene selection and gene clustering based on these predictive models. The estimation procedure using the regression models occurs in two stages. First, the gene expression measurements are transformed using the singular value decomposition. The regression parameters in the model linking the principal components with the clinical responses are then estimated using maximum likelihood. We demonstrate the application of the methodology to data from a breast cancer study.

Breast Neoplasms↗