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At least 1,351 records · Page 75Linked to original sources
PubMed1999

Assessing the consistency of psychometric properties of the HRQoL scales within the EORTC QLQ-C30 across populations by means of the Mokken Scaling Model.

This paper demonstrates how the Mokken Scaling Model and other statistical tools may be useful in assessing the consistency of psychometric properties of health-related quality of life (HRQoL) scales across various populations. The main focus is the psychometric performance of the scales proposed for the EORTC QLQ-C30 in seven patient groups totalling more than 2,000 cancer patients. All scales performed satisfactorily in the total sample with the exception of the role functioning and cognitive functioning scales, which failed in terms of reliability and item discriminant validity. The descriptive statistics for the scales show that several of them, particularly those that build upon only two items, have discrimination problems at the extremes, visible in the high percentages at the maximum or the minimum observed values. The scalability analysis in the subsamples showed that the essential assumption in the Mokken Scaling Model of equal item step order does not hold for the cognitive functioning, emotional functioning and physical functioning scales. We conclude that the Mokken Scaling Model is well suited to the purpose of examining the generalizability of HRQoL scales across subpopulations although a global statistical test of the fit of the measurement model is not available.

Activities of Daily Living↗
PubMed2006

Parametric regression on cumulative incidence function.

We propose parametric regression analysis of cumulative incidence function with competing risks data. A simple form of Gompertz distribution is used for the improper baseline subdistribution of the event of interest. Maximum likelihood inferences on regression parameters and associated cumulative incidence function are developed for parametric models, including a flexible generalized odds rate model. Estimation of the long-term proportion of patients with cause-specific events is straightforward in the parametric setting. Simple goodness-of-fit tests are discussed for evaluating a fixed odds rate assumption. The parametric regression methods are compared with an existing semiparametric regression analysis on a breast cancer data set where the cumulative incidence of recurrence is of interest. The results demonstrate that the likelihood-based parametric analyses for the cumulative incidence function are a practically useful alternative to the semiparametric analyses.

Breast Neoplasms↗
PubMed1997

Spatial statistical analysis of Chinese cancer mortality: a comparison study of the D statistic.

In this paper, we study a nonparametric spatial pattern test statistic, the D statistic. The D statistic is an effective test statistic for testing spatial patterns in regional health data. Comparison studies of the D statistic with fixed weights and random weights are illustrated on the atlas of the Chinese cancer mortality rates and on other cancer atlas. Some social, economic and environmental reasons for statistically significant spatial autocorrelations of the Chinese cancer mortality rates were given in the discussion section. The method for calculating the mean and the variance of the randomly weighted D statistic is given in the appendix.

China↗
PubMed2005

An entropy-based gene selection method for cancer classification using microarray data.

BACKGROUND: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. RESULTS: The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets. CONCLUSION: This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

Algorithms↗
PubMed2006

Risk factors for induction of breast cancer by X-rays and their implications for breast screening.

In order to discuss the balance of benefit and radiation risk in a breast screening programme, it is necessary to have numerical values for the probability of breast cancer induction by X-rays, stratified by age. Various sets of such values have been used hitherto, mainly in relation to breast screening in the UK, both within the NHS Screening Programme and more generally for younger age groups. Further sets have recently been reported. These different sets of values are described and discussed, together with the effects of using additive or relative risk models, and the effect of using a dose and dose rate modifying factor (DDREF). Possible new radiation risk factors for breast cancer induction by X-rays, drawn from these sets, are identified. These are used to calculate fresh values of cancer detection/induction ratios, as an index of benefit/risk, for screening age women and for younger women with and without a family history of breast cancer.

Adult↗