Evaluating the effectiveness of population-based breast cancer service screening: an analysis of parsimonious patient survival information with the time-varying Cox model.

BACKGROUND: This study is aimed at estimating the unbiased effectiveness of population-based breast cancer service screening based on case survival information alone rather than large-scale individual screening data pursuant to the intention-to-treat principle of a randomized-controlled trial. METHODS: A novel time-dependent switched design with two modalities of cancer detection (screen-detected vs clinically detected) was proposed to evaluate the effectiveness of breast cancer screening. We used data on 767 patients from Kopparberg in the Swedish Two-County trial and on 78 587 patients in the Taiwan population-based service screening. We estimated the relative rate of the screen-detected vs the clinically detected with adjustment for both truncation and lead-time biases. The absolute effectiveness in terms of the number needed to screen (NNS) for averting one death from breast cancer was estimated. RESULTS: The relative rate of effectiveness was estimated as 33%, which was consistent with the 37% reported from the original Swedish randomized-controlled trial. The corresponding estimate for the Taiwan screening programme was 42%, which was also very close to that estimated using individual screening history data (41%). Both relative estimates were further applied to yield 446 and 806 of NNS for averting one death from breast cancer for the corresponding two data sets. CONCLUSION: The proposed time-dependent switched design and analysis with two modalities of case survival information provides a very efficient means for estimating the unbiased estimates of relative and absolute effectiveness of population-based breast cancer service screening dispensing with a large amount of individual screening history data.

Health status and life satisfaction among people with disabilities: Evidence from Taiwan.

BACKGROUND: Two important dimensions of subjective well-being are self-reported 'health status' and 'life satisfaction', both of which are generally perceived as being lower among people with disabilities. Although the factors associated with health status and life satisfaction have been well documented among the general population, relevant research relating to disabled people remains limited, indeed, almost non-existent in Taiwan. OBJECTIVE: Our aim in the present study is to explore the levels of, and the factors associated with, self-reported health status and life satisfaction among people with disabilities in Taiwan. METHODS: The dataset used in this study was drawn from a representative population-based survey carried out in a municipal city in Taiwan involving 983 disabled people aged between 15 and 64. Descriptive statistics were applied to provide both a profile of the respondents and the distribution of the related variables, with ordinal logistic regression models being employed to identify the factors associated with health status and life satisfaction. RESULTS: As compared to the findings reported on western societies, health status and life satisfaction levels among disabled people in Taiwan were found to be similar. Age, incidences of chronic conditions, and medical barriers encountered were found to have negative associations with health status, whilst better household finances, living environment, and social support were positively associated with life satisfaction. CONCLUSIONS: Since both individual and contextual factors may be related to the subjective well-being of disabled people, policy interventions should target specific aspects so as to improve the lives of people with disabilities.

The effects of omega-3 fatty acids monotherapy in Alzheimer's disease and mild cognitive impairment: a preliminary randomized double-blind placebo-controlled study.

A 24-week, randomized, double-blind placebo-controlled study was carried out to test the feasibility of using omega-3 polyunsaturated fatty acids (PUFAs) monotherapy in people with cognitive impairment and to explore its effects on cognitive function and general clinical condition in these participants. Twenty three participants with mild or moderate Alzheimer's disease and twenty three with mild cognitive impairment were randomized to receive omega-3 PUFAs 1.8 g/day or placebo (olive oil). The data of 35 (76%) participants with at least one post-treatment visit was analyzed. There were no severe adverse effects in either group and it suggests that omega-3 PUFAs were well tolerable in this population. The treatment group showed better improvement on the Clinician's Interview-Based Impression of Change Scale (CIBIC-plus) than those in the placebo group over the 24 week follow-up (p=0.008). There was no significant difference in the cognitive portion of the Alzheimer's Disease Assessment Scale (ADAS-cog) change during follow-up in these two groups. However, the omega-3 fatty acids group showed significant improvement in ADAS-cog compared to the placebo group in participants with mild cognitive impairment (p=0.03), which was not observed in those with Alzheimer's disease. Higher proportions of eicosapentaenoic acid on RBC membranes were also associated with better cognitive outcome (p=0.003). Further studies should be considered with a larger-sample size, diet registration, higher dosages, comparisons between different combinations of PUFAs, and greater homogeneity of participants, especially those with mild Alzheimer's disease and mild cognitive impairment.

High-breakdown estimation of multivariate mean and covariance with missing observations.

We consider the problem of outliers in incomplete multivariate data when the aim is to estimate a measure of mean and covariance, as is the case, for example, in factor analysis. The ER algorithm of Little and Smith which combines the EM algorithm for missing data and a robust estimation step based on an M-estimator could be used in such a situation. However, the ER algorithm as originally proposed can fail to be robust in some cases, especially in high dimensions. We propose here two alternatives to avoid the problem. One is to combine a small modification of the ER algorithm with a so-called high-breakdown estimator as the starting point for the iterative procedure, and the other is to base the estimation step of the ER algorithm on a high-breakdown estimator. Among the high-breakdown estimators which are actually built to keep their robustness properties even if the number of variables is relatively large, we consider here the minimum covariance determinant estimator and the t-biweight S-estimator. Simulated and real data are used to compare and illustrate the different procedures.