PubMed · 14514950
Two patients are presented with primary low grade pleural B cell lymphomas with no history of a pyothorax.
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H Ahmad, J Pawade, S Falk, J A Morgan, L Balacumaraswami. 2003. Primary pleural lymphomas.. https://doi.org/10.1136/thorax.58.10.908
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We review the literature on the combined association between lung cancer and two environmental exposures, asbestos exposure and smoking, and explore a Bayesian approach to assess evidence of interaction between the exposures. The meta-analysis combines separate indices of additive and multiplicative relationships and multivariate relative risk estimates. By making inferences on posterior probabilities we can explore both the form and strength of interaction. This analysis may be more informative than providing evidence to support one relation over another on the basis of statistical significance. Overall, we find evidence for a more than additive and less than multiplicative relation.
For comparing the validity of rating methods, the adjusted kappa (S coefficient) and Yule's Y index are better than Cohen's kappa which is affected by marginal probabilities. We consider a validity study in which a subject is assessed as exposed or not-exposed by two competing rating methods and the gold standard. We are interested in one of the methods, which is closer in agreement with the gold standard. We present statistical methods taking correlations into account for comparing the validity of the rating methods using S coefficient and Y index. We show how the S coefficient and Yule's Y index are related to sensitivity and specificity. In comparing the two rating methods, the preference is clear when the inference is the same for both S and Y. If the inference using S differs from that using Y, then it is not obvious how to decide a preference. This may occur when one rating method is better than the other in sensitivity but not in specificity. Numerical examples for comparing asbestos-exposure assessment methods are illustrated.
BACKGROUND: Asbestos-linked public health problems were widely reported in Japan, in 2005. The objective is to apply text mining with network analysis to characterize these problems. METHODS: Text mining with network analysis of newspaper headlines including the word 'asbestos' published in 1987 and 2005 was conducted. Outcome measures are occurrence of the words and simultaneous occurrence of two words in the newspaper headlines. RESULTS: In 36 headlines, which contained the word 'asbestos' in 1987, the word 'pollution' (40%) appeared most frequently, followed by 'removal' (31%) and 'campaign' (29%). For combinations of words, the following occurred most frequently: 'campaign and expulsion' (26%) followed by 'removal and campaign' (14%). Of 293 headlines in 2005, the following words appeared: 'hazard' (31%), 'person' (16%) and 'death' (13%). For combinations, the following appeared: 'person and death' (9%). Asbestos pollution and removal campaigns were reported in 1987, but the death of citizens was reported in 2005. CONCLUSIONS: Text mining with network analysis, which presents one of the methods for visualization of text data, suggests the following insight. Insufficient steps against asbestos had been taken for 20 years, which is compatible with the latency period. It has resulted in widespread exposure to asbestos and more severe asbestos-related public health problems among citizens. This methodology suggests that analyzing text data by this method can serve future surveillance and efficient use of epidemiological knowledge.