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Biomedical subjects

Gail E Tudor

Publications and source records attributed to Gail E Tudor.

2 recordsLinked to original sources

Repeated measurement of nasal lavage fluid chemokines in school-age children with asthma.

BACKGROUND: Inflammatory processes at the mucosal surface may play a role in maintenance of asthma pathophysiology. Cross-sectional studies in asthmatic patients suggest that chemokines such as interleukin 8 (IL-8) are overproduced by respiratory epithelium. OBJECTIVE: To test the hypothesis that chemokine levels are persistently elevated in the respiratory secretions of asthmatic children at a stable baseline. METHODS: We measured nasal lavage fluid (NLF) levels of chemokines and other mediators at 3- to 4-month intervals in a longitudinal study of asthmatic children, with nonasthmatic siblings as controls. RESULTS: In a linear mixed-model analysis, both family and day of visit had significant effects on nasal mediators. Thus, data for 12 asthmatic-nonasthmatic sibling pairs who had 3 or more same-day visits were analyzed separately. For sibling pairs, median eosinophil cationic protein levels derived from serial measurements in NLF were elevated in asthmatic patients compared with nonasthmatic patients, with a near-significant tendency for elevation of total protein and eotaxin levels as well. However, no significant differences were found for IL-8 or several other chemokines. Ratios of IL-13 or IL-5 to interferon-gamma released by house dust mite antigen-stimulated peripheral blood mononuclear cells, tested on a single occasion, were significantly increased for asthmatic patients. CONCLUSIONS: Substantial temporal and family-related variability exists in nasal inflammation in asthmatic children. Although higher levels of eosinophil cationic protein are usually present in NLF of patients with stable asthma compared with patients without asthma, chemokines other than eotaxin are not consistently increased. Eosinophil activation at the mucosal surface is a more consistent predictor of asthmatic symptoms than nonspecific elevation of epithelium-derived inflammatory chemokine levels.

Adolescent↗

Can one assess whether missing data are missing at random in medical studies?

For handling missing data, newer methods such as those based on multiple imputation are generally more accurate than older ones and entail weaker assumptions. Yet most do assume that data are missing at random (MAR). The issue of assessing whether the MAR assumption holds to begin with has been largely ignored. In fact, no way to directly test MAR is available. We propose an alternate assumption, MAR+, that can be tested. MAR+ always implies MAR, so inability to reject MAR+ bodes well for MAR. In contrast, MAR implies MAR+ not universally, but under certain conditions that are often plausible; thus, rejection of MAR+ can raise suspicions about MAR. Our approach is applicable mainly to studies that are not longitudinal. We present five illustrative medical examples, in most of which it turns out that MAR+ fails. There are limits to the ability of sophisticated statistical methods to correct for missing data. Efforts to try to prevent missing data in the first place should therefore receive more attention in medical studies than they have heretofore attracted. If MAR+ is found to fail for a study whose data have already been gathered, extra caution may need to be exercised in the interpretation of the results.

Biomedical Research↗