Randomized controlled trial of pimecrolimus 1% cream for treatment of facial acne vulgaris.
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Acne Vulgaris↗
Biomedical subjects
Karen Fung
Publications and source records attributed to Karen Fung.
Dispositional optimism predicts survival status 1 year after diagnosis in head and neck cancer patients.
PURPOSE: The aim of this study was to investigate the hypothesis that, independent of other known prognostic factors, pessimistic head and neck (H&N) cancer patients have a greater risk of being dead 1 year after diagnosis than do optimistic patients. PATIENTS AND METHODS: A prospective observational study design was used with a cohort of H&N cancer patients diagnosed during the period from March 1, 1997, to August 31, 1998, at the Centre Hospitalier Universitaire, Clermont-Ferrand, France. Dispositional optimism (DO) was evaluated at baseline using a French version of the Life Orientation Test translated and validated for this study. One-year survival status was collected on all subjects. The analysis of the hypothesized association between DO and 1-year survival was performed using multiple logistic regression analysis, controlling for other sociodemographic and clinical variables. RESULTS: The sample size was 101 patients, representing all but one of those patients fitting the inclusion criteria who were diagnosed during the recruitment period. Of these, 51 were alive at 1 year after diagnosis, 45 were dead, and five were lost to follow-up. The multivariate analysis was performed on the data from the 96 subjects in whom 1-year survival status was known. Controlling for known predictors of H&N cancer survival, pessimistic subjects (odds ratio [OR], 1.12; 95% confidence interval [CI], 1.01 to 1.24) and those living alone (OR, 4.14; 95% CI, 1.21 to 14.17) were more likely than optimistic subjects and those living with others to be dead at 1 year. CONCLUSION: The results of this study of a cohort of French H&N cancer patients indicate that dispositional optimism predicts 1-year survival independent of other sociodemographic and clinical variables.
Adult↗
Defining patient-based minimal clinically important effect sizes: a study in palliative radiotherapy for painful unresectable pelvic recurrences from rectal cancer.
PURPOSE: To measure patient-based minimal clinically important effect sizes (minimal incremental benefit that an individual would require to accept one treatment option over another) for pain relief between two contrasting palliative radiotherapy regimens for painful pelvic recurrences from rectal cancer. METHODS AND MATERIALS: Forty-three patients with a history of cancer pain without prior pelvic radiotherapy participated in decision aid-facilitated trade-off exercises. The clinical scenario and treatment options of a 5-day vs. a 20-day course of radiotherapy were described. The duration of pain relief for the 20-day regimen was increased until the respondents' preferences switched to the 20-day regimen. The exercises were repeated for different probabilities of benefit and pain intensity at the time of decision making. RESULTS: When the probability of pain relief was unchanged, the median switch point for the duration of pain relief was 6.7 and 7.2 months for severe and mild pain, respectively. The cumulative percentage frequency curve for the switch points approximated a sigmoid distribution. CONCLUSION: Determining the minimal clinically important effect sizes for symptom relief for palliative therapies is feasible. This type of information can be used to incorporate patient values into clinical trial designs. Modification of this method can be used to improve our understanding of shared (physician and patient) decision making.
Decision Making↗
Testing the harvesting hypothesis by time-domain regression analysis. I: baseline analysis.
Although the association between air pollution and daily mortality is well established, the mechanisms by which air pollution results in excess mortality are not yet well understood. In particular, there exists debate over whether air pollution has a direct effect on mortality in the general population or simply shortens the life span of frail individuals, a hypothesis referred to as "harvesting." The goal of this investigation is to test the harvesting hypothesis using the time-domain regression method of Dominici et al. (2003a). We conducted simulations based on a two-compartment model that divides the population into a larger group of healthy individuals and a frail subpopulation. Death from air pollution is assumed to take place in two steps, by first moving from healthy population to the frail pool, then death with probability related to the level of air pollution. Using time-domain analysis, we seek to identify data patterns that would be characteristic of harvesting under different scenarios. For a pure harvesting model, time-domain analysis indicates that mortality is associated with a short-term air pollution episode of less than 2 d if the mean residency time in the frail pool is short. If both entrants and deaths depend on the level of air pollution and the rates of entry to and exit from the frail pool are about the same, the log relative risk estimates are essentially unchanged at all time scales. If pollution affects mortality in the frail pool more than entrants, larger effects will occur at shorter time scales.
Air Pollution↗
Testing the harvesting hypothesis by time-domain regression analysis. II: covariate effects.
This article extends the previous work of Fung et al. (2004) investigating the ability of the time-scale log-linear regression model, proposed by Dominici et al. (2003), to detect mortality displacement (sometimes known as harvesting) in time-series data relating air pollution to excess mortality. We conducted a simulation study based on two different compartment models of the death process: pure frailty model and mixed frailty model. We assume that nonaccidental death only affects frail population in a pure frailty model and affects both frail people and other individuals in the mixed frailty model. With a pure frailty model and a moderate-size pollution effect, we identified a characteristic mortality displacement pattern in the different time-scale coefficients of log relative risk. However, once a covariate like temperature was introduced into the model, such a mortality displacement pattern disappeared. Furthermore, a false mortality displacement effect was present in the incorrectly specified model, when temperature was not taken into account. We believe that time-scale regression has limited value for detecting mortality displacement in time-series data.
Air Pollution↗
A comparison of caries rates in non-institutionalized individuals with and without Down syndrome.
The caries rate of people with Down syndrome (DS) was compared to an age-matched control population without DS. A cross-sectional study design was used. Caries rates were assessed by an adjusted DFT score, expressed as a proportion of number of teeth in the mouth, to control for hypodontia in the subjects with DS. Bivariate and multiple linear regression analyses were used to compare caries rates in persons with and without DS. The sample size was 128, in which 44 were subjects with DS and 84 were subjects without DS. On a range of 0-1, the mean adjusted DFT scores were 0.10 in subjects with DS and 0.18 in the control group. Although this difference was significant at the bivariate level of analysis, in the multiple linear regression model, adjusted DFT was associated with age and professional fluoride therapy only. When expressed as a proportion of number of teeth, caries rates were not different in people with and without DS.
Adolescent↗