Association between an interleukin 1 receptor, type I promoter polymorphism and self-reported attentional function in women with breast cancer.

Subgroups of patients with breast cancer may be at greater risk for cytokine-induced changes in cognitive function after diagnosis and during treatment. The purposes of this study were to identify subgroups of patients with distinct trajectories of attentional function and evaluate for phenotypic and genotypic (i.e., cytokine gene polymorphisms) predictors of subgroup membership. Self-reported attentional function was evaluated in 397 patients with breast cancer using the Attentional Function Index before surgery and for six months after surgery (i.e., seven time points). Using growth mixture modeling, three attentional function latent classes were identified: High (41.6%), Moderate (25.4%), and Low-moderate (33.0%). Patients in the Low-moderate class were significantly younger than those in the High class, with more comorbidities and lower functional status than the other two classes. No differences were found among the classes in years of education, race/ethnicity, or other clinical characteristics. DNA was recovered from 302 patients' samples. Eighty-two single nucleotide polymorphisms among 15 candidate genes were included in the genetic association analyses. After controlling for age, comorbidities, functional status, and population stratification due to race/ethnicity, IL1R1 rs949963 remained a significant genotypic predictor of class membership in the multivariable model. Carrying the rare "A" allele (i.e., GA+AA) was associated with a twofold increase in the odds of belonging to a lower attentional function class (OR: 1.98; 95% CI: 1.18, 3.30; p=.009). Findings provide evidence of subgroups of women with breast cancer who report distinct trajectories of attentional function and of a genetic association between subgroup membership and an IL1R1 promoter polymorphism.

Exploring the clinical course of neck pain in physical therapy: a longitudinal study.

OBJECTIVE: To investigate the short-term trajectory of recovery from mechanical neck pain, and predictors of trajectory. DESIGN: Prospective, longitudinal cohort study with 5 repeated measurements over 4 weeks. SETTING: Community-based physical therapy clinics. PARTICIPANTS: Convenience sample of community-dwelling adults (N=50) with uncomplicated mechanical neck disorders of any duration. INTERVENTIONS: Usual physical therapy care. MAIN OUTCOME MEASURES: Neck Disability Index (NDI), numeric rating scale (NRS) of pain intensity. RESULTS: A total of 50 consecutive subjects provided 5 data points over 4 weeks. Exploratory modeling using latent class growth analysis revealed a linear trend in improvement, at a mean of 1.5 NDI points and 0.5 NRS points per week. Within the NDI trajectory, 3 latent classes were identified, each with a unique trend: worsening (14.5%), rapid improvement (19.6%), and slow improvement (65.8%). Within the NRS trajectory, 2 unique trends were identified: stable (48.0%) and improving (52.0%). Predictors of trajectory class suggest that it may be possible to predict the trajectory. Results are described in view of the sample size. CONCLUSIONS: The mean trajectory of improvement in neck pain adequately fits a linear model and suggests slow but stable improvement over the short term. However, up to 3 different trajectories have been identified that suggest neck pain, and recovery thereof, is not homogenous. This may hold value for the design of clinical trials.

Comparison of phenotypes of childhood wheeze and cough in 2 independent cohorts.

BACKGROUND: Among children with wheeze and recurrent cough there is great variation in clinical presentation and time course of the disease. We previously distinguished 5 phenotypes of wheeze and cough in early childhood by applying latent class analysis to longitudinal data from a population-based cohort (original cohort). OBJECTIVE: To validate previously identified phenotypes of childhood cough and wheeze in an independent cohort. METHODS: We included 903 children reporting wheeze or recurrent cough from an independent population-based cohort (validation cohort). As in the original cohort, we used latent class analysis to identify phenotypes on the basis of symptoms of wheeze and cough at 2 time points (preschool and school age) and objective measurements of atopy, lung function, and airway responsiveness (school age). Prognostic outcomes (wheeze, bronchodilator use, cough apart from colds) 5 years later were compared across phenotypes. RESULTS: When using a 5-phenotype model, the analysis distinguished 3 phenotypes of wheeze and 2 of cough as in the original cohort. Two phenotypes were closely similar in both cohorts: Atopic persistent wheeze (persistent multiple trigger wheeze and chronic cough, atopy and reduced lung function, poor prognosis) and transient viral wheeze (early-onset transient wheeze with viral triggers, favorable prognosis). The other phenotypes differed more between cohorts. These differences might be explained by differences in age at measurements. CONCLUSIONS: Applying the same method to 2 different cohorts, we consistently identified 2 phenotypes of wheeze (atopic persistent wheeze, transient viral wheeze), suggesting that these represent distinct disease processes. Differences found in other phenotypes suggest that the age when features are assessed is critical and should be considered carefully when defining phenotypes.

Discovering different profiles in the dynamics of depression based on real-time monitoring of mood: a first exploration.

BACKGROUND: Although depression is typically characterized by a persistent depressed mood, mood dynamics do seem to vary across a depressed population. Heterogeneity of mood variability (magnitude of changes) and emotional inertia (speed at which mood shifts) is seen in clinical practice. However, studies investigating the heterogeneity of these mood dynamics are still scarce. The aim of the present study is to explore different distinctive profiles in real-time monitored mood dynamics among depressed persons. METHODS: After completing baseline measures, mildly-to-moderately depressed persons (n = 37) were prompted to rate their current mood (1-10 scale) on their smartphones, 3 times a day for 7 consecutive days. Latent profile analyses were applied to identify profiles based on average mood, variability of mood and emotional inertia as reported by the participants. RESULTS: Two profiles were identified in this sample. The overwhelming majority of the sample belonged to profile 1 (n = 31). Persons in profile 1 were characterized by a mood just above the cutoff for positive mood (M = 6.27), with smaller mood shifts (lower variability [SD = 1.05]) than those in profile 2 (n = 6), who displayed an overall negative mood (M = 4.72) and larger mood shifts (higher variability [SD = 1.95]) but at similar speed (emotional inertia) (AC = 0.19, AC = 0.26, respectively). CONCLUSIONS: The present study provides preliminary indications for patterns of average mood and mood variability, but not emotional inertia, among mildly-to-moderately depressed persons.