Depression rating scales in Parkinson's disease: critique and recommendations.

Depression is a common comorbid condition in Parkinson’s disease (PD) and a major contributor to poor quality of life and disability. However, depression can be difficult to assess in patients with PD due to overlapping symptoms and difficulties in the assessment of depression in cognitively impaired patients. As several rating scales have been used to assess depression in PD (dPD), the Movement Disorder Society commissioned a task force to assess their clinimetric properties and make clinical recommendations regarding their use. A systematic literature review was conducted to explore the use of depression scales in PD and determine which scales should be selected for this review. The scales reviewed were the Beck Depression Inventory (BDI), Hamilton Depression Scale (Ham-D), Hospital Anxiety and Depression Scale (HADS), Zung Self-Rating Depression Scale (SDS), Geriatric Depression Scale (GDS), Montgomery-As-berg Depression Rating Scale (MADRS), Unified Parkinson’s Disease Rating Scale (UPDRS) Part I, Cornell Scale for the Assessment of Depression in Dementia (CSDD), and the Center for Epidemiologic Studies Depression Scale (CES-D). Seven clinical researchers with clinical and research experience in the assessment of dPD were assigned to review the scales using a structured format. The most appropriate scale is dependent on the clinical or research goal. However, observer-rated scales are preferred if the study or clinical situation permits. For screening purposes, the HAM-D, BDI, HADS, MADRS, and GDS are valid in dPD. The CES-D and CSDD are alternative instruments that need validation in dPD. For measurement of severity of depressive symptoms, the Ham-D, MADRS, BDI, and SDS scales are recommended. Further studies are needed to validate the CSDD, which could be particularly useful for the assessment of severity of dPD in patients with comorbid dementia. To account for overlapping motor and nonmotor symptoms of depression, adjusted instrument cutoff scores may be needed for dPD, and scales to assess severity of motor symptoms (e.g., UPDRS) should also be included to help adjust for confounding factors. The HADS and the GDS include limited motor symptom assessment and may, therefore, be most useful in rating depression severity across a range of PD severity; however, these scales appear insensitive in severe depression. The complex and time-consuming task of developing a new scale to measure depression specifically for patients with PD is currently not warranted

Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers

A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected

Health-related quality of life and strain in caregivers of Australians with Parkinson’s disease : An observational study

Background: The relationship between health-related quality of life (HRQoL) in people with Parkinson’s disease and their caregivers is little understood and any effects on caregiver strain remain unclear. This paper examines these relationships in an Australian sample. Methods: Using the generic EuroQol (EQ-5D) and disease-specific Parkinson’s Disease Questionnaire-39 Item (PDQ- 39), HRQoL was evaluated in a sample of 97 people with PD and their caregivers. Caregiver strain was assessed using the Modified Caregiver Strain Index. Associations were evaluated between: (i) caregiver and care-recipient HRQoL; (ii) caregiver HRQoL and caregiver strain, and; (iii) between caregiver strain and care-recipient HRQoL. Results: No statistically significant relationships were found between caregiver and care-recipient HRQoL, or between caregiver HRQoL and caregiver strain. Although this Australian sample of caregivers experienced relatively good HRQoL and moderately low strain, a significant correlation was found between HRQoL of people with PD and caregiver strain (rho 0.43, p<.001). Conclusion: Poor HRQoL in people with PD is associated with higher strain in caregivers. Therapy interventions may target problems reported as most troublesome by people with PD, with potential to reduce strain on the caregive

Improved Heterosis Prediction by Combining Information on DNA- and Metabolic Markers

Background: Hybrids represent a cornerstone in the success story of breeding programs. The fundamental principle underlying this success is the phenomenon of hybrid vigour, or heterosis. It describes an advantage of the offspring as compared to the two parental lines with respect to parameters such as growth and resistance against abiotic or biotic stress. Dominance, overdominance or epistasis based models are commonly used explanations. Conclusion/Significance: The heterosis level is clearly a function of the combination of the parents used for offspring production. This results in a major challenge for plant breeders, as usually several thousand combinations of parents have to be tested for identifying the best combinations. Thus, any approach to reliably predict heterosis levels based on properties of the parental lines would be highly beneficial for plant breeding. Methodology/Principal Findings: Recently, genetic data have been used to predict heterosis. Here we show that a combination of parental genetic and metabolic markers, identified via feature selection and minimum-description-length based regression methods, significantly improves the prediction of biomass heterosis in resulting offspring. These findings will help furthering our understanding of the molecular basis of heterosis, revealing, for instance, the presence of nonlinear genotype-phenotype relationships. In addition, we describe a possible approach for accelerated selection in plant breeding

Intrauterine environment, mammary gland mass and breast cancer risk

Two intimately linked hypotheses on breast cancer etiology are described. The main postulate of the first hypothesis is that higher levels of pregnancy estrogens and other hormones favor the generation of a higher number of susceptible stem cells with compromised genomic stability. The second hypothesis postulates that the mammary gland mass, as a correlate of the number of cells susceptible to transformation, is an important determinant of breast cancer risk. A simple integrated etiological model for breast cancer is presented and it is indicated that the model accommodates most epidemiological aspects of breast cancer occurrence and natural history

Feasibility of Patient Reporting of Symptomatic Adverse Events via the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PROCTCAE) in a Chemoradiotherapy Cooperative Group Multicenter Clinical Trial

Purpose—To assess the feasibility of measuring symptomatic adverse events (AEs) in a multicenter clinical trial using the National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Methods and Materials—Patients enrolled in Trial XXXX (XXXX) were asked to self-report 53 PRO-CTCAE items representing 30 symptomatic AEs at 6 time points (baseline; weekly x4 during treatment; 12-weeks post-treatment). Reporting was conducted via wireless tablet computers in clinic waiting areas. Compliance was defined as the proportion of visits when an expected PRO-CTCAE assessment was completed. Results—Among 226 study sites participating in Trial XXXX, 100% completed 35-minute PROCTCAE training for clinical research associates (CRAs); 80 sites enrolled patients of which 34 (43%) required tablet computers to be provided. All 152 patients in Trial XXXX agreed to selfreport using the PRO-CTCAE (median age 66; 47% female; 84% white). Median time for CRAs to learn the system was 60 minutes (range 30–240), and median time for CRAs to teach a patient to self-report was 10 minutes (range 2–60). Compliance was high, particularly during active treatment when patients self-reported at 86% of expected time points, although compliance was lower post-treatment (72%). Common reasons for non-compliance were institutional errors such as forgetting to provide computers to participants; patients missing clinic visits; internet connectivity; and patients feeling “too sick”. Conclusions—Most patients enrolled in a multicenter chemoradiotherapy trial were willing and able to self-report symptomatic adverse events at visits using tablet computers. Minimal effort was required by local site staff to support this system. The observed causes of missing data may be obviated by allowing patients to self-report electronically between-visits, and by employing central compliance monitoring. These approaches are being incorporated into ongoing studies