Medication Risks and Their Association with Patient-Reported Outcomes in Inpatients with Cancer.

BACKGROUND: We aimed to assess medication risks and determine factors influencing the health-related quality of life (HRQOL) in cancer inpatients. METHODS: A retrospective analysis was conducted to identify drug-related problems (DRPs) based on medication reviews, including patient-reported outcomes (PROs). Multiple linear regression analyses were performed to identify sociodemographic, disease-related, and drug therapy-related factors influencing changes from hospital admission to discharge in the scales of the EORTC QLQ-C30 questionnaire. RESULTS: A total of 162 inpatients with various hematological and solid cancer diseases was analyzed. Patients received a mean of 11.6 drugs and 92.6% of patients exhibited polymedication resulting in a mean of 4.0 DRPs per patient. Based on PRO data, 21.5% of DRPs were identified. Multiple linear regression models described the variance of the changes in global HRQOL and physical function in a weak-to-moderate way. While drug therapy-related factors had no influence, relapse status and duration of hospital stay were identified as significant covariates for global HRQOL and physical function, respectively. CONCLUSION: This analysis describes underlying DRPs in a German cancer inpatient population. PROs provided valuable information for performing medication reviews. The multiple linear regression models for global HRQOL and physical function provided explanations for changes during hospital stay.

Developing tumor-specific PRO-CTCAE item sets: analysis of a cross-sectional survey in three German outpatient cancer centers.

BACKGROUND: To include the patient perspective in the assessment of adverse events in oncology, a patient-reported outcomes (PRO) version of the Common Terminology Criteria for Adverse Events (CTCAE) was developed by the US National Cancer Institute, the so called PRO-CTCAE. The objective of this study was the development of disease-specific PRO-CTCAE item sets for patients with breast cancer (BC), multiple myeloma (MM), and prostate cancer (PC). METHODS: The cross-sectional survey was conducted at three German outpatient cancer centers. Prevalence and importance of the 78 PRO-CTCAE symptoms were assessed using a patient questionnaire. To select the most relevant PRO-CTCAE items for each tumor entity, symptoms were ranked based on patient answers. RESULTS: 101 patients with BC, 107 with MM, and 66 with PC participated. The final item sets contained 21 symptoms (BC) or 19 symptoms (MM and PC), respectively. Eight symptoms (fatigue, muscle pain, insomnia, joint pain, general pain, dizziness, shortness of breath, and swelling) were represented in all three item sets. Fatigue was the symptom with the highest ranking across item sets followed by insomnia. Symptoms with the highest rankings represented in only one item set were symptoms affecting the urogenital system in the PC item set, blurred vision in the BC item set, and decreased appetite in the MM item set. CONCLUSIONS: Individual PRO-CTCAE item sets for a German patient population were developed for the three tumor entities on the basis of patients' differences in symptom profiles and perceptions. The quality and psychometric criteria of the newly compiled item sets should be evaluated in validation studies.

TESS DISCOVERY OF A TRANSITING SUPER-EARTH IN THE π MENSAE SYSTEM.

We report the detection of a transiting planet around π Men (HD 39091), using data from the Transiting Exoplanet Survey Satellite (TESS). The solar-type host star is unusually bright (V = 5.7) and was already known to host a Jovian planet on a highly eccentric, 5.7-year orbit. The newly discovered planet has a size of 2.04 ± 0.05 R ⊕ and an orbital period of 6.27 days. Radial-velocity data from the HARPS and AAT/UCLES archives also displays a 6.27-day periodicity, confirming the existence of the planet and leading to a mass determination of 4.82±0.85 M ⊕. The star's proximity and brightness will facilitate further investigations, such as atmospheric spectroscopy, asteroseismology, the Rossiter-McLaughlin effect, astrometry, and direct imaging.

Quantifying and predicting Drosophila larvae crawling phenotypes.

The fruit fly Drosophila melanogaster is a widely used model for cell biology, development, disease, and neuroscience. The fly's power as a genetic model for disease and neuroscience can be augmented by a quantitative description of its behavior. Here we show that we can accurately account for the complex and unique crawling patterns exhibited by individual Drosophila larvae using a small set of four parameters obtained from the trajectories of a few crawling larvae. The values of these parameters change for larvae from different genetic mutants, as we demonstrate for fly models of Alzheimer's disease and the Fragile X syndrome, allowing applications such as genetic or drug screens. Using the quantitative model of larval crawling developed here we use the mutant-specific parameters to robustly simulate larval crawling, which allows estimating the feasibility of laborious experimental assays and aids in their design.