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Since 2010, an intensified ambulatory cardiology care programme has been implemented in southern Germany. To improve patient management, the structure of cardiac disease management was improved, guideline-recommended care was supported, new ambulatory medical services and a morbidity-adapted reimbursement system were set up. Our aim was to determine the effects of this programme on the mortality and hospitalisation of enrolled patients with cardiac disorders. We conducted a comparative observational study in 2015 and 2016, based on insurance claims data. Overall, 13,404 enrolled patients with chronic heart failure (CHF) and 19,537 with coronary artery disease (CAD) were compared, respectively, to 8,776 and 16,696 patients that were receiving usual ambulatory cardiology care. Compared to the control group, patients enrolled in the programme had lower mortality (Hazard Ratio: 0.84; 95% CI: 0.77–0.91) and fewer all-cause hospitalisations (Rate Ratio: 0.94; 95% CI: 0.90–0.97). CHF-related hospitalisations in patients with CHF were also reduced (Rate Ratio: 0.76; 95% CI: 0.69–0.84). CAD patients showed a similar reduction in mortality rates (Hazard Ratio: 0.81; 95% CI: 0.76–0.88) and all-cause hospitalisation (Rate Ratio: 0.94; 95% CI: 0.91–0.97), but there was no effect on CAD-related hospitalisation. We conclude that intensified ambulatory care reduced mortality and hospitalisation in cardiology patients.
Background Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices.
Methods Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses.
Results Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke’s R² 0.507) were depressive symptoms (−2.73 (95% CI: −3.56 to −1.91)), MAI (−0.39 (95% CI: −0.7 to −0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables.
Conclusions Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.
URPOSE: Today, the majority of medical graduates in countries such as the UK, the US or Germany are female. This poses a major problem for workforce planning especially in urology. We here use first the first time the previously established Brüggmann Groneberg (BG) index to assess if female academic career options advance in urology.
METHODS: Different operating parameters (student population, urology specialist population, urology chair female:male (f:m) ratio) were collected from the Federal Office of Statistics, the Federal Chamber of Physicians and the medical faculties of 36 German universities. Four time points were monitored (2000, 2005, 2010 and 2015). From these data, female to male (f:m) ratios and the recently established career advancement (BG) index have been calculated.
RESULTS: The German hospital urology specialists' f:m ratios were 0.257 (499 female vs. 1944 male) for 2015, 0.195 for 2010, 0.133 for 2005 and 0.12 for 2000. The career advancement (BG) index was 0.0007 for 2000, 0,0005 for 2005, 0.094 for 2010 and 0.073 for 2015. The decrease from 2010 to 2015 was due to an increase in the f:m ratio of hospital urologists and female medical students.
CONCLUSION: The BG index clearly illustrated that there is an urgent need for special academic career funding programs to counteract gender problems in urology. The BG index has been shown to be an excellent tool to assess female academic career options and will be very helpful to assess and document positive or negative changes in the next decades.
Background: Eligibility criteria are a critical part of clinical trials, as they define the patient population under investigation. Besides certain patient characteristics, clinical trials often include biomarker testing for eligibility. However, patient-identification mostly relies on the trial site itself and is often a time-consuming procedure, which could result in missing out on potentially eligible patients. Pre-selection of those patients using a registry could facilitate the process of eligibility testing and increase the number of identified patients. One aim with the PRAEGNANT registry (NCT02338167) is to identify patients for therapies based on clinical and molecular data. Here, we report eligibility testing for the SHERBOC trial using the German PRAEGNANT registry.
Methods:Heregulin (HRG) has been reported to identify patients with better responses to therapy with the anti-HER3 monoclonal antibody seribantumab (MM-121). The SHERBOC trial investigated adding seribantumab (MM-121) to standard therapy in patients with advanced HER2-negative, hormone receptor–positive (HR-positive) breast cancer and HRG overexpression. The PRAEGNANT registry was used for identification and tumor testing, helping to link potential HRG positive patients to the trial. Patients enrolled in PRAEGNANT have invasive and metastatic or locally advanced, inoperable breast cancer. Patients eligible for SHERBOC were identified by using the registry. Study aims were to describe the HRG positivity rate, screening procedures, and patient characteristics associated with inclusion and exclusion criteria.
Results: Among 2769 unselected advanced breast cancer patients, 650 were HER2-negative, HR-positive and currently receiving first- or second-line treatment, thus potentially eligible for SHERBOC at the end of current treatment; 125 patients also met further clinical eligibility criteria (e.g. menopausal status, ECOG). In the first/second treatment lines, patients selected for SHERBOC based on further eligibility criteria had a more favorable prognosis than those not selected. HRG status was tested in 38 patients, 14 of whom (36.8%) proved to be HRG-positive.
Conclusion: Using a real-world breast cancer registry allowed identification of potentially eligible patients for SHERBOC focusing on patients with HER3 overexpressing, HR-positive, HER2-negative metastatic breast cancer. This approach may provide insights into differences between patients eligible or non-eligible for clinical trials.
Trial registration: Clinicaltrials, NCT02338167, Registered 14 January 2015 - retrospectively registered.