Treatment in Certified Breast Cancer Centers Improves Chances of Survival of Patients with Breast Cancer: Evidence Based on Health Care Data from the WiZen Study.

Introduction: Certified breast cancer centers offer specific quality standards in terms of their structure, diagnostic and treatment approaches with regards to breast surgery, drug-based cancer therapy, radiotherapy, and psychosocial support. Such centers aim to improve treatment outcomes of breast cancer patients. The question investigated here was whether patients with primary breast cancer have a longer overall survival if they are treated in a certified breast cancer center compared to treatment outside these centers. Methods: We used patient-specific data (demographics, diagnoses, treatments) obtained from data held by mandatory health insurance companies ( gesetzliche Krankenversicherung , GKV) and clinical cancer registries (KKR) for the period 2009-2017 as well as hospital characteristics recorded in standardized quality reports. Using multivariable Cox regression analysis, we investigated differences in survival between patients treated in hospitals certified as breast cancers centers by the German Cancer Society (DKG) and patients treated in hospitals which had not been certified by the DKG. Results: The sample population consisted of 143720 (GKV data) and 59780 (KKR data) patients with breast cancer, who were treated in 1010 hospitals across Germany (280 DKG-certified, 730 not DKG-certified). 63.5% (GKV data) and 66.7% (KKR data) of patients, respectively, were treated in DKG-certified breast cancer centers. Cox regression analysis for overall survival which included patient and hospital characteristics found a significantly lower mortality risk for patients treated in DKG-certified breast cancer centers (GKV data: HR = 0.77, 95% CI = 0.74-0.81; KKR data: HR = 0.88, 95% CI = 0.85-0.92). This result remained stable even after several sensitivity analyses including stratified estimates for subgroups of patients and hospitals. The effect was even more pronounced for recurrence-free survival (KKR data: HR = 0.78, 95% CI = 0.74-0.82). Conclusions: Patients who are treated by an interdisciplinary team in a DKG-certified breast cancer had clear and statistically significantly better survival rates. Certification is therefore an effective means of improving the quality of care, and more patients should be treated in certified breast cancer centers.

Initial Cancer Treatment in Certified Versus Non-Certified Hospitals.

BACKGROUND: According to the National Cancer Plan in Germany, all cancer patients should receive high-quality care in accordance with evidence-based treatment guidelines. Certification programs were established for this purpose but have not yet been comprehensively evaluated. METHODS: In the WiZen project, which was supported by the Innovation Fund (supported project number 01VSF17020), controlled cohort studies were performed to investigate whether initial treatment in hospitals with or without a certificate from the German Cancer Society was associated with a difference in overall survival (primary endpoint) in patients with cancer of the colon, rectum, lung, pancreas, breast, cervix, prostate, endometrium, and ovary, head and neck cancer, and neuro-oncological tumors. The studies were based on nationwide data from adult insurees of the AOK statutory health insurance carrier for the years 2009-2017. RESULTS: The majority of patients with all entities except breast cancer received their initial treatment in non-certified hospitals. Initial treatment in a certified hospital was found to be beneficial in terms of overall survival for all cancer entities, even after extensive adjustment for patient- and hospital-related confounders. The hazard ratio (HR) ranged from 0.97 (95% CI: [0.94; 1.00]) for lung cancer to 0.77 [0.74; 0.81] for breast cancer, corresponding to an absolute risk reduction (ARR) for overall survival of 0.62 months for lung cancer to 4.61 months for cervical cancer. CONCLUSION: The WiZen study shows for the entities studied that initial cancer treatment in a certified center is associated with lower mortality. Despite the recommendations of the National Cancer Plan, however, more than 40% of all cancer patients still receive their initial treatment in a non-certified hospital. The preferential provision of initial care in certified hospitals would be likely to improve overall survival. Although the study design does not permit any conclusion with regard to causality, the findings seem robust considering that a control group was used, confounders were taken into account, and the study population was of large size.

[Methodology and Attribution Success of a Data Linkage of Clinical Registry Data with Health Insurance Data]. / Methodik und Zuordnungserfolg eines Linkage von Daten klinischer Krebsregister mit Abrechnungsdaten gesetzlicher Krankenkassen.

BACKGROUND: The aim of the project "Effectiveness of care in oncological centres" (WiZen), funded by the innovation fund of the federal joint committee, is to investigate the effectiveness of certification in oncology. The project uses nationwide data from the statuory health insurance AOK and data from clinical cancer registries from three different federal states from 2006-2017. To combine the strengths of both data sources, these will be linked for eight different cancer entities in compliance with data protection regulations. METHODS: Data linkage was performed using indirect identifiers and validated using the health insurance's patient ID ("Krankenversichertennummer") as a direct identifier and gold standard. This enables quantification of the quality of different linkage variants. Sensitivity and specificity as well as hit accuracy and a score addressing the quality of the linkage were used as evaluation criteria. The distributions of relevant variables resulting from the linkage were validated against the original distributions in the individual datasets. RESULTS: Depending on the combination of indirect identifiers, we found a range of 22,125 to 3,092,401 linkage hits. An almost perfect linkage could be achieved by combining information on cancer type, date of birth, gender and postal code. A total of 74,586 one-to-one linkages were achieved with these characteristics. The median hit quality for the different entities was more than 98%. In addition, both the age and sex distributions and the dates of death, if any, showed a high degree of agreement. DISCUSSION AND CONCLUSION: SHI and cancer registry data can be linked with high internal and external validity at the individual level. This robust linkage enables completely new possibilities for analysis through simultaneous access to variables from both data sets ("the best of both worlds"): Information on the UICC stage that stems from the registries can now be combined, for instance, with comorbidities from the SHI data at the individual level. Due to the use of readily available variables and the high success of the linkage, our procedure constitutes a promising method for future linkage processes in health care research.

[Recommendations for the Utilization of Claims Data During a Pandemic: Lessons Learned from the Project EgePan-Unimed of the Netzwerk Universitätsmedizin (NUM)]. / Potentiale von und Empfehlungen zur Nutzung von GKV Routinedaten in einer pandemischen Versorgungslage ­ Erfahrungen aus dem Projekt egePan-Unimed des Netzwerk Universitätsmedizin (NUM).

For appropriate response to the COVID-19 pandemic, and for obtaining answers to various relevant research questions, empirical data are required. Claims data of health insurances are a valid data source in such a situation. Within the project egePan-Unimed of the Netzwerk Universitätsmedizin (NUM) we investigated five COVID-19-related research questions using German claims data of statutory health insurances. We studied the prevalence and relevance of risk factors for a severe course of COVID-19, the background incidence of cerebral venous sinus thrombosis and myocarditis, the frequency and symptoms of post-COVID as well as the care of people with a psychiatric condition during the COVID-19 pandemic. Based on these cases, context-specific recommendations regarding the use of German claims data for future pandemics or other public health emergencies were derived, namely that the utilization of established and interdisciplinary project teams enables a timely project start and furthermore, meta-analytic methods are a valuable way to pool aggregated results of claims data analyses when data protection regulations do not allow a consolidation of data sets from different statutory health insurances. Under these circumstances, claims data are a readily available and valid data source of empirical evidence base necessary for public health measures during a pandemic.

Extreme obesity is a strong predictor for in-hospital mortality and the prevalence of long-COVID in severe COVID-19 patients with acute respiratory distress syndrome.

Acute Respiratory Distress Syndrome (ARDS) is common in COVID-19 patients and is associated with high mortality. The aim of this observational study was to describe patients' characteristics and outcome, identifying potential risk factors for in-hospital mortality and for developing Long-COVID symptoms. This retrospective study included all patients with COVID-19 associated ARDS (cARDS) in the period from March 2020 to March 2021 who were invasively ventilated at the intensive care unit (ICU) of the University Hospital Dresden, Germany. Between October 2021 and December 2021 patients discharged alive (at minimum 6 months after hospital discharge-midterm survival) were contacted and interviewed about persistent symptoms possibly associated with COVID-19 as well as the quality of their lives using the EQ-5D-5L-questionnaire. Long-COVID was defined as the occurrence of one of the symptoms at least 6 months after discharge. Risk factors for mortality were assessed with Cox regression models and risk factors for developing Long-COVID symptoms by using relative risk (RR) regression. 184 Patients were included in this study (male: n = 134 (73%), median age 67 (range 25-92). All patients were diagnosed with ARDS according to the Berlin Definition. 89% of patients (n = 164) had severe ARDS (Horovitz-index < 100 mmHg). In 27% (n = 49) extracorporeal membrane oxygenation was necessary to maintain gas exchange. The median length of in-hospital stay was 19 days (range 1-60). ICU mortality was 51%, hospital mortality 59%. Midterm survival (median 11 months) was 83% (n = 55) and 78% (n = 43) of these patients presented Long-COVID symptoms with fatigue as the most common symptom (70%). Extreme obesity (BMI > 40 kg/m2) was the strongest predictor for in-hospital mortality (hazard ratio: 3.147, confidence interval 1.000-9.897) and for developing Long-COVID symptoms (RR 1.61, confidence interval 1.26-2.06). In-hospital mortality in severe cARDS patients was high, but > 80% of patients discharged alive survived the midterm observation period. Nonetheless, most patients developed Long-COVID symptoms. Extreme obesity with BMI > 40 kg/m2 was identified as independent risk factor for in-hospital mortality and for developing Long-COVID symptoms.Trial registration DRKS-ID DRKS00027856.

Characteristics and outcomes of sepsis patients with and without COVID-19.

BACKGROUND: The aim of this study was to describe and compare clinical characteristics and outcomes in critically ill septic patients with and without COVID-19. METHODS: From February 2020 to March 2021, patients from surgical and medical ICUs at the University Hospital Dresden were screened for sepsis. Patient characteristics and outcomes were assessed descriptively. Patient survival was analyzed using the Kaplan-Meier estimator. Associations between in-hospital mortality and risk factors were modeled using robust Poisson regression, which facilitates derivation of adjusted relative risks. RESULTS: In 177 ICU patients treated for sepsis, COVID-19 was diagnosed and compared to 191 septic ICU patients without COVID-19. Age and sex did not differ significantly between sepsis patients with and without COVID-19, but SOFA score at ICU admission was significantly higher in septic COVID-19 patients. In-hospital mortality was significantly higher in COVID-19 patients with 59% compared to 29% in Non-COVID patients. Statistical analysis resulted in an adjusted relative risk for in-hospital mortality of 1.74 (95%-CI=1.35-2-24) in the presence of COVID-19 compared to other septic patients. Age, procalcitonin maximum value over 2 ng/ml, need for renal replacement therapy, need for invasive ventilation and septic shock were identified as additional risk factors for in-hospital mortality. CONCLUSION: COVID-19 was identified as independent risk factor for higher in-hospital mortality in sepsis patients. The need for invasive ventilation and renal replacement therapy as well as the presence of septic shock and higher PCT should be considered to identify high-risk patients.

Occurrence and removal of frequently prescribed pharmaceuticals and corresponding metabolites in wastewater of a sewage treatment plant.

The present study determines removal rates (RR) of 56 pharmaceuticals and metabolites, respectively, in an urban sewage treatment plant using mass flow analysis by comparing influent and effluent loads over a consecutive ten-day monitoring period. Besides well investigated compounds like carbamazepine and metoprolol, less researched targets, such as topiramate, pregabalin, telmisartan, and human metabolites of pharmaceuticals were included. Another aim was to determine the ratio of pharmaceuticals and corresponding metabolites in raw wastewater. Valsartan and gabapentin were detected at the highest average concentrations in influent (c(val) = 29.7 (± 8.1) µg/L, c(gab) = 13.2 (± 3.3) µg/L) and effluent (c(val) = 22.1 (± 5.1) µg/L, c(gab) = 12.1 (± 2.6) µg/L) samples. The comparison of mass loads in influent and effluent showed a significant removal (p<0.1) for 20 compounds but only enalapril, eprosartan, losartan, pregabalin, and quetiapine were removed from the aqueous phase by more than 50%. Another 20 compounds were determined without significant difference and for five compounds (clindamycin, lamotrigine, oxcarbazepine, O-desmethyl venlafaxine, triamterene), a significant higher mass load in the effluent than in the influent was observed. It has to be noticed that metabolites like 10,11-dihydro-10-hydroxy carbamazepine (MHD) are found in higher mass loads than the corresponding parent compound in the sewage samples. Furthermore, metabolites and parent compound behave differently in the sewage treatment process. While MHD (RR = 15.1%) was detected with lower mass load in the effluent than in the influent, oxcarbazepine (RR = -73.2%) showed the contrary pattern. When comparing expected and measured ratios of parent compound and metabolite in raw sewage, citalopram/N-desmethyl citalopram for example, showed good results. However, a major problem exists due to insufficient data regarding metabolism and excretion of many pharmaceuticals. This complicates the prediction of relevant metabolites and further efforts are needed to overcome this problem.

Development of a SPE-HPLC-MS/MS method for the determination of most prescribed pharmaceuticals and related metabolites in urban sewage samples.

Based on regional prescription data several pharmaceuticals with variable amounts of prescription and corresponding metabolites were selected and analyzed in influent and effluent samples of the sewage treatment plant (STP) in Dresden, Germany. Pharmaceuticals of the following most prescribed therapeutic groups were chosen: antibiotics, antifungals, anticonvulsants, antipsychotics, antidepressants, and cardiovascular active compounds like beta blockers and angiotensin-converting enzyme inhibitors. To analyze the selected compounds, a multi-target method was developed and applied to 24-h composite wastewater samples for three single days in May and June 2014. The method was based on a cleanup of a sample with a volume of 1mL using solid phase extraction followed by a high performance liquid chromatography coupled to a tandem mass spectrometer. Analytes were separated in a 15min chromatographic separation and quantified using 23 Internal Standards and a calibration curve in 40-fold diluted blank urine. The limit of quantification varied between 50 and 200ng/L and for all analytes good accuracy and precision as well as linearity for the calibration curve with the correlation coefficient R(2) higher than 0.99 was reached. A total of 41 and 40 of the selected 55 analytes were detected and quantified in the influent and effluent samples of the studied STP, respectively. Valsartan was the compound with the highest maximum concentration in influent (27.1µg/L) and effluent (15.7µg/L). Furthermore, analytes like bezafibrate, candesartan, carbamazepine, gabapentin, metoprolol, levetiracetam, pregabalin and telmisartan as well as the metabolite O-desmethyl venlafaxine were detectable in influent and effluent samples, respectively, with a concentration higher than 1µg/L.