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BACKGROUND: Low back pain has a high economic burden in Germany due to back pain-related sick leave, disability pensions, and health care utilization. Work-related factors can predict disabling back pain. Job exposure matrices can be used to consider job demands and occupational characteristics in routine data analysis. OBJECTIVE: This longitudinal analysis tested whether rehabilitation utilization due to musculoskeletal disorders is associated with occupation-linked job exposures in employees with back pain. METHODS: Data from a German cohort study were used, including employees aged 45 to 59 years with self-reported back pain in the last three months. Individuals' job titles were assessed in the baseline survey in 2017 and matched with parameters of aggregated job exposure indices. Administrative data from the German Pension Insurance were used to extract information on rehabilitation utilization. Proportional hazard models tested the associations. RESULTS: We considered data of 6,569 participants (mean age: 52.3 years; 57.7% women). During follow-up, with a maximum of 21 months, 296 individuals (4.5%) utilized medical rehabilitation due to musculoskeletal disorders. Adjusted analyses showed that high physical (HR = 2.87; 95% CI 1.74; 4.75) and overall (HR = 2.34; 95% CI 1.44; 3.80) job exposures were associated with a higher risk of rehabilitation utilization. CONCLUSION: Individuals with back pain working in occupations with high physical job exposures have a higher risk for rehabilitation utilization. To prevent work disability in individuals with back pain, occupational groups with high physical job exposures should be actively informed about tailored intervention options. [ABSTRACT FROM AUTHOR]

Monitoring of clinical trials is a fundamental process required by regulatory agencies. It assures the compliance of a center to the required regulations and the trial protocol. Traditionally, monitoring teams relied on extensive on-site visits and source data verification. However, this is costly, and the outcome is limited. Thus, central statistical monitoring (CSM) is an additional approach recently embraced by the International Council for Harmonisation (ICH) to detect problematic or erroneous data by using visualizations and statistical control measures. Existing implementations have been primarily focused on detecting inlier and outlier data. Other approaches include principal component analysis and distribution of the data. Here we focus on the utilization of comparisons of centers to the Grand mean for different model types and assumptions for common data types, such as binomial, ordinal, and continuous response variables. We implement the usage of multiple comparisons of single centers to the Grand mean of all centers. This approach is also available for various non-normal data types that are abundant in clinical trials. Further, using confidence intervals, an assessment of equivalence to the Grand mean can be applied. In a Monte Carlo simulation study, the applied statistical approaches have been investigated for their ability to control type I error and the assessment of their respective power for balanced and unbalanced designs which are common in registry data and clinical trials. Data from the German Multiple Sclerosis Registry (GMSR) including proportions of missing data, adverse events and disease severity scores were used to verify the results on Real-World-Data (RWD). [ABSTRACT FROM AUTHOR]

Introduction: Sarcomas are documented in population-based and in clinic-associated databases. This study evaluated the status quo regarding the potential and obstacles of cancer registry-based research on sarcomas exemplified by Germany in comparison to similar databases in the US and Europe. Completeness and quality of data are discussed based on statistical analyses of a pooled data set established for the German Cancer Congress 2020. Methods: We analyzed data derived from 16 German institutions (federal state cancer registries and some facility-based registries). Malignant sarcomas in adults diagnosed between 2000 and 2018 with information on histology were grouped according to the WHO classification of soft tissue and bone tumors. Descriptive analyses of the study population regarding the distribution of age, sex, histology, localization of primary tumors, and metastases were performed. Survival for the ten most frequent histological groups and UICC stages was evaluated according to Kaplan-Meier and Cox regression. Time interval between surgery and subsequent radiation was calculated. Results: The initial data set contained 35,091 sarcomas. After several steps of data cleaning, 28,311 patients with known sex and unambiguous assignment to a histological subgroup remained (13,682 women and 14,629 men). Between 40 and 54 years, women were more likely to develop sarcomas, whereas in the older age groups more men were affected. Gastrointestinal stromal tumors, fibroblastic, and myofibroblastic tumors, smooth muscle tumors (mostly non-uterine leiomyosarcomas), and adipocytic tumors represented 48% of all sarcomas. Preferential sites for fibrosarcomas were the limbs, the trunk, and the head and neck region. The liposarcoma occurred most frequently on the trunk and limbs. Distant primary metastases were mostly located in the lung (43%), followed by the liver (14%), and bones (13%). Vascular and smooth muscle tumors showed the worst survival prognosis (5-year survival: approx. 15%, median survival approx. 8–16 months), whereas in low stages, the probability of survival of many sarcoma patients was beyond 5 years. Adjuvant radiotherapy was applied within 90 days in 71% of patients (n = 2,534). Conclusion: Our results correspond to the data from the literature. However, a lack of data quality and completeness hampers further meaningful analyses, especially nonspecific or missing information about morphology and stage. Compared to some other countries, a comprehensive database is presently missing in Germany. However, currently, there are important efforts and legislative initiatives to create a comprehensive database on a national level within the near future. [ABSTRACT FROM AUTHOR]

Introduction: While physical activity (PA) is recognized as important in Huntington's disease (HD) disease management, there has been no long-term evaluation undertaken. We aimed to evaluate the feasibility of a nested (within cohort) randomized controlled trial (RCT) of a physical therapist-led PA intervention.Methods: Participants were recruited from six HD specialist centers participating in the Enroll-HD cohort study in Germany, Spain and U.S. Assessments were completed at baseline and 12 months and linked to Enroll-HD cohort data. Participants at three sites (cohort) received no contact between baseline and 12 month assessments. Participants at three additional sites (RCT) were randomized to PA intervention or control group. The intervention consisted of 18 sessions delivered over 12 months; control group participants received no intervention, however both groups completed monthly exercise/falls diaries and 6-month assessments.Results: 274 participants were screened, 204 met inclusion criteria and 116 were enrolled (59 in cohort; 57 in RCT). Retention rates at 12-months were 84.7% (cohort) and 79.0% (RCT). Data completeness at baseline ranged from 42.3 to 100% and at 12-months 19.2-85.2%. In the RCT, there was 80.5% adherence, high intervention fidelity, and similar adverse events between groups. There were differences in fitness, walking endurance and self-reported PA at 12 months favoring the intervention group, with data completeness >60%. Participants in the cohort had motor and functional decline at rates comparable to previous studies.Conclusion: Predefined progression criteria indicating feasibility were met. PACE-HD lays the groundwork for a future, fully-powered within cohort trial, but approaches to ensure data completeness must be considered.Clinicaltrials: GOV: NCT03344601. [ABSTRACT FROM AUTHOR]

Background and Aims: The evidence for the benefit of the skin cancer screening introduced in Germany in 2008 is weak. We investigate to what extent data from the German epidemiological cancer registries are suitable to contribute to the evaluation of skin cancer screening and report these evaluation results., Material and Methods: Skin cancer-related cancer registry data from 1999-2019 were described in terms of completeness and comprehensiveness. Regional pools with data of different validity were defined, missing data were multiply imputed where appropriate, and temporal trends were analyzed. In addition, data from the cause of death statistics were used., Results: Reliable estimates of completeness are only available for malignant melanoma (ICD-10: C43). Based on a regional data pool covering approximately 21% of the German population, melanoma-related incidence can be validly described since 2005. Sufficient information for multiple imputation is available for T-stage and localization. The trend analyses show incidence changes that can be expected in the short term in the temporal context of the introduction of early detection, which changes into a long-lasting high incidence. The rate of advanced stages does not decrease significantly. From 2014 onwards, the melanoma mortality rate, which had been rising until then, decreases., Conclusions: Adequately selected and processed cancer registry data are suitable for population-based evaluation of skin cancer screening. An explanation of the persistently high incidence level is not possible based on the cancer registry data. Overdiagnosis or an increase in the background incidence can be considered. The benefit of skin cancer screening remains open., (© 2023 Deutsche Dermatologische Gesellschaft (DDG).)

Purpose: The participation rates in cervical screenings are varying over different countries. This is only partly due to the availability of organized screening programs, as the rates are also varying between countries were such programs were implemented. For Germany the level of knowledge is low, and information are outdated. In order to improve the level of knowledge, we examined whether the participation rates in cervical screenings in a large German insurance population were changing over time, and whether these changes were different with respect to age and qualification of the participating women. Methods: The analyses were based on the complete anonymised dataset of a large statutory health insurance in Lower Saxony, Germany, with case numbers between 940,827 (2006) and 1,044,797 (2011) women aged 20 years and older. Results: Between 2006 and 2011 the overall annual participation rates were increasing from 44.8 to 47.6 %. The highest rates occurred in women with the highest qualification level, thus leading to increasing social differences over time. There was a peak in the age group of 25-29 years from annually 60.3 (2006) to 60.2 % (2011), and bi-annually from 77 to 77.1 % with constantly decreasing rates up to the age of 60. No substantial differences occurred between a 2- and a 3-year observation period. Conclusions: Over time only small increases of participation rates in cervical screenings occurred. These findings may be interpreted in favor of population-based screenings within an invitation program. [ABSTRACT FROM AUTHOR]

The present paper is a description and summary of methods used in non-randomised cohort data where the comparability of the study groups usually is not granted. Such study groups are formed by a diagnostic or therapeutic intervention, or by other characteristics of the patient or the treatment environment. This is a typical situation in the analysis of registry data. The methods are presented together with an illustrative example of whole-body computed tomography in the early phase of treatment of severe trauma cases. The following approaches are considered: (i) unadjusted direct comparisons; (ii) parallelisation; (iii) subgroup analysis; (iv) matched-pairs analysis; (v) outcome adjustment; and (vi) propensity score analysis. All these approaches have in common that they try to separate, or limit, the influence of confounding variables, which are unevenly distributed among the study groups, but also influence the outcome of interest. They differ in the number of confounders being considered, as well as the number of patients regarded. The more sophisticated the approach, the more effectively such confounding factors could be reduced. However, any method used for the reduction of bias depends on the quality and completeness of recorded confounders. Factors which are difficult or even impossible to be measured could thus not be adjusted for. This is a general limitation of retrospective analyses of cohort data., (Copyright © 2014 Elsevier Ltd. All rights reserved.)