An exemplary reanalysis of coronary computed tomography angiography diagnostic meta-analyses shows insufficient data sharing and incorrect sensitivity and specificity estimates.

OBJECTIVES: To systematically evaluate the reproducibility of primary data and, the reproducibility and correctness of pooled sensitivity and specificity estimates reported in a sample of diagnostic meta-analyses. STUDY DESIGN AND SETTING: We conducted an exemplary systematic review of diagnostic meta-analyses comparing coronary computed tomography angiography to invasive coronary angiography in patients with suspected coronary artery disease. The objectives were to assess 1) the reproducibility of contingency tables, 2) the reproducibility of pooled sensitivity and specificity, and 3) differences to reported results when applying a recommended bivariate binomial model for pooling sensitivity and specificity. Therefore, we reproduced the contingency tables and recalculated sensitivity and specificity by utilizing both the pooling method of each meta-analysis and a bivariate binomial model. We used linear trends to assess the improvement of these objectives over time. RESULTS: We identified 38 diagnostic meta-analyses, each including on average 19 primary studies (range: 3 to 89 studies; total: 715-including duplicates) with an average of approximately 1800 patients per meta-analysis (range: 118 to 7516 patients). For 31 meta-analyses (82%, 95% CI: 65%, 91%), the contingency tables were reproducible; however, only 15 published them. Using the pooling method of each meta-analysis, we obtained comparable recalculated sensitivities/specificities for 28 meta-analyses (74% [57%, 86%]). Only 11 meta-analyses pooled sensitivity/specificity using a bivariate binomial model (29% [16%, 46%]). When all meta-analyses were pooled with this model, published sensitivities/specificities were confirmed for 19 of 38 meta-analyses (50% [34%, 66%]). There was only marginal improvement in data availability and application of recommended pooling methods over time. CONCLUSION: Data sharing should become standard practice along with the use of appropriate pooling methods. Journal publication requirements may play a key role in enhancing the quality of scientific reporting and methodological standards which may lead to more reliable and consistent outcomes. The ability to reproduce sensitivity and specificity estimates in diagnostic imaging meta-analyses is dependent on the availability of contingency tables and the explicit reporting of pooling methods and software used.

The Agreement Between Diagnoses as Stated by Patients and Those Contained in Routine Health Insurance Data.

BACKGROUND: The frequency of medical diagnoses is a figure of central importance in epidemiology and health services research. Prevalence estimates vary depending on the underlying data. For a better understanding of such discrepancies, we compared patients' diagnoses as reported by themselves in response to our questioning with their diagnoses as stated in the routine data of their health insurance carrier. METHODS: For 6558 adults insured by BARMER, one of the statutory health insurance carriers in Germany, we compared the diagnoses of various illnesses over a twelve-month period, as reported by the patients themselves in response to our questioning (October to December 2021), with their ICD-10-based diagnosis codes (Q4/2020-Q3/2021). The degree of agreement was assessed with two kappa values, sensitivity, and specificity. RESULTS: The patients' stated diagnoses of diabetes and hypertension agreed well or very well with their diagnosis codes, with kappa and PABAK values near 0.8, as well as very high sensitivity and specificity. Moderately good agreement with respect to kappa was seen for the diagnoses of heart failure (0.4), obesity, anxiety disorder, depression, and coronary heart disease (0.5 each). The poorest agreement (kappa ≤ 0.3) was seen for posttraumatic stress disorder, alcohol-related disorder, and mental and somatoform disorder. Agreement was worse with increasing age. CONCLUSION: Diagnoses as stated by patients often differ from those found in routine health insurance data. Discrepancies that can be considered negligible were found for only two of the 11 diseases that we studied. Our investigation confirms that these two sources of data yield different estimates of prevalence. Age is a key factor; further reasons for the discrepancies should be investigated, and avoidable causes should be addressed.

Sexual and contraceptive behaviour of young adults in Germany - Results from KiGGS Wave 2.

Sexual behaviour is an important aspect of sexual health. 18-year-old and older participants of the KiGGS cohort in KiGGS Wave 2 were asked about their sexual and contraceptive behaviour. Data from 2,966 women and 2,206 men were included in the analysis, which was adjusted to the age and sex distribution of the German population by means of weighting. More than half of the respondents report their first sexual intercourse before reaching the age of majority (women 61%, men 53%). Women report a lower age than men. With regard to the number of opposite-sex sexual partners in the last twelve months, almost 69% of women and 58% of men state that they have had contact. Three or more sexual partners were reported by 11% of women and 20% of men. 7.4% of women have same-sex and 1.4% have both same-sex and opposite-sex sexual contacts, among men the figures are 2.8% and 0.4%, respectively. When asked about the type of contraception used during the last sexual intercourse, about two thirds of the women and more than half of the men indicated the pill; a condom is used by about 44% of the women and about two thirds of the men. Almost one third of the women have already taken the morning-after pill. Overall, the results can help to support prevention and education campaigns on sexual and reproductive health.

Indications of Depressive Symptoms During the COVID-19 Pandemic in Germany: Comparison of National Survey and Twitter Data.

BACKGROUND: The current COVID-19 pandemic is associated with extensive individual and societal challenges, including challenges to both physical and mental health. To date, the development of mental health problems such as depressive symptoms accompanying population-based federal distancing measures is largely unknown, and opportunities for rapid, effective, and valid monitoring are currently a relevant matter of investigation. OBJECTIVE: In this study, we aim to investigate, first, the temporal progression of depressive symptoms during the COVID-19 pandemic and, second, the consistency of the results from tweets and survey-based self-reports of depressive symptoms within the same time period. METHODS: Based on a cross-sectional population survey of 9011 German adolescents and adults (n=4659, 51.7% female; age groups from 15 to 50 years and older) and a sample of 88,900 tweets (n=74,587, 83.9% female; age groups from 10 to 50 years and older), we investigated five depressive symptoms (eg, depressed mood and energy loss) using items from the Patient Health Questionnaire (PHQ-8) before, during, and after relaxation of the first German social contact ban from January to July 2020. RESULTS: On average, feelings of worthlessness were the least frequently reported symptom (survey: n=1011, 13.9%; Twitter: n=5103, 5.7%) and fatigue or loss of energy was the most frequently reported depressive symptom (survey: n=4472, 51.6%; Twitter: n=31,005, 34.9%) among both the survey and Twitter respondents. Young adult women and people living in federal districts with high COVID-19 infection rates were at an increased risk for depressive symptoms. The comparison of the survey and Twitter data before and after the first contact ban showed that German adolescents and adults had a significant decrease in feelings of fatigue and energy loss over time. The temporal progression of depressive symptoms showed high correspondence between both data sources (ρ=0.76-0.93; P<.001), except for diminished interest and depressed mood, which showed a steady increase even after the relaxation of the contact ban among the Twitter respondents but not among the survey respondents. CONCLUSIONS: Overall, the results indicate relatively small differences in depressive symptoms associated with social distancing measures during the COVID-19 pandemic and highlight the need to differentiate between positive (eg, energy level) and negative (eg, depressed mood) associations and variations over time. The results also underscore previous suggestions of Twitter data's potential to help identify hot spots of declining and improving public mental health and thereby help provide early intervention measures, especially for young and middle-aged adults. Further efforts are needed to investigate the long-term consequences of recurring lockdown phases and to address the limitations of social media data such as Twitter data to establish real-time public mental surveillance approaches.

Individual trajectories of asthma, obesity and ADHD during the transition from childhood and adolescence to young adulthood.

The German Health Interview and Examination Survey for Children and Adolescents (KiGGS) provides comprehensive and reliable data on the health situation of the upcoming generation. The KiGGS cohort accompanies participants from the KiGGS baseline study (2003-2006) into adulthood. Until now, two follow-up surveys of the cohort have been implemented with KiGGS Wave 1 (2009-2012) and KiGGS Wave 2 (2014-2017). In KiGGS Wave 2, the cohort was supplemented by the in-depth study 'Family and care-specific factors influencing the development, trajectories and effects of mental disorders (especially ADHD), obesity and allergic diseases (especially asthma)'. One aim of the study was to identify individual trajectories of these health disorders. For this purpose, probabilities for typical transitions from the KiGGS baseline study to KiGGS Wave 2 were calculated. An important result is that many participants who had asthma, obesity or ADHD at KiGGS baseline still had the disease more than ten years later: Over a third still had asthma (35%) or ADHD (37%), and almost half were still affected by obesity (47%). The results point to the need for early preventive measures to stop these potentially chronic diseases from developing in childhood and adolescence.

Carotid IMT and Stiffness in the KiGGS 2 National Survey: Third-Generation Measurement, Quality Algorithms and Determinants of Completeness.

Carotid intima-media thickness (cIMT) and carotid stiffness (CS) are important markers of atherosclerotic risk in the young. We assessed a novel third-generation method for its applicability in large population-based epidemiologic studies to determine strengths, limitations, completeness and predictors of unsuccessful measurement. Four thousand seven hundred ninety-eight 14- to 31-y-old participants of the German KiGGS cohort, which is based on a nationally representative sample with 11-y follow-up, underwent B-mode ultrasound examinations of the left and right common carotid artery with semi-automatic edge detection and automatic electrocardiogram-gated real-time quality control based on a sophisticated snake algorithm and subpixel interpolation. Overall completeness was 98% for far wall cIMT and 89% for CS parameters. Plane-specific completeness varied from 92%-96% for far wall and from 64%-69% for near-wall cIMT. Obesity independently predicted unsuccessful cIMT and CS measurements with odds ratios of 12.67 (95% confidence interval: 5.50-29.19) and 7.30 (4.87-10.94) compared with non-overweight after adjustment for blood pressure, cholesterol, smoking, hazardous drinking, age, sex and sonographer. Inter- and intra-rater reliabilities of cIMT and CS parameters in a sample of 15 young adults were good or excellent. Third-generation cIMT and CS measurements in the young with semi-automatic edge-detection and automatic real-time quality control has been successfully standardized with high reliability and very high completeness in a national survey setting. This provides a strong methodological foundation for further validation of the predictive value of cIMT and CS for atherosclerotic risk in the young.

The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

BACKGROUND: Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. OBJECTIVES: The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. METHODS: Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). RESULTS: The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. CONCLUSIONS: This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach.

Erratum: Development of overweight and obesity in children. Results of the KiGGS cohort.

[This corrects the article DOI: 10.17886/RKI-GBE-2018-030.2.].