The National Institutes of Health COVID-19 Neuro Databank/Biobank: Creation and Evolution.

INTRODUCTION: Diverse neurological conditions are reported associated with the SARS-CoV-2 virus; neurological symptoms are the most common conditions to persist after the resolution of acute infection, affecting 20% of patients 6 months after acute illness. The COVID-19 Neuro Databank (NeuroCOVID) was created to overcome the limitations of siloed small local cohorts to collect detailed, curated, and harmonized de-identified data from a large diverse cohort of adults with new or worsened neurological conditions associated with COVID-19 illness, as a scientific resource. METHODS: A Steering Committee including US and international experts meets quarterly to provide guidance. Initial study sites were recruited to include a wide US geographic distribution; academic and non-academic sites; urban and non-urban locations; and patients of different ages, disease severity, and comorbidities seen by a variety of clinical specialists. The NeuroCOVID REDCap database was developed, incorporating input from professional guidelines, existing common data elements, and subject matter experts. A cohort of eligible adults is identified at each site; inclusion criteria are: a new or worsened neurological condition associated with a COVID-19 infection confirmed by testing. De-identified data are abstracted from patients' medical records, using standardized common data elements and five case report forms. The database was carefully enhanced in response to feedback from site investigators and evolving scientific interest in post-acute conditions and their timing. Additional US and international sites were added, focusing on diversity and populations not already described in published literature. By early 2024, NeuroCOVID included over 2,700 patient records, including data from 16 US and 5 international sites. Data are being shared with the scientific community in compliance with NIH requirements. The program has been invited to share case report forms with the National Library of Medicine as an ongoing resource for the scientific community. CONCLUSION: The NeuroCOVID database is a unique and valuable source of comprehensive de-identified data on a wide variety of neurological conditions associated with COVID-19 illness, including a diverse patient population. Initiated early in the pandemic, data collection has been responsive to evolving scientific interests. NeuroCOVID will continue to contribute to scientific efforts to characterize and treat this challenging illness and its consequences.

A comprehensive assessment of quality management methods in the SMESH study.

BACKGROUND: This paper aims to instigate discussion and publication of methodologies applied to enhance quality management through comprehensive scientific reports. It provides a detailed description of the design, implementation, and results of the quality control program employed in the SMESH study. METHODS: Cross-sectional, multicenter, national study designed to assess the prevalence of human papillomavirus in sex workers and in men who have sex with men (MSM). Respondent-driven sampling recruitment was used. An online system was developed for the study and checkpoints were defined for data entry. The system checked the quality of biological samples and performed a retest with part of the sample. RESULTS: A total of 1.598 participants (442 sex workers and 1.156 MSM) were included. Fifty-four health professionals were trained for face-to-face data collection. The retest showed Kappa values ranging between 0.3030 and 0.7663. CONCLUSION: The retest data were mostly classified as indicating a strong association. The data generated by the checkpoints showed the successful implementation of the quality control program.

Using a novel 'difference-in-differences' method and syndromic surveillance to estimate the change in local healthcare utilisation during periods of media reporting in the early stages of the COVID-19 pandemic in England.

OBJECTIVES: Syndromic surveillance supplements traditional laboratory reporting for infectious diseases monitoring. Prior to widespread COVID-19 community surveillance, syndromic surveillance was one of several systems providing real-time information on changes in healthcare-seeking behaviour. The study objective was to identify changes in healthcare utilisation during periods of high local media reporting in England using 'difference-in-differences' (DiD). STUDY DESIGN: A retrospective observational study was conducted using five media events in January-February 2020 in England on four routinely monitored syndromic surveillance indicators. METHODS: Dates 'exposed' to a media event were estimated using Google Trends internet search intensity data (terms = 'coronavirus' and local authority [LA]). We constructed a negative-binomial regression model for each indicator and event time period to estimate a direct effect. RESULTS: We estimated a four-fold increase in telehealth 'cough' calls and a 1.4-fold increase in emergency department (ED) attendances for acute respiratory illness in Brighton and Hove, when a so-called 'superspreading event' in this location was reported in local and national media. Significant decreases were observed in the Buxton (telehealth and ED attendance) and Wirral (ED attendance) areas during media reports of a returnee from an outbreak abroad and a quarantine site opening in the area respectively. CONCLUSIONS: We used a novel approach to directly estimate changes in syndromic surveillance reporting during the early phase of the COVID-19 pandemic in England, providing contextual information on the interpretation of changes in health indicators. With careful consideration of event timings, DiD is useful in producing real-time estimates on specific indicators for informing public health action.

Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021-June 2022.

Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the country also offers free SARS-CoV-2 PCR tests to all residents. Using time series analysis for modeling, we found that wastewater data, combined with information on circulating variants and the number of human tests performed, closely fitted the incidence curve of persons testing positive. The results were consistent at a regional level and among a subpopulation of frequently tested healthcare personnel. We used wastewater analysis data to estimate incidence after testing was reduced to a minimum after March 2022. These results imply that data from a large-scale wastewater surveillance system can serve as a good proxy for COVID-19 incidence and for epidemic control.

The Epidemiology of Moderate and Severe Traumatic Brain Injury in Central Norway.

INTRODUCTION: Few studies account for prehospital deaths when estimating incidence and mortality rates of moderate and severe traumatic brain injury (msTBI). In a population-based study, covering both urban and rural areas, including also prehospital deaths, the aim was to estimate incidence and mortality rates of msTBI. Further, we studied the 30-day and 6-month case-fatality proportion of severe TBI in relation to age. METHODS: All patients aged ≥17 years who sustained an msTBI in Central Norway were identified by three sources: (1) the regional trauma center, (2) the general hospitals, and (3) the Norwegian Cause of Death Registry. Incidence and mortality rates were standardized according to the World Health Organization's world standard population. Case-fatality proportions were calculated by the number of deaths from severe TBI at 30 days and 6 months, divided by all patients with severe TBI. RESULTS: The overall incidence rates of moderate and severe TBI were 4.9 and 6.7 per 100,000 person-years, respectively, increasing from age 70 years. The overall mortality rate was 3.4 per 100,000 person-years, also increasing from age 70 years. Incidence and mortality rates were highest in men. The case-fatality proportion in people with severe TBI was 49% in people aged 60-69 years and 81% in people aged 70-79 years. CONCLUSION: The overall incidence and mortality rates for msTBI in Central Norway were low but increased from age 70 years, and among those ≥80 years of age with severe TBI, nearly all died. Overall estimates are strongly influenced by high incidence and mortality rates in the elderly, and studies should therefore report age-specific estimates, for better comparison of incidence and mortality rates.

Response to Tsuda et al. "demonstrating the undermining of science and health policy after the Fukushima nuclear accident by applying the toolkit for detecting misused epidemiological methods".

BACKGROUND: The SHAMISEN (Nuclear Emergency Situations - Improvement of Medical And Health Surveillance) European project was conducted in 2015-2017 to review the lessons learned from the experience of past nuclear accidents and develop recommendations for preparedness and health surveillance of populations affected by a nuclear accident. Using a toolkit approach, Tsuda et al. recently published a critical review of the article by Cléro et al. derived from the SHAMISEN project on thyroid cancer screening after nuclear accident. MAIN BODY: We address the main points of criticism of our publication on the SHAMISEN European project. CONCLUSION: We disagree with some of the arguments and criticisms mentioned by Tsuda et al. We continue to support the conclusions and recommendations of the SHAMISEN consortium, including the recommendation not to launch a mass thyroid cancer screening after a nuclear accident, but rather to make it available (with appropriate information counselling) to those who request it.

COVID-19 severity scale for claims data research.

OBJECTIVE: To create and validate a methodology to assign a severity level to an episode of COVID-19 for retrospective analysis in claims data. DATA SOURCE: Secondary data obtained by license agreement from Optum provided claims records nationally for 19,761,754 persons, of which, 692,094 persons had COVID-19 in 2020. STUDY DESIGN: The World Health Organization (WHO) COVID-19 Progression Scale was used as a model to identify endpoints as measures of episode severity within claims data. Endpoints used included symptoms, respiratory status, progression to levels of treatment and mortality. DATA COLLECTION/EXTRACTION METHODS: The strategy for identification of cases relied upon the February 2020 guidance from the Centers for Disease Control and Prevention (CDC). PRINCIPAL FINDINGS: A total of 709,846 persons (3.6%) met the criteria for one of the nine severity levels based on diagnosis codes with 692,094 having confirmatory diagnoses. The rates for each level varied considerably by age groups, with the older age groups reaching higher severity levels at a higher rate. Mean and median costs increased as severity level increased. Statistical validation of the severity scales revealed that the rates for each level varied considerably by age group, with the older ages reaching higher severity levels (p < 0.001). Other demographic factors such as race and ethnicity, geographic region, and comorbidity count had statistically significant associations with severity level of COVID-19. CONCLUSION: A standardized severity scale for use with claims data will allow researchers to evaluate episodes so that analyses can be conducted on the processes of intervention, effectiveness, efficiencies, costs and outcomes related to COVID-19.

Assessing Mbiotisho: A smartphone application used to collect high-frequency health and nutrition data from difficult-to-reach populations.

There is an urgent need for improved and timely health and nutrition data. We developed and tested a smartphone application that caregivers from a pastoral population used to measure, record and submit high-frequency and longitudinal health and nutrition information on themselves and their children. The data were assessed by comparing caregiver-submitted measurements of mid-upper arm circumference (MUAC) to several benchmark data sets, including data collected by community health volunteers from the participating caregivers during the project period and data generated by interpreting photographs of MUAC measurements submitted by all participants. We found that the caregivers participated frequently and consistently over the 12-month period of the project; most of them made several measurements and submissions in at least 48 of the 52 weeks of the project. The evaluation of data quality was sensitive to which data set was used as the benchmark, but the results indicate that the errors in the caregivers' submissions were similar to that of enumerators in other studies. We then compare the costs of this alternative approach to data collection through more conventional methods, concluding that conventional methods can be more cost-effective for large socioeconomic surveys that value the breadth of the survey over the frequency of data, while the alternative we tested is favoured for those with objectives that are better met by high-frequency observations of a smaller number of well-defined outcomes.

A modified self-controlled case series method for event-dependent exposures and high event-related mortality, with application to COVID-19 vaccine safety.

We propose a modified self-controlled case series (SCCS) method to handle both event-dependent exposures and high event-related mortality. This development is motivated by an epidemiological study undertaken in France to quantify potential risks of cardiovascular events associated with COVID-19 vaccines. Event-dependence of vaccinations, and high event-related mortality, are likely to arise in other SCCS studies of COVID-19 vaccine safety. Using this case study and simulations to broaden its scope, we explore these features and the biases they may generate, implement the modified SCCS model, illustrate some of the properties of this model, and develop a new test for presence of a dose effect. The model we propose has wider application, notably when the event of interest is death.

Modelling multiple time-scales with flexible parametric survival models.

BACKGROUND: There are situations when we need to model multiple time-scales in survival analysis. A usual approach in this setting would involve fitting Cox or Poisson models to a time-split dataset. However, this leads to large datasets and can be computationally intensive when model fitting, especially if interest lies in displaying how the estimated hazard rate or survival change along multiple time-scales continuously. METHODS: We propose to use flexible parametric survival models on the log hazard scale as an alternative method when modelling data with multiple time-scales. By choosing one of the time-scales as reference, and rewriting other time-scales as a function of this reference time-scale, users can avoid time-splitting of the data. RESULT: Through case-studies we demonstrate the usefulness of this method and provide examples of graphical representations of estimated hazard rates and survival proportions. The model gives nearly identical results to using a Poisson model, without requiring time-splitting. CONCLUSION: Flexible parametric survival models are a powerful tool for modelling multiple time-scales. This method does not require splitting the data into small time-intervals, and therefore saves time, helps avoid technological limitations and reduces room for error.

Response to Toshihide Tsuda, Yumiko Miyano and Eiji Yamamoto [1].

BACKGROUND: In August 2021, we published in Environmental Health a Toolkit for detecting misused epidemiological methods with the goal of providing an organizational framework for transparently evaluating epidemiological studies, a body of evidence, and resultant conclusions. Tsuda et al., the first group to utilize the Toolkit in a systematic fashion, have offered suggestions for its modification. MAIN BODY: Among the suggested modifications made by Tsuda et al., we agree that rearrangement of Part A of the Toolkit to reflect the sequence of the epidemiological study process would facilitate its usefulness. Expansion or adaptation of the Toolkit to other disciplines would be valuable but would require the input of discipline-specific expertise. We caution against using the sections of the Toolkit to produce a tally or cumulative score, because none of the items are weighted as to importance or impact. Rather, we suggest a visual representation of how a study meets the Toolkit items, such as the heat maps used to present risk of bias criteria for studies included in Cochrane reviews. We suggest that the Toolkit be incorporated in the sub-specialty known as "forensic epidemiology," as well as in graduate training curricula, continuing education programs, and conferences, with the recognition that it is an extension of widely accepted ethics guidelines for epidemiological research. CONCLUSION: We welcome feedback from the research community about ways to strengthen the Toolkit as it is applied to a broader assemblage of research studies and disciplines, contributing to its value as a living tool/instrument. The application of the Toolkit by Tsuda et al. exemplifies the usefulness of this framework for transparently evaluating, in a systematic way, epidemiological research, conclusions relating to causation, and policy decisions. POSTSCRIPT: We note that our Toolkit has, most recently, inspired authors with discipline-specific expertise in the field of Conservation Biology to adapt it for use in the Biological Sciences.

HUNT for better public health.

AIMS: The Trøndelag Health Study (HUNT) has collected population data through comprehensive decennial surveys over the last four decades and has so far collected data from 240,000 participants. The participants are identified with the unique Norwegian birth number, which enables them to be followed throughout different life stages, from survey to survey, and to endpoint measures in Norwegian national health registers without attrition bias. METHODS: The study design of HUNT offers several advantages: it provides an overview of the public health development in the population over decades, the data can be used in health services research, clinical epidemiology, studies of causation, trajectories, and consequences of diseases, and to study gene × environment interactions. RESULTS: HUNT data have shown major shifts in public health trends, such as decreasing mean blood pressure and resting heart rate among adults, increasing prevalence of obesity, geographical and socioeconomic inequalities in health, increasing mental health distress among adolescents and young adults with an opposite development among the elderly. Data from HUNT have been used in several major international research projects, where data harmonization with several other population cohorts internationally has been done. HUNT has placed great emphasis on safeguarding research ethics, privacy, and data security. The Norwegian authorities established national regulations for the surveys from the time General Data Protection Regulation was introduced in 2018. CONCLUSIONS: Researchers can apply for HUNT data access from HUNT Research Centre provided they have obtained project approval from the Regional Committee for Medical and Health Research Ethics. Researchers not affiliated to a Norwegian research institution must collaborate with and apply through a Norwegian principal investigator. Information on the application and conditions for data access is available at www.ntnu.edu/hunt/data.

Stressful work in primary health care and mental health: The role of gender inequities in Brazil.

BACKGROUND: This study aims to analyze the association between occupational stressors, evaluated by the Effort-Reward Imbalance Model (ERI), and the occurrence of common mental disorders (CMD) among healthcare workers (HCW), additionally considering mediation by over-commitment from work (OW) and mediation of gender effects by work stressors. METHODS: Cross-sectional study, including a random sample of 3343 HCWs, from six municipalities of Bahia, Brazil. The ERI scale measured the occupational stressors (main exposure), and the Self-Reporting Questionnaire (SRQ-20) was used to screen for CMD. Data analysis used Structural Equation Modeling techniques to understand the relationships between gender, occupational stressors, and the occurrence of CMD. RESULTS: ERI and OW were associated with CMD. OW mediated the negative effect of ERI on the mental health of HCW. Female workers had higher levels of ERI, OW, and CMD prevalence; the total gender effect on CMD prevalence was mediated by ERI and OW. CONCLUSIONS: The findings highlight the association of work psychosocial stressors and CMD among HCW, including partial mediation by OW. Gender inequalities persisted among HCW, with women most exposed to occupational stressors and CMD. ERI and OW partially mediated the effect of gender on CMD.

Avoiding bias in self-controlled case series studies of coronavirus disease 2019.

Many studies, including self-controlled case series (SCCS) studies, are being undertaken to quantify the risks of complications following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). One such SCCS study, based on all COVID-19 cases arising in Sweden over an 8-month period, has shown that SARS-CoV-2 infection increases the risks of AMI and ischemic stroke. Some features of SARS-CoV-2 infection and COVID-19, present in this study and likely in others, complicate the analysis and may introduce bias. In the present paper we describe these features, and explore the biases they may generate. Motivated by data-based simulations, we propose methods to reduce or remove these biases.

A framework for exploring non-response patterns over time in health surveys.

BACKGROUND: Most health surveys have experienced a decline in response rates. A structured approach to evaluate whether a decreasing - and potentially more selective - response over time biased estimated trends in health behaviours is lacking. We developed a framework to explore the role of differential non-response over time. This framework was applied to a repeated cross-sectional survey in which the response rate gradually declined. METHODS: We used data from a survey conducted biannually between 1995 and 2017 in the city of Rotterdam, The Netherlands. Information on the sociodemographic determinants of age, sex, and ethnicity was available for respondents and non-respondents. The main outcome measures of prevalence of sport participation and watching TV were only available for respondents. The framework consisted of four steps: 1) investigating the sociodemographic determinants of responding to the survey and the difference in response over time between sociodemographic groups; 2) estimating variation in health behaviour over time; 3) comparing weighted and unweighted prevalence estimates of health behaviour over time; and 4) comparing associations between sociodemographic determinants and health behaviour over time. RESULTS: The overall response rate per survey declined from 47% in 1995 to 15% in 2017. The probability of responding was higher among older people, females, and those with a Western background. The response rate declined in all subgroups, and a faster decline was observed among younger persons and those with a non-Western ethnicity as compared to older persons and those with a Western ethnicity. Variation in health behaviours remained constant. Prevalence estimates and associations did not follow the changes in response over time. On the contrary, the difference in probability of participating in sport gradually decreased between males and females, while no differential change in the response rate was observed. CONCLUSIONS: Providing insights on non-response patterns over time is essential to understand whether declines in response rates may have influenced estimated trends in health behaviours. The framework outlined in this study can be used for this purpose. In our example, in spite of a major decline in response rate, there was no evidence that the risk of non-response bias increased over time.

The effect of primary care policy changes on hospitalisation for ambulatory care sensitive conditions: notes from Brazil.

OBJECTIVES: The aim of this study was to assess the effect of the Primary Health Care Reform and the impact of recent national policy changes on the trend in hospitalisation rates for Ambulatory Conditions Sensitive to Primary Care (ACSC) in the city of Rio de Janeiro, Brazil. STUDY DESIGN: Ecological study with data from the Brazilian National Health Information System. METHODS: This study performed an interrupted time-series analysis, comparing three different time periods related to important changes in primary care policies in Brazil: Baseline (2008-2009); Primary Health Care Reform (RCAPS) (2010-2017); and National Primary Health Care Policy (PNAB) (2018-2019). Data included total monthly admissions for ACSC and rates for 19 groups of causes for hospitalisation. RESULTS: There was a non-significant increasing trend in ACSC hospital admissions between January 2008 and December 2009 (ß = 4.01, 95% confidence interval [CI] -12.14 to 20.15). The Primary Health Care Reform (RCAPS), which commenced in January 2010, resulted in a significant reduction in ACSC hospital admission trends during this time period (ß = -7.97, 95% CI -9.78 to -6.16). Change in the PNAB did not change the declining ACSC hospital admission trend but it did reduce the rate of decline. In addition, the coefficient was no longer significant (ß = -1.93, 95% CI -2.46 to 0.59), suggesting that monitoring of the historical series for a long time may show a reversal of the downward trend in some months. The most consistent change in ACSC hospital admission trend occurred between baseline and the RCAPS (ß slope = -0.143, P < 0.001) and the level between the RCAPS period and the new PNAB (ß step = 7.00, P = 0.008). Trends and differences in the time periods vary in the different ACSC hospitalisation-cause groups. CONCLUSION: Changes in public health policies impact ACSC hospitalisation rates, which can thus be used as an indicator for monitoring primary health care. We also recommend analysing admission rates by the individual ACSC hospitalisation-cause groups.

A Scoping Review of Socioeconomic Inequalities in Distributions of Birth Outcomes: Through a Conceptual and Methodological Lens.

INTRODUCTION: The extant literature has examined social inequalities in high-risk categories of birth weight and gestational age (i.e., low birth weight and preterm birth) with little attention given to their distributional nature. As such, a scoping review was conducted to understand how researchers have conceptualized and analyzed socioeconomic inequalities in entire distributions of these birth outcomes. METHODS: Bibliographic databases were searched from their inception until August 2016 for articles from five similar, English-speaking, advanced capitalist democracies: Canada, United States, United Kingdom, Australia and New Zealand. RESULTS: Twenty-one studies were included in the review, all of which provided rationales for examining socioeconomic inequalities in the entire distribution of birth weight. Yet, only three studies examined non-uniform associations of socioeconomic factors across the distribution of birth weight using conditional quantile regression, while the majority focused on mean birth weight using descriptive analysis or linear regression to analyze inequalities. Nevertheless, study results indicated that socioeconomic inequalities exist throughout the distribution of birth weight, extending beyond the high-risk category of low birth weight. DISCUSSION: Although social inequalities in distributions of birth weight have been conceptualized, few studies have analytically engaged with this concept. As such, this review supports further investigation of distributional inequalities in birth outcomes using methodology which allows one to empirically quantify and explain differences in population risk distributions, rather than solely between infants born low birth weight or preterm birth, versus not.

Glucose-lowering medications and the risk of cancer: A methodological review of studies based on real-world data.

AIM: To review the methodology of observational studies examining the association between glucose-lowering medications and cancer to identify the most common methodological challenges and sources of bias. METHODS: We searched PubMed systematically to identify observational studies on glucose-lowering medications and cancer published between January 2000 and January 2016. We assessed the design and analytical methods used in each study, with a focus on their ability to achieve study validity, and further evaluated the prevalence of major methodological choices over time. RESULTS: Of 155 studies evaluated, only 26% implemented a new-user design, 41% used an active comparator, 33% implemented a lag or latency period, and 51% adjusted for diabetes duration. Potential for immortal person-time bias was identified in 63% of the studies; 55% of the studies adjusted for variables measured during the follow-up without appropriate statistical methods. Aside from a decreasing trend in adjusting for variables measured during the follow-up, we observed no trends in methodological choices over time. CONCLUSIONS: The prevalence of well-known design and analysis flaws that may lead to biased results remains high among observational studies on glucose-lowering medications and cancer, limiting the conclusions that can be drawn from these studies. Avoiding known pitfalls could substantially improve the quality and validity of real-world evidence in this field.

Towards risk-stratified colorectal cancer screening. Adding risk factors to the fecal immunochemical test: Evidence, evolution and expectations.

With increasing incidence and mortality, colorectal cancer (CRC) is a growing health problem worldwide. An effective way to address CRC is by screening for fecal (occult) blood by the fecal immunochemical test (FIT). However, there is room for improvement since precursor lesions and CRC bleed intermittent and can therefore be missed by the FIT (false negatives) or, the detected blood did not result from precursor lesions or CRC (false positives). This review provides the latest evidence on risk prediction models using FIT combined with additional risk factors before colonoscopy, which risk factors to include and if these models will better discriminate between normal findings and CRC compared to the FIT-only. Many prediction models are known for CRC, but compared to the FIT, these are less effective in detecting CRC. The literature search resulted in 645 titles where 11 papers matched the inclusion criteria and were analyzed. Comparing the FIT-only with the risk prediction models for detecting CRC resulted in a significantly increased discrimination for the models. In addition, 2 different risk-stratification categories before colonoscopy were distinguished, namely the 1-model approach which combined risk factors with FIT results in a prediction model while the 2 step approach used risk factors apart from the FIT. Finally, combining FIT with CRC risk factors by means of a model before colonoscopy seems effective regarding discriminative power, however, more research is needed for validation combined with transparent and standardized reporting to improve quality assessment, for which suggestions are reported in this study.

Investigating the association between occupational exposure to asbestos and ovarian carcinoma: results from a pilot study in Germany.

BACKGROUND: The aim of this pilot study was to assess the feasibility of a large-scale epidemiologic investigation elucidating the quantitative association between occupational exposure to asbestos and ovarian cancer in former German asbestos workers. METHODS: Between December 2017 and May 2018, a random sample of one thousand insured woman registered at the health service of a German trade association as formerly occupationally exposed to asbestos were invited to participate in a pilot study. Participation included a phone interview using a standardised questionnaire. The feasibility of the project was evaluated using a priori defined criteria. They included response, number of cases, eligibility of the questionnaire data for exact estimation of asbestos fibre-years, and availability of relevant medical documentation (imaging procedures, medical reports, and histologic materials). RESULTS: The response (17%) was clearly below the intended number of 60%. With six tumour suspects, of which two could be confirmed by medical documents, the number of cases was within the expected range of two to eleven cases. Exact asbestos fibre-year estimations could be performed for 29% of all interviewees, but only for one suspected case. Medical documentation could be collected for only few participants, while no histology reports could be obtained for all cases. Thus, only the feasibility criterion of the expected number of cases was fulfilled. CONCLUSION: The results of the pilot study indicate that the planned project is feasible only to a very limited extent. For further planning of the study, measures to improve recruitment of participants are necessary.