To estimate the effects of Janus kinase inhibitors (JAKis) vs biologic disease-modifying antirheumatic drugs (bDMARDs) on the risk of incident malignancies (excluding nonmelanoma skin cancer) in patients and patient subgroups with rheumatoid arthritis. Episodes of disease-modifying antirheumatic drug (DMARD) treatment initiated between January 2017 and December 2020 and followed up to June 2024 in RABBIT, the German register for the long-term observation of therapy with biologics and targeted disease-modifying antirheumatic drugs in adult patients with rheumatoid arthritis, were analysed. Incidence rates (IRs) per 1000 patient-years with 95% CIs were calculated, and incident malignancy risk was estimated as hazard ratios (HRs) by inverse probability weighted adjusted Cox models. Among 2285 JAKi and 4259 bDMARD treatment episodes, 88 and 135 malignancies occurred, respectively. JAKi treatments were dominated by baricitinib and tofacitinib, while most bDMARD treatments comprised tumour necrosis factor inhibitors. IRs were 11.6 (95% CI: 9.3, 14.3) in JAKi- and 8.9 (95% CI: 7.4, 10.5) in bDMARD-treated groups. The adjusted HR comparing JAKis with bDMARDs was 1.40 (95% CI: 1.09, 1.80). An increase in the malignancy risk for JAKi vs bDMARD treatment could only be observed in treatment episodes lasting longer than 16 months. The risk appeared higher in some subgroups of patients, including those who started treatment aged ≥60 years, patients with ≥3 prior conventional synthetic DMARD treatments, and patients with high disease activity. In this German observational cohort study, an overall small increase in malignancy risk for JAKi vs bDMARD treatment was observed, with more pronounced risks in some subgroups of patients. The observed risk should be carefully counterbalanced to the known malignancy risk associated with insufficient disease control.

Magnetic resonance imaging (MRI) yields numerous tumor-related incidental findings (IFs) which may trigger diagnostics such as biopsies. To clarify these effects, we studied how whole-body MRI IF disclosure in a population-based cohort affected biopsy frequency and the detection of malignancies. Laboratory disclosures were also assessed. Data from 6753 participants in the Study of Health in Pomerania (SHIP) examined between 2008 and 2012 were utilized. All underwent laboratory examinations and 3371 (49.9%) a whole-body MRI. Electronic biopsy reports from 2002 to 2017 were linked to participants and assigned to outcome categories. Biopsy frequency 2 years pre- and post-SHIP was investigated using generalized estimating equations with a negative-binomial distribution. Overall 8208 IFs (laboratory findings outside reference limits: 6839; MRI: 1369) were disclosed to 4707 participants; 2271 biopsy reports belonged to 1200 participants (17.8%). Of these, 938 biopsies occurred pre-SHIP; 1333 post-SHIP (event rate/100 observation years = 6.9 [95% CI 6.5; 7.4]; 9.9 [9.3; 10.4]). Age, cancer history, recent hospitalization, female sex, and IF disclosure were associated with higher biopsy rates. Nonmalignant biopsy results increased more in participants with disclosures (post-/pre-SHIP rate ratio 1.39 [95% CI 1.22; 1.58]) than without (1.09 [95% CI 0.85; 1.38]). Malignant biopsy results were more frequent post-SHIP (rate ratio 1.74 [95% CI 1.27; 2.42]). Biopsies increased after participation in a population-based cohort study with MRI and laboratory IF disclosure. Most biopsies resulted in no findings and few malignancies were diagnosed, indicating potential overtesting and overdiagnosis. A more restrictive policy regarding IF disclosure from research findings is required.

In 2009, the Democratic Republic of Congo (DRC) started its journey towards achieving Universal Health Coverage (UHC). This study examines the evolution of financial risk protection and health outcomes indicators in the context of the commitment of DRC to UHC. To measure the effects of such a commitment on financial risk protection and health outcomes indicators, we analyse whether changes have occurred over the last two decades and, if applicable, when these changes happened. Using five variables as indicators for the measurement of the financial risk protection component, there as well retained three indicators to measure health outcomes. To identify time-related effects, we applied the parametric approach of breakpoint regression to detect whether the UHC journey has brought change and when exactly the change has occurred.Although there is a slight improvement in the financial risk protection indicators, we found that the adopted strategies have fostered access to healthcare for the wealthiest quantile of the population while neglecting the majority of the poorest. The government did not thrive persistently over the past decade to meet its commitment to allocate adequate funds to health expenditures. In addition, the support from donors appears to be unstable, unpredictable and unsustainable. We found a slight improvement in health outcomes attributable to direct investment in building health centres by the private sector and international organizations. Overall, our findings reveal that the prevention of catastrophic health expenditure is still not sufficiently prioritized by the country, and mostly for the majority of the poorest. Therefore, our work suggests that DRC’s UHC journey has slightly contributed to improve the financial risk protection and health outcomes indicators but much effort should be undertaken.

The data linkage of different data sources for research purposes is being increasingly used in recent years. However, generally accepted methodological guidance is missing. The aim of this article is to provide methodological guidelines and recommendations for research projects that have been consented to across different German research societies. Another aim is to endow readers with a checklist for the critical appraisal of research proposals and articles. This Good Practice Data Linkage (GPD) was already published in German in 2019, but the aspects mentioned can easily be transferred to an international context, especially for other European Union (EU) member states. Therefore, it is now also published in English. Since 2016, an expert panel of members of different German scientific societies have worked together and developed seven guidelines with a total of 27 practical recommendations. These recommendations include (1) the research objectives, research questions, data sources, and resources; (2) the data infrastructure and data flow; (3) data protection; (4) ethics; (5) the key variables and linkage methods; (6) data validation/quality assurance; and (7) the long-term use of data for questions still to be determined. The authors provide a rationale for each recommendation. Future revisions will include new developments in science and updates of data privacy regulations.

This study estimates the prevalence of health insurance coverage and associated socioeconomic factors in the Democratic Republic of Congo (DRC). Using the nationally representative household survey of the 2017/2018 DRC Multiple Indicator Cluster Survey (MICS), we applied weighted logistic regression models to identify regions and subgroups with low health insurance coverage. The study's findings revealed a low insurance coverage of less than 5%, with significant disparities across provinces and socioeconomic status. Additionally, three factors were strongly associated with the low health insurance coverage rates: education, wealth, and financial inclusion proxied by bank account ownership. Consequently, we recommend that the government, the private sector, and donors prioritize programs targeting provinces with less coverage and individuals without formal education to increase health insurance coverage. This study encourages the government to establish national programs to improve financial inclusion, which could positively impact poverty reduction and health insurance coverage. We also propose that the government initiates pilot projects for premium exemptions and through subsidies for vulnerable populations in the short term, and ensure formal employment for the majority of the population in the long term to facilitate the proper collection of premiums for individuals. Overall, this study contributes to the literature on health insurance in the DRC and sub‐Saharan Africa by identifying the socioeconomic factors that explain the prevalence of health insurance coverage. The findings of this study have important policy implications for the government, the private sector, and donors to promote health insurance coverage and achieve universal health coverage.