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Simone de Vries,1 Michael Schaapveld,1 Jan WPF Kardaun,2,3 Kim H de Bruin,2 Augustinus DG Krol,4 Pieternella J Lugtenburg,5 Judy N Jacobse,1 Berthe MP Aleman,6 Flora E van Leeuwen1 1Department of Epidemiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; 2Department of Health and Care, Statistics Netherlands, The Hague, the Netherlands; 3Department of Public Health, Academic Medical Center, Amsterdam, the Netherlands; 4Department of Radiotherapy, Leiden University Medical Center, Leiden, the Netherlands; 5Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; 6Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands Objective: Obtaining accurate data about causes of death may be difficult in patients with a complicated disease history, including cancer survivors. This study compared causes of death derived from medical records (CODMR) with causes of death derived from death certificates (CODDC) as processed by Statistics Netherlands of patients primarily treated for Hodgkin lymphoma (HL) or breast cancer (BC).Methods: Two hospital-based cohorts comprising 1,215 HL patients who died in the period 1980–2013 and 714 BC patients who died in the period 2000–2013 were linked with cause-of-death statistics files. The level of agreement was assessed for common underlying causes of death using Cohen’s kappa, and original death certificates were reviewed when CODDC and CODMR showed discrepancies. We examined the influence of using CODDC or CODMR on standardized mortality ratio (SMR) estimates.Results: Agreement for the most common causes of death, including selected malignant neoplasms and circulatory and respiratory diseases, was 81% for HL patients and 97% for BC patients. HL was more often reported as CODDC (CODDC=33.1% vs. CODMR=23.2%), whereas circulatory disease (CODDC=15.6% vs. CODMR=20.9%) or other diseases potentially related to HL treatment were more often reported as CODMR. Compared to SMRs based on CODDC, SMRs based on CODMR complemented with CODDC were lower for HL and higher for circulatory disease.Conclusion: Overall, we observed high levels of agreement between CODMR and CODDC for common causes of death in HL and BC patients. Observed discrepancies between CODMR and CODDC frequently occurred in the presence of late effects of treatment for HL. Keywords: cause of death, Hodgkin lymphoma, breast cancer, mortality statistics

Objectives: Systemic autoimmune diseases (SAIDs) have chronic trajectories and share characteristics of self-directed inflammation, as well as aspects of clinical expression. Nonetheless, burden-of-disease studies rarely investigate them as a distinct category. This study aims to assess the mortality rate of SAIDs as a group and to evaluate co-occurring causes of death., Methods: We used death certificate data in the Netherlands, 2013-2017 (N = 711 247), and constructed a SAIDs list at the fourth-position ICD-10 level. The mortality rate of SAIDs as underlying cause of death (CoD), non-underlying CoD, and any-mention CoD was calculated. We estimated age-sex-standardized observed/expected (O/E) ratios to assess comorbidities in deaths with SAID relative to the general deceased population., Results: We observed 3335 deaths with SAID on their death certificate (0.47% of all deaths). The mortality rate of SAID was 14.6 per million population as underlying CoD, 28.0 as non-underlying CoD, and 39.7 as any-mention CoD. The mortality rate was higher for females and increased exponentially with age. SAID-related deaths were positively associated with all comorbidities except for solid neoplasms and mental conditions. Particularly strong was the association with diseases of the musculoskeletal system (O/E = 3.38; 95% CI: 2.98, 3.82), other diseases of the genitourinary system (O/E = 2.73; 95% CI: 2.18, 3.38), influenza (O/E = 2.71; 95% CI: 1.74, 4.03), blood diseases (O/E = 2.02; 95% CI: 1.70, 2.39), skin and subcutaneous tissue diseases (O/E = 1.95; 95% CI: 1.54, 2.45), and infectious diseases (O/E = 1.85; 95% CI: 1.70, 2.01)., Conclusion: Systemic autoimmune diseases constitute a rare group of causes of death, but contribute to mortality through multiple comorbidities. Classification systems could be adapted to better encompass these diseases as a category., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Objectives: The International Classification of Diseases (ICD-10) distinguishes a large number of causes of death (CODs) that could each be studied individually when monitoring time-trends. We aimed to develop recommendations for using the size of CODs as a criterion for their inclusion in long-term trend analysis., Design: Retrospective trend analysis., Setting: 21 European countries of the WHO Mortality Database., Participants: Deaths from CODs (3-position ICD-10 codes) with ≥5 average annual deaths in a 15-year period between 2000 and 2016., Primary and Secondary Outcome Measures: Fitting polynomial regression models, we examined for each COD in each country whether or not changes over time were statistically significant (with α=0.05) and we assessed correlates of this outcome. Applying receiver operating characteristicROC curve diagnostics, we derived COD size thresholds for selecting CODs for trends analysis., Results: Across all countries, 64.0% of CODs had significant long-term trends. The odds of having a significant trend increased by 18% for every 10% increase of COD size. The independent effect of country was negligible. As compared to circulatory system diseases, the probability of a significant trend was lower for neoplasms and digestive system diseases, and higher for infectious diseases, mental diseases and signs-and-symptoms. We derived a general threshold of around 30 (range: 28-33) annual deaths for inclusion of a COD in trend analysis. The relevant threshold for neoplasms was around 65 (range: 61-70) and for infectious diseases was 20 (range: 19-20)., Conclusions: The likelihood that long-term trends are detected with statistical significance is strongly related to COD size and varies between ICD-10 chapters, but has no independent relation to country. We recommend a general size criterion of 30 annual deaths to select CODs for long-term mortality-trends analysis in European countries., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Cause of death (COD) data are essential to public health monitoring and policy. This study aims to determine the proportion of CODs, at ICD-10 three-position level, for which a long-term or short-term trend can be identified, and to examine how much the likelihood of identifying trends varies with COD size. We calculated annual age-standardized counts of deaths from Statistics Netherlands for the period 1996-2015 for 625 CODs. We applied linear regression models to estimate long-term trends, and outlier analysis to detect short-term changes. The association of the likelihood of a long-term trend with COD size was analyzed with multinomial logistic regression. No long-term trend could be demonstrated for 216 CODs (34.5%). For the remaining 409 causes, a trend could be detected, following a linear (211, 33.8%), quadratic (126, 20.2%) or cubic model (72, 11.5%). The probability of detecting a long-term trend increased from about 50% at six mean annual deaths, to 65% at 22 deaths and 75% at 60 deaths. An exceptionally high or low number of deaths in a single year was found for 16 CODs. When monitoring long-term mortality trends, one could consider a much broader range of causes of death, including ones with a relatively low number of annual deaths, than commonly used in condensed lists.