ArticleEpidemiology (Cambridge, Mass.)2017
Survival Analysis with Multiple Causes of Death: Extending the Competing Risks Model.
Article in Epidemiology (Cambridge, Mass.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
40 citing papers in PubMed, 72 citations in OpenAlex.
- Reclassification and weighting of multiple causes of death: US death certificates 2003-2023.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Re-classification and Weighting of Multiple Causes of Death: US Death Certificates 2003-2023.medRxiv : the preprint server for health sciences · 2026Article
- Multiple cause of death during the COVID-19 pandemic: a population study In Colombia and Brazil.International journal of public health · 2026Article
- An Introduction to Competing Risks in Epidemiology.Clinical epidemiology · 2026Review
- Underlying and contributing causes of mortality from CDC WONDER-Insights for researchers.American heart journal plus : cardiology research and practice · 2025Article
- Estimating mortality attributable to alcohol or tobacco - a cohort study from Germany.Substance abuse treatment, prevention, and policy · 2025Article
- Beyond the underlying cause of death: an algorithm to study multi-morbidity at death.Population health metrics · 2024Article
- Survival Prediction After Transarterial Chemoembolization for Hepatocellular Carcinoma: a Deep Multitask Survival Analysis Approach.Journal of healthcare informatics research · 2023Article
- Body Mass Index and Cause-Specific Mortality after Lung Transplantation in the United States.Annals of the American Thoracic Society · 2023Article
- Analysis of Multiple Causes of Death: A Review of Methods and Practices.Epidemiology (Cambridge, Mass.) · 2023Review
- A new data driven method for summarising multiple cause of death data.BMC medical research methodology · 2023Article
- Levels, trends, and determinants of cause-of-death diversity in a global perspective: 1990-2019.BMC public health · 2023Article
- Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations.International journal of epidemiology · 2023Article
- A novel cuproptosis-related gene signature of prognosis and immune microenvironment in head and neck squamous cell carcinoma cancer.Journal of cancer research and clinical oncology · 2023Article
- Subclinical cardiovascular disease and frailty risk: the atherosclerosis risk in communities study.BMC geriatrics · 2022Article
- Observed and predicted premature mortality in Australia due to non-communicable diseases: a population-based study examining progress towards the WHO 25X25 goal.BMC medicine · 2022Article
- KLRK1 as a prognostic biomarker for lung adenocarcinoma cancer.Scientific reports · 2022Article
- Synergistic impact of diabetes and cognitive impairment on all-cause and cause-specific mortality in Chinese older adults: A prospective population-based cohort study.Frontiers in endocrinology · 2022Article
- Quantifying the population burden of musculoskeletal disorders, including impact on sickness absence: analysis of national Scottish data.Rheumatology advances in practice · 2022Article
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4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Statistics on mortality related to each disease are usually based on the so-called underlying cause of death, which is selected from the diseases declared on the standardized death certificate using international rules. However, the assumption that each death is caused by exactly one disease is debatable, particularly with an aging population in an era where infectious diseases are replaced by chronic and degenerative diseases. The need to consider multiple causes of death has been acknowledged in epidemiologic research, with a growing body of literature producing statistics based on any mention of a disease on the death certificate. Yet there has not been a formal framework proposed for the statistical modeling of death arising from multiple causes. We propose a model for multiple cause of death data grounded on an empirical approach that assigns weights to each cause on the death certificate. We describe how this model for multiple-cause mortality, which extends the usual competing risks model used to conceptualize single-cause mortality, can serve to study the burden and etiology of mortality related to each disease, particularly using Cox regression methodology. We discuss how the multiple-cause, single-cause, and "any-mention" approaches compare in this regard. A simulation study and an application to a study of socioeconomic inequalities in mortality show the value of the proposed methods for exploiting this precious source of data to gain new insights, especially for certain diseases. See video abstract at, http://links.lww.com/EDE/B84.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.