Cited by 986Statistical Methods in EpidemiologyProbability and Statistical ResearchStatistical Methods and Inference

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Competing risks in epidemiology: possibilities and pitfalls

Open access

Andersen, Per Kragh, Geskus, Ronald B, de Witte, Theo, Putter, Hein·2012·International Journal of Epidemiology

Open this paper in CoChat — free account Open PDF

Abstract

BACKGROUND: In studies of all-cause mortality, the fundamental epidemiological concepts of rate and risk are connected through a well-defined one-to-one relation. An important consequence of this relation is that regression models such as the proportional hazards model that are defined through the hazard (the rate) immediately dictate how the covariates relate to the survival function (the risk). METHODS: This introductory paper reviews the concepts of rate and risk and their one-to-one relation in all-cause mortality studies and introduces the analogous concepts of rate and risk in the context of competing risks, the cause-specific hazard and the cause-specific cumulative incidence function. RESULTS: The key feature of competing risks is that the one-to-one correspondence between cause-specific hazard and cumulative incidence, between rate and risk, is lost. This fact has two important implications. First, the naïve Kaplan-Meier that takes the competing events as censored observations, is biased. Secondly, the way in which covariates are associated with the cause-specific hazards may not coincide with the way these covariates are associated with the cumulative incidence. An example with relapse and non-relapse mortality as competing risks in a stem cell transplantation study is used for illustration. CONCLUSION: The two implications of the loss of one-to-one correspondence between cause-specific hazard and cumulative incidence should be kept in mind when deciding on how to make inference in a competing risks situation.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1093/ije/dyr213

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Regression Models and Life-Tables
Cox, D. R. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00899.x · Cited by 39,793
Regression Models and Life-Tables
Cox, D. R. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4380-9_37 · Cited by 26,297
A Proportional Hazards Model for the Subdistribution of a Competing Risk
Fine, J. P., & Gray, R. J. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10474144 · Cited by 14,290
The Statistical Analysis of Failure Time Data.
Aitkin, M. A., Kalbfleisch, J. D., & Prentice, R. L. (1981) · Biometrics · doi:10.2307/2530581 · Cited by 9,875
The Statistical Analysis of Failure Time Data
Kalbfleisch, J. D., & Prentice, R. L. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781118032985 · Cited by 3,219
Epidemiology: Principles and Methods
MacMahon, B., & Pugh, T. F. (1970) · Cited by 1,472
- Statistical Models for Epidemiology
Broemeling, L. D. (2013) · Chapman & Hall/CRC eBooks · doi:10.1201/b15382-9 · Cited by 1,346
A nonidentifiability aspect of the problem of competing risks.
Tsiatis, A. A. (1975) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.72.1.20 · Cited by 870
Risk assessment for patients with chronic myeloid leukaemia before allogeneic blood or marrow transplantation
Gratwohl, A. A., Hermans, J., Goldman, J. M., Arcese, W., Carreras, E., Devergié, A., Frassoni, F., Gahrton, G., Kolb, H., Niederwieser, D. W., et al. (1998) · The Lancet · doi:10.1016/s0140-6736(98)03030-x · Cited by 646
Epidemiology: An Introduction
Schottenfeld, D. (2002) · American Journal of Epidemiology · doi:10.1093/aje/kwf028 · Cited by 627

Flagged first, then by citations

Show all 18 references

Sorted by citations

Items 501–600 of 986

Clinical outcomes of prolonged dual antiplatelet therapy after coronary drug-eluting stent implantation in dialysis patients
Park, S., Kim, Y., Jo, H. A., Lee, S., Kim, M., Yang, B. R., Lee, J., Han, S. S., Lee, H., Lee, J. P., et al. (2020) · Clinical Kidney Journal · doi:10.1093/ckj/sfaa037 · Cited by 11
Evaluating the Age-Based Recommendations for Long-Term Follow-Up in Breast Cancer
Witteveen, A., de Munck, L., Groothuis‐Oudshoorn, C. G. M., Sonke, G. S., Poortmans, P. M., Boersma, L. J., Smidt, M. L., Vliegen, I. M. H., IJzerman, M. J., & Siesling, S. (2020) · The Oncologist · doi:10.1634/theoncologist.2019-0973 · Cited by 11
Cardiovascular events in cancer patients with bone metastases—A Danish population‐based cohort study of 23,113 patients
Asdahl, P. H., Sundbøll, J., Adelborg, K., Rasmussen, T. B., Seesaghur, A., Hernandez, R. K., Sørensen, H. T., & Pedersen, A. B. (2021) · Cancer Medicine · doi:10.1002/cam4.4027 · Cited by 11
Time-to-event methodology improved statistical evaluation in register-based health services research
Bluhmki, T., Bramlage, P., Volk, M., Kaltheuner, M., Danne, T., Rathmann, W., & Beyersmann, J. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2016.11.001 · Cited by 11
A latent class model for competing risks
Rowley, M., Garmo, H., Hemelrijck, M. V., Wulaningsih, W., Grundmark, B., Zethelius, B., Hammar, N., Walldius, G., Inoue, M., Holmberg, L., et al. (2017) · Statistics in Medicine · doi:10.1002/sim.7246 · Cited by 11
Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19
Martinuka, O., von Cube, M., Hazard, D. Y., Marateb, H. R., Mansourian, M., Sami, R., Hajian, M. R., Ebrahimi, S. H., & Wolkewitz, M. (2023) · Life · doi:10.3390/life13030777 · Cited by 10
Competing-risks analysis for evaluating the prognosis of patients with microinvasive cutaneous squamous cell carcinoma based on the SEER database
Zheng, S., Xie, S., Yu, H., Duan, X., He, Y., Ho, C. A., Yang, W., Hang, T., Chen, W., Lyu, J., et al. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-02109-x · Cited by 10
Association of platinum-based chemotherapy with live birth and infertility in female survivors of adolescent and young adult cancer
Zhou, B., Kwan, B., Desai, M. J., Nalawade, V. V., Henk, J., Viravalli, N., Murphy, J. D., Nathan, P. C., Ruddy, K. J., Shliakhtsitsava, K., et al. (2024) · Fertility and Sterility · doi:10.1016/j.fertnstert.2024.01.039 · Cited by 10
Nonparametric Assessment of Differences Between Competing Risk Hazard Ratios: Application to Racial Differences in Pediatric Chronic Kidney Disease Progression
Ng, D. K., Antiporta, D. A., Matheson, M. B., & Muñoz, Á. (2020) · Clinical Epidemiology · doi:10.2147/clep.s225763 · Cited by 10
Effectiveness and Safety of Ticagrelor Implementation in Patients with Acute Coronary Syndrome undergoing Percutaneous Coronary Intervention: A Cohort Study in Western Denmark
Thrane, P. G., Olesen, K. K. W., Würtz, M., Gyldenkerne, C., Madsen, M., Jensen, L. O., Raungaard, B., Sørensen, H. T., Thim, T., Kristensen, S. D., et al. (2022) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2021.100301 · Cited by 10
Incidence and Predictors of Neurologic Death in Patients with Brain Metastases
Reese, R. A., Lamba, N., Catalano, P. J., Cagney, D. N., Wen, P. Y., & Aizer, A. A. (2022) · World Neurosurgery · doi:10.1016/j.wneu.2022.03.028 · Cited by 10
causalCmprsk: An R package for nonparametric and Cox-based estimation of average treatment effects in competing risks data
Vakulenko‐Lagun, B., Magdamo, C., Charpignon, M., Zheng, B., Albers, M. W., & Das, S. (2023) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2023.107819 · Cited by 10
Editor's Choice -- Survival, Limb Salvage, and Management of Patients with Lower Limb Acute Ischaemia: A French National Retrospective Observational Study
Espitia, O., Giudice, C. D., Hartung, O., Herquelot, É., Schmidt, A., Sapoval, M. R., & Sobocinski, J. (2023) · European Journal of Vascular and Endovascular Surgery · doi:10.1016/j.ejvs.2023.11.001 · Cited by 10
Long-term HIV care outcomes under universal HIV treatment guidelines: A retrospective cohort study in 25 countries
Brazier, E., Tymejczyk, O., Wools‐Kaloustian, K., Jiamsakul, A., Torres, M. T. L., Lee, J. S., Abuogi, L., Khol, V., Mejía, F., Althoff, K. N., et al. (2024) · PLoS Medicine · doi:10.1371/journal.pmed.1004367 · Cited by 10
Methodological biases in observational hospital studies of COVID-19 treatment effectiveness: pitfalls and potential
Martinuka, O., Hazard, D. Y., Marateb, H. R., Mansourian, M., Mañanas, M. Á., Romero, S., Rubio‐Rivas, M., & Wolkewitz, M. (2024) · Frontiers in Medicine · doi:10.3389/fmed.2024.1362192 · Cited by 10
Estimation of Relative and Absolute Risks in a Competing-Risks Setting Using a Nested Case-Control Study Design: Example From the ProMort Study
Zelić, R., Zugna, D., Bottai, M., Andrén, O., Fridfeldt, J., Carlsson, J., Davidsson, S., Fiano, V., Fiorentino, M., Giunchi, F., et al. (2019) · American Journal of Epidemiology · doi:10.1093/aje/kwz026 · Cited by 10
Immune checkpoint blockade in the treatment of advanced non-small cell lung cancer – predictors of response and impact of previous radiotherapy
Öjlert, Å. K., Nebdal, D. J. H., Lund‐Iversen, M., Ellefsen, R. Å., Brustugun, O. T., Gran, J. M., Halvorsen, A. R., & Helland, Å. (2020) · Acta Oncologica · doi:10.1080/0284186x.2020.1854851 · Cited by 10
Genetic polymorphism in ATIC is associated with effectiveness and toxicity of pemetrexed in non-small-cell lung cancer
Visser, S., Koolen, S. L. W., van Donk, N., van Walree, N., van der Leest, C., Cornelissen, R., van Schaik, R. H., Mathijssen, R. H. J., Aerts, J. G. J. V., & Stricker, B. H. C. (2021) · Thorax · doi:10.1136/thoraxjnl-2020-216504 · Cited by 10
Ten-Year Probabilities of Death Due to Cancer and Cardiovascular Disease among Breast Cancer Patients Diagnosed in North-Eastern Spain
Clèries, R., Ameijide, A., Buxó, M., Vilardell, M., Martı́nez, J. M., Font, R., Marcos‐Gragera, R., Puigdemont, M., Viñas, G., Carulla, M., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20010405 · Cited by 10
Trends in length of stay, mortality and readmission among patients with community-acquired bacteraemia
Søgaard, M., Thomsen, R. W., Bang, R. B., Schønheyder, H. C., & Nørgaard, M. (2015) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2015.05.018 · Cited by 10
Impact of dependent left truncation in semiparametric competing risks methods: A simulation study
Bakoyannis, G., & Touloumi, G. (2015) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2015.1030415 · Cited by 10
Occult cancer‐related first venous thromboembolism is associated with an increased risk of recurrent venous thromboembolism
Gran, O. V., Brækkan, S. K., Paulsen, B., Skille, H., Rosendaal, F. R., & Hansen, J. (2017) · Journal of Thrombosis and Haemostasis · doi:10.1111/jth.13714 · Cited by 10
Competing mortality risks among women aged 50–79 years when diagnosed with invasive breast cancer, Queensland, 1997–2012
Dasgupta, P., Aitken, J. F., Pyke, C., & Baade, P. D. (2018) · The Breast · doi:10.1016/j.breast.2018.07.005 · Cited by 10
Response to “Early hydroxychloroquine but not chloroquine use reduces ICU admission in COVID-19 patients”
Linschoten, M., Nab, L., van der Horst, I. C. C., Tieleman, R. G., & Asselbergs, F. W. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.12.006 · Cited by 10
To Trach or Not To Trach: Long-term Tracheostomy Outcomes in Infants with BPD
Kielt, M. J., Levin, J. C., & MBI (2023) · NeoReviews · doi:10.1542/neo.24-11-e704 · Cited by 9
Ultra-processed food consumption, genetic susceptibility, and the risk of hip/knee osteoarthritis
Wei, Y., Zhang, T., Liu, Y., Liu, H., Zhou, Y., Su, J., Chen, L., Bai, L., & Xia, Y. (2024) · Clinical Nutrition · doi:10.1016/j.clnu.2024.04.030 · Cited by 9
Immunosuppression at ICU admission is not associated with a higher incidence of ICU-acquired bacterial bloodstream infections: the COCONUT study
Zebian, G., Kreitmann, L., Houard, M., Piantoni, A., Piga, G., Aimes, S. R. D., Holik, B., Wallet, F., Labreuche, J., & Nseir, S. (2024) · Annals of Intensive Care · doi:10.1186/s13613-024-01314-1 · Cited by 12
Air pollution exacerbates cardiovascular-kidney-metabolic syndrome and sarcopenia comorbidity via shared genetic-epigenetic mechanisms: A multi-omics and Mendelian Randomization study
Wei, S., Shu, Z., Li, X., Zhong, S., Xiao, L., Shen, R., Lu, X., He, L., Zhang, Y., Quan, Y., et al. (2025) · Metabolism · doi:10.1016/j.metabol.2025.156452 · Cited by 11
The importance of considering competing risks in recurrence analysis of intracranial meningioma
Mirian, C., Jensen, L. R., Juratli, T. A., Maier, A. D., TORP, S. H., Shih, H. A., Morshed, R. A., Young, J. S., Magill, S. T., Bertero, L., et al. (2024) · Journal of Neuro-Oncology · doi:10.1007/s11060-024-04572-y · Cited by 9
Should We Use Standard Survival Models or the Illness-Death Model for Interval-Censored Data to Investigate Risk Factors of Chronic Kidney Disease Progression?
Boucquemont, J., Metzger, M., Combe, C., Stengel, B., Leffondré, K., & on behalf of the NephroTest Study Group (2014) · PLoS ONE · doi:10.1371/journal.pone.0114839 · Cited by 9
Long-Term Outcome After Carotid Artery Stenting
Jonsson, M., Lindstrom, D. J., Gillgren, P., Wanhainen, A., & Malmstedt, J. (2016) · Stroke · doi:10.1161/strokeaha.116.013018 · Cited by 9
S. Typhimurium virulence changes caused by exposure to different non-thermal preservation treatments using C. elegans
Sanz-Puig, M., Lázaro, E., Armero, C., Alvares, D., Martínez, A., & Rodrigo, D. (2017) · International Journal of Food Microbiology · doi:10.1016/j.ijfoodmicro.2017.09.006 · Cited by 9
Competing mortality risks analysis of prediagnostic lifestyle and dietary factors in colorectal cancer survival: the Norwegian Women and Cancer Study
Oyeyemi, S. O., Braaten, T., Skeie, G., & Borch, K. B. (2019) · BMJ Open Gastroenterology · doi:10.1136/bmjgast-2019-000338 · Cited by 9
Acute myeloid leukemia: negative prognostic impact of early blast persistence can be in part overcome by a later remission prior to post-induction therapy
Ihlow, J., Gross, S., Busack, L. M., Flörcken, A., Jesse, J., Schwarz, M., Neuendorff, N. R., von Brünneck, A., Anagnostopoulos, I., Türkmen, S., et al. (2021) · Haematologica · doi:10.3324/haematol.2021.279134 · Cited by 9
Impact of Late and Recurrent Acute Graft Pyelonephritis on Long-Term Kidney Graft Outcomes
Pacaud, M., Colas, L., Kerleau, C., Leborgne, F., Giral, M., Brouard, S., & Dantal, J. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.824425 · Cited by 9
A competing risks approach to “biologic” interaction
Andersen, P. K., & Skrondal, A. (2015) · Lifetime Data Analysis · doi:10.1007/s10985-015-9318-z · Cited by 9
Self-citation
Effect of Prophylactic Antifungal Protocols on the Prognosis of Liver Transplantation: A Propensity Score Matching and Multistate Model Approach
Chen, Y.-C., Huang, T., Wang, Y., Cheng, C., Lee, C., Wu, T.-J., Chou, H., Chan, K., Lee, W., & Soong, R. (2016) · BioMed Research International · doi:10.1155/2016/6212503 · Cited by 10
Trajectories in suicide attempt method lethality over a five-year period: Associations with suicide attempt repetition, all-cause, and suicide mortality
Witt, K., Pirkis, J., Scott, D. A., Smith, K. L., & Lubman, D. I. (2021) · PLoS ONE · doi:10.1371/journal.pone.0245780 · Cited by 9
A Multinational Cohort Study Examining Sex Differences in Excess Risk of Death With Graft Function After Kidney Transplant
Vinson, A. J., Zhang, X., Dahhou, M., Süsal, C., Döhler, B., Sapir‐Pichhadze, R., Cardinal, H., Melk, A., Wong, G., Francis, A., et al. (2024) · Transplantation · doi:10.1097/tp.0000000000004915 · Cited by 8
A retrospective cohort study of pulp prognosis in luxated permanent teeth: a competing risk analysis
Coste, S. C., Rodrigues, M. A., Chaves, J. F. M., Lima, T. C. D. S., Colosimo, E. A., & Bastos, J. V. (2024) · Clinical Oral Investigations · doi:10.1007/s00784-024-05574-w · Cited by 9
Pitfalls in time-to-event analysis of registry data: a tutorial based on simulated and real cases
Alligon, M., Mahlaoui, N., & Bouaziz, O. (2024) · Frontiers in Epidemiology · doi:10.3389/fepid.2024.1386922 · Cited by 8
Bleeding risk using non-steroidal anti-inflammatory drugs in anticoagulated patients with atrial fibrillation: a nationwide cohort study
Petersen, S. R., Bonnesen, K., Larsen, J. B., Pedersen, L. H., & Schmidt, M. (2025) · European Heart Journal - Quality of Care and Clinical Outcomes · doi:10.1093/ehjqcco/qcaf076 · Cited by 8
Prediction of frailty in community older adults based on machine learning: a systematic review and meta-analysis
Ou, Y., Jiang, D., Li, P., Zhang, W., Zhou, Y., Chen, Y., & Yin, X. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1667792 · Cited by 10
An Introduction to Competing Risks in Epidemiology
Sørensen, H. T., Horváth–Puhó, E., & Peacock, J. L. (2026) · Clinical Epidemiology · doi:10.2147/clep.s574928 · Cited by 8
Primary preventive potential of major lifestyle risk factors for acute myocardial infarction in men: an analysis of the EPIC-Heidelberg cohort
Li, K., Monni, S., Hüsing, A., Wendt, A., Kneisel, J., Groß, M.-L., & Kaaks, R. (2014) · European Journal of Epidemiology · doi:10.1007/s10654-013-9872-1 · Cited by 8
Multilevel competing risks in the evaluation of nosocomial infections: time to move on from proportional hazards and even from hazards altogether
Muñoz, Á., Mongilardi, N., & Checkley, W. (2014) · Critical Care · doi:10.1186/cc13892 · Cited by 8
Competing risk events in antimalarial drug trials in uncomplicated Plasmodium falciparum malaria: a WorldWide Antimalarial Resistance Network individual participant data meta-analysis
The WorldWide Antimalarial Resistance Network Methodology Study Group (2019) · Malaria Journal · doi:10.1186/s12936-019-2837-4 · Cited by 8
Association between gastroesophageal reflux disease and colorectal cancer risk: a population-based cohort study
Hu, J., Wu, J.-J., Hsu, C., Chen, Y., Tian, Y., Chang, P.-K., Chen, C.-Y., Chou, Y., & Sun, C. (2021) · International Journal of Colorectal Disease · doi:10.1007/s00384-021-03873-2 · Cited by 8
Additive Subdistribution Hazards Regression for Competing Risks Data in Case-Cohort Studies
Wogu, A. F., Li, H., Zhao, S., Nichols, H. B., & Cai, J. (2023) · Biometrics · doi:10.1111/biom.13821 · Cited by 8
Proportion and number of incident cancer deaths in coronary artery disease
Liu, J., Chen, S., Zhou, Y., Huang, H., Li, Q., Liang, Y., Dong, S., Huang, X., Chen, L., Zheng, X., et al. (2023) · Cancer Medicine · doi:10.1002/cam4.6595 · Cited by 8
Calculation of Life-Time Death Probability due Malignant Tumors Based on a Sampling Survey Area in China
Yuan, P., Chen, T.-H., Chen, Z.-W., & Lin, X. (2014) · Asian Pacific Journal of Cancer Prevention · doi:10.7314/apjcp.2014.15.10.4307 · Cited by 8
Using the Payoff Time in Decision-Analytic Models: A Case Study for Using Statins in Primary Prevention
Thompson, A., Guthrie, B., & Payne, K. (2017) · Medical Decision Making · doi:10.1177/0272989x17700846 · Cited by 8
Stabilizing cumulative incidence estimation of pregnancy outcome with delayed entries
Rousson, V., Allignol, A., Aurousseau, A., Winterfeld, U., & Beyersmann, J. (2018) · Biometrical Journal · doi:10.1002/bimj.201700237 · Cited by 8
Second Cancers in Patients With Locally Advanced Prostate Cancer Randomized to Lifelong Endocrine Treatment With or Without Radical Radiation Therapy: Long-Term Follow-up of the Scandinavian Prostate Cancer Group-7 Trial
Aksnessæther, B. Y., Myklebust, T. Å., Solberg, A., Klepp, O., Skovlund, E., Hoff, S. R., Fosså, S. D., Widmark, A., & Lund, J. (2019) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2019.11.027 · Cited by 8
Analysis of lifetime death probability for major causes of death among residents in China
Yuan, P., Xiang, J., Borg, M., Chen, T., Lin, X., Peng, X., & Zheng, K. (2020) · BMC Public Health · doi:10.1186/s12889-020-09201-7 · Cited by 8
Early stage breast cancer treatment and outcome of older patients treated in an oncogeriatric care and a standard care setting: an international comparison
de Boer, A. Z., van de Water, W., Bastiaannet, E., de Glas, N. A., Kiderlen, M., Portielje, J. E. A., & Extermann, M. (2020) · Breast Cancer Research and Treatment · doi:10.1007/s10549-020-05860-7 · Cited by 8
A competing risk model for bond strength data analysis
Tichý, A., Brabec, M., Bradna, P., Hosaka, K., & Tagami, J. (2020) · Dental Materials · doi:10.1016/j.dental.2020.09.004 · Cited by 8
Stenting as a bridge to surgery in obstructing colon cancer: Long-term recurrence pattern and competing risk of mortality
Chok, A. Y., Zhao, Y., Lim, H. J., Ng, Y. Y. R., & Tan, E. (2023) · World Journal of Gastrointestinal Endoscopy · doi:10.4253/wjge.v15.i2.64 · Cited by 8
Compliance-Adjusted Estimates of Aspirin Effects Among Older Persons in the ASPREE Randomized Trial
Smith, C. L., Kasza, J., Woods, R. L., Lockery, J. E., Kirpach, B., Reid, C. M., Storey, E., Nelson, M. R., Shah, R. C., Orchard, S. G., et al. (2023) · American Journal of Epidemiology · doi:10.1093/aje/kwad168 · Cited by 8
Joint Inference for Competing Risks Survival Data
Li, G., & Yang, Q. (2015) · Journal of the American Statistical Association · doi:10.1080/01621459.2015.1093942 · Cited by 8
Impact of chronic hepatitis C on mortality in cirrhotic patients admitted to intensive-care unit
Álvaro‐Meca, A., Jiménez‐Sousa, M. Á., Boyer, A., Medraño, J., Reulen, H., Kneib, T., & Resino, S. (2016) · BMC Infectious Diseases · doi:10.1186/s12879-016-1448-8 · Cited by 8
No Impact of Preadmission Anti-Inflammatory Drug Use on Risk of Depression and Anxiety After Critical Illness*
Medici, C. R., Gradus, J. L., Pedersen, L. H., Sørensen, H. T., Østergaard, S. D., & Christiansen, C. F. (2017) · Critical Care Medicine · doi:10.1097/ccm.0000000000002571 · Cited by 8
Progression of chronic kidney disease: an illness-death model approach
Vejakama, P., Ingsathit, A., McEvoy, M., Attia, J., & Thakkinstian, A. (2017) · BMC Nephrology · doi:10.1186/s12882-017-0604-8 · Cited by 8
Controlling the crystal polymorph by exploiting the time dependence of nucleation rates
Little, L. J., King, A. A. K., Sear, R. P., & Keddie, J. L. (2017) · The Journal of Chemical Physics · doi:10.1063/1.4993566 · Cited by 8
Evaluating mortality in an intensive care unit requires extended survival models
Wolkewitz, M., & Sommer, H. (2014) · Critical Care · doi:10.1186/cc13757 · Cited by 8
Factors associated with hospital length of stay in patients admitted with suspected malaria in Kenya: secondary analysis of a cross-sectional survey
Machini, B., Achia, T., Kipruto, H., Amboko, B., & Chesang, J. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-059263 · Cited by 7
Preservative food additives, hypertension, and cardiovascular diseases: the NutriNet-Santé study
Hasenböhler, A., Javaux, G., de la Garanderie, M. P., de Edelenyi, F. S., Yvroud, P., Agaësse, C., Sa, A. D., Huybrechts, I., Pierre, F. H. F., Coumoul, X., et al. (2026) · European Heart Journal · doi:10.1093/eurheartj/ehag308 · Cited by 7
Trends in disease incidence and survival and their effect on mortality in Scotland: nationwide cohort study of linked hospital admission and death records 2001–2016
Timmers, P. R. H. J., Kerssens, J. J., Minton, J., Grant, I., Wilson, J. F., Campbell, H. J., Fischbacher, C., & Joshi, P. K. (2020) · BMJ Open · doi:10.1136/bmjopen-2019-034299 · Cited by 7
The implications of competing risks and direct treatment disutility in cardiovascular disease and osteoporotic fracture: risk prediction and cost effectiveness analysis
Guthrie, B., Rogers, G., Livingstone, S. J., Morales, D. R., Donnan, P. T., Davis, S., Youn, J.-H., Hainsworth, R., Thompson, A., & Payne, K. (2024) · Health and Social Care Delivery Research · doi:10.3310/kltr7714 · Cited by 8
Is coffee, tea, and red wine consumption beneficial for individuals with hypertension?
Zhang, S., Xiang, B., Su, X., Zhou, Y., Zhao, Y., & Zhou, X. (2024) · Postgraduate Medical Journal · doi:10.1093/postmj/qgae039 · Cited by 7
Reassessing Halm's clinical stability criteria in community-acquired pneumonia management
Israelsen, S. B., Fally, M., Nielsen, P. B., Kolte, L., Iversen, K. K., Ravn, P., & Benfield, T. (2024) · European Respiratory Journal · doi:10.1183/13993003.00054-2024 · Cited by 8
Thrombolysis in acute ischemic stroke is associated with lower long-term hospital bed day use: A nationwide propensity score-matched follow-up study
Terkelsen, T., Schmitz, M. L., Simonsen, C. Z., Hundborg, H. H., Christensen, H., Gyllenborg, J., Sandal, B. F., Iversen, H. K., Madsen, C., Rasmussen, M.-J., et al. (2016) · International Journal of Stroke · doi:10.1177/1747493016654491 · Cited by 7
Impact of cancer diagnosis on persistence of oral antidiabetic drugs
Létinier, L., Mansiaux, Y., Pariente, A., & Fourrier‐Réglat, A. (2018) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2018.03.011 · Cited by 7
Renin–angiotensin system blocker use and the risk of acute kidney injury after colorectal cancer surgery: a population-based cohort study
Slagelse, C., Gammelager, H., Iversen, L. H., Liu, K. D., Sørensen, H. T., & Christiansen, C. F. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-032964 · Cited by 7
Analysis of survival outcomes in haematopoietic cell transplant studies: Pitfalls and solutions
de Wreede, L. C., Schetelig, J., & Putter, H. (2022) · Bone Marrow Transplantation · doi:10.1038/s41409-022-01740-4 · Cited by 7
Self-citation
Long-Term Outcomes of Perioperative Versus Nonoperative Myocardial Infarction: A Danish Population-Based Cohort Study (2000–2016)
Korsgaard, S., Schmidt, M., Mæng, M., Jakobsen, L., Pedersen, L. H., Christiansen, C. F., & Sørensen, H. T. (2022) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.121.008212 · Cited by 7
Estimating disease incidence rates and transition probabilities in elderly patients using multi-state models: a case study in fragility fracture using a Bayesian approach
Llopis-Cardona, F., Armero, C., & Sanfélix‐Gimeno, G. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-01859-y · Cited by 7
National cohort study of absolute risk and age-specific incidence of multiple adverse outcomes between adolescence and early middle age
Mok, P. L. H., Antonsen, S., Pedersen, C. B., Appleby, L., Shaw, J. J., & Webb, R. T. (2015) · BMC Public Health · doi:10.1186/s12889-015-2249-5 · Cited by 7
Normal Myocardial Perfusion Gated SPECT and Positive Stress Test: Different Prognoses in Women and Men
Romero-Farina, G., Candell‐Riera, J., González, I. F., Aguadé‐Bruix, S., Pizzi, M. N., & David Garcia-dorado, A. (2014) · Journal of Nuclear Cardiology · doi:10.1007/s12350-014-0009-z · Cited by 7
Assessing the Effectiveness of Treatment Sequences for Older Patients With High-risk Follicular Lymphoma With a Multistate Model
Çağlayan, Ç., Terawaki, H., Ayer, T., Goldstein, J., Rai, A., Chen, Q., & Flowers, C. R. (2019) · Clinical Lymphoma Myeloma & Leukemia · doi:10.1016/j.clml.2018.12.019 · Cited by 7
Assessing the calibration of subdistribution hazard models in discrete time
Berger, M., & Schmid, M. C. (2021) · Canadian Journal of Statistics · doi:10.1002/cjs.11633 · Cited by 7
Cancer- and noncancer-specific cumulative incidence of death after exposure to polychlorinated biphenyls and dioxins: A competing risk analysis among Yusho patients
Onozuka, D., Nakamura, Y., Tsuji, G., & Furue, M. (2020) · Environment International · doi:10.1016/j.envint.2020.106320 · Cited by 7
Serum uric acid is associated with increased risk of posttransplantation diabetes in kidney transplant recipients: a prospective cohort study
Sotomayor, C. G., Sokooti, S., Bustos, N. I., Nolte, I. M., Neto, A. W. G., Marcia Erazo, B., Gormaz, J. G., Berger, S. P., Navis, G. J., Rodrigo, R., et al. (2020) · Metabolism · doi:10.1016/j.metabol.2020.154465 · Cited by 7
Prevalence, outcome, and management of risk factors in breast cancer patients with peripheral arterial disease: A tertiary cancer center’s experience
Bryce, Y., Bourguillon, R. O., Vázquez, J. C., Ziv, E., Kim, D., & Santos, E. (2020) · Clinical Breast Cancer · doi:10.1016/j.clbc.2020.12.010 · Cited by 5
Competing risks in quality and safety research: a framework to guide choice of analysis and improve reporting
de Mheen, P. J. M., Putter, H., Bastiaannet, E., & Bottle, A. (2021) · BMJ Quality & Safety · doi:10.1136/bmjqs-2021-012988 · Cited by 7
Self-citation
Horizontal mixture model for competing risks: a method used in waitlisted renal transplant candidates
Trébern-Launay, K., Kessler, M., Bayat, S., Querard, A.-H., Briançon, S., Giral, M., & Foucher, Y. (2017) · European Journal of Epidemiology · doi:10.1007/s10654-017-0322-3 · Cited by 7
Comment on ‘The latency period of mesothelioma among a cohort of British asbestos workers (1978–2005)’
Mirabelli, D., & Zugna, D. (2014) · British Journal of Cancer · doi:10.1038/bjc.2014.111 · Cited by 7
Loss to follow-up correction increased mortality estimates in HIV-positive people on antiretroviral therapy in MozambiquePreprint
Anderegg, N., Hector, J., Jefferys, L. F., Burgos-Soto, J., Hobbins, M. A., Ehmer, J., Meier, L., Maathuis, M. H., & Egger, M. (2020) · medRxiv · doi:10.1101/2020.08.04.20167155 · Cited by 7
Drug repurposing of metformin for Alzheimer’s disease: Combining causal inference in medical records data and systems pharmacology for biomarker identificationPreprint
Charpignon, M., Vakulenko‐Lagun, B., Zheng, B., Magdamo, C., Su, B., Evans, K. E., Rodriguez, S., Sokolov, A., Boswell, S. A., Sheu, Y.-H., et al. (2021) · medRxiv · doi:10.1101/2021.08.10.21261747 · Cited by 7
Sensory Loss and its Association with Different Types of Departures from the Labor Force Among Older Adults in the US
Morales, E. E. G., Powell, D. S., Gray, A., Assi, L., & Reed, N. S. (2023) · Work Aging and Retirement · doi:10.1093/workar/waad010 · Cited by 6
Prediction of dementia risk from multimodal repeated measures: The added value of brain MRI biomarkers
Bercu, A., Dufouil, C., Debette, S., Joliot, M., Tsuchida, A., Helmer, C., Devaux, A., Bouteloup, V., Proust‐Lima, C., & Jacqmin‐Gadda, H. (2024) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12578 · Cited by 6
Olfactory dysfunction increases progression to dementia in cognitively impaired older adults: a 12-year population-based study
Oltra, J., Ekström, I., Larsson, M. U., Yan, J., Grande, G., & Laukka, E. J. (2025) · GeroScience · doi:10.1007/s11357-025-01705-7 · Cited by 6
Arterial and venous thromboembolic events in patients with cancer treated with targeted therapies: a population-based cohort study
Moik, F., Horváth–Puhó, E., Ay, C., Pabinger, I., Mulder, F. I., van Es, N., & Sørensen, H. T. (2025) · EClinicalMedicine · doi:10.1016/j.eclinm.2025.103440 · Cited by 6
Common methodological issues in observational epidemiological studies of older adults
Nichols, E. L., & Hayes‐Larson, E. (2025) · BMJ Medicine · doi:10.1136/bmjmed-2025-001332 · Cited by 6
Drug Survival of Biologics in Bionaive and Bioexperienced Patients With Psoriasis
Schwarz, C., Loft, N., Bryld, L. E., Nissen, C., Ajgeiy, K. K., Bertelsen, T., Hjuler, K. F., Dam, T. N., Iversen, L., Rasmussen, M. K., et al. (2026) · JAMA Dermatology · doi:10.1001/jamadermatol.2025.5205 · Cited by 6
Predicting the risk of distant and local recurrence for patients with ocular adnexal extranodal marginal zone lymphoma: a matched case–control study
Shi, J., Zhu, T., Zhou, M., Zhou, X., Song, X., Wang, Y., Jia, R., Yu, Z., Zhou, Y., & Fan, X. (2022) · British Journal of Ophthalmology · doi:10.1136/bjo-2022-321656 · Cited by 6
Developing and validating prediction models for severe exacerbations and readmissions in patients hospitalised for COPD exacerbation (SERCO) in China: a prospective observational study
Wang, Y., He, R., Ren, X., Huang, K., Lei, J., Niu, H., Li, W., Dong, F., Li, B., Yang, T., et al. (2024) · BMJ Open Respiratory Research · doi:10.1136/bmjresp-2023-001881 · Cited by 6
The role of donor hypertension and angiotensin II in the occurrence of early pancreas allograft thrombosis
Masset, C., Branchereau, J., Buron, F., Karam, G., Rabeyrin, M., Renaudin, K., Leborgne, F., Badet, L., Matillon, X., Legendre, C. M., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1359381 · Cited by 6
Mortality follow-up of Fernald Feed Materials Production Center workers exposed to uranium from 1951 to 1985
Milder, C. M., Bellamy, M. B., Howard, S. C., Ellis, E. D., Golden, A. P., Cohen, S. S., Mumma, M. T., French, B. C., Zablotska, L. B., & Boice, J. D. (2024) · Occupational and Environmental Medicine · doi:10.1136/oemed-2023-109192 · Cited by 5
All‐Cause and Cause‐Specific Mortality Among Individuals With Major Depression: A Nationwide Danish Matched‐Cohort Study
Osler, M., Rosenqvist, T. W., Rozing, M. P., Jørgensen, A., Jørgensen, M. B., Jørgensen, T. S. H., & Gronemann, F. H. (2025) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13800 · Cited by 6

Authors: Andersen, P. K., Geskus, R. B., de Witte, T., & Putter, H.
Affiliations: University of Copenhagen (DK)
Amsterdam UMC Location University of Amsterdam (NL)
Leiden University Medical Center (NL)
Corresponding author: Putter, Hein
ORCID: Andersen, Per Kragh
Geskus, Ronald B
Putter, Hein
Venue: International Journal of Epidemiology
Publisher: Oxford University Press (OUP)
Published: 2012-01-09
Volume: 41
Issue: 3
Pages: 861-870
ISSN: 0300-5771 (ISSN-L)
1464-3685
DOI: 10.1093/ije/dyr213
PMC: PMC3396320
OpenAlex: W2154117702
Semantic Scholar: fad89d6c4d4b7b80df8a26be5a2c8e1dd54eec29
Cited by: 985
References: 18
Citations by year: 2026: 83 · 2025: 59 · 2024: 78 · 2023: 75 · 2022: 71 · 2021: 66 · 2020: 102 · 2019: 88 · 2018: 77 · 2017: 77 · 2016: 73 · 2015: 47 · 2014: 51 · 2013: 29 · 2012: 9
FWCI: 41.50
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: International Journal of Epidemiology (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Data Archiving and Networked Services (DANS) (submittedVersion)
Leiden Repository (Leiden University) (submittedVersion)
HighWire Press Open Archive (submittedVersion)
Pure Amsterdam UMC (submittedVersion)
Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
Radboud Repository (Radboud University) (submittedVersion)
Funders: U.S. Public Health Service (R01-54706-12)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Keywords: competing risks, all-cause mortality, cause-specific hazard, cumulative incidence function, stem cell transplantation
MeSH terms: Humans, Models, Theoretical, Mortality, Survival Analysis, Epidemiologic Studies, Risk Assessment

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Competing risks in epidemiology: possibilities and pitfalls

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks