Modelling of time-to-events in an ambispective study: illustration with the analysis of ABO blood groups on venous thrombosis recurrence
Munsch, G.; Goumidi, L.; van Hylckama Vlieg, A.; Ibrahim-Kosta, M.; Bruzelius, M.; Deleuze, J.-F.; Rosendaal, F. R.; Jacqmin-Gadda, H.; Morange, P.-E.; Tregouët, D.-A.
Show abstract
In studies of time-to-events, it is common to collect information about events that occurred before the inclusion in a prospective cohort. In an ambispective design, when the risk factors studied are independent of time, including both pre- and post-inclusion events in the analyses increases the statistical power but may lead to a selection bias. To avoid such a bias, we propose a survival analysis weighted by the inverse of the survival probability at the time of data collection about the events. This method is applied to the study of the association of ABO blood groups with the risk of venous thromboembolism (VT) recurrence in the MARTHA and MEGA cohorts. The former relying on an ambispective design and the latter on a standard prospective one. In the combined sample totalling 2,752 patients including 993 recurrences, compared with the O1 group, A1 has an increased risk (Hazard Ratio (HR) of 1.18, p=4.2x10-3), homogeneously in MARTHA and in MEGA. The same trend (HR=1.19, p=0.06) was observed for the less frequent A2 group. In conclusion, this work clarified the association of ABO blood groups with the risk of VT recurrence. Besides, the methodology proposed here to analyse time-independent risk factors of events in an ambispective design has an immediate field of application in the context of genome wide association studies.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- COVID-19 is associated with higher risk of venous thrombosis, but not arterial thrombosis, compared with influenza: Insights from a large US cohort 94%
- An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes 94%
- The usefulness of D-dimer as a predictive marker for mortality in patients with COVID-19 hospitalized during the first wave in Italy 94%
Similar papers in this journal
Similar papers in this journal
- The effect of sex and underlying disease on the genetic association of QT interval and sudden cardiac death 92%
- Association between prostate cancer and myocardial infarction management and post-infarction outcomes: A Norwegian registry study 92%
- Predictors of survival in patients with ischemic stroke and active cancer: A prospective, multicenter, observational study 92%
Similar papers in this journal
- Machine learning model predicts new-onset deep vein thrombosis of the lower extremities after pelvic floor fracture surgery and targeted diagnosis 92%
- Risk factors for heart failure with preserved or reduced ejection fraction among Medicare beneficiaries: Applications of competing risks analysis and gradient boosted model. 87%
- Pre-morbid risk factors for amyotrophic lateral sclerosis: prospective cohort study 87%
Similar papers in this journal
- Elevated Angiopoietin-2 inhibits thrombomodulin-mediated anticoagulation in critically ill COVID-19 patients 91%
- Rapid assessment of COVID-19 mortality risk with GASS classifiers 91%
- Multi-level analysis of adipose tissue reveals the relevance of perivascular subpopulations and an increased endothelial permeability in early-stage lipedema 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.