# Time-to-event analysis in nested case-control designs

**URL:** <https://discourse.datamethods.org/t/time-to-event-analysis-in-nested-case-control-designs/3010>\
**Category:** modeling strategy\
**Tags:** epi, survival-analysis, design\
**Created:** [February 16, 2020, 1:11pm UTC](https://discourse.datamethods.org/t/time-to-event-analysis-in-nested-case-control-designs/3010 "2020-02-16T13:11:00Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![albertoca](https://discourse.datamethods.org/user_avatar/discourse.datamethods.org/albertoca/32/297_2.png) [@albertoca](https://discourse.datamethods.org/u/albertoca)\
**Post date:** [February 16, 2020, 1:11pm UTC](https://discourse.datamethods.org/t/time-to-event-analysis-in-nested-case-control-designs/3010/1 "2020-02-16T13:11:00Z")

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I would like to ask for ideas on nested case-control study analysis for time-to-event analysis in the presence of competing risks. For example, a database with 500 cancer patients with thrombosis (cases), and 500 cancer patients without thrombosis (controls). Thromboses occur months after diagnosis, data are censored, and death represents a competing event. The design is nested since the true incidence of thrombosis is around 7-10%. If competing risk models (e.g., FG model) are applied, I do not know how the subhazards should be interpreted. Or how the hazard ratio would be interpreted if I fit a cause-specific Cox model.