# \[ANN\] NetSurvival.jl: A pure-Julia take on standard net survival routines

**URL:** https://discourse.julialang.org/t/ann-netsurvival-jl-a-pure-julia-take-on-standard-net-survival-routines/116722
**Category:** Package Announcements
**Tags:** statistics, health, public-health
**Created:** [July 7, 2024, 2:15pm UTC](https://discourse.julialang.org/t/ann-netsurvival-jl-a-pure-julia-take-on-standard-net-survival-routines/116722 "2024-07-07T14:15:34Z")
**Posts on this page:** 1
**Page:** 1

<div class="post-metadata">

### Author: ![lrnv](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lrnv/32/19373_2.png) [@lrnv](https://discourse.julialang.org/u/lrnv)
#### Post date: [July 7, 2024, 2:15pm UTC](https://discourse.julialang.org/t/ann-netsurvival-jl-a-pure-julia-take-on-standard-net-survival-routines/116722/1 "2024-07-07T14:15:34Z")

</div>

Hi there ! I wanted to officially announce [`JuliaSurv/NetSurvival.jl`](https://github.com/JuliaSurv/NetSurvival.jl), a new Julia package that gathers implementation of net survival related routines, joint work with @rimhajal.

Net survival is a specialized branch of Survival Analysis that focuses on estimating the probability of survival from a specific event of interest, for example a given cancer, without considering other causes of death, in the (unfortunately quite common) case where the cause of death indicatrix is unavailable (or e.g. untrustworthy). Consequently, the so-called _missing indicatrix_ issue forbids the use of standard competitive risks survival analysis methods on these datasets. Thus, a few standard estimators were established in the last 50 years, backed by a constantly growing literature.

This package is an attempt to bring standard relative survival analysis modeling routines to Julia, while providing an interface that is close to the R package `relsurv`, albeit significantly faster and easier to maintain in the future. We aim at covering the standard estimators, needed for routines and comparisons, but also to provide the most up-to-date state of the art for the use of biostatisticians and oncologists around the world.

An extensive list of standard estimators in the field is implemented: Ederer I & II, Hakulinen, Pohar Perme, Grafféo’s test, Croning-Feuer’s crude probabilities, etc… But most importantly, thanks to Julia, the obtained codebase is compact, readable, well documented and well tested, and provides significant performance improvements compared to the R standard.

This is also the first output of a more general work at the [`JuliaSurv`](https://github.com/JuliaSurv) GitHub organization, that aims at covering survival analysis more generally. More will come, and contributions are of course welcomed.

Check out [our documentation](https://juliasurv.github.io/NetSurvival.jl/dev/) to learn about the field or simply learn about our implementation ! You may star the project [on github](https://github.com/JuliaSurv/NetSurvival.jl) to show support! 🙂

We’ll also be at Juliacon2024 next week if you want to know more.