# A new discrimination measure for assessing predictive performance of non-linear survival models

arXiv: https://arxiv.org/abs/2504.05630 · HTML: https://mlsanity.com/paper/2504.05630/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2025.

## Built on by (most cited first, 1 of 1)

- [The C-index Multiverse](https://mlsanity.com/paper/2508.14821/) (2025)

## Abstract (arXiv)

Non-linear survival models are flexible models in which the proportional hazard assumption is not required. This poses difficulties in their evaluation. We introduce a new discrimination measure, time-dependent Uno's C-index, to assess the discrimination performance of non-linear survival models. This is an unbiased version of Antolini's time-dependent concordance. We prove convergence of both measures employing Nolan and Pollard's results on U-statistics. We explore the relationship between these measures and, in particular, the bias of Antolini's concordance in the presence of censoring using simulated data. We demonstrate the value of time-dependent Uno's C-index for the evaluation of models trained on censored real data and for model tuning.