Multi-state relative survival modelling of XXXX progression and mortality.

@entity5 @entity1 @entity204 @entity14
UNASSIGNED: Accurate identification of factors associated with progression of @entity14 remains a challenge. In particular, it is unclear which statistical methods are most suitable to separate the effects of putative prognostic factors on @entity5 progression vs @entity5 -specific and other cause mortality. To address these challenges, we analyzed 10 year follow-up data for @entity1 who underwent curative surgery for @entity14 in 1985-2000. Separate analyses were performed in two French @entity5 registries. Results of three multivariable models were compared: Cox model with recurrence as a time-dependent variable, and two multi-state models, which separated prognostic factor effects on recurrence vs @entity204 , with or without recurrence. Conventional multi-state model analyzed all-cause mortality while new relative survival multi-state model focused on @entity5 -specific mortality. Among the 2517 and 2677 @entity1 in the two registries, about 50% died without a recurrence, and 28% had a recurrence, of whom almost 90% died. In both multi-state models @entity1 had significantly increased risk of @entity5 recurrence in both registries (HR=0.79; 95% CI: 0.68-0.92 and HR=0.83; 95% CI: 0.71-0.96). However, the two multi-state models identified different prognostic factors for mortality without recurrence. In contrast to the conventional model, in the relative survival analyses gender had no independent association with @entity5 -specific mortality whereas @entity1 diagnosed with @entity5 had significantly higher risks in both registries (HR=1.67; 95% CI: 1.27-2.22 and HR=2.38; 95% CI: 1.29-3.27). In conclusion, relative survival multi-state model revealed that different factors may be associated with @entity5 recurrence vs @entity5 -specific mortality either after or without a recurrence.
