Association between patterns of return-to-work trajectories and long-term depressive symptoms among breast cancer survivors [O-282 ]

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Bertin, Mélanie | Roquelaure, Yves | Porro, Bertrand | Gilbert, Fabien | Rapicault, Clémence

Edité par CCSD ; BMJ Publishing Group Ltd -

International audience. Introduction Depressive symptoms and fatigue are well known factors affecting return-to-work (RTW) after breast cancer (BC). However, the RTW process may in turn have a positive impact on long-term health and psychological well-being among breast cancer survivors (BCS).Objective Our aim was to identify RTW trajectories within the 5-years following BC using a multi-phase and diachronic process and to assess their associations with depressive symptoms measured at least five year after their BC diagnostic.Methods We used data from the French Constances cohort that included more than 200,000 participants from 2012 to 2020. Our study relied on a sub-sample of women aged up to 55 years at the time of their diagnostic, who were working at the time of their diagnostic and who fully completed their occupational calendar up to five years after their diagnostic (n=939). Sequence analysis was used to identify RTW trajectories among BCS from their diagnosis up to 5 years later. Depressive symptoms were assessed using the 20-items CES-D scale. Adjusted logistic regression analyses were performed to assess the association between RTW trajectories and depressive symptoms.Results In our sample, 12.8% of BCS suffered from depressive symptoms at their inclusion in the cohort. Four types of RTW trajectories were identified: full-time RTW (n=645), late or no RTW (n=114), early and progressive RTW (n=134), full time RTW before early retirement (n=46). BCS that had a late or did not RTW within the five years following their diagnostic were associated with an increased risk of long-term depressive symptoms (OR : 2.73, 95% CI [1.47–5.04]).Conclusion This study highlighted that a late or absence of RTW within the 5 years after BC was associated with poorer long-term psychosocial factors and confirmed the potential of using sequence analysis to capture the multi-state aspect of RTW trajectories.

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