Risk factors for employment difficulties after cancer diagnosis are incompletely understood, and interventions to improve post-cancer employment remain few. New targets for intervention are needed.

We assessed a cohort of 530 nonmetastatic cancer patients (aged≤65 years, >6 months from diagnosis, off chemo- or radiotherapy) from the observational multi-site Symptom Outcomes and Practice Patterns study. Participants reported employment change, current employment, and symptoms. Groups were based on employment at survey (working full- or part-time versus not working) and whether there had been a change due to illness (yes versus no). The predictive power of symptom interference with work was evaluated for employment group (working stably versus no longer working). Race/ethnicity, gender, cancer type, therapy, and time since diagnosis were also assessed. Association between employment group and specific symptoms was examined.

The cohort was largely non-Hispanic white (76 %), female (85 %), and diagnosed with breast cancer (75 %); 24 % reported a change in employment. On multivariable analysis, participants with at least moderate symptom interference were more likely to report no longer working than their less effected counterparts (odds ratio (OR)=8.0, 95 % CI, 4.2–15.4), as were minority participants compared with their non-Hispanic white counterparts (OR=3.2, 95 % CI, 1.8– 5.6). Results from the multiple regression model indicated the combination of fatigue (OR=2.3, 95 % CI, 1.1–4.7), distress (OR=3.9, 95 % CI, 1.7–9.0), and dry mouth (OR=2.6, 95 % CI, 1.1–6.2) together with race/ethnicity and time since diagnosis adequately predicted for employment group.

Our findings support the hypothesis that residual symptom burden affects post-cancer employment: Residual symptoms may be targets for intervention to improve work outcomes among cancer survivors.

This analysis examines whether increased symptom burden predicts a change to not working following a cancer diagnosis. We also examined individual symptoms to assess which symptoms were most strongly associated with not working after a cancer diagnosis. Our hope is that we will be able to use this information to both screen survivors post-active treatment and to identify those at risk, as well as target high-risk symptoms for further and more aggressive intervention, in an attempt to improve post-cancer work outcomes.