Information: Corresponding Author's Institution: University of Wisconsin. Corresponding Author's Secondary. Institution: First Author: Amye Juliet Tevaarwerk, MD.
Journal of Cancer Survivorship: Research and Practice Employment outcomes among survivors of common cancers: analysis from the Eastern Cooperative Oncology Group (ECOG) "Symptom Outcomes and Practice Patterns (SOAPP)" study --Manuscript Draft-Manuscript Number: Full Title:
Employment outcomes among survivors of common cancers: analysis from the Eastern Cooperative Oncology Group (ECOG) "Symptom Outcomes and Practice Patterns (SOAPP)" study
Article Type:
Original Research
Keywords:
Cancer survivor Post-cancer employment Work disability Survivor symptom burden Return to work
Corresponding Author:
Amye Juliet Tevaarwerk, MD University of Wisconsin Madison, WI UNITED STATES
Corresponding Author Secondary Information: Corresponding Author's Institution:
University of Wisconsin
Corresponding Author's Secondary Institution: First Author:
Amye Juliet Tevaarwerk, MD
First Author Secondary Information: Order of Authors:
Amye Juliet Tevaarwerk, MD Ju-whei Lee, PhD Mary E Sesto, PhD Kevin A Buhr, PhD Charles S Cleeland, MD Judith Manola, PhD Lynne I Wagner, PhD Victor T S Chang, MD Micheal J Fisch, MD
Order of Authors Secondary Information: Abstract:
Intro: 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. Methods: 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 SOAPP study. Participants reported employment change due to illness, current employment and symptoms. Employment groups were defined based on selfreported employment at survey (working full or part-time vs not working) and whether there had been a change due to illness (yes vs 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 outcome and specific symptoms was examined. Powered by Editorial Manager® and Preprint Manager® from Aries Systems Corporation
Results: Overall, 24% of the cohort reported a change in employment due to illness. On multivariable analysis, participants with moderate or greater symptom interference were more likely to report no longer working than their less effected counterparts (OR=8.0, p=0.002), as were minority participants compared to their non-Hispanic white counterparts (OR=3.2, p 6 months from diagnosis, off chemo- or radiotherapy) from the observational multi-site SOAPP study. Participants reported employment change due to illness, current employment and symptoms. Employment groups were defined based on self-reported employment at survey (working full or part-time vs not working) and whether there had been a change due to illness (yes vs 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 outcome and specific symptoms was examined. Results: Overall, 24% of the cohort reported a change in employment due to illness. On multivariable analysis, participants with moderate or greater symptom interference were more likely to report no longer working than their less effected counterparts (OR=8.0, p=0.002), as were minority participants compared to their nonHispanic white counterparts (OR=3.2, p 5) and the zero/mild level (0-4) for the analysis, based on cut-offs established for the MDASI.[17-20] In addition, cancer type, age, time from diagnosis, gender, race/ethnicity, and therapy were examined as covariates for employment group. We used generalized estimating equations to account for the intra-cluster correlation by institution.[21] Univariable and multivariable logistic regression analyses (via PROC GENMOD) with the exchangeable working correlation structure were performed to identify predictors for employment group. Any significant explanatory variable (p5) versus zero/mild (0-4). Among the 19 symptoms, 16 were identified with at least 10% of patients in one of the employment groups reporting moderate/severe level of that symptom. The univariable regression model was fitted to each of these symptoms. Due to multiple testing on these symptoms, Bonferroni correction was used to safeguard familywise error rate,. Symptoms with a p-value less than 0.003 were further included in the multivariable model along with the confounding patient characteristics, in order to identify the symptoms most associated with employment group. The best model was built by the stepwise forward selection of symptom predictors considering the QICu criterion measure (quasi-likelihood under the independence model information criterion). The model with the smallest QICu measure was preferred.[22] All p-values are twoPage 6 of 15
sided. A level of 5% was considered statistically significant unless specified otherwise. SAS 9.2 (SAS Institute, Cary, NC) was used for all data analyses.
RESULTS Employment Status and Changes. Table 1 shows the employment status based on reported change due to illness for the 530 participants in the cohort of interest. Among nonmetastatic participants no longer receiving active treatment and who were at least 6 months from diagnosis, 15% reported both undergoing change as well as no longer working due to illness (Group B). A further 9% reported change due to illness, but continued to work full or part-time (Group D). For Group D, the direction of change is not known (i.e. change from full-time to parttime versus change from not working to full-time or part-time). Nor is the nature of change (i.e., from a difficult job to an easier job or vice versa). As a whole, nearly one-quarter (24%) of the cohort reported some change in employment due to illness. Demographics. Table 2 presents detailed demographics and disease characteristics for the cohort of interest and the four employment groups. As a whole, the cohort was largely non-Hispanic white (76%), had breast cancer (75%), female (85%), and more than 2 years from diagnosis (61%). Median age was 56 yrs (range 18-65). More patients in Group A were non-Hispanic white (80 vs 56%) and over 2 years from diagnosis (67 vs 49%) than Group B (both p values < 0.005). Symptom Interference with Work. As shown in Table 3, fewer patients in Group A reported moderate or severe symptom interference than Group B (7% vs. 40%), p
