90 Chapter 5 physicians use the Dutch Classification of Occupational Health and Social Insurance (CAS) to categorize diagnoses, derived from the International Statistical Classification of Disease and Related Health Problems (ICD-10) [32]. For generalizability, the primary, secondary, and tertiary (when available) CAS diagnoses were recoded to the 22 chapters of the ICD-10 disease groups. Multimorbidity (yes/no) was defined as having one or more additional diagnosis from a different ICD-10 disease group than cancer. Statistical methods First, descriptive statistics were used to gain insight into the number of applicants with a primary diagnosis of cancer and with or without residual work capacity. Differences between applicants with and without residual work capacity were compared using t-tests for continuous data and chi2 tests for categorical and ordinal data. Only specific cancer diagnosis groups including more than 40 applicants were included in the analyses. Second, within the applicants with residual work capacity and complete data on all variables, the prevalence and degree of inability to work fulltime were studied for the total group and for each specific cancer diagnosis group. Third, univariable and multivariable logistic regression analyses were performed to study the association of each socio-demographic variable (age, gender, and educational level) and disease-related variable (cancer group and multimorbidity) with no residual work capacity (yes/no) and the inability to work fulltime (yes/no). Analyses on the ability to work fulltime also included educational level. Fourth, univariable and multivariable logistic regression analyses (adjusted for age, gender, multimorbidity, and educational level for the analyses on inability to work fulltime) were performed to study the association of the specific cancer diagnosis groups with no residual work capacity and inability to work fulltime. Fifth, multivariable logistic regression analyses were performed, stratified to the cancer diagnosis groups including more than 100 applicants (to have enough power), to study the association of each socio-demographic variable (age, gender for no residual work capacity, and additionally educational level for inability to work fulltime) and disease-related variable (multimorbidity) with no residual work capacity and inability to work fulltime within the specific cancer diagnosis groups. Analyses were performed using IBM SPSS Statistics version 25. For all analyses, a p-level of < 0.05 was considered to indicate statistical significance.
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