Cases described as 'well differentiated' were assigned grade 1; 'moderately differentiated,' grade 2; 'poorly differentiated,' grade 3 and 'ungraded (including grade Gx and missing data),' grade unknown.
Cases described as 'well differentiated' were assigned as grade 1; 'moderately differentiated' as grade 2; 'poorly differentiated and undifferentiated' as grade 3, and 'ungraded (including grade Gx and missing data),' grade unknown.
To account for missing data on grade, morphology and deprivation quintile, multiple imputation using chained equations (ICE) was employed [ 25, 26].
For all regression analyses, we used multiple imputation using chained equations (ICE) to account for missing data on grade and deprivation quintile [ 18, 19].
We used multiple imputation using chained equations (ICEs) to account for missing data on grade, morphology and deprivation quintile (Table 1; Royston, 2005; Nur et al, 2010).
Of the 1,996 participants excluded, 125 had died between phase 1 and phase 3 and 1,871 were nonrespondents or had missing data on employment grade.
Although there is only a small proportion of cases with missing histology and stage at diagnosis data, 28%and55%5% of live and deceased non-responders versus 17% of responders have missing data for tumor grade.
Findings related to prostate cancer outcomes have been reported previously, including area-level predictors of prostate cancer stage at diagnosis and tumor histologic grade [11], predictors of missing data on staging and grade in registry cases [12], and geographic clustering of tumor and other prostate cancer characteristics [15], [35] [36].
We estimated the hazard ratios for breast cancer specific death using Cox regression implemented in a multiple imputation framework to deal with missing data on stage and grade (Table 3).
For our example, this might occur if the pattern of missing data were related to the grade.
Percentages of other missing data on tumor size, tumor grade and LN involvement were 15.0%, 20.4% and 3.0%, respectively.
