Assessment of Missing Data on Glaucoma Severity Among Participants in the NIH All of Us Research Program of the United States.

PRCIS

There were statistically significant differences across multiple socioeconomic characteristics and self-reported barriers to care among primary glaucoma patients with severity staging data versus those missing this data in the NIH All of Us database.

PURPOSE

To characterize missing data among glaucoma patients within All of Us .

MATERIALS AND METHODS

We used diagnosis codes to define cohorts of primary glaucoma patients with and without severity staging specified. Descriptive analyses were conducted by presence of disease severity stage. Analysis of missing data was conducted using a set intersection plot and the Little Test of Missing Completely at Random. T tests were performed to evaluate differences.

RESULTS

Of 2982 participants, 1714 (57%) did not have glaucoma severity stage specified, and 11 of 23 analyzed variables had missing data. The Little Test indicated data was not missing completely at random ( P <0.001). Significant differences existed between the 2 cohorts with respect to age, age of first glaucoma diagnosis, gender, ethnicity, education, income, insurance, history of glaucoma surgery and medication use, and answers regarding the ability to afford eyeglasses and having seen an eye care provider in the last 12 months (all P- values ≤0.01).

CONCLUSION

There were significant differences between glaucoma participants with glaucoma severity stage specified versus those with unstaged disease across multiple socioeconomic characteristics and self-reported barriers to care. Glaucoma severity staging data was not missing completely at random. The unstaged cohort included higher rates of multiple underrepresented communities, which may potentially contribute to bias in ophthalmology research as participants from vulnerable populations may be disproportionately excluded from electronic health records or claims data studies where diagnosis codes with severity/staging levels are used to examine risk factors for disease, progression, and treatment efficacy.