Factors Predicting a Greater Likelihood of Poor Visual Field Reliability in Glaucoma Patients and Suspects

Abstract

Purpose: Identify factors predicting worse or better than expected visual field (VF) performance.

Methods: A total of 10,262 VFs from 1538 eyes of 909 subjects with manifest or suspected glaucoma were analyzed. Linear mixed-effects models predicted mean deviation (MD) at each timepoint. Differences between observed and predicted MD (ΔMD) were calculated and logistic regression identified factors predicting lower than expected (ΔMD <-1 dB) or higher than expected (ΔMD >1 dB) sensitivity.

Results: Both higher and lower than expected sensitivity were more likely in VFs with severe compared with mild damage (relative risk [RR] >1.3, P < 0.05). Higher than expected sensitivity was more likely in VFs with moderate damage (RR = 2.57, P < 0.001). False-positive (FP) errors increased the likelihood of higher than expected sensitivity at all disease stages (RR >2.1 per 10% increase, P < 0.001), whereas false-negative (FN) errors increased the likelihood of lower than expected sensitivity in mild and moderate disease (RR >1.19 per 10% increase, P < 0.05). Fixation loss errors slightly increased the likelihood of higher than expected VF sensitivity in moderate and severe disease (RR >1.1 per 10% increase, P < 0.01). Longer test duration increased likelihood of lower than expected sensitivity at all disease stages (RR >1.36 per minute increase, P < 0.001). Lower than expected sensitivity was more likely in late afternoon tests (RR = 1.27, P < 0.01). A total of 26.6% of VFs had higher or lower than expected sensitivity in the absence of FPs, FNs, or fixation losses.

Conclusions: FPs, test duration, and FNs are the primary measures predicting if a VF is likely to be reliable, although tests with normal reliability measures may still be unreliable. Our results help clinicians judge VF reliability and highlight the need to integrate reliability measures with other clinical data when making treatment decisions.

Translational relevance: This likelihood model derived from a large dataset helps clinicians identify VFs that may either falsely suggest disease progression or mask true worsening, thereby improving the utility of VFs in clinical practice.

Keywords: false negatives; false positives; fixation losses; visual field; visual field reliability.

Figure 1.

Depiction of the difference in measured versus predicted MD and identification of visual fields with higher than expected and lower than expected sensitivity. (A) Schematic shows how ΔMD was calculated. The predicted MD at each time point was calculated using a mixed-effects linear regression model using the set of input variables listed in Supplementary Table S1. The ΔMD was obtained by subtracting the predicted MD from the observed MD at that point (ΔMD = MD_observed – MD_predicted). (B) Visual fields with lower than expected sensitivity were those in which the observed MD was worse than predicted (ΔMD <−1), whereas VFs with higher than expected sensitivity were those in which the observed MD was better than predicted (ΔMD >1). (Figure adapted from Yohannan et al.⁵)

Figure 2.

Influence of false positives, false negatives, fixation losses, and test duration on the likelihood of lower or higher than expected visual field sensitivity across the range of observed values. (A) False positives decrease the likelihood of a lower-than-expected sensitivity at all stages of disease severity. (B) False positives also increase the likelihood of a higher-than-expected sensitivity at all stages of disease severity. (C) False negatives increase the likelihood of a lower-than-expected sensitivity in mild and moderate disease. There was no significant effect in severe disease (P > 0.05). (D) False negatives have no significant effect on the likelihood of higher-than-expected sensitivity (P > 0.05). (E) Fixation losses slightly decrease the likelihood of lower-than-expected sensitivity in early disease. There was no significant effect in moderate and severe disease. (F) Fixation losses have a mild effect on the likelihood of higher-than-expected sensitivity in moderate and severe disease. (G) Longer test duration increases the likelihood of a lower-than-expected sensitivity at all disease stages. (H) Longer test duration decreases the likelihood of a higher-than-expected sensitivity at all stages of disease severity.