A Joint Bayesian Longitudinal Model for Macular Structure-Function Correlations in Glaucoma.

PURPOSE

To investigate global longitudinal structure-function (SF) relationships between macular ganglion cell complex (GCC) thickness and central visual field (VF) mean deviation (MD) rates of change using a Bayesian joint bivariate longitudinal model.

DESIGN

Prospective cohort study.

PARTICIPANTS

One hundred seventeen eyes from 117 patients with glaucoma with central damage or moderate to advanced glaucoma were included. Eligible patients had at least 4 visits over a follow-up period of 2 years or longer.

METHODS

Longitudinal GCC thickness was assessed using optical coherence tomography, and central VF MD was measured with 10-2 standard automated perimetry. A Bayesian joint bivariate longitudinal model was used to estimate random intercepts, slopes, and residual standard deviations (SDs) for structural and functional measures and their correlations. A simulation study compared the Bayesian model (BM)'s performance against simple linear regression (SLR) in estimating these correlations.

MAIN OUTCOME MEASURES

Correlations between GCC and MD intercepts, slopes, and residual errors.

RESULTS

The mean baseline MD was -8.3 (SD: 5.2) decibels, with an average follow-up period of 5.0 (SD: 0.9) years. The mean correlation was 0.47 (95% credible interval: 0.32 to 0.61) for GCC-MD intercepts (baseline values), 0.29 (95% credible interval: 0.04 to 0.52) for GCC-MD slopes (rates of change), 0.20 (95% credible interval: -0.06 to 0.44) for GCC-MD log residual SDs, and 0.060 (95% credible interval: -0.013, 0.132) for the observation-level GCC-MD residual correlation. The BM consistently demonstrated a smaller root mean squared error than SLR in estimating GCC-MD slope correlations in all simulated scenarios where GCC-MD residual correlation differed from GCC-MD slope correlation.

CONCLUSIONS

The Bayesian joint model improved accuracy and reduced uncertainty in estimating SF relationships compared to SLR. Correlations between global SF rates of change were significantly positive, although weaker than random intercept correlations. This model represents a key step towards developing local longitudinal SF models to enhance glaucoma progression monitoring.

FINANCIAL DISCLOSURES

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.