Retinal Thickness Analysis by Race, Gender, and Age Using Stratus OCT




Purpose


To detect differences in retinal thickness among patients of different race, gender, and age using Stratus OCT.


Design


Cross-sectional study.


Methods


In a multicenter, university-based study, 126 patients with no history of ocular disease were enrolled (78 diabetics without retinopathy and 48 nondiabetics). Optical coherence tomography measurements were performed using Stratus OCT. Statistical comparisons of center point foveal thickness and mean foveal thickness were made using generalized estimating equations adjusting for diabetic status, race, age, and gender.


Results


The study population consisted of 36% male subjects, 39% Caucasian, 33% African-American, and 28% Hispanic. Mean foveal thickness was 191.6 ± 2.7 μm and 194.5 ± 2.7 μm for diabetics and nondiabetics, respectively ( P = .49). Mean foveal thickness in male subjects was significantly larger than in female (201.8 ± 2.7 μm and 186.9 ± 2.6 μm, respectively; P < .001). Mean foveal thickness was 200.2 ± 2.7 μm for Caucasian, 181.0 ± 3.7 μm for African-American, and 194.7 ± 3.9 μm for Hispanic subjects. Mean foveal thickness was significantly less for African-American than Caucasian ( P < .0001) or Hispanic subjects ( P = .005). Center point foveal thickness and mean foveal thickness showed a significant increase with age.


Conclusions


There are statistically significant differences in retinal thickness between subjects of different race, gender, and age. When compared to Caucasian and Hispanic subjects, African-American race is a predictor of decreased mean foveal thickness; and male sex (regardless of race) is a significant predictor of increased mean foveal thickness. Mean foveal thickness is similar among diabetics and nondiabetics when data are controlled for age, race, and sex. These results suggest that studies comparing OCT measurements should carefully control for age-based, race-based, and gender-based variations in retinal thickness.


The Stratus OCT normative database reported by Fraser-Bell and associates (Fraser-Bell S, et al. IOVS 2005;46:ARVO E-Abstract 1542) suggests differences in retinal thickness based on age, gender, ethnicity, and refractive error; however, very few published studies have systematically attempted to establish a normative range of optical coherence tomography (OCT) measurements in healthy patients. Such a database is important for identifying and characterizing pathologic changes. Asrani and associates used a retinal thickness analyzer to measure retinal thickness in a small sample (n = 29) of normal patients. Their results suggested that race and gender have a small effect (<35 μm) on retinal thickness, but the authors found no correlation between retinal thickness and age. Wong and associates reported that a larger body mass index, higher axial length, and male gender were significantly correlated with increasing central retinal thickness as measured by Stratus OCT. A number of other small studies have suggested significant differences in retinal thickness between genders and among races. Recently, Kelty and associates showed that mean foveal thickness was greater in Caucasians than African Americans and greater in healthy males than in females.


One example of the impact of race and gender on OCT measurements may be in studies of retinal thickness measurements in diabetic patients with minimal or no diabetic retinopathy. Studies evaluating the retinal thickness in diabetic and nondiabetic patients have reported variable findings for unclear reasons. Using first-generation OCT, Hee and associates found no significant difference in mean foveal thickness between diabetics without retinopathy and nondiabetic controls. Lattanzio and associates showed that there is as much as 40 to 50 μm difference between diabetics without retinopathy and nondiabetic controls. Bressler and associates recently reported no difference in central subfield thickness on Stratus OCT among diabetics without retinopathy and nondiabetic patients without any ocular pathology. The variability in these findings suggests that factors such as race, gender, and age may affect retinal thickness in these study populations.


Currently, there are no reports of OCT-based retinal thickness measurements controlling for age, race, and sex simultaneously in a multiethnic population of Caucasians, African Americans, and Hispanics. In the present study, we report Stratus OCT measurements of retinal thickness in a population of diabetics and healthy patients stratified by race, gender, and age, and we analyze correlations based on these demographic data.


Methods


Patients were prospectively recruited from the diabetic screening clinics and private practices of individual investigators at the Wilmer Eye Institute and the Doheny Eye Institute, Los Angeles County/University of Southern California (LAC/USC) Hospital from October 1, 2005, through April 20, 2008. All patients were recruited with procedures, consents, and protocols approved by the Johns Hopkins University and University of Southern California Institutional Review Boards. Because relatively few diabetic patients without diabetic retinopathy are seen at tertiary care centers, we also recruited patients from diabetic screening examinations at both institutions. The patients seen for screening examinations at the LAC/USC and the Wilmer Eye Institute comprised referrals from physicians in the community specifically for evaluation of diabetic retinopathy. In many cases, these patients had no visual complaints and were only screened for diabetic retinopathy; they did not undergo a full ophthalmic examination. Among this population, only patients with no visual complaints and no clinical signs of diabetic retinopathy were referred for this study. Nondiabetic patients were recruited among volunteers or patients with normal examinations from the above-mentioned clinics. Nondiabetic patients were not required to be dilated for OCT scanning. For all patients, demographic data including age, sex, and race were recorded. All patients who were enrolled were self-identified as Caucasian, African-American, or Hispanic. Inclusion criteria included patients with unremarkable ocular histories or patients with diabetes but with no signs of diabetic retinopathy. Exclusion criteria included any visual complaint not corrected by refraction; self-reported history of ocular disease (other than ocular surface disease and mild refractive error), trauma, or surgery; or any findings suggestive of ocular pathology. Any patient with an abnormal fundus examination (including asymmetric cup-to-disc ratios greater than 0.2) was excluded to avoid enrollment of patients with clinically detectable glaucoma.


OCT scanning was performed using Stratus OCT (OCT3; Zeiss-Humphrey Systems, Dublin, California, USA) by experienced OCT operators. One or 2 scans were performed on each eye for each protocol. Only OCT scans with signal strength of 5 or greater were used for analysis. Analyses were performed employing Stratus OCT software for 6.0-mm scan protocols. In this paradigm, retinal thickness is the distance measured between the vitreoretinal interface and the junction between the inner and outer segments of the photoreceptors. The location of these boundaries is determined by a thresholding algorithm that detects changes in reflectivity at each of these interfaces. Retinal images were generated from 6 radial scans in a spoke-like pattern using the fast macular and macular thickness automated protocols. The fast macular scan compresses the 6 radial line scans of the 2000 OCT macular thickness mapping protocol into 1 scan that is obtained in 1.92 seconds. Each line scan consists of 128 A-scans; therefore, retinal thickness is measured at 768 points along 6 intersecting lines. This feature decreases the total acquisition time but sacrifices resolution. Where possible, higher-resolution macular thickness scans were obtained and used. Scan analysis was performed using the Stratus OCT hardware with the Zeiss commercial scan analysis software. We manually reviewed the retinal boundaries in 198 of the 756 line scans (26%) in the study to estimate the error rate of boundary detection by the automated software.


Center point foveal thickness and mean foveal thickness were the primary OCT parameters used for analysis. Overall, 11 OCT parameters (corresponding to 9 Early Treatment Diabetic Retinopathy Study areas, 1 measurement for center point foveal thickness, and 1 measurement for total macular volume) were tabulated and analyzed as shown in Table 1 . Mean foveal thickness refers to the average thickness of the retina across the entire fovea or central subfield. Center point foveal thickness refers to the thinnest point measured in the fovea. Secondary analyses included inner and outer retinal parameters as defined by standard Stratus OCT analysis software. Both eyes of all patients were scanned for the study. Statistical models were generated with generalized estimating equations controlling for the correlation between 2 eyes. The SAS 9.13 programming language (SAS Institute, Cary, North Carolina, USA) was used for all analyses.



TABLE 1

Retinal Thickness Analysis by Diabetic Status: Summary Data of Stratus OCT Parameters for Diabetic and Nondiabetic Patients
































































OCT Parameter Diabetic Nondiabetic P value a
Center point foveal thickness 157.8 ± 3.2 μm 156.9 ± 3.2 μm .86
Mean foveal thickness 191.6 ± 2.7 μm 194.5 ± 2.7 μm .49
Temporal inner macula 255.6 ± 1.9 μm 259.7 ± 2.4 μm .16
Superior inner macula 272.2 ± 2.1 μm 274.9 ± 2.1 μm .39
Nasal inner macula 269.3 ± 2.0 μm 273.3 ± 2.0 μm .18
Inferior inner macula 266.8 ± 2.0 μm 270.5 ± 2.5 μm .22
Temporal outer macula 221.0 ± 1.8 μm 222.7 ± 1.8 μm .54
Superior outer macula 240.7 ± 2.1 μm 242.3 ± 2.8 μm .64
Nasal outer macula 257.6 ± 2.2 μm 257.0 ± 2.2 μm .85
Inferior outer macula 230.3 ± 1.9 μm 229.3 ± 2.6 μm .75
Total macular volume 6.91 ± 0.06 mm 3 6.81 ± 0.11 mm 3 .50

a Generalized estimating equation (GEE), which adjusts for the correlation between eyes, was employed in the analyses. The Wald χ 2 P value is reported and means are given as least square mean ± SE. All models are adjusted for race, gender, and age group (categorized by decades: 20s, 30s, 40s, 50s, and 60+).





Results


Overall, the study population consisted of 126 patients, including 78 diabetics and 48 nondiabetics. The mean age of the diabetic patients and nondiabetic patients was 54 ± 11 and 41 ± 10 (years ± SD), respectively. The overall study population was 36% male and 39% Caucasian. The diabetic group was 32% male, 38% Caucasian, 36% African-American, and 26% Hispanic. The nondiabetic group was 42% male, 40% Caucasian, 29% African-American, and 31% Hispanic. Patient demographics are summarized in Table 2 .



TABLE 2

Retinal Thickness Analysis by Age, Race, and Gender: Population Demographics of Patients Enrolled in the Study a










































































Total Diabetic Nondiabetic
All races 126 78 (62%) 48 (38%)
Male 45/126 (36%) 25/78 (32%) 20/48 (42%)
Female 81/126 53/78 28/48
Caucasian 49 (39%) 30 (38%) 19 (40%)
Male 17/49 (35%) 8/30 (27%) 9/19 (47%)
Female 32/49 22/30 10/19
African-American 42 (33%) 28 (36%) 14 (29%)
Male 14/42 (33%) 9/28 (32%) 5/14 (36%)
Female 28/42 19/28 9/14
Hispanic 35 (28%) 20 (26%) 15 (31%)
Male 14/35 (40%) 8/20 (40%) 6/15 (40%)
Female 21/35 12/20 9/15
Mean age (years) 49 ± 12 54 ± 11 41 ± 10

a Percentages are given in parentheses. Where appropriate, ratios are provided adjacent to percentages to clarify the total.



Table 1 summarizes the mean OCT parameters for the diabetic and nondiabetic groups. In our data set, there was no difference in Stratus OCT retinal thickness parameters between diabetics and nondiabetics. The mean foveal thickness was 191.6 ± 2.7 μm in diabetics and 194.5 ± 2.7 μm in nondiabetics ( P = .49). Diabetes was not significantly correlated with any change in retinal thickness or volume after controlling for age, race, and gender. Only data for retinal thickness are shown since volumetric data are derived from polar approximations of line scans by the Stratus OCT.


Our data showed that male gender was a statistically significant predictor of increased mean foveal thickness and center point foveal thickness ( Table 3 ). Center point foveal thickness was 163.0 ± 3.0 μm for all male and 154.7 ± 2.5 μm for all female subjects ( P = .03). Similarly, mean foveal thickness was 201.8 ± 2.7 μm for all male and 186.9 ± 2.6 μm for all female subjects ( P < .001).



TABLE 3

Retinal Thickness Analysis by Gender: Summary Data of Stratus OCT Parameters for Male and Female Subjects



























































OCT Parameter Male (mean) Female (mean) P value a
Center point foveal thickness 163.0 ± 3.0 μm 154.7 ± 2.5 μm .03
Mean foveal thickness 201.8 ± 2.7 μm 186.9 ± 2.6 μm <.001
Temporal inner macula 263.1 ± 1.9 μm 250.9 ± 1.8 μm <.001
Superior inner macula 278.5 ± 1.8 μm 265.8 ± 2.1 μm <.001
Nasal inner macula 278.4 ± 1.9 μm 263.0 ± 2.1 μm <.001
Inferior inner macula 274.2 ± 2.1 μm 261.2 ± 2.0 μm <.001
Temporal outer macula 226.5 ± 1.8 μm 215.4 ± 1.7 μm <.001
Superior outer macula 244.5 ± 2.0 μm 236.1 ± 2.0 μm .003
Nasal outer macula 261.5 ± 2.2 μm 251.2 ± 1.9 μm <.001
Inferior outer macula 232.7 ± 2.0 μm 223.7 ± 2.3 μm .003

a Generalized estimating equation, which adjusts for the correlation between eyes, diabetic status, race, age, and gender, was used in the analyses. Errors are given as least square mean ± SE.



African-American race was significantly correlated with decreased mean foveal thickness and center point foveal thickness ( Table 4 ). Center point foveal thickness for African Americans was 147.2 ± 3.6 μm, which was significantly less than the center point foveal thickness for Caucasians (164.1 ± 2.8 μm; P < .0001) and Hispanics (161.5 ± 3.6 μm; P = .002). In addition, mean foveal thickness for African Americans was 181.0 ± 3.7 μm. This value was also significantly less than the mean foveal thickness for Caucasians (200.2 ± 2.7 μm; P < .0001) and Hispanics (194.7 ± 3.9 μm; P = .005). Across all races, male subjects had a tendency for thicker retinal measurements. The retinal thickness data for center point foveal thickness and mean foveal thickness demographic are summarized in Table 5 .



TABLE 4

Retinal Thickness Analysis by Race: Summary Data of Stratus OCT Parameters by Race



























































OCT Parameter African-American (mean) Caucasian (mean) Hispanic (mean)
Center point foveal thickness 147.2 ± 3.6 μm 164.1 ± 2.8 μm a 161.5 ± 3.6 μm a
Mean foveal thickness 181.0 ± 3.7 μm 200.2 ± 2.7 μm a 194.7 ± 3.9 μm a
Temporal inner macula 251.5 ± 2.5 μm 257.1 ± 2.4 μm 257.5 ± 2.6 μm
Superior inner macula 264.6 ± 2.8 μm 272.3 ± 2.6 μm 274.8 ± 2.9 μm
Nasal inner macula 262.7 ± 2.8 μm 271.9 ± 2.8 μm 270.8 ± 3.0 μm
Inferior inner macula 261.7 ± 2.8 μm 268.8 ± 2.7 μm 266.7 ± 2.6 μm
Temporal outer macula 217.8 ± 2.7μm 218.6 ± 2.1 μm 222.5 ± 2.4 μm
Superior outer macula 236.5 ± 3.0 μm 238.7 ± 2.4 μm 243.0 ± 2.9 μm
Nasal outer macula 251.9 ± 2.8 μm 256.3 ± 2.6 μm 256.8 ± 2.6 μm
Inferior outer macula 225.5 ± 2.8 μm 230.0 ± 2.5 μm 224.7 ± 3.8 μm

a Generalized estimating equation, which adjusts for the correlation between eyes, diabetic status, race, age, and gender, was used in the analyses. Please see text for P values. Errors are given as least square mean ± SE.



TABLE 5

Retinal Thickness Analysis by Sex: Retinal Thickness Values Between Male and Female Subjects of All Races Using Stratus OCT








































































Center Point Foveal Thickness Mean Foveal Thickness
Male
Caucasian 166.4 ± 4.2 μm 207.9 ± 3.7 μm
African-American 149.7 ± 4.5 μm 187.9 ± 4.7 μm
Hispanic 172.3 ± 5.7 μm 210.2 ± 4.1 μm
P value a
C-A .008 .001
C-H .41 .67
A-H .002 .0003
Female
Caucasian 162.1 ± 3.4 μm 196.0 ± 3.4 μm
African-American 144.1 ± 4.9 μm 176.6 ± 4.9 μm
Hispanic 154.4 ± 3.5 μm 184.4 ± 3.9 μm
P value a
C-A .002 .001
C-H .11 .02
A-H .08 .22

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Jan 17, 2017 | Posted by in OPHTHALMOLOGY | Comments Off on Retinal Thickness Analysis by Race, Gender, and Age Using Stratus OCT

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