To identify factors that influence visual and anatomic response to treatment with intravitreal anti–vascular endothelial growth factor (VEGF) for neovascular age-related macular degeneration (AMD).
Observational cohort study.
Seventy-two patients were included in this study. Best-corrected Snellen visual acuity (VA) and central foveal thickness measured on optical coherence tomography (OCT) at time of treatment and post-treatment follow-up visits were recorded. Associations between demographic, behavioral, and genetic risk factors and the 2 outcomes were analyzed using mixed-effects linear regression models. Two loci in complement factor H ( CFH ) were included in a risk score to determine the association between CFH risk and improvement in VA and central foveal thickness.
There was a small improvement in VA following anti-VEGF treatment (mean: 3.7 ± 3.0 letters), which was not statistically significant. Significant improvement in VA was observed for the nonrisk CFH Y402H genotype ( P < .001) and for a low CFH risk score ( P = .019). Regarding the outcome of change in central foveal thickness, improvement was noted in all genotype groups, but reduction after treatment was significantly higher in the low CFH risk score group ( P = .033). A significant improvement in mean VA was seen among smokers ( P < .001), but this relationship was not observed for central foveal thickness.
After anti-VEGF therapy, significant improvement in VA was observed for low-risk CFH genotypes and subjects with a low risk score. There was a statistically significant reduction in central foveal thickness overall, and subjects with a low CFH risk score improved more than the high-risk group.
Prior to the advent of anti–vascular endothelial growth factor (VEGF) treatment, neovascular age-related macular degeneration (AMD) was a leading cause of irreversible vision loss in people over age 50 in the western world. Pivotal trials such as the Minimally Classic/Occult Trial of the Anti-VEGF Antibody Ranibizumab in the Treatment of Neovascular AMD (MARINA) and Anti-vascular endothelial growth factor Antibody for the Treatment of Predominantly Classic Choroidal Neovascularization in Age-related Macular Degeneration (ANCHOR) confirmed the efficacy of ranibizumab and subsequent studies, such as the Comparison of AMD Treatments Trial (CATT), demonstrated that the use of bevacizumab yielded similar visual acuity (VA) and anatomic outcomes when comparing identical treatment regimens. Despite the overall success of anti-VEGF medications, in clinical practice there are variations in response to these drugs among individuals. Differences in relative improvement in vision, decrease in intraretinal and subretinal fluid, and length of effect of the drug in each patient have led to a variety of proposed treatment regimens, aiming to minimize treatment burden and cost while still maintaining maximum potential benefits.
Several reports have identified genetic as well as modifiable risk factors, including body mass index (BMI) and smoking history, as contributors to increased susceptibility to development and progression to neovascular AMD. There are numerous confirmed genetic variants implicated in the development of neovascular AMD. It has been proposed that these same genetic and behavioral risk factors may contribute to varying responses to treatment with anti-VEGF. This hypothesis that underlying genetic susceptibility can modify treatment responsiveness has gained considerable attention, with recent reports suggesting that the effects of antioxidant and zinc supplements on rate of progression of AMD vary according to genotype, although reports are inconsistent. Many studies have also been conducted to assess associations between some of these factors and response to treatment after anti-VEGF agents. Despite the growing body of literature on this subject, results are conflicting and it is difficult to contrast studies. Methods and outcome measures differ, and there is no uniform consensus on the definition of good and poor response. There are a limited number of studies on the effect of behavioral or demographic factors on response to treatment, and these also have conflicting results.
At the time of this study, we reviewed existing literature on genetic and behavioral influences that affect response to treatment with intravitreal anti-VEGF medication for neovascular AMD, and we employed methods of analysis that may be used for future studies with similar aims. Unlike some previously published reports, we analyzed behavioral and demographic characteristics as well as several recently reported genetic loci. The impact of the various factors individually as well as the combined effect of potentially predictive genetic and behavioral characteristics on response to anti-VEGF therapy were assessed.
A retrospective chart review was conducted for 220 patients from a single institution (New England Eye Center, Boston, Massachusetts, USA) who had been concurrently or previously enrolled in genetic and epidemiologic studies of the etiology of AMD, and who were diagnosed with neovascular AMD. This research adhered to the tenets of the Declaration of Helsinki and was performed under appropriate institutional review board protocol from the New England Eye Center and Ophthalmic Epidemiology and Genetics Service at Tufts Medical Center. Signed informed consent was obtained from all subjects.
Seventy-two subjects with subretinal or intraretinal fluid on optical coherence tomography (OCT) at the time of first injection were included in this analysis. The remaining patients were excluded as follows: (1) another treatment for neovascular AMD was given within 3 months prior to the first injection with bevacizumab or ranibizumab (n = 17); (2) there was no history of treatment with bevacizumab or ranibizumab (n = 24); (3) injections were given at another institution during the first 12 months of treatment (n = 31); (4) no intraretinal or subretinal fluid was seen on OCT at the time of first injection (n = 13); or (5) a subject had incomplete data at the time of any treatment or follow-up visit, or less than 12 months follow-up (n = 53). Only the first eye treated with anti-VEGF intravitreal injection was included in the analysis. Best-corrected Snellen VA and central foveal thickness as measured by OCT imaging, performed on either the Stratus or Cirrus OCT (Carl Zeiss Meditec, Inc, Dublin, California, USA), were recorded for each visit in which treatment was received, and each post-treatment follow-up visit for a period of 1 year, as well as at 6-month and 12-month visits. Central foveal thickness measurements were recorded as the central value on the retinal thickness map, calculated by standard OCT retinal mapping software. Diagnosis of neovascular AMD was made by a retina specialist on the basis of a dilated fundus examination, OCT findings, color fundus photography, and fluorescein angiography. Initial and subsequent anti-VEGF treatments were given at the discretion of the treating physician, and were based on VA, a dilated fundus examination, and OCT results during follow-up visits. Demographic (age, sex, and education) and behavioral (BMI and smoking history) data were also evaluated. Genotypes were derived from genotyping and sequencing platforms as previously described. The following AMD-related genes were assessed as risk factors in these analyses: CFH , CFB , C3 , CFI , VEGFA , TGFBR1 , LIPC , ABCA1 , CETP , APOC1/APOE , TNFRSF10A , SLC16A8 , COL8A1 , COL10A1 , ARMS2/HTRA1 , RAD51B , DDR1 , ADAMTS9/ADAMTS9-AS2 , and HSPH1/B3GALTL .
A PubMed search using the terms “age related macular degeneration genetic response to treatment” was conducted at the time of the study. English language research articles assessing the association between genetic variables and response to intravitreal anti-VEGF treatment that were available before October 16, 2014 were included in the review. A Google Scholar search was also conducted using the same terms and inclusion criteria. Review or meta-analysis articles, as well as those that did not evaluate genetic risk factors, were not included. Details of these studies are included in Supplemental Table 1 (Supplemental Material available at AJO.com ).
VA measurements at baseline, 6 months, and 12 months were assessed. OCT central foveal thickness measurements were analyzed at baseline and either 6 or 12 months follow-up. Snellen VA was transformed to logarithm of the minimal angle of resolution (logMAR) units by the following calculation: log (VA)/20. Means and standard deviations of log (VA)/20 and OCT central foveal thickness were calculated for each time point. Higher mean values of log (VA)/20 were indicative of worse VA. Mean change and standard error using Early Treatment Diabetic Retinopathy Study (ETDRS) acuity in letters were also calculated.
Longitudinal analyses were conducted to examine the association between demographic, behavioral, and genetic factors and change in VA and central foveal thickness measurements after anti-VEGF treatments. The associations between risk factors and the 2 outcomes over time were analyzed using mixed-effects linear regression models. Improvement in these outcomes was assessed based on slope, or change over time. A negative slope indicates improvement over time, a positive slope indicates worsening, and a slope of zero is equal to no change. Statistical significance was assessed using standard P values and P values for heterogeneity ( P het ). P values were obtained to assess whether the change for each level of a variable was significantly different from zero (ie, no change) for both VA and central foveal thickness. P het assessed whether the change over time for distinct levels within one particular risk factor significantly differed from each other for a particular outcome.
Changes in VA and central foveal thickness over time were also evaluated according to risk score category. These analyses used an externally derived and previously calculated composite score to assess risk of progression to advanced AMD. The risk score was calculated using regression coefficients of all demographic, behavioral, genetic, and ocular factors. The hazard ratio for the ith subject is given from the Cox proportional hazards model by <SPAN role=presentation tabIndex=0 id=MathJax-Element-1-Frame class=MathJax style="POSITION: relative" data-mathml='λi=exp∑j=1Jβjxij,’>λi=exp(∑Jj=1βjxij),λi=exp∑j=1Jβjxij,
λ i = exp ∑ j = 1 J β j x i j ,
where β j is the regression coefficient for the jth variable and x ij is the value of the jth variable for the ith subject. The variables included in the score are as follows: 10 genetic loci, age, sex, education, BMI, and smoking status. The low-risk category was defined as less than the median score, and the high-risk category was defined as greater than or equal to the median risk score.
A risk score for complement factor H ( CFH ) was calculated using the number of risk alleles for selected single nucleotide polymorphisms (SNPs). The score was composed of rs1061170 and rs1410996, with subjects having 0–4 risk alleles for these selected CFH variants. Groups for each score were classified as low risk (0–2 risk alleles) or high risk (3–4 risk alleles).
We also calculated similar risk scores for complement factor I ( CFI) , as variants in CFI have been implicated as potentially related to outcome after lampalizumab treatment in a small study (Regillo CD. Lampalizumab [anti-factor D] in patients with geographic atrophy: the MAHALO phase 2 results. Paper presented at the 2013 Annual Meeting of the American Academy of Ophthalmology, November 16-19, 2013, New Orleans, LA.). The CFI risk score comprised the number of risk alleles for CFI rare variants (0–2). The common CFI variant, rs10033900, was also evaluated based on number of risk alleles (0–2). CFI risk was classified as low or high risk by the number of risk alleles present (0 and 1–2, respectively).
As this study is considered exploratory, multiple comparisons and interactions between risk factors were not assessed. All analyses were conducted using SAS 9.3 (SAS Institute, Inc, Cary, North Carolina, USA). The alpha level for statistical significance was set a priori at P < .05.
Table 1 shows VA measurements at baseline, 6 months, and 12 months for selected demographic, behavioral, and genetic risk factors. The overall mean change in VA from baseline to 12 months was −0.2 logMAR units, which is an improvement of 3.65 letters over 1 year. This change, however, was not statistically significant. A greater improvement in mean VA over time was observed in the 55- to 70-year-old age group, among male subjects, and among ever smokers (current and past smokers). Improvement was also exhibited by subjects carrying the nonrisk genotype (TT) for CFH Y402H. Specifically, subjects with the TT genotype improved by 22.0 ± 6.6 letters, whereas there was no significant change in the other 2 genotype groups. Similar results were obtained for CFH rs1410996. No significant trend relating improvement in VA to the number of risk alleles for other AMD SNPs was apparent ( CFB , C3 , CFI , VEGFA , TGFBR1 , ABCA1 , CETP , APOC1/APOE , TNFRSF10A , COL8A1 , COL10A1 , ARMS2/HTRA1 , RAD51B , DDR1 , ADAMTS9/ADAMTS9-AS2 , HSPH1/B3GALTL ). Some differences in response were noted for LIPC and SLC16A8 , but these differences were not statistically significant.
|Variable||VA (LogMAR ) a at Baseline||Change in VA From Baseline to 6 Months||Change in VA From Baseline to 12 Months||Change in-ETDRS b VA from Baseline to 12 Months|
|N c||Mean||Standard Deviation||Mean||Standard Deviation||Mean||Standard Deviation||Mean||Standard Error|
|≤ High school||22||1.7||1.1||0.002||0.8||0.2||1.2||−3.4||5.4|
|> High school||46||1.7||1.0||−0.2||0.9||−0.3||1.1||7.2||3.4|
|Body mass index|
|Genetic variables/pathways d|
|CFH : rs1061170 (Y402H)|
|CFH : rs1410996|
|CFB : rs541862|
|C3 : rs2230199 (R102G)|
|CFI : rs10033900|
|VEGFA : rs943080|
|TGFBR1 : rs334353|
|LIPC : rs10468017|
|ABCA1 : rs1883025|
|CETP : rs3764261|
|APOC1/APOE : rs4420638|
|TNFRSF10A : rs13278062|
|SLC16A8 : rs8135665|
|COL8A1 : rs13095226 (P195L)|
|COL10A1 : rs1064583|
|ARMS2/HTRA1 : rs10490924 (A69S)|
|RAD51B : rs8017304|
|DDR1 : rs3094111|
|ADAMTS9/ADAMTS9-AS2 : rs6795735|
|HSPH1/B3GALTL : rs9542236|