Discussion
Using an automated pipeline for EHR data extraction, we retrospectively examined 800 eyes that underwent AGI-FP7, BGI-250 or BGI-350 implantation, finding remarkably similar failure rates (30%, 39% and 33%, respectively, p=0.159) and performance at 1-year despite differences in patient characteristics at baseline.
While other studies have examined outcomes following tube shunt implantation, some do not differentiate between BGI-250 and BGI-350,24–26 or compare AGI-FP7 to BGI-350 only,27–29 or in one instance (Kilgore et al23) do compare the AGI-FP7/BGI-250/BGI-350 implants separately but are limited by population homogeneity and inclusion of multiple eyes per patient without statistical correction, which may confound effects. These studies also vary in success/failure definitions. Our study, therefore, supplements this literature with data from a large, diverse population comparing the three most-used implants and a pipeline for data extraction and analysis that can be used in the future to continually provide surgeons with information on their outcomes.
Comparing our results to the 1-year pooled ABC trial data,14 which used an IOP>21 mm Hg cut-off for failure, we find higher failure rates (26% in our study vs 16% in ABC for AGI-FP7; and 29% vs 14% in BGI-350). However, the AVB trial30 used an IOP>18 mm Hg cut-off and reported failure rates higher than ours in the case of AGI-FP7 (43% in AVB vs 30% in our study) but not BGI-350 (28% vs 33%). The reasons for failure also differed, with VA loss being the largest contributor in our study, whereas high IOP was the most common reason for failure in both the ABC14 and AVB30 trials. This variability largely stems from differences in success/failure definitions. Our study defined VA loss as ≥3 lines lost, while the trials used the more conservative loss of light-perception as their criterion. However, when looking at the trials’ secondary VA outcomes, we find similar rates of VA loss in our study. The higher rates of VA loss in the BGI groups compared with the AGI-FP7 group may be due to the worse baseline VA of the latter, potentially creating a ‘floor’ effect for VA loss, while BGI patients had more initial VA to lose.
Another study that contextualises our work is Kilgore et al’s23 report on outcomes following AGI-FP7, BGI-250 and BGI-350 implantation. There, they also find the three implants to have similar failure rates, but contrary to our study, do not find differences in postoperative IOP between groups. They report month 12 mean IOP of 12.6, 11.6 and 13.3 mm Hg (p=0.327) in AGI-FP7, BGI-250 and BGI-350, respectively, compared with 14.8, 13.1 and 12.4 mm Hg (p=0.002) for the same groups in our study, perhaps reflecting a difference in patient selection/populations at baseline. Notably, their study population is 95% white compared with 43% in this study.
The ABC/AVB trials did not look at the proportion of patients meeting their target IOP, which is an important indicator of success. In this study, 71% of AGI-FP7, 66% of BGI-250 and 76% of BGI-350 eyes were in their target range by month 12. Neither the trials nor other retrospective studies examining glaucoma drainage devices, to our knowledge, have looked at the number of postoperative glaucoma clinic visits. We reasoned that this information may be useful to surgeons when counselling their patients regarding what to expect postoperatively. Indeed, we found both BGI groups to have significantly more postoperative visits, which may be due to the non-valved nature, and therefore, delayed IOP lowering effects secondary to suture dissolution of the Baerveldt implants requiring closer follow-up,31 32 or a difference in patient populations between groups at baseline.
With regard to those differences at baseline and possible confounders, AGI-FP7 patients were far more likely to be LTFU. This, in conjunction with the characteristics of those LTFU (younger age, more non-white race, more Hispanic, worse VA and more secondary glaucoma diagnoses) may reflect underlying social determinants of health and correspondingly more medically complicated patients who face barriers in accessing care.
The differences in age, race, ethnicity, diagnosis and baseline ocular characteristics between groups in our study may additionally reflect surgeon preferences and differences in indications between patients. For example, valved AGI shunts may be deliberately selected for patients who need rapid IOP lowering.14 17 31 Indeed, our data are consistent with this indication, as mean preoperative IOP was higher in the AGI-FP7 group but fell rapidly in the immediate postoperative period.
While rates of return to the OR within 12 months did not differ between groups, the proportion of procedures did. BGI-250 patients were more likely to undergo a trabeculectomy/repeat tube shunt or revision than both the AGI-FP7 and BGI-350 groups. We speculate that these findings may be related to the preoperative characteristics of these patients which led their physician to place the BGI-250, such as stage of glaucoma and IOP target or other characteristics, but we cannot exclude plate size as a possible contributor.
With regard to plate size, BGI-250 and BGI-350 performed remarkably similarly in this study. Their baseline patient characteristics, failure rates and secondary outcomes largely did not differ. However, only the BGI-350 group had a lower mean IOP when compared with AGI-FP7 (12.4±4.4 vs 14.8±5.6, p=0.003), while the BGI-250 found no difference (13.1±4.6, p=0.074). The mean IOP at month 12 did not differ between the two BGI groups, which is consistent with previous data.33 Rate of hypotony also only differed between BGI-250 and AGI-FP7 (8% vs 2%, p=0.041), but not in any of the other pairwise comparisons, which may be a due to the non-valved nature of the BGI implant, though it is unclear why the same effect is not true for the BGI-350 group. Ultimately, our study is limited by its retrospective nature with differences between groups that could not be controlled for.
Among other limitations of our study is the reliance on EHR for automated data extraction. Data not entered in specific fields could not be reliably extracted, resulting in more missing values than if charts were manually reviewed. Prior surgical history was also limited to data extracted during the study period, leaving open the possibility that patients could have had prior procedures that were not accounted for in our study. Moreover, surgeon preference and surgical variations such as ripcord and ligature versus ligature alone, method for venting prior to ligature opening and size of ligature suture, among others, all present additional confounders. Our study is also limited by its retrospective cohort nature, with important differences in patient characteristics at baseline. Lack of statistical significance may also not reflect a lack of clinical significance. Furthermore, indication bias is certainly present here as patient characteristics between groups differed substantially. We also cannot be sure if other factors associated with outcome played a role in surgical decision-making, which is a limitation of all retrospective studies. Defining the baseline visit as the one closest to and prior to the procedure may also present important confounders when certain patients require more emergent surgery than others, such as in the case of acutely elevated IOP. True baselines would have to be determined by averaging historical data for each patient. Moreover, data for social determinants of health, disease course/severity, comorbidities, and surgical complications were not recorded and may present possible confounders. Hypotony was also limited to an IOP cut-off rather than clinical diagnosis, though this is consistent with the ABC/AVB trials and other retrospective studies.14 23 30 Glaucoma medication use was also not assessed.
Taken together, while indications and baseline characteristics differed between those receiving AGI-FP7, BGI-250, or BGI-350 implants, these findings reflect real-world practice patterns and demonstrate remarkably similar outcomes at 1 year after surgery. Our largely automated data extraction and analysis using the EHR will also facilitate future comparisons between other surgeries/devices and reanalyses of cohorts with longer-term outcome data.