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| ORIGINAL ARTICLE |
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| Year : 2013 | Volume
: 6
| Issue : 2 | Page : 92-95 |
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Selective laser trabeculoplasty: Does energy dosage predict response?
Larissa Habib1, James Lin1, Tamara Berezina1, Bart Holland2, Robert D Fechtner1, Albert S Khouri1
1 Institute of Ophthalmology and Visual Science, Rutgers New Jersey Medical School, Newark, NJ, USA
2 Rutgers New Jersey Medical School, Newark, NJ, USA
| Date of Web Publication | 19-Aug-2013 |
Correspondence Address:
Albert S Khouri
MD, Institute of Ophthalmology and Visual Science, 90 Bergen St., Suite 6100, Newark, NJ, 07103
USA
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/0974-620X.116635
 Abstract | | |
Background: Selective laser trabeculoplasty (SLT) is a widely used treatment for open angle glaucoma, producing sustained reductions of intraocular pressure (IOP). The aim of this study was to evaluate the long-term relationship between SLT energy dosage and IOP reduction.
Materials and Methods: A retrospective review was performed for patients receiving primary SLT therapy, with inclusion of subjects treated with 360° of SLT. Energy settings were collected upon treatment and IOP was collected at baseline up to 36 months. Pearson's correlation coefficient was used to determine whether there was a significant correlation between SLT energy and IOP reduction at all time points. Kaplan-Meier analysis with log-rank test was performed to determine the differences in IOP reduction ≥20% from baseline among those treated with low (<85 mJ), medium (85-105 mJ), and high (>105 mJ) energy SLT.
Results: A total of 104 eyes (75 patients) were included. The mean total SLT energy was 93.73 mJ (standard deviation (SD) = 21.83 mJ, range: 34.4-122 mJ). A significant positive correlation (P ≤ 0.05) between the amount of energy delivered and IOP reduction was found at all time points. Log-rank test showed a significant difference in IOP reduction ≥20% from baseline between the three energy groups, with low energy patients experiencing failure at an earlier time (P = 0.05).
Conclusions: Within the range of total energy examined, there is a positive correlation between total energy used and amount of pressure reduction achieved at up to 3 years of follow-up. This may be useful in determining the optimal energy dosage for maximum effect for patients receiving SLT. Keywords: Glaucoma, laser therapy, selective laser trabeculoplasty
How to cite this article:
Habib L, Lin J, Berezina T, Holland B, Fechtner RD, Khouri AS. Selective laser trabeculoplasty: Does energy dosage predict response?. Oman J Ophthalmol 2013;6:92-5 |
How to cite this URL:
Habib L, Lin J, Berezina T, Holland B, Fechtner RD, Khouri AS. Selective laser trabeculoplasty: Does energy dosage predict response?. Oman J Ophthalmol [serial online] 2013 [cited 2023 Mar 27];6:92-5. Available from: https://www.ojoonline.org/text.asp?2013/6/2/92/116635 |
| Introduction | |  |
Glaucoma is currently the second leading cause of blindness worldwide. [1] It is characterized by optic neuropathy associated with progressive visual field loss. Intraocular pressure (IOP) reduction is currently the only modifiable risk factor and is the mainstay of glaucoma treatment. [2] This can be achieved through topical medications, surgery, or laser therapy.
Selective laser trabeculoplasty (SLT) has been shown in numerous studies to be as effective as argon laser trabeculoplasty (ALT) and is considered repeatable. [3],[4],[5],[6],[7],[8] Although the exact mechanism of action of SLT is not yet fully elucidated, a relationship to an inflammatory process within the treated angle structures has been suggested. [9],[10],[11] This along with the minimal structural changes in trabecular meshwork (TM) induced by treatment may contribute to its repeatability. [12],[13] The relationship between the degree of inflammation and extent of IOP reduction has not been determined. In clinical practice, a range of laser energy is often used. Within that range, a higher total energy is expected to induce an enhanced inflammatory response compared with lower energy levels. If the induced inflammatory response is the main mechanism behind SLT efficacy, this could lead to a more effective drop in IOP. The purpose of this study was to test this hypothesis by determining the relationship between total SLT energy dose and IOP reduction.
| Materials and Methods | | |
Under a protocol approved by the University of Medicine and Dentistry of New Jersey Institutional Review Board, a retrospective review of patients with open angle glaucoma who underwent SLT for IOP reduction from 2006-2010 were identified from medical records at both the Institute of Ophthalmology and Visual Sciences at the University of Medicine and Dentistry of New Jersey and an affiliate site at the Hudson Eye Physicians and Surgeons in Jersey City, New Jersey. Any patient with a prior history of laser trabeculoplasty (ALT or SLT) or incisional glaucoma surgery was excluded. Patients who received repeat SLT were excluded (followed-up after initial SLT until the time of their retreatment). For uniformity of comparison, any SLT performed other than to 360° of angle was also excluded.
Data collected included age, sex, glaucoma diagnosis, and SLT parameters (number of spots and energy per spot). The parameters used for SLT were determined according to the discretion of glaucoma specialists. Total energy was calculated by multiplying the number of treatment spots by the energy per spot in millijoules (mJ). Endpoints included additional laser therapy and glaucoma surgery. The number of glaucoma medications and Goldmann IOP were collected at baseline (the visit prior to SLT) and post-SLT at 1, 4, 8, 12, 18, 24, and 36 months.
By using the response variable of ≥ 20% reduction in IOP from baseline, patients were divided into low (<85 mJ), medium (85-105 mJ) and high (>105 mJ) energy treated groups and compared by Kaplan-Meier analysis using the log-rank test. Demographic and baseline data were compared using one-way analysis of variance (ANOVA) testing.
Baseline data was further stratified by follow-up time and analyzed for means, standard deviation (SD), paired t-test for comparison of means, and Pearson's correlation coefficient between total SLT energy and IOP reduction from baseline. Correlation coefficient (r) was calculated at 1, 4, 8, 12, 18, 24, and 36 months. Statistical significance for all comparisons was set at P ≤ 0.05. A post-hoc power analysis was conducted based on the sample size of this study. Statistical analyses were performed using Stata 11.0 software (Stata Corporation, College Station, TX).
| Results | | |
A total of 104 eyes from 75 patients were included. Baseline characteristics of the patients stratified by energy group are shown in [Table 1]. Significant differences were seen in the number of glaucoma meds at baseline (P < 0.001), with those in the low energy group having a higher mean number of glaucoma medications at baseline. Those who were in the high energy group had a higher mean IOP at baseline (P = 0.03). The mean number of SLT treatment spots was 102 (SD = 15.2, range: 37-130), with the mean single spot energy of 0.88 mJ (SD = 0.14, range: 0.41-1.05 mJ). The mean total SLT energy was 93.73 mJ (SD = 21.83 mJ, range: 34.4-122 mJ). | Table 1: Baseline characteristics of patients stratified by energy group
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[Table 2] shows the number of glaucoma medications and reduction in IOP at each follow-up time point compared to baseline. When comparing number of glaucoma medications at each follow-up time to baseline, there was a statistically significant decrease in the number of medications at 1 month (P = 0.03). The IOP reductions from baseline were significant at all time points after SLT treatment (P < 0.05). | Table 2: Number of medications and IOP reduction from baseline at all time points
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[Table 3] shows that the correlation coefficients at all time points were positive (higher IOP reduction from baseline with higher total energy) and significant at 1, 4, 8, 12, 18, 24, and 36 months (P ≤ 0.05 for all time points). [Figure 1],[Figure 2] and [Figure 3] shows the correlation graphs corresponding to the time points of 12, 24, and 36 months, respectively. In a post-hoc analysis of power, we were able to detect correlations of r > 0.27. When stratified by energy dosage level into low, medium, and high; patients treated with medium and high energies were more likely to sustain a ≥ 20% reduction in IOP over time compared to those with low energy treatments (log-rank, P = 0.05) [Figure 4]. | Figure 1: Scatter plot with best fit line showing relationship between total energy and intraocular pressure reduction from baseline at 12 months
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 | Figure 2: Scatter plot with best fit line showing relationship between total energy and intraocular pressure reduction from baseline at 24 months
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 | Figure 3: Scatter plot with best fit line showing relationship between total energy and intraocular pressure reduction from baseline at 36 months
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 | Figure 4: Kaplan-Meier analysis for intraocular pressure reduction ≥20% compared by energy treatment group. Low energy (<85 mJ), medium energy (85-105 mJ), high energy (>105 mJ)
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 | Table 3: Correlation coefficients between total energy and IOP reduction from baseline at all time points
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| Discussion | | |
The question that our study answers is whether using higher laser energy levels within the clinically approved range leads to an increase in SLT efficacy. Since its introduction, SLT energy level selection has been based on theoretical reduction of histologic damage rather than a maximization of efficacy. Although the mechanism of SLT remains unclear, experiments by Alvarado et al., [9] have shown that activation of the TM cells by SLT causes the release of various cytokines that modulate the permeability of endothelial cells of Schlemm's canal. The activation of TM cells also causes release of matrix metalloproteinases that promote fluid flow across the extracellular matrix, increasing the overall rate of aqueous outflow. [12] It could be hypothesized that higher energy levels (within the clinically approved range) leads to enhanced activation of TM cells and therefore, a greater release of inflammatory mediators and cellular factors.
SLT uses a frequency doubled neodymium:yttrium-aluminum-garnet (Nd:YAG) laser to produce a green pulse (532 nm) with a duration of 3 ns. [10],[14],[15] The laser at the clinically approved range uses the process of selective photothermolysis to target the pigmented cells of the TM with minimal associated changes to surrounding adjacent nonpigmented cells. [14],[15] Although a range of energy can be utilized, it has been generally accepted to adjust the SLT energy level per spot at or just below the threshold of observing cavitation bubbles (or champagne bubbles) on the surface of TM. It remains to be determined, whether adjusting energy levels through the observation of champagne bubbles is associated with the optimal efficacy of SLT.
Another theory on the mechanism of SLT is that the inflammatory process in TM causes release of oxygen free radicals that spread and lead to low grade generalized inflammation. [13] It has been proposed that macrophages attracted to the areas of inflammation, engulf the cellular debris leading to an increase in aqueous outflow. [16] Because the efficacy of SLT has been clearly linked to inflammation, the amount of total energy used in SLT could influence the inflammatory response and hence laser efficacy.
In our study we found that up to 3 years of follow-up after SLT, a significant positive correlation existed between the total energy used and amount of pressure reduction achieved. The mean IOP reduction at all time points was statistically significant and consistent with previous studies. [10],[17] Kaplan-Meier analysis further demonstrated the beneficial effect of higher energy treatment. While average number of glaucoma medications was significantly decreased from 1 month post-SLT compared to baseline (2.03 ± 1.01 vs 1.88 ± 1.10, P = 0.03), the sustained positive correlation between energy dosage and IOP reduction up to 36 months was not likely to have been significantly influenced by any changes in mean number of glaucoma medications as indicated in [Table 2].
There have been few studies that have commented on the effect of energy dosing and efficacy. Ayala et al., [18] found a significant positive correlation between amount of laser energy used and time to failure. [18] Time to failure was defined as change in pharmaceutical treatment, the need for repeat SLT, or the need for further surgery. However, total energy was not considered in their analysis, but rather energy per spot. Furthermore, patients in that study were treated with 90° SLT in contrast to our patients that had 360° SLT. In another study by Song et al., [19] it was noted that within their cohort, successes had more treatment spots than failures. SLT parameters were not clearly defined in that study, making it difficult to compare with our results.
This study is limited by possible selection bias in the study population as both clinics serve referred patients with advanced glaucoma, with loss to follow-up over the 36-month period. Energy dosage was decided according to the physician's discretion, with our patients treated at total energy levels commonly used in clinical practice. However, there were fewer patients in the low energy range. The drop off in follow-up at 24 and 36 months is accounted for by Kaplan-Meier analysis that still showed a difference in SLT effectiveness depending on energy levels used in treatment [Figure 4].
Our results show that a significant positive correlation exists between SLT total energy and IOP response in this cohort of patients. This correlation was observed in those treated with 360° within the range of energy commonly used by clinicians. Most significantly this study highlights the need for a better understanding of relationship between SLT energy and efficacy through future prospective analyses. At present there is a paucity of data to support using a visible response (champagne bubbles) as the optimal indicator of delivering effective treatment. Our data indicates that higher total energy results in greater short and long term IOP reduction.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3]
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