Cost-Offset Analysis: Bimatoprost Versus Other Prostaglandin Analogues in Open-Angle Glaucoma

Objectives:

To develop a cost-offset model from a US payer perspective comparing glaucomatous progression and costs among primary open-angle glaucoma (POAG) patients using bimatoprost, latanoprost, or travoprost.

Study Design:

Cost-offset model.

Methods:

A Markov cohort model was used to estimate glaucomatous progression for POAG patients over 7 years. The model assumed bimatoprost-treated patients had lower resulting intraocular pressure (IOP) (by 1 mm Hg) for all presenting IOP categories than latanoprost- or travoprost-treated patients. Patients with lower IOP were assumed to have lower probability of progression. Those that progressed were assumed to do so at a rate of —0.6 dB per year. Direct costs associated with mean deviation score categories were applied to each treatment cohort to calculate the expected 7-year costs of treating patients with each prostaglandin analogue (PGA). Literature was used to support assumptions. A budget impact analysis was conducted where all travoprost patients switched to generic latanoprost and where all bimatoprost patients switched to generic latanoprost. The base case market share was 22% bimatoprost, 23% travoprost, and 55% latanoprost.

Results:

Model results demonstrate that for a managed care plan with 9500 PGA-treated glaucoma patients, exclusive bimatoprost use would prevent progression in 136 additional individuals compared with exclusive travoprost or latanoprost treatment. Model results demonstrate that greater IOP reduction from bimatoprost is associated with increased cost savings compared with latanoprost or travoprost treatments.

Conclusions:

Model results demonstrate that greater IOP reduction from bimatoprost could reduce managed care spending.

(Am J Manag Care. 2011;17(9):e365-e374)

Greater intraocular pressure (IOP) reduction with bimatoprost is associated with cost savings compared with treatment with latanoprost or travoprost.

• In a health plan with 9500 prostaglandin analogue—treated glaucoma patients, exclusive bimatoprost use would prevent progression in an estimated 136 incremental patients over 7 years compared with exclusive travoprost or latanoprost treatment.

• Exclusive treatment with bimatoprost would generate cost savings from reduced resource utilization estimated at $4009 per avoided progression of early glaucoma and $4543 per avoided progression of advanced glaucoma over 7 years.

• Cost benefits of lower IOP provide incentive for health system—level policies to promote bimatoprost use.

More than 2 million people in the United States 40 years and older have glaucoma.¹ Primary open-angle glaucoma (POAG) is the most common form of the disease. While there are numerous risk factors associated with glaucoma progression,^2-4 intraocular pressure (IOP) is one of the only known modifiable risk factors that can be controlled to prevent progressive optic neuropathy.⁵

The incidence of glaucoma is expected to rise with the continued growth of the elderly population and is a leading cause of preventable blindness in the United States.⁵ Glaucoma costs the healthcare system an estimated $2.9 billion annually in direct medical expenditures.⁶ An analysis using a Markov model to replicate health events over the remaining lifetime of someone newly diagnosed with glaucoma estimated that the cost of care for people with POAG was higher than that of people without the disease by $1688 over their expected lifetime, or approximately $137 per year.⁷ Lee et al estimated the average direct cost of treatment for glaucoma to range from $523 per patient per year to $2125 per patient per year depending upon the stage of disease (early vs severe).⁸ Given the burden of glaucoma on the healthcare system, there is a financial incentive to delay or prevent glaucomatous progression and associated visual field loss.⁹

Multiple medical therapies that are intended to lower IOP are available, the most common of which are prostaglandin analogues (PGAs).¹⁰ PGAs are generally well tolerated^11-13 and are not associated with the significant systemic side effects associated with topical beta blockers, such as bronchospasm, shortness of breath, depression, fatigue, impotence, hair loss, heart failure, and bradycardia.¹⁰

Latanoprost, travoprost, and bimatoprost are once-daily PGAs that lower IOP effectively and continuously, allowing for flat diurnal curves with few systemic side effects.^10,14,15 Numerous randomized clinical trials have demonstrated that patients achieve greater IOP lowering with bimatoprost than either latanoprost or travoprost.^14,16-23 Furthermore, a recent meta-analysis of multiple studies concluded that bimatoprost has greater efficacy than latanoprost or travoprost.²⁴

Law et al²⁵ reported on the latanoprost to bimatoprost switching patterns of an HMO. The study found that the HMO achieved a high switch rate, with few patients switching back. Moreover, there was a statistically significant reduction in mean IOP for patients who switched from latanoprost to bimatoprost. Similar studies that examined high switch rates from latanoprost to travoprost did not demonstrate a statistically significant reduction in mean IOP.^26,27 The impact of this superior efficacy of bimatoprost on direct medical costs has not been evaluated to date.

The primary objective of this study was to develop a cost-offset model from a payer perspective to compare glaucomatous progression and costs among POAG patients treated with bimatoprost, latanoprost, or travoprost in the United States. The analysis aimed to support the hypothesis that a reduction in IOP leads to a decreased risk of glaucoma progression, which in turn leads to cost savings from less healthcare resource utilization; specifically, due to bimatoprost’s greater efficacy in IOP reduction compared with travoprost and latanoprost, its use should lead to cost savings for payers. Fewer advanced glaucoma patients would result in lower expenses as increased resources needed for advanced disease stages are avoided.

METHODS

Model Overview

Figure 1

A cohort model () was constructed (1) to evaluate the difference in glaucomatous progression rates with bimatoprost, travoprost, or latanoprost; and (2) to provide a cost-offset analysis for these PGAs. This analysis was driven by the link between the treatments’ clinical efficacy, as represented by IOP after treatment (called the resultant IOP) and resource utilization. The model accounted for various healthcare resources (detailed below), the use of which increased with the resultant IOP. As the model assumed that IOP increase is associated with increased glaucomatous progression risk (detailed below), this analysis demonstrated the cost savings that arise from decreasing resource utilization due to the prevention of disease progression. While a cost-offset analysis provides useful insight into whether an intervention is worth financing from a budgetary standpoint, it is based on efficacy and resource utilization assumptions that may differ from real world rates and practices.

The model calculated results over a 7-year period in a hypothetical health plan of 1,000,000 members. Given the slow-progressing nature of glaucoma, a 7-year time horizon was utilized, as in previous studies.^2,28,29 Progression was defined as the loss of visual field as it is measured by the mean deviation (MD) score. POAG prevalence was assumed to be 1.9% (ie, 19,000 plan members had glaucoma).³⁰ Based on IMS 2009 data,³¹ the PGA treatment rate was estimated at 50% (N = 9500).^8,31

A subsequent budget impact analysis assumed bimatoprost as a first-line treatment with PGA market share as follows: 22% bimatoprost, 23% travoprost, and 55% latanoprost.³² This budget impact analysis compared the total cost to the payer, including the cost of the PGAs, medical costs (such as physician visits), and other glaucoma medication costs between different market share scenarios. In general, these budget impact analyses are useful for estimating systemwide (eg, medical and pharmacy) budget impact; they are often used by managed care organizations³³ to justify therapy reimbursement. While these analyses are limited in that they do not account for the full impact of clinical and patient outcomes and therefore do not establish the overall value of the product, they are not intended to do so; budget impact analyses are intended to present a financial perspective when considering a particular therapeutic decision.

Two scenarios were explored: In scenario A, all bimatoprost patients were switched to generic latanoprost, resulting in a market share of 0% bimatoprost, 23% travoprost, and 77% latanoprost. In scenario B, all travoprost patients were switched to generic latanoprost; market shares were 22% bimatoprost, 0% travoprost, and 78% latanoprost.

This model accounted for 3 different payer situations: all Medicare Part D patients, all commercial patients, and a mix of Medicare Part D and commercial patients. Medicare Part D patients included the assumed number of individuals covered by the plan who were 65 years or older. Commercial patients included the assumed number of individuals on the plan who were younger than 65 years.

Intraocular Pressure

Intraocular pressure ranges 19-21, 22, 23, 24, 25, and 26 (all mm Hg) and the percentage of patients allocated to them were based on a population-based study (the Beaver Dam Eye Study).³⁴ The resultant IOP with bimatoprost treatment was calculated by reducing the presenting IOP by 27%.³⁵ As the model assumes a 1 mm Hg reduction advantage for bimatoprost over latanoprost or travoprost,^19,24 the resultant IOPs for the latter PGAs were calculated by adding 1 mm Hg to the resultant IOP scores calculated for bimatoprost. This resultant IOP value was the basis of the patients’ probability of progression (discussed in the Progression Rate section).

Mean Deviation Score

As supported by literature, a baseline mean deviation (MD) score of —4 decibels² (dB) for early glaucoma patients or —10 dB³ for advanced glaucoma patients was assigned to the “worse seeing eye” of each patient cohort.³ Baseline MD score for the “better seeing eye” was estimated based upon a correlation with the worse seeing eye using the following equation:

BetterEYEMD = (WorseEYEMD —1.83) / 1.307.^3,29

PROGRESSION RATE

Table 1

The annual probability of progression was estimated using the resultant IOP following PGA treatment. It was estimated from literature that a 1 mm Hg decrease in IOP would reduce the probability of glaucoma progression by 10%⁴ or 19%²⁸ (). An IOP of 21 mm Hg⁴ was the benchmark. Based on the Early Manifest Glaucoma Trial data, the probability that a patient with an IOP of 21 mm Hg would progress was 10.2%.⁴ Therefore, the calculation for progression probability for IOP values other than 21 mm Hg was estimated using the following equation:

(10.2%) / ([1 Progression Risk Change]^{[21 mm Hg - Current IOP])}

After PGA treatment, the probability of progression remained constant throughout the model. Based on data from the Early Manifest Glaucoma Trial,² patients who progressed did so at a mean rate of —0.6 dB/year (Table 1).

The model also considered the impact of IOP fluctuation on probability of progression. The percentage of patients with IOP fluctuation greater than 3 mm Hg was 7.8% for latanoprost and 2.5% for bimatoprost.³⁶ The percentage of patients on travoprost with high fluctuation was assumed to be similar to or greater than the percentage of those on latanoprost³⁸; therefore, the percentage of travoprost patients with IOP fluctuation greater than 3 mm Hg defaulted to 7.8%. Inclusion of IOP fluctuation in the model was supported by a literature review that demonstrated that individuals who had an IOP fluctuation greater than 2 standard deviations would be 3 times more likely to experience glaucomatous progression.³⁹ The risk ratio (progression due to IOP fluctuation) was calculated as follows: 30% (probability of progression among patients with IOP fluctuation of >2 mm Hg)³⁹ / 9.7% (probability of progression among patients with IOP fluctuation of <2 mm Hg)³⁹ = 3.10.

Healthcare Costs

Table 2

The annual per-patient PGA cost was calculated based on drug cost (average wholesale price [AWP] or Medicare), dispensing fees ($2 for each brand name drug and $3 for generic drugs), copays,³⁷ rebates, and pharmacy discounts (which were 15% of the monthly cost of branded products and 17% of the monthly cost of generic products; Table 1). Rebates and copays were subtracted from the price to get the net cost to the managed care payer. As there were no data for the generic price of latanoprost, it was assumed that the cost of generic latanoprost would be 80% of the branded price. A lower copay for the generic ($10 instead of $25)³⁷ was also assumed. The number of office visits and visual field tests were predicted from the MD score and IOP value.⁴⁰ The annual number of concomitant glaucoma medications (non-PGA) was predicted from the MD score (Y[number of glaucoma medications] = 0.70 — 0.0455 [MD score]), as derived from literature on the number of medications by stage.⁸ Surgery was applied as a per-eye cost and the number of surgeries per year was estimated using literature on the annual rate of surgery by stage.⁴¹ For nonprogressors, the annual rate of surgery was assumed to be the literature-based rate for the stage of disease corresponding to the MD score in the model. For progressors, this annual rate was assumed to be higher based on literature showing that those who had disease stage progression were more likely to receive surgery (rate ratio of 1.92).⁴¹ The model conservatively assumed that patients who underwent surgery discontinued their medication and were therefore dropped out of the cohort. Direct medical and non-PGA pharmacy costs, which were based on resource utilization estimates, were applied to each treatment cohort to calculate the expected 7-year costs (). Unit costs for office visits, visual field tests, additional non-PGA glaucoma medications, and surgeries were based on resource utilization and 2008 Current Procedural Terminology codes (Table 2).^42,43 A discount rate of 3% for future costs was applied.⁴⁴ Results were presented as total annual costs and annual per member per month (PMPM) costs.

Sensitivity Analyses

Two 1-way sensitivity analyses were conducted for the estimated reduction in risk of progression per 1 mm Hg change in IOP. The base case assumed that there is a 10% reduction in the risk of progression per 1 mm Hg decrease in IOP. The sensitivity analyses assumed that this reduction in risk is 19%. This parameter change was tested for both less severe and more severe glaucoma patients.

Four 1-way sensitivity analyses were conducted for the price of generic latanoprost. Since the analysis was originally conducted, generic latanoprost has entered the market. Therefore, the sensitivity analyses assessed how the results would change should the price of generic latanoprost be as low as $16.44⁴⁵ or as high as $64.07.⁴⁶ These results were calculated for patients with less severe and more severe disease.

Study Design

This study is a health-related outcomes analysis based on available peer-reviewed literature and therefore was not subject to approval by an institutional review board.

RESULTS

Long-Term Progression Rates: Base Case for Early and Advanced Glaucoma Patients

Figure 2

In a health plan of 1,000,000 members with 19,000 glaucoma patients (presenting MD score —4 dB or –10 dB), the number of PGA-treated glaucoma patients who would develop visual field or glaucomatous progression over 7 years was as follows: 630 if all patients were treated with bimatoprost, 766 if all patients were treated with travoprost, and 766 if all patients were treated with latanoprost (). Due to the 1 mm Hg IOP reduction advantage, treating 100% of patients with bimatoprost would result in 136 fewer cases of progression than treating 100% of patients with either travoprost or latanoprost.

Cost-Offset Analysis

Table 3

Treating the hypothetical health plan’s PGA-treated glaucoma population exclusively with bimatoprost as a first-line therapy would result in cost savings on office visits, visual field tests, additional glaucoma medications, and surgeries over 7 years due to delayed or avoided progression. The savings per delayed or avoided progression were estimated to be $4009 for early glaucoma patients (presenting MD score −4 dB) and $4543 for advanced glaucoma patients (presenting MD score −10 dB). The total cost savings from the aforementioned direct costs due to delayed or avoided progression for all glaucoma patients treated with bimatoprost in this plan was estimated to be $545,224 if the population presented with early glaucoma and $617,848 if the population presented with advanced glaucoma ().

Budget Impact Analysis: Base Case for Early Glaucoma Patients

Table 4

With the default PGA market shares of 22% bimatoprost, 23% travoprost, and 55% latanoprost, and a presenting MD score for early glaucoma patients of −4 dB, the total cost for all PGAs over 7 years was $109,647,980 (0.01 PMPM) and the total cost of bimatoprost was $25,231,400. In scenario A, where travoprost patients did not change therapies and all bimatoprost patients were switched to generic latanoprost, the total cost for all PGAs over 7 years was $108,992,520 (0.01 PMPM) (); in scenario B, where bimatoprost patients did not change therapies and all travoprost patients were switched to generic latanoprost, this cost was $108,773,450 (0.01 PMPM) (Table 4).

Budget Impact Analysis: Base Case for Advanced Glaucoma Patients

When the analysis assumed a presenting MD score of −10 dB (greater severity) in the worse seeing eye, the total cost of all PGAs over 7 years was $131,079,830 (0.01 PMPM) in the default market share breakdown, $130,440,330 (0.01 PMPM) in scenario A (Table 4), and $130,205,250 (0.01 PMPM) in scenario B (Table 4).

Sensitivity Analyses

Two 1-way sensitivity analyses were conducted with respect to the estimated reduction in risk of progression per 1 mm Hg decrease in IOP. For early glaucoma patients (presenting MD score −4 dB), when the model assumed 19% risk reduction, the total cost of all PGAs over 7 years was $109,481,760 (0.01 PMPM) in the default market share breakdown, $108,826,020 (0.01 PMPM) in scenario A, and $108,607,240 (0.01 PMPM) in scenario B. Subsequently, the savings per avoided progression was estimated to be $4047 and the total cost savings due to delayed or avoided progression for all glaucoma patients treated with bimatoprost in this plan was estimated to be $546,345.

For advanced glaucoma patients (presenting MD score −10 dB), when the model assumed a 19% risk reduction, the total cost of all PGAs over 7 years was $130,804,190 (0.01 PMPM) in the default market share breakdown, $130,164,220 (0.01 PMPM) in scenario A, and $129,929,610 (0.01 PMPM) in scenario B. The savings per avoided progression was $4581 and the total cost savings due to delayed or avoided progression for all glaucoma patients treated with bimatoprost in this plan was estimated to be $618,435.

For both early and advanced glaucoma populations, treating the hypothetical health plan’s PGA-treated glaucoma patients exclusively with bimatoprost as a first-line therapy would result in cost savings over 7 years and would prevent 135 cases of progression that would have occurred had the patients been treated exclusively with travoprost or latanoprost.

Four 1-way sensitivity analyses were conducted for the price of generic latanoprost. The analyses were first conducted for early glaucoma patients (patients with a presenting MD score of −4 dB). With an AWP of $64.07, in scenario A, where travoprost patients did not change therapies and all bimatoprost patients were switched to generic latanoprost, the total cost for all PGAs over 7 years was $108,463,130 (0.01 PMPM) (Table 4); in scenario B, where bimatoprost patients did not change therapies and all travoprost patients were switched to generic latanoprost, this cost was $108,237,190 (0.01 PMPM) (Table 4). With a generic latanoprost AWP of $16.44, the total cost over 7 years was $96,282,030 (0.01 PMPM) for scennario A and $95,897,890 (0.01 PMPM) for scenario B. When the analysis assumed a presenting MD score of −10 dB in the worse seeing eye, given a generic latanoprost AWP of $64.07, the total cost of all PGAs over 7 years was $129,910,940 (0.01 PMPM) in scenario A (Table 4), and $129,668,980 (0.01 PMPM) in scenario B (Table 4). With a generic latanoprost AWP of $16.44, the total cost over 7 years was $117,729,840 (0.01 PMPM) for scenario A and $117,329,680 (0.01 PMPM) for scenario B.

DISCUSSION

Results presented herein demonstrate that if 100% of PGA-treated glaucoma patients in a healthcare plan of 1,000,000 members were treated with the same agent (bimatoprost, travoprost, or latanoprost), bimatoprost would prevent the greatest number of patients from glaucomatous progression as a result of the greater IOP-lowering effect of bimatoprost compared with travoprost and latanoprost.^14,16-23 Intraocular pressure is understood to be the most frequent causative risk factor for glaucoma development, and one of the only known risk factors that can be controlled to prevent progression of visual field loss.⁵ Furthermore, under these model assumptions, the payer would also realize cost savings due to the decreased use of resources such as hospital visits, visual field tests, additional glaucoma medications, and surgeries, which were estimated to be $4009 per avoided progression for early glaucoma patients and $4543 per avoided progression for advanced glaucoma patients. These findings demonstrate that the exclusive use of bimatoprost rather than latanoprost or travoprost in treating POAG patients is a way of decreasing the financial burden that glaucoma and associated visual field loss have on the healthcare system. From a payer perspective, while switching to generics is expected, the analysis demonstrates that maintaining patients on bimatoprost results in a neutral budget impact on a PMPM basis.

As with all health economic analyses, the model contains inherent limitations. It incorporates numerous assumptions, which have the potential to affect the magnitude of the results. For example, this analysis assumes that POAG prevanlence is 1.9%.³⁰ While our assumption is based on 1 study, it is important to note that this source\ included the following studies in its open angle prevalence calculation: the Baltimore Eye Survey,⁴⁷ the Beaver Dam Eye Study,⁴⁸ the Blue Mountains Eye Study,⁴⁹ Proyecto Vision Evaluation Research,⁵⁰ the Rotterdam Study,⁵¹ and the Melbourne Visual Impairment Project.⁵² Therefore, this assumption is supported by multiple data sets.

The model also assumes that bimatoprost has a 1 mm Hg efficacy advantage over both latanoprost and travoprost, based on the peer-reviewed literature.^3,19,24

Furthermore, the link between progression and IOP is based on predictive models developed using the Early Manifest Glaucoma Trial.² The model assessed glaucoma progression based on MD scores and patients’ progression risk based on resultant IOP. It should be noted that while there is an established connection between progression and MD score, the relationship between IOP and MD scores is not well proven.²²

In the current analysis, latanoprost and travoprost are assumed to have the same IOP fluctuation rate, based on the available literature, which demonstrated that the 2 drugs have similar efficacy.^26,27 However, these studies did not specifically mention IOP fluctuation. A single post hoc analysis did demonstrate greater IOP fluctuation with travoprost relative to latanoprost,³⁹ and for the purposes of this analysis, travoprost was assumed to have the same fluctuation as latanoprost. While this assumption carries uncertainty, the limited available literature comparing latanoprost and travoprost does not strongly support an assumption that these drugs differ in IOP fluctuation rate. Given the lack of evidence surrounding this assumption, it is important to consider that there may be a difference between the 2 rates and this may affect the magnitude of the results.

The model also did not include the costs of side effects. This parameter was excluded as bimatoprost, latanoprost, and travoprost have similar safety profiles,^21,26,27 thus rendering such cost calculations unnecessary. However, as there may be some differences in the adverse event rates between the drugs, the model may have underestimated or overestimated the cost savings realized if all PGA-treated glaucoma patients on a particular health plan were to use bimatoprost exclusively.

It should be emphasized that the results provide estimated progression rates and cost savings and must be validatedwith further clinical and modeling research. There are limited data examining the effect of PGA treatments on progression, and to the best of the authors’ knowledge, there are no other published models that offer cost-offset results that could be compared with those of this model. This model was based on reviews and meta-analyses of the most recent peerreviewed, published literature.

CONCLUSIONS

This model used support from literature to assume that lower IOP reduction leads to a reduction in risk of glaucomatous progression.^4,28 As bimatoprost is assumed to have an efficacy advantage over travoprost and latanoprost, the model demonstrated that this greater IOP reduction from bimatoprost treatment was associated with lower glaucomatous progression rates. As the cost-offset model calculated the cost of glaucomatous progression due to increased resource utilization, the analysis demonstrated that a managed care organization could reduce spending on follow-up glaucoma treatment costs by treating patients with bimatoprost compared with travoprost or latanoprost. Furthermore, this model demonstrated that greater IOP reduction from bimatoprost treatment was associated with lower glaucomatous progression rates and greater cost savings compared with treatment with latanoprost or travoprost. These findings are important for those in the managed care industry to consider when determining the appropriate clinical decisions to make in the face of cost constraints.

Acknowledgment

Jacob M. Willet, MPH, and Allison R. Perrin, BA, of Analytica International provided editorial assistance in the preparation of this manuscript. These data were presented in part at the Academy of Managed Care Pharmacy 22nd Annual Meeting and Showcase; April 7-10, 2010; San Diego, CA.

Author Affiliations: From Analytica International (KB), New York, NY; Washington University School of Medicine (SK), St. Louis, MO; Allergan, Inc (DAH, VP), Irvine, CA; College of Pharmacy (RF), University of Illinois, Chicago; Outcomes Research Consultant (CB), Laguna Beach, CA.

Funding Source: Funding for this study was provided by Allergan, Inc (Irvine, CA). The funding organization aided in the collection of data, its analysis and interpretation, and exercised the right to approve or disapprove publication of the finished manuscript.

Author Disclosures: Ms Berenson reports previous employment with Analytica International, which received funding from Allergan, Inc, for this research and consulting services. Dr Kymes reports having received consultancies or paid advisory boards from Allergan, Genentech, and Pfizer. He has received and has pending grants from Genentech, Pfizer, and Genzyme, and has attended meetings/conferences for Pfizer. Dr Hollander reports employment with Allergan, which manufactures bimatoprost. He also reports having stock ownership with the company. Dr Fiscella reports having received consultancies or paid advisory boards and has received and pending grants from Allergan. He has also received honoraria from SCS Healthcare and royalties from Clinical Ocular Pharmacology. Dr Burk reports employment with Allergan. Dr Patel reports employment and stock ownership with Allergan.

Authorship Information: Concept and design (KLB, SK, RF, CB, VDP); acquisition of data (KLB, RF, VDP); analysis and interpretation of data (KLB, SK, DAH, RF, CB, VDP); drafting of the manuscript (KLB, SK, RF, CB); critical revision of the manuscript for important intellectual content (KLB, SK, DAH, RF, CB, VDP); statistical analysis (KLB); provision of study materials or patients (RF); obtaining funding (VDP); administrative, technical, or logistic support (RF, CB); and supervision (RF, CB, VDP).

Corresponding Author: Vaishali D. Patel, PharmD, MS, Global Health Outcomes Strategy & Research, Allergan, Inc, 2525 Dupont Dr, Irvine, CA 92623. E-mail: Patel_Vaishali@Allergan.com.

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