Intravitreal Anti–Vascular Endothelial Growth Factor Treatment and the Risk of Thromboembolism




Purpose


To evaluate the subsequent risk of thromboembolic events in patients receiving intravitreal ranibizumab and bevacizumab for age-related macular degeneration or macular edema.


Design


Population-based crossover analysis with self-matched historical control data.


Methods


setting : Ontario, Canada, between April 1, 2006, and March 31, 2013. study population : Consecutive patients 65 and older who initiated intravitreal treatment (N = 57 919). intervention : Intravitreal injection of ranibizumab or bevacizumab. main outcome measures : Emergency visits for thromboembolic events spanning 1–4 years before treatment were compared to 1 year after treatment. Also examined were other secondary events including hip fractures, congestive heart failure, angina, falls, depression, cholecystitis, and total emergencies, as well as a control group following cataract surgery.


Results


A total of 57 919 patients were included who accounted for 1858 thromboembolic emergencies (48 per month) during the 3-year Baseline interval and 1077 thromboembolic emergencies (83 per month) during the 1-year Subsequent interval after initiating treatment. The absolute change in risk equaled an increase from 10.7 to 18.6 per 1000 patients annually after initiation of treatment (rate ratio 1.74; 95% confidence interval 1.58–1.92; P < .0001). The relative increase was particularly pronounced for ischemic stroke (rate ratio 2.18; 95% confidence interval 1.94–2.46; P < .0001). The observed increase exceeded trends due to aging, applied across patients with diverse characteristics, occurred with each medication (ranibizumab and bevacizumab), was not apparent for emergencies unrelated to thromboembolic events, and did not occur in a control group following cataract surgery.


Conclusions


Intravitreal anti–vascular endothelial growth factor medications ranibizumab and bevacizumab may contribute to systemic thromboembolic events in patients aged 65 years or older.


Age-related macular degeneration (AMD) is the third most common cause of blindness worldwide and the second most common cause in high-income countries. For the United States, over 8 million adults have the milder dry form where lipoprotein (drusen) accumulates under the retina. About one-quarter will eventually progress to wet AMD, characterized by abnormal choroidal blood vessels, hemorrhage, lipid exudation, and severe central vision loss. For wet AMD, serial intravitreal anti–vascular endothelial growth factor (VEGF) treatments protect 90%–95% of patients from a clinically significant decrease in visual acuity, and 33%–40% of patients experience a clinically significant improvement. These intravitreal treatments are now also indicated to treat macular edema secondary to diabetes or vein occlusion, the main complication causing vision loss from these 2 common medical conditions.


Vision loss is devastating but it is not usually life-threatening. Cardiac and cerebrovascular disorders are the most common systemic medical causes of mortality from a population perspective, as exemplified by an acute thromboembolic event. Thromboembolic events are a recognized complication of systemic anti-VEGF medications, as observed in studies of patients treated with intravenous therapy for malignant carcinomas. As well, a small meta-analysis of preliminary trials of patients who received intravitreal ranibizumab suggested an increased risk of subsequent stroke; however, surveillance studies and a nested case-control study showed no excess strokes following intravitreal injections. Major randomized clinical trials and meta-analyses of studies investigating intravitreal bevacizumab and ranibizumab have been insufficiently powered to detect systemic adverse events.


We conducted a population-based patient-level self-matching exposure-crossover analysis to investigate whether intravitreal anti-VEGF medications were associated with changes in the subsequent risk of acute thromboembolic events in patients aged 65 years or older.


Methods


Setting for Patient-Level Self-Matching Analysis


Ontario’s population at the study midpoint (2009) was 12 934 500, including 1 746 158 aged 65 years or older. Cerebrovascular disease accounted for 18% of total hospital admissions, more than any other single disease. In Ontario, intravitreal medication treatments for AMD and macular edema became popular in 2006 (bevacizumab) and fully funded in 2008 (ranibizumab). Over the study period, the rate of initiating intravitreal treatment equaled about 4.60 patients annually per 1000 individuals aged 65 and older. A past history of thromboembolic events was not an established contraindication to initiating intravitreal treatment (potential bias from withholding treatment owing to thromboembolic event history is explored in secondary analyses). The study was approved by the Sunnybrook Research Ethics Board prospectively and followed privacy guidelines of the Institute for Clinical Evaluative Sciences, including a waiver for consent.


Medical Care


Throughout the study, patients aged 65 years or older in Ontario were covered by universal health insurance that provided free access to physician services, diagnostic procedures, emergency visits, and prescription medications for outpatient and inpatient care. Patients could be tracked forward and backward in time through validated population-based databases. The health care databases included demographic information, physician fees, medication prescriptions, emergency contacts, and discharge diagnoses following hospitalization linked through unique coded patient identifiers. The accuracy of these databases has been previously validated. The available databases did not contain information on the specific indication for anti-VEGF treatment, contralateral eye disease, overall visual acuity, functional status, blood pressure, or anticoagulation compliance.


Patients


We identified consecutive patients initiating intravitreal injections between April 1, 2006 and March 31, 2013 by tracking health care database codes used in past research. The treatment date for each patient was defined as the day of the first intravitreal injection (OHIP billing codes E147 or E149). The 7-year enrollment period was selected to provide all data available since initiation of intravitreal anti-VEGF treatment for AMD and macular edema, with the exception of a few early adopters in 2005. The enrollment interval also provided a minimum of 1 year follow-up for all patients. We excluded patients under 65 years of age and those living outside of Ontario because of a lack of available data. In secondary analyses, we excluded the small number of patients who might have received intravitreal injections of antibiotics, steroids, or gas (explained below).


Patient Characteristics


Individual patient data ascertained on the treatment date ( Table 1 ) included age, sex, socioeconomic quintile (based on postal code average income), home location (urban or rural), and year of study enrollment. The patient ocular history included information on intraocular interventions in the prior 6 weeks (corneal, glaucoma, cataract, retina, and retinal laser), number of intravitreal injections, and cataract surgery in the prior decade. The presence of hypertension, diabetes, and emphysema was determined using validated algorithms, with special attention to diabetes in accord with past research. Health care utilization data were ascertained for the full year prior to initiating intravitreal treatment for total hospitalizations, emergency department visits, outpatient encounters (ophthalmology and non-ophthalmology), prescription medications, and AMD or macular edema diagnosis.



Table 1

Characteristics of Patients Receiving Anti–Vascular Endothelial Growth Factor Treatment

























































































































































































































Ranibizumab (N = 24 002) Bevacizumab a (N = 33 917)
Patient Demographics
Age (y)
65–74 5116 (21%) 13 860 (41%)
75–84 11 449 (48%) 14 423 (42%)
≥85 7437 (31%) 5634 (17%)
Sex
Female 14 601 (61%) 18 254 (54%)
Male 9401 (39%) 15 663 (46%)
Home location b
Urban 20 695 (86%) 29 372 (87%)
Rural 3299 (14%) 4533 (13%)
Socioeconomic quintiles c
Lowest 4792 (20%) 6627 (20%)
Next to lowest 4977 (21%) 7233 (21%)
Middle 4717 (20%) 6703 (20%)
Next to highest 4636 (19%) 6728 (20%)
Highest 4793 (20%) 6515 (19%)
Year of enrollment d
Early 0 (0%) 13 196 (39%)
Late 24 002 (100%) 20 721 (61%)
Ocular History
Macular degeneration or edema diagnosis e 22 671 (94%) 30 834 (91%)
Treatment regimen f , g
Short 1952 (8%) 16 893 (50%)
Sustained 22 050 (92%) 17 024 (50%)
Recent intervention h 819 (3%) 8890 (26%)
Cataract surgery 479 (2%) 3698 (11%)
Retinal surgery 48 (0%) 4602 (14%)
Retinal laser 313 (1%) 3442 (10%)
Cornea surgery 6 (0%) 177 (1%)
Glaucoma surgery 8 (0%) 109 (0%)
Cataract surgery in past decade 12 152 (51%) 18 630 (55%)
Medical History
Hypertension i
Yes 19 417 (81%) 26 526 (78%)
Diabetes i
Yes 7686 (32%) 14 714 (43%)
Emphysema i
Yes 6715 (28%) 8046 (24%)
No. of outpatient visits f
≤6 2418 (10%) 2173 (6%)
≥7 21 584 (90%) 31 744 (94%)
No. of ophthalmologist visits f
≤6 20 504 (85%) 23 188 (68%)
≥7 3498 (15%) 10 729 (32%)
Emergency visit f
Yes 8701 (36%) 12 859 (38%)
Hospital admission f
Yes 3438 (14%) 5384 (16%)
Total drugs dispensed f
≤6 6145 (26%) 9098 (27%)
≥7 17 857 (74%) 24 819 (73%)

a Intravitreal injections with no associated ranibizumab prescription.


b Missing 8 for ranibizumab, 12 for bevacizumab.


c Missing 87 for ranibizumab, 111 for bevacizumab.


d Early is 2006–2007; late is 2008–2013.


e Includes macular degeneration, diabetic retinopathy, and retinal vascular occlusion diagnosis from 1 year before to 1 year after index date (codes 362, 379).


f In past year.


g Short is 2 or fewer injections; sustained is 3 or more injections.


h In past 6 weeks.


i Using validated algorithms.



Specific Anti–Vascular Endothelial Growth Factor Medications


A patient was defined as receiving ranibizumab if a prescription for ranibizumab was filled within 2 weeks of initiating intravitreal treatment. The remaining patients were defined to have received bevacizumab (compounded off-label and not tracked by prescriptions). A separate prespecified subgroup analysis was also conducted to explore artifacts from fallible definitions by invoking a more stringent 2-step definition intended to reduce misclassification of treatment for uveitis, retinal detachment, or endophthalmitis. For this subgroup analysis, first, patients who had fewer than 3 intravitreal injections were excluded under the assumption that treatment for AMD or macular edema would consist of at least 3 loading injections. Second, patients who had an acute intraocular intervention (cataract, retinal, cornea, glaucoma surgery, or retinal laser) from 6 weeks prior to 1 week after the initial treatment date were excluded under the assumption that these intravitreal injections might be performed for other indications.


Acute Thromboembolic Events


We evaluated emergency department visits for thromboembolic events to test for acute unintended systemic consequences before and after initiating intravitreal anti-VEGF treatment. Physician diagnostic codes in the emergency department were used to identify the 3 most frequent specific thromboembolic emergencies; namely, ischemic stroke (codes I60–I64), acute myocardial infarction (codes I21, I22), and venous thromboembolism (codes I26, I80). The accuracy of these diagnostic codes has been previously validated. We did not stratify results by day of the week, season, or year owing to small sample sizes in subgroups. Other patient characteristics were subjected to subgroup analysis to test robustness.


Self-Matching Approach


Our analytic design (exposure crossover analysis) defined each patient as his or her own control since randomized trials have been insufficiently powered to assess toxicities and are ethically problematic, given that anti-VEGF treatment has become the standard of care. The design identified patients by the intervention and then tracked each patient’s outcomes forward and backward in time. A strength of the self-matching design was that it avoided all potential biases associated with selecting an independent control group. Similar to case-crossover analysis, the self-matching design removed confounding due to genetics, personality, education, and other stable characteristics (measured or unmeasured). Similar to time series analysis, an extended observational interval before and after intervention attenuated temporal confounders.


Time Intervals


Each patient’s 5-year time series data were divided into consecutive 28-day segments grouped into 3 larger intervals ( Supplemental Figure 1 , available at AJO.com ): the Baseline interval (year -4, -3, and -2 before first injection), the Induction interval (year -1 before first injection), and the Subsequent interval (year +1 after first injection). The main strength of this approach was in generating consecutive 1-month intervals before and after initiation of treatment for each individual patient. The 1-year Induction interval was defined in advance and considered a time when a patient’s functioning might have potentially differed from baseline. Serious medical events might be attenuated during the Induction interval before beginning ophthalmologic treatment; hence, the outcome rate during this period may be artificially distorted by selection bias and was not used to assess baseline risk.


Selection Bias


We assumed that patients might be less likely to receive anti-VEGF injections immediately following a thromboembolic event. As noted above, the analytic approach excluded the interval 1 year immediately prior to the first anti-VEGF injection to reduce such selection bias followed by regression to the mean. Thromboembolic risk naturally increases with age, thereby necessitating an extended baseline interval and possible general estimated equations models to adjust for anticipated (eg, age) and unanticipated temporal trends (eg, calendar year). Unlike population-level analyses, the analysis was patient-level and individually matched, thereby avoiding ecologic biases. Together, these analytic strategies helped to avoid spurious findings related to selection bias and temporal confounding.


Secondary Analyses


Further analyses explored more potential artifacts due to selection bias, assessed robustness, and checked for survivor bias. The first set examined a separate control group in a companion analysis, where the same analytic criteria were applied to identify patients undergoing first eye cataract surgery instead of intravitreal anti-VEGF therapy. We hypothesized cataract surgery would also be prone to selection bias, especially given the medical evaluation and anesthetic required for the operation. The second set explored other life-threatening emergencies, including unstable angina (code I20), congestive heart failure (code I50), hip fractures (code S72), depression (codes F32, F33), falls (codes W0, W1), cholecystitis (codes K80–K83), and total emergency visits among the patients receiving anti-VEGF treatment. To investigate survivor bias the third set excluded patients who did not survive the entire Subsequent interval (n = 2107).


One more set of secondary analyses stratified results based on the patient’s history of thromboembolic events (accounting for those with a remote history, a recent history, and remote or recent history of thromboembolic events). This analysis required defining year -3 and year -2 before initiating anti-VEGF injection as the Baseline interval, and then excluding patients who had a thromboembolic event in year -1, year -4, and year -4 or year -1 ( Supplemental Figure 3 , available at AJO.com ). This analysis addressed many other forms of selection bias, including the concern that ophthalmologists might delay treatment temporarily after an acute thromboembolic event.


Statistical Analysis


Our primary analysis evaluated emergency department visits for thromboembolic events and compared the patient’s Baseline interval to Subsequent interval. Statistical testing was calculated based on the McNemar approach and further explored using parsimonious longitudinal Poisson generalized estimating equations (GEE). A linear slope variable was included in the model when statistically significant (ie, outcomes with a trending baseline due to increasing age or other time trends). The Induction interval was examined only for descriptive purposes. A prespecified subgroup analysis was conducted to determine adverse event rate differences by the patient’s specific anti-VEGF medication and diabetic status. Post hoc subgroup analyses based on patient characteristics were used to assess robustness. Analyses were performed at the Institute for Clinical Evaluative Sciences using SAS version 9.3 (SAS Inc, Cary, North Carolina, USA).




Results


Patient Characteristics


We identified 57 919 total patients. The patients were widely distributed over the full range of socioeconomic quintiles ( Table 1 ). About two-fifths received ranibizumab and about three-fifths received bevacizumab. Patients who received ranibizumab rather than bevacizumab were older, more likely to be female, more likely to have emphysema, less likely to have diabetes, and less likely to have undergone recent intraocular intervention. The 2 groups had similar mean numbers of total outpatient encounters, emergency visits, hospital admissions, and unique medication prescriptions during the year before initiating treatment.


Thromboembolic Events


A total of 3592 thromboembolic events occurred during the study interval, including 1858 during the 3-year Baseline interval and 1077 during the 1-year Subsequent interval ( Figure 1 ). The annual thromboembolic event rate per 1000 patients was 10.7 in the Baseline interval and 18.6 in the Subsequent interval. The absolute risk increase equaled 7.9 events per 1000 patients and was mathematically equivalent to a number needed to harm of 127 annually. The GEE model yielded a rate ratio of 1.74 (95% confidence interval [CI] 1.58–1.92; P < .0001). The thromboembolic events occurred at a median time of 58 days from last injection.




Figure 1


Thromboembolic emergencies after anti–vascular endothelial growth factor (VEGF) treatment and after cataract surgery. Each patient followed for thromboembolic emergencies resulting in an emergency visit. X-axis is divided into segments of 28 days, with time 0 defined as the patient’s first anti-VEGF treatment (Top) and first cataract surgery (Bottom). Y-axis shows the rate of emergency department visits for thromboembolic emergencies per 1000 patients annually. Induction interval denoted in orange is excluded from analysis owing to potential selection bias. Comparing the Baseline interval to the Subsequent interval, there was a significant increase in thromboembolic events after ant-VEGF treatment (Top), which was not apparent after cataract surgery (Bottom).


Specific Events


Of the 3 specific thromboembolic emergencies, acute ischemic stroke had the highest relative increase ( Table 2 , Figure 2 ). The rate per 1000 patients annually increased from 4.2 during the Baseline interval to 9.1 during the Subsequent interval (GEE-modeled rate ratio [RR] 2.18; 95% CI 1.94–2.46; P < .0001). The rate per 1000 patients annually for myocardial infarction increased from 3.1 to 5.1 (GEE-modeled RR 1.65; 95% CI 1.43–1.91; P < .0001) and for venous thromboembolism increased from 3.5 to 4.5 (GEE-modeled RR 1.29; 95% CI 0.99–1.69; P = .059).



Table 2

Outcomes of Patients Receiving Anti–Vascular Endothelial Growth Factor Treatment During Baseline and Subsequent Interval




































































































Characteristic Total No. of Events Baseline Rate a Subsequent Rate a Rate Ratio b 95% Confidence Interval b
Thromboembolic events 3592 10.69 18.59 1.74 (1.58–1.92) ∗∗∗
Ischemic stroke c 1526 4.17 9.12 2.18 (1.94–2.46) ∗∗∗
Myocardial infaraction d 1003 3.08 5.08 1.65 (1.43–1.91) ∗∗∗
Venous thromboembolism e 1070 3.46 4.47 1.29 (0.99–1.69)
Total emergency visits f , g 184 730 560.39 791.69 1.04 (1.00–1.07)
Unstable angina g , h 2549 9.04 8.68 1.18 (0.95–1.47)
Congestive heart failure g , i 5094 12.67 30.89 1.25 (1.07–1.48) ∗∗
Hip fractures g , j 1439 4.15 7.91 1.19 (0.91–1.56)
Falls g , k 16 819 51.25 74.90 1.04 (0.96–1.13)
Depression l 414 1.37 1.74 1.28 (0.98–1.66)
Cholecystitis m 919 2.83 3.56 1.26 (1.05–1.52)

* P < .05; ** P < .01; *** P < .005.

a Event rates were calculated per 1000 patients annually during the corresponding interval.


b Based on generalized estimating equations model.


c ICD-9 codes I60–I64.


d ICD-9 codes I21–I22.


e ICD-9 codes I26, I80.


f Any visit to an Ontario emergency department.


g Statistically significant slope over time was incorporated into a generalized estimating equations model, with the resultant rate ratio shown.


h ICD-9 code I20.


i ICD-9 code I50.


j ICD-9 code S72.


k ICD-9 codes W1–W2.


l ICD-9 codes F22–F23.


m ICD-9 codes K80–K83.




Figure 2


Stroke emergencies and total emergencies after anti–vascular endothelial growth factor (VEGF) treatment. Each patient followed for medical event resulting in an emergency visit. X-axis divided into segments of 28 days, with time 0 defined as the patient’s first anti-VEGF treatment. Y-axis shows the rate of emergency department visits per 1000 patients annually. Induction interval denoted in orange is excluded from analysis owing to potential selection bias. Stroke emergencies (Top) and total emergencies (Bottom) are displayed. Comparing the Baseline interval to the Subsequent interval, there was a significant increase in stroke emergencies but not total emergencies after anti-VEGF treatment.


Control Group Companion Analysis


The control group companion analysis consisted of patients who underwent first eye cataract surgery (n = 471 429). A total of 25 880 thromboembolic events occurred during the study interval, including 13 977 during the 3-year Baseline interval and 6966 during the 1-year Subsequent interval ( Figure 1 ). The Baseline annual thromboembolic event rate per 1000 patients was 9.9, near identical to the Baseline rate among the patients receiving anti-VEGF treatment ( Figure 1 ). The time trend–adjusted GEE modeled rate ratio after cataract surgery was 1.10 (95% CI 0.97–1.24; P = .1372).


Other Life-Threatening Emergencies


No increase in Subsequent adverse event rates was apparent for unstable angina, hip fractures, falls, depression, or total emergency visits after anti-VEGF treatment. A small increase was observed for congestive heart failure and cholecystitis. The trending baseline was accounted for when a significant slope was identified ( P < .05); no significant slope was apparent for ischemic stroke, myocardial infarction, or venous thromboembolism ( Figure 2 , Supplemental Figure 2 , available at AJO.com ).


Selection Bias and Other Secondary Analyses


The higher rate of thromboembolic events during the Subsequent interval after anti-VEGF treatment was observed after stratifying by the patients’ demographic characteristics, ocular history, medical comorbidities, and specific intravitreal injection medication ( Table 3 ). The increased risk was similar in magnitude for patients enrolled during the early years and during the later years of the study. The increased risk persisted in the subgroup with no medical emergencies for any reason during the entire year before initiating treatment. The relative increase was accentuated among patients not diagnosed with hypertension or diabetes, as well as among those with fewer physician outpatient visits or those with fewer prescribed medications (perhaps suggesting some patients were not medically optimized).



Table 3

Thromboembolic Events During Baseline and Subsequent Interval in Patients Receiving Anti–Vascular Endothelial Growth Factor Treatment Stratified by Patient Characteristics








































































































































































































































































































































































































































Total Events Baseline Rate a Subsequent Rate a Rate Ratio 95% Confidence Interval
Patient Demographics
Full cohort 3592 10.7 18.6 1.74 (1.58–1.92)
Age
65–74 954 9.0 15.4 1.71 (1.40–2.09)
75–84 1599 10.7 18.5 1.73 (1.51–1.99)
≥85 1039 13.2 23.5 1.78 (1.48–2.15)
Sex
Female 1945 10.1 18.1 1.80 (1.56–2.07)
Male 1647 11.5 19.2 1.68 (1.47–1.92)
Home status b
Urban 3062 10.5 18.3 1.74 (1.57–1.94)
Rural 530 12.0 20.7 1.72 (1.34–2.22)
Socioeconomic status c
Lowest 803 12.0 20.6 1.72 (1.42–2.08)
Next to lowest 775 10.6 18.2 1.72 (1.38–2.14)
Middle 726 11.4 18.6 1.63 (1.26–2.09)
Next to highest 663 9.9 19.5 1.97 (1.60–2.42)
Highest 612 9.6 15.8 1.65 (1.33–2.06)
Year of enrollment d
Early 803 9.9 19.2 1.94 (1.56–2.41)
Late 2789 10.9 18.4 1.69 (1.51–1.88)
Ocular History
Treatment regimen e , f
Short 1336 11.8 23.5 2.00 (1.69–2.36)
Sustained 2256 10.2 16.2 1.60 (1.42–1.80)
Recent intervention g
Yes 627 11.2 18.6 1.66 (1.34–2.07)
No 2965 10.6 18.6 1.76 (1.58–1.96)
Cataract surgery in past decade
Yes 2086 12.0 20.2 1.68 (1.47–1.91)
No 1506 9.2 16.8 1.84 (1.59–2.12)
Medical History
Hypertension e , h
Yes 3129 12.0 19.6 1.64 (1.48–1.82)
No 463 5.8 14.7 2.56 (1.93–3.40)
Diabetes e , h
Yes 1692 13.5 20.9 1.56 (1.36–1.78)
No 1900 8.9 17.1 1.92 (1.67–2.20)
Emphysema e , h
Yes 1135 13.8 22.4 1.63 (1.37–1.93)
No 2457 9.6 17.3 1.80 (1.60–2.02)
No. of outpatient visits e
≤6 157 6.0 14.8 2.40 (1.35–4.28)
≥7 3435 11.1 18.9 1.71 (1.55–1.88)
No. of ophthalmologist visits e
≤6 2703 10.5 18.7 1.77 (1.58–1.99)
≥7 889 11.2 18.4 1.65 (1.38–1.98)
Any emergency visit e
Yes 2145 14.9 24.3 1.63 (1.41–1.88)
No 1447 8.2 15.2 1.86 (1.63–2.13)
Any hospital admission e
Yes 1215 17.9 30.6 1.72 (1.38–2.14)
No 2377 9.4 16.4 1.75 (1.57–1.95)
Total drugs dispensed e
≤6 473 4.9 13.5 2.77 (2.10–3.66)
≥7 3119 12.8 20.4 1.60 (1.44–1.78)
Medication
Ranibizumab 1456 10.6 17.2 1.61 (1.39–1.87)
Bevacizumab i 2136 10.7 19.6 1.83 (1.61–2.09)

Only gold members can continue reading. Log In or Register to continue

Stay updated, free articles. Join our Telegram channel

Jan 6, 2017 | Posted by in OPHTHALMOLOGY | Comments Off on Intravitreal Anti–Vascular Endothelial Growth Factor Treatment and the Risk of Thromboembolism

Full access? Get Clinical Tree

Get Clinical Tree app for offline access