To compare the visual functioning (VF) and vision-related QoL (VRQoL) of children 8–18 years old treated for primary congenital glaucoma (PCG) and secondary childhood glaucoma.
A total of 309 children 8–18 years old treated for PCG and secondary childhood glaucoma between 2000 and 2010 by a single pediatric glaucoma specialist were prospectively enrolled at LV Prasad Eye Institute, Hyderabad, India. Children completed 2 questionnaires, the LV Prasad Functional Vision Questionnaire–II (LVP-FVQ-II), and the Impact of Vision Impairment-Children (IVI-C) questionnaire. Rasch-calibrated scores from both these questionnaires were used to compare the VF and VFQoL between the 2 groups.
Mean ages of the children were 12.2 and 12.6 years in the PCG (53%, median age at diagnosis = 5 months) and secondary glaucoma groups (47%, median age at diagnosis = 3 years), respectively. A majority (80%) of children had bilateral glaucoma and underwent filtering surgery (83%). Mean better eye logMAR visual acuity (VA) was comparable between PCG and secondary childhood glaucoma groups (0.49 vs 0.52, respectively; P = 0.59). Children with PCG reported significantly better VF and VRQoL than secondary childhood glaucoma patients. Unadjusted and adjusted childhood glaucoma group comparisons revealed secondary childhood glaucoma to be associated with worse VF and VRQoL compared to PCG (difference for VF, −0.83; 95% confidence interval [CI], −1.34 to 0.31; P = 0.002; 0.39; 95% CI, 0.16–0.62; P = 0.001 for VRQoL).
Results show that children with treated PCG experience significantly better VF and VRQoL than those with secondary childhood glaucoma, despite comparable VA and IOP.
Childhood glaucoma is a heterogeneous group of vision-threatening disorders associated with elevated intraocular pressure (IOP) and accounts for approximately 5% of blindness in children worldwide. It can divided into 2 broad types: primary, which includes primary congenital glaucoma (PCG), and juvenile open angle glaucoma due to causes such as developmental defects of the aqueous drainage pathways, or secondary due to causes such as ocular maldevelopment, due to systemic diseases or a combination, and following surgery for congenital cataract. The detection and management of childhood glaucoma is stressful both emotionally and financially for the affected child and the caregivers, given the need for life-long care, and frequent examinations under anesthesia until the child is co-operative enough for office-based procedures. Moreover, these children may be required to use topical antiglaucoma medications, causing discomfort, and some may also be required to undergo multiple ocular surgeries, thereby, interfering with their school attendance and academic activities.
Treatment modalities for childhood glaucoma include both medications as adjuvant therapy to lower IOP as well as surgery, which remains the main stay of management. Several published studies have reported the long-term outcomes of treatment for childhood glaucoma and have used conventional outcome measurements such as IOP in the criteria for success. However, if the interventions are not improving the well-being and quality of life (QoL) of children with glaucoma, then the value of these interventions is questionable. Objective measurements alone, such as visual acuity (VA), are recognized as inadequate descriptors of visual functioning (VF) and even less predictive of vision-related QoL (VRQoL). ,
VRQoL is a complex trait that encompasses vision functioning, VF (ability to perform vision-dependent tasks such as reading, watching TV, copying from board, and others), symptoms, emotional wellbeing, social relationships, concerns, and convenience as they are affected by vision. To date, there is limited published research on the VRQoL of children with glaucoma. Measuring subjective outcomes such as VRQoL in childhood glaucoma provides an insight into the affected child’s perspectives regarding various aspects of his/her life such as physical, emotional, social, and schooling as it relates to his/her vision. In a cross-sectional study from the United States, better VRQoL was found to be associated with higher VA in the better-seeing eye in childhood glaucoma (n = 50). In a study from the United Kingdom, children with glaucoma (n = 119) reported reduced functional visual ability, VRQoL, and health-related QoL compared with their normally sighted peers. More recently, investigators from Saudi Arabia found that the visual ability and VRQoL were reduced in their cohort of childhood glaucoma. Given the variation in lifestyle, environment, cultural, and access to resources, however, it is unclear whether childhood glaucoma and its treatment has similar impacts on the VF and VRQoL of children with glaucoma in non-Western societies, such as in India. Therefore, the perspectives on the impact of glaucoma on children’s QoL need to be widened. Moreover, the prevalence of PCG is approximately 3–5 times higher in the developing countries such as India (1 in 3,300 ) than in the United States (1 in 10,000 to 1 in 30,000 , ), and the patterns of presentation (severity) and its management vary significantly between these regions. Thus, an understanding of the perspectives of children treated for glaucoma in India regarding the impact of the disease and its treatment on their psychological aspects, VF, independence, social integration, and overall QoL is needed for clinical and research purposes. The aims of this study were twofold: first, to compare the VF and VRQoL of children treated for PCG and secondary glaucoma, and second, to determine factors influencing the VF and VRQoL of these children.
Children with glaucoma were enrolled in this prospective, cross-sectional, observational study conducted at the LV Prasad Eye Institute (LVPEI), Hyderabad, India, over a 1-year period from September 2017 to October 2018. The Institutional Review Board of the LVPEI approved the study methods. Written informed consent was obtained from a parent after an explanation of the nature and possible consequences of the study. In addition, written informed assent was obtained from children 8–18 years old. All study methods adhered to the tenets of the Declaration of Helsinki.
Medical records of patients with childhood glaucoma (PCG and secondary) treated by a single pediatric glaucoma specialist (A.K.M.) from 2000 to 2010 who were scheduled for a clinic visit between September 2017 and October 2018 at the VST Centre for Glaucoma care, LVPEI, Hyderabad, India, were examined to identify the potentially eligible participants for the present study Eligibility criteria consisted of children with glaucoma between the ages of 8 and 18 years at the time of inclusion in the study; ability to communicate in English or 1 of the 2 local languages; and studying in mainstream education. Children who were attending special schools or who could not communicate in English or either of the 2 local languages, had a diagnosis of traumatic glaucoma, and underwent incisional ocular surgery within 6 months prior to inclusion in the study or were scheduled for surgery within 1 month were excluded. Patients with traumatic glaucoma were excluded because they are a multifactorial group of disorders, and the visual outcomes can be highly varied depending on the type (blunt versus penetrating) of injury and duration since the injury.
The following data were collected from every patient from the medical record: demographic information, including age at first clinic visit, age at glaucoma diagnosis, type and laterality of glaucoma, date and eye of glaucoma surgery, number of glaucoma surgeries per eye, number and type of antiglaucoma medications, habitual distance VA in each eye, with glasses if worn (recorded as fraction using ComPlog and later converted to logarithm of the minimum angle of resolution, logMAR), and intraocular pressure (IOP) in the affected eye (at the time of inclusion in the study). During the clinic visit, each child underwent an extensive and standardized examination procedure, which included measurement of VA and a detailed slit-lamp examination including applanation tonometry. For each eye, initially the participant’s habitual VA was ascertained with them wearing their habitual optical correction (spectacles). This was followed by manual refraction and recording of the best spectacle-corrected VA. However, in the current study, only presenting (habitual) VA data were used because it was believed that this VA gave a more accurate picture of the role of visual status in study participants’ performance of the activities of daily living. VA was measured using a computerized VA measurement system (COMPlog clinical VA measuring system) measuring ranges from −0.30 to 1.68 logMAR acuity in Snellen format and was converted to logarithm of the minimum angle of resolution (logMAR). If no letters were identified on the chart (indicating worse than 1.68 logMAR), then VA was assessed as counting fingers, hand movements, perception of light, or no perception of light, and logMAR values of 2.1, 2.4, 2.7, and 3.0 were assigned to indicate these, respectively.
Assessment of Visual Functioning and Vision-related Quality of Life
The VF (or visual ability) was assessed by using the second version of LV Prasad Functional Vision Questionnaire (LVP-FVQ-II) developed and validated by using Rasch analysis. The original version of the LVP-FVQ was developed more than a decade ago. Higher LVP-FVQ-II scores indicate worse VF. The 24-item IVI-C questionnaire was used to assess the VRQoL and was scored as recommended by the developers. , Although a higher IVI-C score indicates better VRQoL on most of the items (n = 18), 6 items have been reverse scored (such that a higher score indicates worse VRQoL) to avoid response bias. However, scores for these 6 items were reversed during Rasch analysis (described later) so a high IVI-C score indicates high VRQoL for all 24 items. Although the IVI-C was developed for an Australian population, it was validated by the present authors previously. Children were escorted along with their parents to a separate quiet room away from the clinic where the research assistants (S.S., V.K.G.) completed the basic demographic data sheet (such as the child’s age, and sex) prior to handing the 2 questionnaires over to the child. In addition, children were asked to report their overall health-related QoL by using a single question on a scale of 1–5 (where 1 = very poor and 5 = very good). Children were encouraged to answer the questions without prompting from their parents, and 1 of the 2 research assistants was available to clarify any practical issues and help with reading difficulties in younger patients. In case the child could not self administer the questionnaires, the research assistants administered them in face-to-face interviews.
We performed Rasch analysis to assess the psychometric properties of the questionnaires using the Andrich rating scale model with Winsteps version 3.74 software (Chicago, Illinois). , It converts raw questionnaire scores of LVP-FVQ II and IVI-C into data that approximate interval-level measurement expressed in log of the odds units (logits). We used the linear Rasch-calibrated scores for subsequent parametric analyses.
We examined characteristics of the study population using means and ± SD for normally distributed continuous data, or the median and interquartile (IQR) range for skewed distributed data, and counts and percentages for categorical data. The factors associated with lower VF and VRQoL were investigated using univariate and multivariate regression analyses and used t -based 95% confidence intervals (CI) for the regression coefficients. For this purpose, the linearly estimated Rasch-scaled scores of VF (from LVP-FV-II) and VRQoL (from IVI-C) were used and built separate multivariate regression models for VF (i.e., LVP-FVQ-II score) and VRQoL (i.e., IVI-C score). Factors were included such as age, sex, laterality of glaucoma, duration since glaucoma diagnosis, number of glaucoma surgeries, type of glaucoma (primary vs. secondary), and habitual VA in the better eye (logMAR) as independent variables. Factors found to be associated with VF and VRQoL scores in univariate analysis at a 2-sided P value of 0.10 or less were then entered into a stepwise multiple linear regression model for visual functioning and VRQoL. A separate adjusted analysis was performed using generalized linear models for both VF and VRQoL to determine whether the glaucoma type (primary vs secondary) was specifically associated with reduced VF and VRQoL. All these factors were adjusted regardless of whether they were statistically significant in the univariate analysis. A forward stepwise strategy was applied to select significant independent variables with P < 0.05 as the inclusion criterion. The difference in VF and VRQoL between the 2 groups was estimated and calculated effect size (ES) using Cohen’s d statistic, which was categorized as small (0.20), moderate (0.50), or large (0.80). All statistical tests were performed using SPSS version 19.0 software (IBM, Armonk, New York). A P value <0.05 was statistically significant.
Of the 311 consecutive children with glaucoma and their parents who were approached, parents of 2 children declined due to lack of time, leaving 309 children in this study (response rate, 99%). The overall mean age of the children was 12.4 ± 3.01 years old (range, 8–18 years old) and there was no statistically significant differences in the mean ages between the 2 groups of glaucoma. Glaucoma following cataract surgery was the most common type of secondary glaucoma (34%) followed by glaucoma associated with acquired conditions (steroid-induced glaucoma [18%]). The other types of secondary glaucoma included glaucoma associated with nonacquired systemic disease or syndrome (Sturge-Weber syndrome [11%]), glaucoma associated with nonacquired ocular anomalies (Weill-Marchesani syndrome [10%], Axenfeld-Rieger spectrum [8%], aniridia [6%], Peters anomaly [5%]), congenital hereditary endothelial dystrophy (3%), and glaucoma associated with acquired conditions (postvitreoretinal surgery [5%]). Although we used the presenting acuity for our analyses, the mean best spectacle-corrected VA (±SD, logMAR) in the better eye (0.50 ± 0.49; Snellen equivalent, 20/63) was not significantly different from that of the presenting VA (0.49 ± 0.49; P = 0.85) for children with primary glaucoma. Likewise, the best spectacle-corrected VA was the same as the presenting VA in the better eye for children (0.52 ± 0.49; Snellen equivalent, 20/63 −1 ) with secondary glaucoma. Participant demographics are listed in Table 1 .
|Characteristic||Primary (n = 163)||Secondary (n = 146)||P Value d|
|Mean ± SD age, years||12.2 ± 3.1||12.6 ± 3.1||0.25|
|Sex, n (%)|
|Males||96 (59)||96 (66)||0.25|
|Females||67 (41)||49 (34)|
|Laterality, n (%)|
|Unilateral||32 (20)||30 (21)||0.94|
|Bilateral||131 (80)||116 (79)|
|Mean ± SD duration since glaucoma diagnosis, years||9.9 ± 4.2||8.0 ± 4.6||0.0002|
|Mean ± SD age at glaucoma diagnosis, years||2.3 ± 3.8||4.9 ± 4.9||<0.0001|
|Median (IQR)||0.42 (0.08-4)||3 (0.33-8.5)|
|Number of glaucoma surgeries, median (IQR)||1 (1-2)||2 (1-2)|
|Mean ± SD duration of follow-up, years||9.8 ± 4.1||8.1 ± 4.6||0.0007|
|Number of antiglaucoma medications, n (%)|
|0||90 (55)||59 (40)||0.01|
|1||40 (25)||32 (22)|
|>1||33 (20)||55 (38)|
|Mean ± SD presenting visual acuity in the better eye, logMAR||0.49 ± 0.49||0.52 ± 0.49||0.59|
|Median (IQR)||0.39 (0.09-0.80)||0.39 (0.09-0.80)|
|Self-rated overall health-related quality of life, n (%)|
|Very poor/poor||10 (6)||10 (7)||0.90|
|Neither good nor poor||34 (21)||38 (26)|
|Very good/good||119 (73)||97 (66)|
|Mean ± SD visual ability a , b||−2.68 ± 2.26||−1.85 ± 2.37||0.002|
|Mean ± SD vision-related quality of life a , c||1.16 ± 1.11||0.78 ± 0.92||0.001|