Overuse and Underuse of Visual Field Testing Over 15 Years (original) (raw)
Related papers
2003
and the CIGTS Study Group 6 PURPOSE. To compare the baseline Collaborative Initial Glaucoma Treatment Study (CIGTS) visual field (VF) score and mean deviation (MD), investigate test-retest variability, and identify variables associated with VF loss and VF measurement variability. METHODS. Baseline data from a randomized clinical trial of 607 patients with newly diagnosed open-angle glaucoma were collected at 14 clinical centers. The CIGTS VF score and MD were obtained from 24-2 VF tests (Zeiss-Humphrey Systems, Dublin, CA) at two visits approximately 2 weeks apart. RESULTS. Although most baseline CIGTS VF scores showed limited field loss, 15% (91/607) of patients showed a substantial deficit (VF score Ͼ10 on a 0 -20 scale). A small but significant learning effect was seen over the two baseline measures for CIGTS VF score and MD. CIGTS VF score and MD correlate highly (r ϭ Ϫ0.93); both have high test-retest correlation (0.83 and 0.91, respectively). Variables associated with greater baseline VF loss for both CIGTS VF score and MD include (probabilities for VF only): male sex (P ϭ 0.018), black race (P Յ 0.0001), lower visual acuity (P Յ 0.0001), higher intraocular pressure if more than 30 mm Hg (P ϭ 0.0034), poor field reliability score (P Յ 0.0001), cardiovascular disease (P ϭ 0.015), reduced patient-reported alertness (P ϭ 0.023), and CIGTS clinical center (P Յ 0.0001). Predictors of increased CIGTS VF score variability include a midrange VF score (P Յ 0.0001), first-tested eye (P ϭ 0.0027), reduced patient-reported alertness (P ϭ 0.0177), increasing age (P ϭ 0.0040), current smoker (P ϭ 0.0014), and CIGTS clinical center (P ϭ 0.0215). CONCLUSIONS. The CIGTS VF score provides a measure of VF strikingly similar to the MD. Variables associated with VF loss and VF variability may help identify patients who need greater clinical scrutiny. (Invest Ophthalmol Vis Sci.
How useful is visual field testing in an African glaucoma clinic?
Clinical Ophthalmology, 2014
of surgery, groote schuur hospital, Cape Town, south africa; 2 The University of Cape Town, Cape Town, south africa Purpose: To investigate the usefulness of visual field testing in the diagnosis and subsequent management of glaucoma in a specialist glaucoma clinic at Groote Schuur Hospital, Cape Town, South Africa. Methods: A retrospective case note review of 344 patients who attended the glaucoma clinic between January and June 2010.
Influence of Visual Field Testing Frequency on Detection of Glaucoma Progression With Trend Analyses
Archives of Ophthalmology, 2011
To explore whether increased frequency of visual field testing leads to earlier detection of glaucoma progression with trend analyses. Methods: The visual fields of 468 eyes (381 patients) from the Advanced Glaucoma Intervention Study with 10 or more reliable visual field tests and 3 or more years of follow-up were studied. Starting at year 1, every other visual field examination was deleted to create a lowfrequency data set, and the original group was kept as the high-frequency data set. The proportion of progressing eyes and the time to progression were compared between the 2 data sets with global and pointwise linear regression criteria. Results: The median number of visual field examinations was 20 and 12 for the high-and low-frequency data sets, respectively. Based on primary mean deviation criteria, 204 eyes (43.6%) in the high-frequency data set and 160 eyes (34.2%) in the low-frequency data set progressed (PϽ.001), whereas 185 eyes (39.5%) in the highfrequency data set and 167 eyes (35.7%) in the low-frequency data set progressed according to pointwise linear regression (P =.02). The high-frequency data set was more likely to detect progression with mean deviation (hazard ratio [HR], 1.69 [95% confidence interval {CI}, 1.36-2.10]) or pointwise linear regression criteria (HR, 1.52 [95% CI, 1.21-1.90]). A similar number of improving eyes were detected with mean deviation criteria (HR, 0.95 [95% CI, 0.58-1.60]), but pointwise linear regression criteria were more likely to detect improvement in the high-frequency data set (HR, 2.27 [95% CI, 1.43-3.62]). The results did not significantly change after censoring data at 5 years. Conclusions: Increasing the frequency of visual field testing leads to earlier detection of glaucoma progression, especially with global trend analyses. This finding has significant implications for the care of patients with glaucoma.
Glaucoma, an age-related eye disease, can lead to blindness if left untreated. The risk of blindness from glaucoma is relatively low but is determined largely by the severity of disease at diagnosis. It is likely that many of those who present late have rapidly progressing disease. Once diagnosed, a patient must be monitored for life using a machine that detects worsening (‘progression’) of their vision [‘visual field’ (VF)]. Patients with fast VF progression are in greater danger of going blind, in a given time frame, than patients with slow progression. However, VF test measurements can fluctuate considerably, meaning that patients need several tests over a period of time before any change can be detected or acted on – this can be expensive for the NHS. We set out to see if the benefits of extra tests were cost-effective. We first established, using a clinical audit, that patients are tested less frequently than is recommended in guidelines. Next, we found that eye doctors thought the idea of increased testing would be useful but not practical given current NHS resources. Patient interviews (focus groups) indicated that, although patients do not like VF testing, and some raised concerns about its current delivery, they accepted it as an important part of their clinical care. Another study, making predictions based on statistical analysis of large numbers of VF data, indicated that increasing frequency of VF testing could identify progression sooner than current practice. Furthermore, an examination of costs and benefits (health economics) suggested that increased monitoring of the VF in diagnosed patients is likely to also be cost-effective.
Role of Visual Field Reliability Indices in Ruling Out Glaucoma
JAMA Ophthalmology, 2015
IMPORTANCE Standard automated perimetry is the current criterion standard for assessment of visual field (VF) loss in glaucoma. The 3 commonly used reliability indices to judge the quality of standard automated perimetry results are fixation losses (FLs) and false-positive (FP) and false-negative (FN) response rates. However, the influence of reliability indices, when within the manufacturer-recommended limits, on VF classification has been sparsely studied. OBJECTIVE To evaluate the role of VF reliability indices in ruling out glaucoma.
British Journal of Ophthalmology, 2010
Aim To examine the level of agreement among nine clinicians in assessing progressive deterioration in visual field (VF) overview using three different methods of analysis. Methods Each visual field was assessed by Humphrey Field Analyzer (HFA), program 24-2 SITA Standard. Nine expert clinicians assessed the progression status of each series by using HFA 'overview printouts' (HFA OP), the Guided Progression Analysis (GPA) and the Guided Progression Analysis (GPA2). VF series were presented in random order, but each patient's VF remained in chronological order within a given field series. Each clinician adopted his personal methods based on his knowledge to evaluate VF progression. The level of agreement between the clinicians was evaluated by using weighted k statistics. Results A total of 303 tests, comprising 38 visual field series of 7.963.4 tests (mean6SD), were assessed by the nine glaucoma specialists. When the intra-observer agreement was evaluated between HFA OP and GPA, the mean k statistic was 0.5860.13, between HFA OP and GPA2, k was 0.5560.06 and between GPA and GPA2 it was 0.5660.17. When the inter-observer agreement was analysed k statistic was 0.65 for HFA OP, 0.54 for GPA and 0.70 for GPA2. Conclusions Using any procedure for evaluating the progression of a series of VF, agreement between expert clinicians is moderate. Clinicians had higher agreement when GPA2 was used, followed by HFA OP and GPA printouts, but these differences were not significant.
Detecting glaucomatous progression with infrequent visual field testing
Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists), 2018
Previous work has investigated whether a significant regression slope in the first 2 years for the summary index Mean Deviation (MD) is predictive of rapid (≤-2 dB year ) glaucomatous visual field progression. This work assumed six visual fields were obtained as per management guidelines, but in clinical practice commonly only two or three fields are measured. We used simulation methods to investigate how reducing test frequency influences the prediction of rapid visual field progression, along with the influence of including criteria based on regression slope. We simulated visual field series (N = 100 000) spaced annually in the first 2 years and then biennially. We calculated positive and negative predictive values (PPV & NPV) for detecting rapid progression, based on a criterion of a significant negative regression slope of any magnitude, or of a magnitude less than a particular limit. We performed a second simulation using test frequency and disease prevalence parameters from a ...
Controlled Clinical Trials, 1998
and the CIGTS Study Group 6 PURPOSE. To compare the baseline Collaborative Initial Glaucoma Treatment Study (CIGTS) visual field (VF) score and mean deviation (MD), investigate test-retest variability, and identify variables associated with VF loss and VF measurement variability. METHODS. Baseline data from a randomized clinical trial of 607 patients with newly diagnosed open-angle glaucoma were collected at 14 clinical centers. The CIGTS VF score and MD were obtained from 24-2 VF tests (Zeiss-Humphrey Systems, Dublin, CA) at two visits approximately 2 weeks apart. RESULTS. Although most baseline CIGTS VF scores showed limited field loss, 15% (91/607) of patients showed a substantial deficit (VF score Ͼ10 on a 0 -20 scale). A small but significant learning effect was seen over the two baseline measures for CIGTS VF score and MD. CIGTS VF score and MD correlate highly (r ϭ Ϫ0.93); both have high test-retest correlation (0.83 and 0.91, respectively). Variables associated with greater baseline VF loss for both CIGTS VF score and MD include (probabilities for VF only): male sex (P ϭ 0.018), black race (P Յ 0.0001), lower visual acuity (P Յ 0.0001), higher intraocular pressure if more than 30 mm Hg (P ϭ 0.0034), poor field reliability score (P Յ 0.0001), cardiovascular disease (P ϭ 0.015), reduced patient-reported alertness (P ϭ 0.023), and CIGTS clinical center (P Յ 0.0001). Predictors of increased CIGTS VF score variability include a midrange VF score (P Յ 0.0001), first-tested eye (P ϭ 0.0027), reduced patient-reported alertness (P ϭ 0.0177), increasing age (P ϭ 0.0040), current smoker (P ϭ 0.0014), and CIGTS clinical center (P ϭ 0.0215). CONCLUSIONS. The CIGTS VF score provides a measure of VF strikingly similar to the MD. Variables associated with VF loss and VF variability may help identify patients who need greater clinical scrutiny. (Invest Ophthalmol Vis Sci.