Faster Sensitivity Loss around Dense Scotomas than for Overall Macular Sensitivity in Stargardt Disease: ProgStar Report No. 14
Bibliographic record
Abstract
•This study reports a novel automated approach to quantify progression of visual dysfunction.•This automated approach was validated relative to a manual grading.•The progression rate at the disease front in Stargardt disease is reported.•The new method may allow shorter clinical trials or smaller cohorts or both. PurposeMean sensitivity (MS) derived from a standard test grid using microperimetry is a sensitive outcome measure in clinical trials investigating new treatments for degenerative retinal diseases. This study hypothesizes that the functional decline is faster at the edge of the dense scotoma (eMS) than by using the overall MS.DesignMulticenter, international, prospective cohort study: ProgStar Study.MethodsStargardt disease type 1 patients (carrying at least 1 mutation in the ABCA4 gene) were followed over 12 months using microperimetry with a Humphrey 10-2 test grid. Customized software was developed to automatically define and selectively follow the test points directly adjacent to the dense scotoma points and to calculate their mean sensitivity (eMS).ResultsAmong 361 eyes (185 patients), the mean age was 32.9 ± 15.1 years old. At baseline, MS was 10.4 ± 5.2 dB (n = 361), and the eMS was 9.3 ± 3.3 dB (n = 335). The yearly progression rate of MS (1.5 ± 2.1 dB/year) was significantly lower (β = −1.33; P < .001) than that for eMS (2.9 ± 2.9 dB/year). There were no differences between progression rates using automated grading and those using manual grading (β = .09; P = .461).ConclusionsIn Stargardt disease type 1, macular sensitivity declines significantly faster at the edge of the dense scotoma than in the overall test grid. An automated, time-efficient approach for extracting and grading eMS is possible and appears valid. Thus, eMS offers a valuable tool and sensitive outcome parameter with which to follow Stargardt patients in clinical trials, allowing clinical trial designs with shorter duration and/or smaller cohorts. Mean sensitivity (MS) derived from a standard test grid using microperimetry is a sensitive outcome measure in clinical trials investigating new treatments for degenerative retinal diseases. This study hypothesizes that the functional decline is faster at the edge of the dense scotoma (eMS) than by using the overall MS. Multicenter, international, prospective cohort study: ProgStar Study. Stargardt disease type 1 patients (carrying at least 1 mutation in the ABCA4 gene) were followed over 12 months using microperimetry with a Humphrey 10-2 test grid. Customized software was developed to automatically define and selectively follow the test points directly adjacent to the dense scotoma points and to calculate their mean sensitivity (eMS). Among 361 eyes (185 patients), the mean age was 32.9 ± 15.1 years old. At baseline, MS was 10.4 ± 5.2 dB (n = 361), and the eMS was 9.3 ± 3.3 dB (n = 335). The yearly progression rate of MS (1.5 ± 2.1 dB/year) was significantly lower (β = −1.33; P < .001) than that for eMS (2.9 ± 2.9 dB/year). There were no differences between progression rates using automated grading and those using manual grading (β = .09; P = .461). In Stargardt disease type 1, macular sensitivity declines significantly faster at the edge of the dense scotoma than in the overall test grid. An automated, time-efficient approach for extracting and grading eMS is possible and appears valid. Thus, eMS offers a valuable tool and sensitive outcome parameter with which to follow Stargardt patients in clinical trials, allowing clinical trial designs with shorter duration and/or smaller cohorts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".