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Original Article

Using Decision Curve Analysis to Evaluate Common Strategies for Myopia Screening in School-Aged Children

, , , &
Pages 286-294 | Received 19 Nov 2018, Accepted 04 May 2019, Published online: 16 May 2019
 

ABSTRACT

Purpose: To evaluate common strategies for screening myopia.

Methods: A total of 2,248 children aged 6 to 12 years from five randomly selected primary schools were included for the screening. Enrolled study participants underwent distant uncorrected visual acuity (UCVA, Standard Logarithmic Visual Acuity E Chart) and non-cycloplegic auto-refraction (NCAR, Topcon KR-8800). Among them, 1,639 children (72.9%) accepted cycloplegic auto-refraction. Taking rejection of cycloplegia into account, receiver operating characteristic curves were drawn to compare the accuracies of the four strategies (I, Cycloplegic auto-refraction; II, NCAR; III, UCVA; IV, Combination of UCVA and NCAR). Decision curve analysis (DCA) was used to compare net benefits. Tenfold cross-validation was used for statistical analyses.

Results: For myopia (spherical equivalent refraction, SE ≤ −0.5D) screening, the mean sensitivities were 73.79% (SD: 5.40%), 85.57% (6.84%), 59.71% (13.49%), and 85.06% (6.68%) for Strategy I to IV; with mean specificities of 100% (0%), 87.43% (4.27%), 89.74% (10.25%), and 88.65% (5.07%), respectively. For screening early myopia (SE ≤ −0.5D and ≥−1.0D), the mean sensitivities were 73.44% (7.69%), 82.39% (5.32%), 54.27% (14.58%), and 81.76% (9.60%) for Strategy I to IV; with mean specificities of 100% (0%), 79.13% (4.86%), 85.48% (9.86%), and 81.17% (4.16%). Based on DCA, the net benefits of Strategy IV were the highest, with the probability thresholds ranging from 12% to 50%, after adjusting the TestHarms. For early myopia, the net benefits of Strategy IV were the highest with the probability threshold ranging from 5% to 34%.

Conclusion: Combination of UCVA and NCAR produced the highest net benefits for myopia screening.

Acknowledgments

We thank Prof. Andrew Vickers for his guidance of solving problems we met while using the DCA methods.

Disclosure statement

None of the authors have any proprietary interests or conflicts of interest related to this submission.

Additional information

Funding

The study was funded by Chinese National Nature Science Foundation (Project number 81670898 and 81800881). The Chronic Diseases Prevention and Treatment Project of Shanghai Shen Kang Hospital Development Centre (Grant No·SHDC12015315, SHDC2015644); The Shanghai Three Year Public Health Action Program (Project No·GWIV-3·3); The Shanghai High-level Oversea Training Team Program on Eye Public Health (Project No·GWTD2015S08); The Shanghai Outstanding Academic Leader Program (Project No·16XD1402300); Shanghai Municipal Commission of Health and Family Planning Grant (Project No·201440529); The Science and Technology Commission of Shanghai Municipality (Project No. 17511107901); Shanghai Municipal Education Commission – Gaofeng Clinical Medicine Grant Support (Project No. 20172022); Natural Science Foundation of Shanghai (15ZR1438400); Shanghai Sailing Program (17YF1415400); and Foundation of Shanghai Municipal Health Commission (20184Y0217).

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