Interobserver agreement of international classification of myopic maculopathy_Chinese Journal of Ocular Fundus Diseases

Authors：

He Hailong ¹ , Qi Yue ² , Fang Yuxin ² , Ma Ya ¹ , Liu Zhuolin ¹ , Song Hao ¹ ,  Jin Zibing ¹

1. Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing 100005, China;
2. Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100005, China;

Corresponding author：

Jin Zibing, Email: jinzb502@ccmu.edu.cn

Keywords：

Myopia, degenerative; Maculopathy; Consistency

DOI：

10.3760/cma.j.cn511434-20220330-00185

Video：

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Objective To observe the interobserver agreement of classification of macular degeneration in severe pathological myopia (PM) by ophthalmologists with different clinical experience. Methods A retrospective study. From January 2019 to December 2021, 171 eyes of 102 patients with severe PM macular degeneration who were examined at Eye Center of Beijing Tongren Hospital of Capital Medical University were included in the study. The clinical data such as age, gender, axial length, spherical equivalent power, fundus color photography, and optical coherence tomography (OCT) were collected in detail. Six independent ophthalmologists (A, B, C, D, E, F) classified each fundus photography based on META-PM and ATN classification of atrophy (A) system and interobserver agreement was assessed by Kappa statistics. According to the classification standard of traction (T) in the ATN classification, the OCT images were interpreted and classified, in which T0 was subdivided into retinal pigment epithelium (RPE) and choroidal thinning, choroidal neovascularization (CNV) with partial RPE and choroidal atrophy, RPE, and choroidal atrophy. Lamellar macular hole can't be classified by ATN system, which was defined as TX. Kappa (κ) test was used to analyze the consistency of classification results between physicians A, B, C, D, E and F. κ value ≤0.4 indicates low consistency, 0.4＜κ value ≤ 0.6 indicates moderate consistency, and κ value ＞0.6 indicates strong consistency. Results Among the 171 eyes of 102 cases, there were 20 males with 37 eyes (19.6%, 20/102), and 82 females with 134 eyes (80.4%, 82/102); age was 61.97±8.78 years; axial length was (30.87±1.93) mm; equivalent spherical power was (－16.56±7.00) D. Atrophy (A) classification results in META-PM classification and ATN classification, the consistency of physician A, B, C, D, E and physician F were 73.01%, 77.19%, 81.28%, 81.28%, 88.89%; κ value were 0.472, 0.538, 0.608, 0.610, 0.753, respectively. In the ATN classification, the T0, T1, T2, T3, T4, and T5 were in 109, 18, 11, 12, 9, and 8 eyes, respectively; TX was in 4 eyes. Conclusions There are differences in the consistency of classification of severe PM macular lesions among physicians with different clinical experience, and the consistency will gradually improve with the accumulation of clinical experience.

Citation： He Hailong, Qi Yue, Fang Yuxin, Ma Ya, Liu Zhuolin, Song Hao, Jin Zibing. Interobserver agreement of international classification of myopic maculopathy. Chinese Journal of Ocular Fundus Diseases, 2022, 38(6): 510-515. doi: 10.3760/cma.j.cn511434-20220330-00185 Copy

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11.	Fang Y, Yokoi T, Nagaoka N, et al. Progression of myopic maculopathy during 18-year follow-up[J]. Ophthalmology, 2018, 125(6): 863-877. DOI: 10.1016/j.ophtha.2017.12.005.
12.	Zhang RR, Yu Y, Hou YF, et al. Intra- and interobserver concordance of a new classification system for myopic maculopathy[J]. BMC Ophthalmol, 2021, 21(1): 187. DOI: 10.1186/s12886-021-01940-4.
13.	Tian J, Qi Y, Lin C, et al. The association in myopic tractional maculopathy with myopic atrophy maculopathy[J/OL]. Front Med (Lausanne), 2021, 8: 679192[2021-08-20]. https://pubmed.ncbi.nlm.nih.gov/34490288/. DOI: 10.3389/fmed.2021.679192.
14.	Matsumura S, Sabanayagam C, Wong CW, et al. Characteristics of myopic traction maculopathy in myopic Singaporean adults[J]. Br J Ophthalmol, 2021, 105(4): 531-537. DOI: 10.1136/bjophthalmol-2020-316182.
15.	Fang Y, Du R, Nagaoka N, et al. OCT-based diagnostic criteria for different stages of myopic maculopathy[J]. Ophthalmology, 2019, 126(7): 1018-1032. DOI: 10.1016/j.ophtha.2019.01.012.
16.	dell'Omo R, Virgili G, Bottoni F, et al. Lamellar macular holes in the eyes with pathological myopia[J]. Graefe's Arch Clin Exp Ophthalmol, 2018, 256(7): 1281-1290. DOI: 10.1007/s00417-018-3995-8.
17.	Hemelings R, Elen B, Blaschko MB, et al. Pathological myopia classification with simultaneous lesion segmentation using deep learning[J/OL]. Comput Methods Programs Biomed, 2021, 199: 105920[2020-12-28]. https://pubmed.ncbi.nlm.nih.gov/33412285/. DOI: 10.1016/j.cmpb.2020.105920.
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1. Tang Y, Wang X, Wang J, et al. Prevalence and causes of visual impairment in a Chinese adult population: the Taizhou eye study[J]. Ophthalmology, 2015, 122(7): 1480-1488. DOI: 10.1016/j.ophtha.2015.03.022.
2. Ohno-Matsui K, Kawasaki R, Jonas JB, et al. International photographic classification and grading system for myopic maculopathy[J]. Am J Ophthalmol, 2015, 159: 877-883. DOI: 10.1016/j.ajo.2015.01.022.
3. Ruiz-Medrano J, Montero JA, Flores-Moreno I, et al. Myopic maculopathy: current status and proposal for a new classification and grading system (ATN)[J]. Prog Retin Eye Res, 2019, 69: 80-115. DOI: 10.1016/j.preteyeres.2018.10.005.
4. Ruiz-Medrano J, Flores-Moreno I, Ohno-Matsui K, et al. Validation of the recently developed ATN classification and grading system for myopic maculopathy[J]. Retina, 2020, 40(11): 2113-2118. DOI: 10.1097/IAE.0000000000002725.
5. Chen Q, He J, Hu G, et al. Morphological characteristics and risk factors of myopic maculopathy in an older high myopia population-based on the new classification system (ATN)[J]. Am J Ophthalmol, 2019, 208: 356-366. DOI: 10.1016/j.ajo.2019.07.010.
6. Wong CW, Phua V, Lee SY, et al. Is choroidal or scleral thickness related to myopic macular degeneration?[J]. Invest Ophthalmol Vis Sci, 2017, 58(2): 907-913. DOI: 10.1167/iovs.16-20742.
7. Viera AJ, Garrett JM. Understanding interobserver agreement: the kappa statistic[J]. Fam Med, 2005, 37(5): 360-363.
8. Ye L, Chen Q, Hu G, et al. Distribution and association of visual impairment with myopic maculopathy across age groups among highly myopic eyes-based on the new classification system (ATN)[J]. Acta Ophthalmol, 2022, 100(4): 957-967. DOI: 10.1111/aos.15020.
9. Lin C, Li SM, Ohno-Matsui K, et al. Five-year incidence and progression of myopic maculopathy in a rural Chinese adult population: the Handan eye study[J]. Ophthalmic Physiol Opt, 2018, 38(3): 337-345. DOI: 10.1111/opo.12456.
10. Yan YN, Wang YX, Yang Y, et al. Ten-year progression of myopic maculopathy: the Beijing eye study 2001-2011[J]. Ophthalmology, 2018, 125(8): 1253-1263. DOI: 10.1016/j.ophtha.2018.01.035.
11. Fang Y, Yokoi T, Nagaoka N, et al. Progression of myopic maculopathy during 18-year follow-up[J]. Ophthalmology, 2018, 125(6): 863-877. DOI: 10.1016/j.ophtha.2017.12.005.
12. Zhang RR, Yu Y, Hou YF, et al. Intra- and interobserver concordance of a new classification system for myopic maculopathy[J]. BMC Ophthalmol, 2021, 21(1): 187. DOI: 10.1186/s12886-021-01940-4.
13. Tian J, Qi Y, Lin C, et al. The association in myopic tractional maculopathy with myopic atrophy maculopathy[J/OL]. Front Med (Lausanne), 2021, 8: 679192[2021-08-20]. https://pubmed.ncbi.nlm.nih.gov/34490288/. DOI: 10.3389/fmed.2021.679192.
14. Matsumura S, Sabanayagam C, Wong CW, et al. Characteristics of myopic traction maculopathy in myopic Singaporean adults[J]. Br J Ophthalmol, 2021, 105(4): 531-537. DOI: 10.1136/bjophthalmol-2020-316182.
15. Fang Y, Du R, Nagaoka N, et al. OCT-based diagnostic criteria for different stages of myopic maculopathy[J]. Ophthalmology, 2019, 126(7): 1018-1032. DOI: 10.1016/j.ophtha.2019.01.012.
16. dell'Omo R, Virgili G, Bottoni F, et al. Lamellar macular holes in the eyes with pathological myopia[J]. Graefe's Arch Clin Exp Ophthalmol, 2018, 256(7): 1281-1290. DOI: 10.1007/s00417-018-3995-8.
17. Hemelings R, Elen B, Blaschko MB, et al. Pathological myopia classification with simultaneous lesion segmentation using deep learning[J/OL]. Comput Methods Programs Biomed, 2021, 199: 105920[2020-12-28]. https://pubmed.ncbi.nlm.nih.gov/33412285/. DOI: 10.1016/j.cmpb.2020.105920.
18. Shao L, Zhang QL, Long TF, et al. Quantitative assessment of fundus tessellated density and associated factors in fundus images using artificial intelligence[J]. Transl Vis Sci Technol, 2021, 10(9): 23. DOI: 10.1167/tvst.10.9.23.

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Interobserver agreement of international classification of myopic maculopathy

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