Table 1.
Summary of general characteristics of studies included in the review.
| Author(s), (Publication Year) | Study design* | Country | Eye disease | Sample size | Mean age (SD) | Sex (males / females) | Study aim classification |
|---|---|---|---|---|---|---|---|
| Dry Eye, Sjögren’s Syndrome, Meibomian Gland Dysfunction | |||||||
| Aqrawi et al., (2017) | Cross-sectional | Norway | Sjögren’s |
pSS: 27 C: 32 |
pSS: 52.40 (12.22) C: - |
pSS: - C: - |
Biomarker discovery Identification of pathophysiology |
| González et al., (2020) |
Prospective case-controlled |
Spain |
DE MGD |
DE: 29 MGD: 27 CT: 37 |
DE: 52.1 (13.5) MGD: 53.4 (15.2) CT: 40.2 (12.5) |
DE: 10/19 MGD: 11/16 CT: 13/24 |
Biomarker discovery Identification of pathophysiology |
| Grus et al., (2005) | Cross-sectional | Germany | DE |
DE: 88 CT: 71 |
– | – |
Biomarker discovery Identification of pathophysiology |
| Huang et al., (2018) | Cross-sectional | China | DE | – | – | – |
Biomarker discovery Identification of pathophysiology |
| Ji et al., (2019) | Prospective cohort | South Korea | DE |
CsA: 9 DQ3: 9 |
CsA: 46.2 (1.4) DQ3: 53.3 (15.5) |
CsA: 4/5 DQ3: 4/5 |
Disease severity Treatment outcome |
| Jiang et al., (2020) | Cross-sectional | China | DE |
DE: 85 CT: 28 |
DE: 55.4 (8.8) CT: 60.8 (11.2) |
DE: 50/35 CT: 15/13 |
Biomarker discovery Identification of pathophysiology |
| Piyacomm et al., (2019) | Prospective RCT | Thailand | MGD |
IPL: 57 Sham: 57 |
IPL: 59.0 (12.7) Sham: 59.5 (11.4) |
IPL: 10/47 Sham: 5/52 |
Treatment outcome |
| Sembler-Møller et al., (2020) | Cross-sectional | Denmark | Sjögren’s |
pSS: 24 C: 16 |
pSS: 55 (11) C: 53 (16) |
pSS: 2/22 C: 2/14 |
Biomarker discovery Identification of pathophysiology |
| Soria et al., (2013) | Cross-sectional | Spain |
DE MGD CT |
DE: 63 MGD: 38 CT: 43 |
DE: 55.3 (14.1) MGD: 63.4 (16.6) CT: 42.7 (14.0) |
DE: 31/32 MGD: 22/16 CT: 27/16 |
Biomarker discovery Identification of pathophysiology |
| Srinivasan et al., (2012) | Cross-sectional | Canada | DE |
NDE:6 MDE:6 MSDE:6 MXDE: 6 |
NDE: 29.8 (8.1) MDE: 59.6 (16) MSDE: 45.2 (10.5) MXDE: 36.7 (17) |
NDE: 2/4 MDE:2/4 MSDE:2/4 MXDE:4/2 |
Biomarker discovery Identification of pathophysiology |
| Tong et al., (2017) | Prospective cohort | Singapore | DE | 23 | 49.8 (14) | 6/23 | Treatment outcome |
| Zou et al., (2020) | Cross-sectional | China |
Adult DM w/ DE Child DM w/ DE Adult DM Child DM |
Adult DM w/ DE: 10 Child DM w/ DE:10 Adult DM:10 Child DM:10 Adult CT:10 Child CT:10 |
Adult DM w/ DE: 58.8 (4.3) Child DM w/ DE: 11.7 (2.8) Adult DM: 57.7 (7.2) Child DM: 12 (3.3) Adult CT: 58 (4.3) Child CT: 11.2 (1.3) |
Adult DM w/ DE: 6/4 Child DM w/ DE: 6/4 Adult DM: 7/3 Child DM: 6/4 Adult CT: 7/3 Child CT: 6/4 |
Biomarker discovery Identification of pathophysiology |
| Keratoconus and other Corneal Diseases | |||||||
| Borges et al., (2020) | Cross-sectional | Germany |
KC Pterygium GVHD |
KC: 4 Pterygium: 9 GVHD: 10 CT: 6 |
KC: 30.5 Pterygium: 47.2 GVHD: 49.6 CT: 47.5 |
KC: 2/2 Pterygium: 6/3 GVHD: 3/7 CT:1/5 |
Biomarker discovery Identification of pathophysiology |
| Fodor et al., (2009) | Prospective cohort | Hungary | PKP‡ | PKP: 12 | PKP: 45 (14.2) | PKP: 8/4 |
Treatment outcome Prognosis |
| Fodor et al., (2021) | Prospective cohort | Hungary | KC | KC: 45 | KC: 34 (12.3) | KC: 30/15 | Prognosis |
| Kim et al., (2014) | Cross-sectional | South Korea | Pterygium |
Pterygium: 24 HCC: 24 |
Pterygium: 49 (5.2) HCC: 49 (5.2) |
Pterygium: 10/14 HCC: 10/14 |
Biomarker discovery Identification of pathophysiology |
| Leonardi et al., (2014) | Cross-sectional | Italy | VKC |
VKC: 18 C: 10 |
VKC: 10.06 (4.76) C: - |
VKC:16/2 C:- |
Biomarker discovery Identification of pathophysiology Treatment outcome |
| Linghu et al., (2017) | Cross-sectional | China | Pterygium | Pterygium: 10 | Pterygium: 52 | Pterygium: 6/4 | Risk factors |
| Menegay et al., (2008) | Cross-sectional | U.S. Germany | CDKDE |
CDK: 2 C: - DE: 88 CT: 71 |
CDK: 69.5 (3.54) C:-- |
CDK:2/0 C:-- |
Biomarker discovery Identification of pathophysiology Biomarker discovery Identification of pathophysiology |
| O’Leary et al., (2020) | Cross-sectional | Switzerland | oGVHD |
NIH 0: 14 NIH 1: 9 NIH 2: 16 NIH 3: 10 |
NIH 0: 56.1 (9.6) NIH 1: 48.4 (15.4) NIH 2: 52.6 (14.0) NIH 3: 52.6 (15.2) |
NIH 0: 9/5 NIH 1:7/2 NIH 2: 9/7 NIH 3:10/1 |
Treatment outcome Prognosis |
| Soria et al., (2015) | Cross-sectional | Spain | KC |
KC: 5 Myopic: 5 |
KC: 34.2 (9.6) Myopic: 36 (7.5) |
KC: 4/1 Myopic: 3/2 |
Biomarker discovery Identification of pathophysiology |
| Wojakoswka et al., (2020) | Cross-sectional | Poland | KC |
KC: 7 C: 6 |
KC: 42–59 C: 40–69 |
- |
Biomarker discovery Identification of pathophysiology |
| Yawata et al., (2020) | Prospective cohort | Japan |
BK FED |
BK: 19 FED: 2 |
BK: 69.8 (15.1) FED: 73.2 (11.3) |
BK: 9/10 FED:2/0 |
Treatment outcome Prognosis |
CsA topical cyclosporine A, DQS diquafosol tetrasodium, NDE no symptoms and sign, MDE mildly symptomatic with aqueous deficiency, MSDE symptomatic aqueous deficiency, MXDE combination group, KC keratoconus, GVD graft-versus-host-disease, MGD meibomian gland dysfunction, DE dry eye, DM diabetes, w/ with, CDK climatic droplet keratopathy, BK bullous keratopathy, FED Fuchs’ endothelial dystrophy, PKP penetrating keratoplasty, VKC vernal keratoconjunctivitis, IPL intense pulsed light, oGVHD ocular graft versus host disease, NIH National institute of health, NIH 0 normal no symptoms, NIH 1 mild no effect on activities of daily living, hydrating drops <3 time/day, NIH 2 moderate, some effect on activities of daily living, loss of vision caused by keratopathy, pSS primary Sjögren’s syndrome (pSS), HCC healthy conjunctiva from the same patient who underwent pterygium excision.
‡PKP patients with various indications: bullous keratopathy (1), keratoconus (3), salzmann’s nodular degeneration (2), herpes keratitis, transplant rejection (2), Haab-Dimmer dystrophy, recurrence of dystrophy (2), chronic superficial keratitis (pannus) (1), bullous keratopathy, transplant rejection.
Controls refers to healthy individuals unless otherwise specified.
Validation refers to an additional analysis based on discovered candidate proteins performed on a new sample.
Treatment outcome refers to articles that analysed biofluids using AI/bioinformatics with the purpose of predicting treatment responses.
Biomarker discovery or identification of pathophysiology refers to articles that analysed biofluids using AI/bioinformatics with the purpose of identifying candidate markers for ocular surface disease pathogenesis, classify ocular surface diseases based on identified biofluids, or classify different subgroups within one ocular surface disease category based on biofluids.