The Potential of a Small Melanocytic Lesion to Transform into Choroidal Melanoma: A Retrospective Study and Literature Review

The Potential of a Small Melanocytic Lesion to Transform into Choroidal Melanoma: A Retrospective Study and Literature Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Potential of a Small Melanocytic Lesion to Transform into Choroidal Melanoma: A Retrospective Study and Literature Review Sara Garcia-Caride, Laura Formoso, Elia De Esteban Maciñeira, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3927201/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose This research aimed to identify critical risk factors for the malignant transformation of small melanocytic choroidal lesions (SMCL) Methods A retrospective longitudinal study was conducted on 218 SMCL cases at the University Hospital of Santiago de Compostela from January 2013 to January 2023. Patients were selected based on their diagnosis of SMCL and their undergoing of comprehensive multimodal imaging such as optical coherence tomography, ultrasonography, and fundus autofluorescence. The primary focus was on evaluating demographic data, symptomatic presentations, and detailed imaging features. Results The cohort consisted of 43% males and 57% females, with a mean age of 69 years. Notably, 19% of the lesions were symptomatic, and 25.5% exhibited orange pigment. Approximately 33% of the tumours were proximate to the optic disc. Multivariate analysis revealed orange pigment presence and a lesion height greater than 2 mm as significant predictors of transformation. The Cox and Snell R-squared coefficient of 0.292 indicated that these factors accounted for about 29.2% of the variability in lesion transformation. The average follow-up period was 52 months, during which 4.6% of the SMCLs evolved into CM. Conclusion This study highlights the substantial role of lesion height exceeding 2 mm and the presence of orange pigment as key risk factors for the transformation of SMCL into CM. These findings are instrumental in aiding clinicians to identify and monitor high-risk patients, enabling early and potentially more effective interventions. Future research is essential to further explore these risk factors and to establish a more comprehensive understanding of SMCL progression to CM. Choroidal melanoma Melanocytic lesions Risk factors Retrospective study Literature review Introduction Uveal melanoma encompasses lesions originating from the uvea, which includes the iris, ciliary body, and choroid, with choroidal melanoma (CM) being the most frequent subtype. The pathogenesis of uveal melanoma is distinct from that of cutaneous melanoma and is less understood. Risk factors specific to uveal melanoma include ocular and cutaneous pigmentation, UV exposure, and genetic predispositions. Recent advancements in molecular biology have shed light on genetic mutations and chromosomal aberrations associated with uveal melanoma, contributing to a better understanding of its pathogenesis and potential therapeutic targets.[1] In the context of choroidal nevus (CN) transforming into CM, several clinical and imaging factors have been identified as predictive markers. These include lesion thickness greater than 2 mm, the presence of subretinal fluid, symptoms indicative of visual acuity reduction to 20/50 or worse, the presence of orange pigment on the lesion, and a marginal location near the optic disc. The annual risk of a choroidal nevus transforming into malignant melanoma is estimated to be approximately 1 in 8,845.[2, 3] However, this statistic underscores the importance of rigorous monitoring and early identification of high-risk lesions. The primary objective of this study is to elucidate the risk factors associated with the malignant transformation of small melanocytic choroidal lesions (SMCL) into melanoma, particularly focusing on CN. Choroidal nevus, a prevalent ocular finding, is generally benign but holds the potential to transform into CM. CM represents a significant form of uveal melanoma, the most common primary intraocular malignancy in adults. The transformation from CN to CM is a critical clinical concern due to the aggressive nature of CM, which can result in severe visual impairment and potentially be life-threatening.[4] Our study aims to contribute significant insights into the risk factors and clinical indicators that may signal the malignant transformation of choroidal nevus into melanoma. By identifying these risk factors, clinicians can better monitor patients with CN, enabling early intervention and potentially improving prognostic outcomes for those at heightened risk of developing CM. This revised introduction provides a more detailed context of SMCL, CN, and CM, emphasizing the importance of understanding and identifying the risk factors associated with the malignant transformation of CN into CM. It also places the study within the broader framework of uveal melanoma research, highlighting its clinical significance. METHODS Our study involved a cohort of small melanocytic choroidal lesions (SMCL) from the adult tumour unit at the University Hospital of Santiago de Compostela. The aim was to assess the risk of these lesions transforming into choroidal melanoma. This research received approval from the local Institutional Ethics Committee (Registration Code: 2009/128) and was conducted in accordance with the principles of the Declaration of Helsinki. This retrospective longitudinal study analysed follow-ups of 218 SMCL cases. It encompassed patients who visited the unit consecutively between January 2013 and January 2023 and met the inclusion criteria. Inclusion criteria were defined as patients diagnosed with SMCL who underwent comprehensive multimodal imaging, including optical coherence tomography (OCT), ultrasonography (US), and fundus autofluorescence (AF), and for whom follow-up data were available. Patients were excluded if the required imaging tests could not be performed. Enrolment of patients occurred at their initial visit, with subsequent follow-ups scheduled every three months. All examinations were conducted by one of the senior authors, utilizing advanced techniques such as indirect ophthalmoscopy for full fundus evaluation and high-resolution magnification ophthalmoscopy (using Goldman or 90-diopter lens with slit lamp biomicroscopy) for detailed assessment of the nevus or macula, when necessary and feasible. Fundus photography was also routinely performed. Clinical data collected during the initial examination included patient demographics (age and sex), symptoms, and best-corrected visual acuity, measured using decimal charts. Additional data encompassed the quadrantic location of the tumour epicenter (inferior, temporal, superior, nasal, or macula), proximity of the nearest tumour margin to the optic disc and foveola (measured in millimetres), largest tumour basal dimension and thickness (in millimetres), and the presence of an amelanotic halo and orange pigment. Imaging characteristics of CN were evaluated using OCT, AF, and US. Particular attention was paid to variables identified by Shields et al. as risk factors for progression to CM. A key variable monitored during follow-up was the transformation to melanoma. This was determined by expert physicians based on criteria such as a minimum enlargement of 0.5 mm in basal dimension or thickness, increased thickness, presence of subretinal fluid, symptoms, orange pigment, proximity to the optic disc margin, ultrasonographic hollowness, and absence of a halo. Qualitative variables were presented in terms of absolute and relative frequencies. Quantitative variables were summarized using mean and standard deviation (±SD). The chi-square statistical test was employed to compare characteristics and progression in patients with SMCL under observation. A subsequent multivariate analysis was conducted on variables identified as significant in the preliminary analysis. This approach is crucial in understanding a complex phenomenon like the transformation to choroidal melanoma, where multiple interrelated factors may collectively influence the outcome. Confounding variables, potentially representing additional risk factors, were considered for both the primary outcome (conversion to choroidal melanoma) and predictor variables identified in the univariate analysis. In the multivariate analysis, various variables were evaluated in relation to the transformation of SMCL. Results are reported in terms of coefficients (B), standard errors, statistical significance (Sig.), odds ratios (OR), and 95% confidence intervals for these ratios. RESULTS In this study, 218 small choroidal melanocytic lesions (SMCLs) were analysed. Of these, 43% (94 individuals) were male and 57% (123 individuals) were female. The mean age of the subjects was 69 years, with a standard deviation of 15 years. Tumour characteristic revealed that 19% of cases were symptomatic and 25.5% exhibited orange pigment. Approximately 33% of tumours were in proximity to the optic disc. Optical coherence tomography (OCT) characteristics included subretinal fluid in 26.3% of cases, choroidal neovascularization in 1.4%, and the presence of drusen in 57.4%. Autofluorescence (AF) imaging indicated that 25.5% of cases had orange pigment (Table 1). For choroidal nevi with more than three risk factors, the mean age was 64.78 years (±15), intraocular pressure (IOP) averaged 14.4 mmHg (±3), and visual acuity was 0.76 (±0.9). Tumour sizes were measured in terms of longitudinal base and height, with an average transversal base of 7.70 mm (±2) and an average transversal height of 1.45 mm (±0.62) (Table 2). During the follow-up period, 4.6% (10 cases) of SMCLs transformed into CM. The mean follow-up duration was 52 months, ranging from 3 to 113 months. Table 3 provides an analysis of various initial presentation factors and their correlation with the growth of choroidal nevus into melanoma. It was observed that 43% of males and 57% of females did not progress to melanoma. Gender did not show a significant difference in terms of transformation risk (p = 0.662). However, the presence of symptoms (p < 0.001), orange pigment (p < 0.001), and a height greater than 2mm (p < 0.001) were significantly associated with the transformation to CM. The multivariate analysis revealed that the variable 'Orange pigment' had a coefficient (B) of 4.331, with a standard error of 1.589 and a statistically significant odds ratio (OR) of 76.031, suggesting a notably higher likelihood of transformation in cases with orange pigment. The variable 'Height > 2mm' had a coefficient (B) of 4.980, standard error of 1.477, and an OR of 145.480, indicating a significantly increased risk of transformation for lesions exceeding 2mm in height. The 'Symptoms' variable, with a coefficient (B) of 1.952 and an OR of 7.046, demonstrated an association with transformation risk, though it did not reach conventional statistical significance (Table 4). The Cox and Snell R-squared coefficient was calculated as 0.292, indicating that the model accounts for approximately 29.2% of the variability in lesion transformation. This suggests that while the factors of orange pigment, height greater than 2mm, and symptoms are significant predictors, other unaccounted factors may also influence the progression to choroidal melanoma. DISCUSION Our study has elucidated that a lesion height exceeding 2 mm, as ascertained through ultrasonography (US), coupled with the presence of orange pigment, are the exclusive statistically significant risk factors for the transformation of SMCL into CM. This revelation is congruent with preceding scholarly inquiries, which have identified a lesion thickness surpassing 2 mm as a pivotal risk factor in such malignant transformations (references 3, 5, 6). Complementary studies have further delineated risk factors including subretinal fluid, symptomatic presentation, orange pigment, proximity to the optic disc, ultrasonographic hollowness, and the absence of a halo, all contributing to the transformation of SMCL into CM. Moreover, a synthesis of features discerned via multimodal imaging has been recognized as prognostic of SMCL progression to CM.[3, 5, 6] The seminal research conducted by Augsburger et al.[7] was at the forefront of exploring risk factors in these lesions. Their analysis revealed that certain characteristics, notably a base size exceeding 5 mm, a height greater than 1.5 mm, juxtapapillary location, symptomatology, presence of orange pigment, and subretinal fluid, were significantly correlated with an augmented risk of lesion growth. These initial findings have been substantiated through ensuing, larger-scale retrospective analyses.[8] In the ambit of the Collaborative Ocular Melanoma Study (COMS)[9], a prospective investigation discerned that the existence of orange pigment, the absence of drusen, and adjacent alterations in the retinal pigment epithelium (RPE) were indicative of an elevated risk of growth in LCMPT. However, this study did not establish any associations with the proximity to the optic nerve or the presence of subretinal fluid. The investigative efforts of Shields et al.[10] have identified a compendium of factors predictive of melanoma genesis, encompassing increased lesion thickness, subretinal fluid, symptoms, orange pigment, proximity to the optic disc, ultrasonographic hollowness, and the absence of a halo. Furthermore, it was determined that the annual rate of malignant transformation from CN to CM is approximately 1 in 8,845, with an increasing propensity with advancing age.[2, 11] The identification of these risk factors is imperative for clinicians in the meticulous monitoring of patients with CN, thereby facilitating the identification of individuals at an elevated risk of developing CM. The scholarly article by Harbour et al.[12] leveraged a validated genomic biomarker to evaluate risk factors and their correlation with the transformation of these lesions. Focusing on clinical and pathological characteristics such as tumour size and thickness, presence of retinal detachment, orange pigment, drusen, RPE fibrosis, atrophy, visual symptoms, and documented tumour growth, the study deduced that no singular clinical feature or amalgamation thereof is pathognomonic for the transformation of these lesions into melanoma. Specifically, a definitive clinical or pathological profile signifying malignant conversion was not identified. Nonetheless, patient age and tumour thickness emerged as potentially indicative of small choroidal melanocytic tumours with a higher likelihood of possessing a class 2 genomic profile, associated with malignant progression. Further corroboration from an additional study[3] emphasized the significance of cytogenetic analysis as an instrumental tool in the assessment and management of LCMPT transformation cases, with prevalent chromosomal alterations such as gains on chromosomes 6p, 8q, 11q, and losses on chromosome 3, predominantly observed in melanomas of higher grade and larger dimensions. A comprehensive summary of the studies pertinent to this subject matter is succinctly encapsulated in Table 5, which offers a consolidated overview of the various research endeavours undertaken in this domain. Notwithstanding, our study is subject to certain limitations, including a relatively modest sample size and a follow-up period that may not comprehensively capture all instances of SMCL transformation into CM. The retrospective nature of this study may inherently introduce biases into the findings. Despite these limitations, our study contributes valuable insights into the risk factors for the transformation of CN into CM, which are instrumental in identifying CNs warranting rigorous monitoring or therapeutic intervention.[12] The study also accentuates the pivotal role of US in detecting CNs predisposed to transformation into CM.[13] In summary, our research corroborates the critical importance of identifying risk factors for the transformation of CN into CM. Such identification enables clinicians to more effectively surveil patients with CN and discern those with an increased risk of developing CM. Future investigations are warranted to validate these findings and to unearth additional risk factors for the transformation of SMCL into CM. Declarations Conflicts of Interest Statement: We declare that we have no conflicts of interest. Author Contribution S.G., M.B. and L.F. wrote the main manuscript text and E.M., M.B. recollected data, P.S. and M.P prepared tables. All authors reviewed the manuscript. References Jager MJ, Shields CL, Cebulla CM, Abdel-Rahman MH, Grossniklaus HE, Stern MH, Carvajal RD, Belfort RN, Jia R, Shields JA, Damato BE (2020) Uveal melanoma. Nat Rev Dis Primers 6: 24 DOI 10.1038/s41572-020-0158-0 Singh AD, Kalyani P, Topham A (2005) Estimating the risk of malignant transformation of a choroidal nevus. Ophthalmology 112: 1784–1789 DOI 10.1016/j.ophtha.2005.06.011 Shields CL, Dalvin LA, Ancona-Lezama D, Yu MD, Di Nicola M, Williams BK, Jr., Lucio-Alvarez JA, Ang SM, Maloney S, Welch RJ, Shields JA (2019) CHOROIDAL NEVUS IMAGING FEATURES IN 3,806 CASES AND RISK FACTORS FOR TRANSFORMATION INTO MELANOMA IN 2,355 CASES: The 2020 Taylor R. Smith and Victor T. Curtin Lecture. Retina 39: 1840–1851 DOI 10.1097/IAE.0000000000002440 Rodriguez-Vidal C, Fernandez-Diaz D, Fernandez-Marta B, Lago-Baameiro N, Pardo M, Silva P, Paniagua L, Blanco-Teijeiro MJ, Pineiro A, Bande M (2020) Treatment of Metastatic Uveal Melanoma: Systematic Review. Cancers (Basel) 12 DOI 10.3390/cancers12092557 Obuchowska I, Konopinska J (2022) Importance of Optical Coherence Tomography and Optical Coherence Tomography Angiography in the Imaging and Differentiation of Choroidal Melanoma: A Review. Cancers (Basel) 14 DOI 10.3390/cancers14143354 Gunduz K, Pulido JS, Ezzat K, Salomao D, Hann C (2009) Review of fundus autofluorescence in choroidal melanocytic lesions. Eye (Lond) 23: 497–503 DOI 10.1038/eye.2008.244 Augsburger JJ, Schroeder RP, Territo C, Gamel JW, Shields JA (1989) Clinical parameters predictive of enlargement of melanocytic choroidal lesions. Br J Ophthalmol 73: 911–917 DOI 10.1136/bjo.73.11.911 Butler P, Char DH, Zarbin M, Kroll S (1994) Natural history of indeterminate pigmented choroidal tumors. Ophthalmology 101: 710–716; discussion 717 DOI 10.1016/s0161-6420(94)31274-7 (1997) Factors predictive of growth and treatment of small choroidal melanoma: COMS Report No. 5. The Collaborative Ocular Melanoma Study Group. Arch Ophthalmol 115: 1537–1544 DOI 10.1001/archopht.1997.01100160707007 Shields CL, Furuta M, Berman EL, Zahler JD, Hoberman DM, Dinh DH, Mashayekhi A, Shields JA (2009) Choroidal nevus transformation into melanoma: analysis of 2514 consecutive cases. Arch Ophthalmol 127: 981–987 DOI 10.1001/archophthalmol.2009.151 Kivela T, Eskelin S (2006) Transformation of nevus to melanoma. Ophthalmology 113: 887–888 e881 DOI 10.1016/j.ophtha.2006.01.047 Harbour JW, Paez-Escamilla M, Cai L, Walter SD, Augsburger JJ, Correa ZM (2019) Are Risk Factors for Growth of Choroidal Nevi Associated With Malignant Transformation? Assessment With a Validated Genomic Biomarker. Am J Ophthalmol 197: 168–179 DOI 10.1016/j.ajo.2018.08.045 Gass JD (1977) Problems in the differential diagnosis of choroidal nevi and malignant melanomas. The XXXIII Edward Jackson Memorial Lecture. Am J Ophthalmol 83: 299–323 DOI 10.1089/ten.2005.11.1254 Singh AD, Mokashi AA, Bena JF, Jacques R, Rundle PA, Rennie IG (2006) Small choroidal melanocytic lesions: features predictive of growth. Ophthalmology 113: 1032–1039 DOI 10.1016/j.ophtha.2006.01.053 Lane AM, Egan KM, Kim IK, Gragoudas ES (2010) Mortality after diagnosis of small melanocytic lesions of the choroid. Arch Ophthalmol 128: 996–1000 DOI 10.1001/archophthalmol.2010.166 Mashayekhi A, Siu S, Shields CL, Shields JA (2011) Slow enlargement of choroidal nevi: a long-term follow-up study. Ophthalmology 118: 382–388 DOI 10.1016/j.ophtha.2010.06.006 Shields CL, Pefkianaki M, Mashayekhi A, Shields JA, Ganguly A (2018) Cytogenetic results of choroidal nevus growth into melanoma in 55 consecutive cases. Saudi J Ophthalmol 32: 28–32 DOI 10.1016/j.sjopt.2018.02.004 Marous CL, Shields CL, Yu MD, Dalvin LA, Ancona-Lezama D, Shields JA (2019) Malignant transformation of choroidal nevus according to race in 3334 consecutive patients. Indian J Ophthalmol 67: 2035–2042 DOI 10.4103/ijo.IJO_1217_19 Dalvin LA, Shields CL, Ancona-Lezama DA, Yu MD, Di Nicola M, Williams BK, Jr., Lucio-Alvarez JA, Ang SM, Maloney SM, Welch RJ, Shields JA (2019) Combination of multimodal imaging features predictive of choroidal nevus transformation into melanoma. Br J Ophthalmol 103: 1441–1447 DOI 10.1136/bjophthalmol-2018-312967 Raval V, Luo S, Zabor EC, Singh AD (2021) Small Choroidal Melanoma: Correlation of Growth Rate with Pathology. Ocul Oncol Pathol 7: 401–410 DOI 10.1159/000517203 Zabor EC, Raval V, Luo S, Pelayes DE, Singh AD (2022) A Prediction Model to Discriminate Small Choroidal Melanoma from Choroidal Nevus. Ocul Oncol Pathol 8: 71–78 DOI 10.1159/000521541 Tables Table 1. Tumor characteristics and results of multimodal imaging tests. DEMOGRAPHIC FEATURES TOTAL (n=218) % Sex male 43 female 57 Iris color dark 74 bright 26 Tumor features Symptoms no 81 yes 19 Eye affected right 47.2 left 52.8 both 2.7 Pigmentation dark 87 amelanotic 4.3 both 8.7 Localization posterior pole 82.8 peripheral 14 equator 3.3 Proximity to the optic disk <3 mm no 67 yes 33 Halo nevus no 93.2 yes 6.8 IMAGING FEATURES OCT Subretinal fluid no 73.7 yes 26.3 Choroidal neovascularization no 92.7 yes 1.4 RPE detachment no 5 yes 95 Drusen no 42.6 yes 57.4 AF Orange Pigment no 74.5 yes 25.5 Table 2. Relevant parameters in choroidal nevi with three or more risk factors. MEAN (SD) Age 69 ± 15 IOP (mmHg) 14.4 ± 3 Visual acuity 0.76 ± 0.9 Tumor Size Longitudinal base (mm) 7.70 ± 2 Longitudinal height (mm) 1.45± 0.62 Table 3 . Analysis of Factors at Initial Presentation Predicting Growth of Choroidal Nevus into Melanoma. No Growth into melanoma (%) Growth into melanoma (%) P Value Sex Male 43.0% 50.0% 0.662 Female 57.0% 50.0% Iris Dark 74.3% 70.0% 0.765 Bright 25.7% 30.0% Pigmentation Pigmented 87.4% 77.8% 0.56 Amelanotic 4.0% 11.1% Both 8.5% 11.1% Localization Peripheral 14.1% 10.0% 0.769 Equatorial 3.4% 0.0% Posterior Pole 82.4% 90.0% Laterality Right 47.6% 40.0% 0.638 Left 52.4% 60.0% PVD No 61.8% 50.0% 0.842 Complet 36.4% 50.0% Parcial 1.8% 0.0% Symptoms No 83.2% 40.0% 0.001 Yes 16.8% 60.0% Orange Pigment No 72.1% 10.0% 0.001 Yes 27.9% 90.0% Abscence Halo No 5.3% 0.0% 0.455 Yes 94.7% 100.0% 3mm Optic Disk No 67.3% 60.0% 0.631 Yes 32.7% 40.0% No drusas No 47.0% 20.0% 0.094 Yes 53.0% 80.0% EPD No 92.9% 100.0% 0.406 Yes 7.1% 0.0% Subretinal fluid OCT No 74.9% 50.0% 0.081 Yes 25.1% 50.0% Hollow echogenicity No 86.5% 75.0% 0.375 Yes 13.5% 25.0% Height >2mm No 86.5% 22.2% 0.001 Yes 13.5% 77.8% Base >5mm No 7.0% 0.0% 0.44 Yes 93.0% 100.0% Kappa anglen No 79.8% 50.0% 0.055 Yes 20.2% 50.0% Echogenicity Baja 28.2% 28.6% 0.165 Media 25.4% 57.1% Alta 21.1% 0.0% Media-Alta 21.1% 0.0% Media-Baja 4.2% 14.3% Pulse No 98.1% 100.0% 0.782 Yes 1.9% 0.0% Table 4. Results of the logistic regression model, dependent variable: Transformation to choroidal melanoma Variable B Standard error Sig. OR 95% C.I. para EXP(B) Inferior Superior Orange Pigment 4,331 1,589 0,006 76,031 3,373 1713,572 Height > 2mm 4,980 1,477 0,001 145,480 8,043 2631,384 Symptoms 1,952 1,221 0,110 7,046 0,644 77,123 Constant -8,276 2,147 0,000 0,000 Table 5 . Comparative Summary of Studies on the Transformation of Small Choroidal Melanocytic Lesions to Melanoma Study Year Sample Size Evaluated Characteristics Main Findings Augsburger et al. [7] 1989 197 Demographics (age, sex, race), Visual Acuity (VA), lesion size, presence of Retinal Detachment (RD), location, Orange Pigment (OP), drusen. - Lesion height, juxtapapillary location, symptoms, OP, and Subretinal Fluid (SRF) correlate with higher growth risk. - Drusen suggest a state of lesion inactivity. COMS [9] 1997 204 Lesion height and base, OP, drusen, changes in Retinal Pigment Epithelium (RPE). - OP, absence of drusen, and changes in the RPE are related to the growth risk of SCML. Singh et al [14] . 2006 240 Demographics, tumour size and location, SCML characteristics (orange pigment, drusen, SRF, CNV). Risk factors for growth: - Height >2mm - Male sex - <3mm to foveola - Symptoms - Orange pigment Shields et al. [10] 2008 3187 Age, symptoms, base, height, and pigmentation of SCML, presence of OP, atrophy or hyperplasia of the RPE, drusen, SRF. - Clinical characteristics do not differ by age of presentation. - Older patients had more lesions per eye, drusen, and greater thickness compared to younger patients. - Symptomatic SCML more likely to be located beneath the foveola, have subfoveal fluid, and be non-pigmented. Lane, Egan et al. [15] 2010 1063 Demographics, involved eye, tumour size, symptoms. Mortality rate from metastasis at 5, 10, and 15 years (average follow-up of 8.4 years): - Indeterminate Melanocytic Lesions (IML): 0%, 1%, 3% - Choroidal Melanoma (CM): 2%, 5%, 7% - No SCML patient died from metastasis Mashayekhi et al. [16] 2011 278 Demographics, base and height of SCML, presence of SRF, OP, drusen, atrophy, hyperplasia, metaplasia. 31% of SCML showed slight size increase without clinical evidence of transformation. - Growth frequency inversely related to patient age. Shields et al. [17] 2018 55 Demographics, height and base, chromosomes 3, 6, and 8. SCML with rapid transformation into CM within 1 year are more likely to demonstrate a high-risk cytogenetic profile (risk of metastatic disease) compared to those with slow transformation. Marous et al. [18] 2019 3334 Demographics, clinical characteristics, imaging features, and transformation rate by race. - Transformation risk did not differ by race. - Caucasians with nevus growth had lower risk of presenting acoustic hollowness on ultrasound. Harbour, Paez-Escamilla et al. [12] 2019 3806 Risk of transformation by increase in height in mm. Each increase in thickness showed a transformation risk (HR) of: - 4.7 for thin lesions - 35.7 for medium lesions - 52.0 for thick lesions. Dalvin et al. [19] 2019 3806 Height and base, SRF, symptoms, OP, void in US. - 6 risk factors for transformation identified by multimodal imaging. - Transformation risk is 1% with no risk factors and approaches 100% with specific combinations of 3 or more risk factors. Raval et al. [20] 2021 61 Age, sex, laterality, tumour dimensions, tumour location, presence of orange pigment, subretinal fluid, drusen, atrophy of the retinal pigment epithelium. Choroidal melanocytic lesions showing a defined growth rate can be clinically diagnosed as SCM without the need for biopsy. Zabor et al. [21] 2022 123 SRF, height, drusen, OP, distance to the Optic Nerve (ON). - Distance to ON >3mm and drusen are associated with a lower probability of CM. - SRF, OP are associated with a higher probability of CM. Our study 2023 218 Demographics, affected eye, symptoms, VA, OP, size, distance of lesion to ON. The presence of orange pigment and height > 2 mm are significantly predictive of transformation. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3927201","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271639155,"identity":"16762ad3-e31b-4b2c-8728-fd0839791cf1","order_by":0,"name":"Sara Garcia-Caride","email":"","orcid":"","institution":"Hospital Povisa","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Garcia-Caride","suffix":""},{"id":271639156,"identity":"6fd599eb-a255-474f-8817-d08c2cdbb086","order_by":1,"name":"Laura Formoso","email":"","orcid":"","institution":"University Hospital of Santiago de Compostela","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Formoso","suffix":""},{"id":271639157,"identity":"c9dfd96d-e222-41e4-9c65-44e6e8ca484f","order_by":2,"name":"Elia De Esteban Maciñeira","email":"","orcid":"","institution":"University Hospital of Santiago de Compostela","correspondingAuthor":false,"prefix":"","firstName":"Elia","middleName":"De Esteban","lastName":"Maciñeira","suffix":""},{"id":271639158,"identity":"64120778-a373-4a09-8d6d-7a1c9d481e4d","order_by":3,"name":"Paula Silva-Rodriguez","email":"","orcid":"","institution":"Fundación Pública Galega de Medicina Xenómica, Clinica University Hospital of Santiago de Compostela, Santiago de Compostela,","correspondingAuthor":false,"prefix":"","firstName":"Paula","middleName":"","lastName":"Silva-Rodriguez","suffix":""},{"id":271639159,"identity":"14f32333-22a9-47da-bc6c-5a1a0e7da0f7","order_by":4,"name":"Maria Pardo","email":"","orcid":"","institution":"Grupo Obesidómica, Instituto de Investigación Sanitaria de Santiago (IDIS), CIBEROBN, ISCIII, Santiago de Compostela, 15706, Spain","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Pardo","suffix":""},{"id":271639160,"identity":"30372018-83e3-4fbe-9bc0-4e6053fb2aaa","order_by":5,"name":"Manuel F Bande","email":"data:image/png;base64,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","orcid":"","institution":"University Hospital of Santiago de Compostela","correspondingAuthor":true,"prefix":"","firstName":"Manuel","middleName":"F","lastName":"Bande","suffix":""},{"id":271639161,"identity":"5ac929a2-84ec-437d-ba03-539da4c6be13","order_by":6,"name":"María Jose Blanco-Teijeiro","email":"","orcid":"","institution":"University Hospital of Santiago de Compostela","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"Jose","lastName":"Blanco-Teijeiro","suffix":""}],"badges":[],"createdAt":"2024-02-04 10:29:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3927201/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3927201/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53333392,"identity":"f6d76513-e44f-41bf-9f16-bc953ec3e4d6","added_by":"auto","created_at":"2024-03-24 12:22:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":410445,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3927201/v1/1fd28a89-71a1-4e29-876b-a682b4f8481c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Potential of a Small Melanocytic Lesion to Transform into Choroidal Melanoma: A Retrospective Study and Literature Review","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUveal melanoma encompasses lesions originating from the uvea, which includes the iris, ciliary body, and choroid, with choroidal melanoma (CM) being the most frequent subtype. The pathogenesis of uveal melanoma is distinct from that of cutaneous melanoma and is less understood. Risk factors specific to uveal melanoma include ocular and cutaneous pigmentation, UV exposure, and genetic predispositions. Recent advancements in molecular biology have shed light on genetic mutations and chromosomal aberrations associated with uveal melanoma, contributing to a better understanding of its pathogenesis and potential therapeutic targets.[1]\u003c/p\u003e\n\u003cp\u003eIn the context of choroidal nevus (CN) transforming into CM, several clinical and imaging factors have been identified as predictive markers. These include lesion thickness greater than 2 mm, the presence of subretinal fluid, symptoms indicative of visual acuity reduction to 20/50 or worse, the presence of orange pigment on the lesion, and a marginal location near the optic disc. The annual risk of a choroidal nevus transforming into malignant melanoma is estimated to be approximately 1 in 8,845.[2, 3]\u0026nbsp;However, this statistic underscores the importance of rigorous monitoring and early identification of high-risk lesions.\u003c/p\u003e\n\u003cp\u003eThe primary objective of this study is to elucidate the risk factors associated with the malignant transformation of small melanocytic choroidal lesions (SMCL) into melanoma, particularly focusing on CN. Choroidal nevus, a prevalent ocular finding, is generally benign but holds the potential to transform into CM. CM represents a significant form of uveal melanoma, the most common primary intraocular malignancy in adults. The transformation from CN to CM is a critical clinical concern due to the aggressive nature of CM, which can result in severe visual impairment and potentially be life-threatening.[4]\u003c/p\u003e\n\u003cp\u003eOur study aims to contribute significant insights into the risk factors and clinical indicators that may signal the malignant transformation of choroidal nevus into melanoma. By identifying these risk factors, clinicians can better monitor patients with CN, enabling early intervention and potentially improving prognostic outcomes for those at heightened risk of developing CM.\u003c/p\u003e\n\u003cp\u003eThis revised introduction provides a more detailed context of SMCL, CN, and CM, emphasizing the importance of understanding and identifying the risk factors associated with the malignant transformation of CN into CM. It also places the study within the broader framework of uveal melanoma research, highlighting its clinical significance.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eOur study involved a cohort of small melanocytic choroidal lesions (SMCL) from the adult tumour unit at the University Hospital of Santiago de Compostela. The aim was to assess the risk of these lesions transforming into choroidal melanoma. This research received approval from the local Institutional Ethics Committee (Registration Code: 2009/128) and was conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eThis retrospective longitudinal study analysed follow-ups of 218 SMCL cases. It encompassed patients who visited the unit consecutively between January 2013 and January 2023 and met the inclusion criteria.\u003c/p\u003e\n\u003cp\u003eInclusion criteria were defined as patients diagnosed with SMCL who underwent comprehensive multimodal imaging, including optical coherence tomography (OCT), ultrasonography (US), and fundus autofluorescence (AF), and for whom follow-up data were available. Patients were excluded if the required imaging tests could not be performed.\u003c/p\u003e\n\u003cp\u003eEnrolment of patients occurred at their initial visit, with subsequent follow-ups scheduled every three months. All examinations were conducted by one of the senior authors, utilizing advanced techniques such as indirect ophthalmoscopy for full fundus evaluation and high-resolution magnification ophthalmoscopy (using Goldman or 90-diopter lens with slit lamp biomicroscopy) for detailed assessment of the nevus or macula, when necessary and feasible. Fundus photography was also routinely performed.\u003c/p\u003e\n\u003cp\u003eClinical data collected during the initial examination included patient demographics (age and sex), symptoms, and best-corrected visual acuity, measured using decimal charts. Additional data encompassed the quadrantic location of the tumour epicenter (inferior, temporal, superior, nasal, or macula), proximity of the nearest tumour margin to the optic disc and foveola (measured in millimetres), largest tumour basal dimension and thickness (in millimetres), and the presence of an amelanotic halo and orange pigment. Imaging characteristics of CN were evaluated using OCT, AF, and US. Particular attention was paid to variables identified by Shields et al. as risk factors for progression to CM.\u003c/p\u003e\n\u003cp\u003eA key variable monitored during follow-up was the transformation to melanoma. This was determined by expert physicians based on criteria such as a minimum enlargement of 0.5 mm in basal dimension or thickness, increased thickness, presence of subretinal fluid, symptoms, orange pigment, proximity to the optic disc margin, ultrasonographic hollowness, and absence of a halo.\u003c/p\u003e\n\u003cp\u003eQualitative variables were presented in terms of absolute and relative frequencies. Quantitative variables were summarized using mean and standard deviation (\u0026plusmn;SD). The chi-square statistical test was employed to compare characteristics and progression in patients with SMCL under observation. A subsequent multivariate analysis was conducted on variables identified as significant in the preliminary analysis. This approach is crucial in understanding a complex phenomenon like the transformation to choroidal melanoma, where multiple interrelated factors may collectively influence the outcome. Confounding variables, potentially representing additional risk factors, were considered for both the primary outcome (conversion to choroidal melanoma) and predictor variables identified in the univariate analysis. In the multivariate analysis, various variables were evaluated in relation to the transformation of SMCL. Results are reported in terms of coefficients (B), standard errors, statistical significance (Sig.), odds ratios (OR), and 95% confidence intervals for these ratios.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn this study, 218 small choroidal melanocytic lesions (SMCLs) were analysed. Of these, 43% (94 individuals) were male and 57% (123 individuals) were female. The mean age of the subjects was 69 years, with a standard deviation of 15 years. Tumour characteristic revealed that 19% of cases were symptomatic and 25.5% exhibited orange pigment. Approximately 33% of tumours were in proximity to the optic disc.\u003c/p\u003e\n\u003cp\u003eOptical coherence tomography (OCT) characteristics included subretinal fluid in 26.3% of cases, choroidal neovascularization in 1.4%, and the presence of drusen in 57.4%. Autofluorescence (AF) imaging indicated that 25.5% of cases had orange pigment (Table 1).\u003c/p\u003e\n\u003cp\u003eFor choroidal nevi with more than three risk factors, the mean age was 64.78 years (\u0026plusmn;15), intraocular pressure (IOP) averaged 14.4 mmHg (\u0026plusmn;3), and visual acuity was 0.76 (\u0026plusmn;0.9). Tumour sizes were measured in terms of longitudinal base and height, with an average transversal base of 7.70 mm (\u0026plusmn;2) and an average transversal height of 1.45 mm (\u0026plusmn;0.62) (Table 2).\u003c/p\u003e\n\u003cp\u003eDuring the follow-up period, 4.6% (10 cases) of SMCLs transformed into CM. The mean follow-up duration was 52 months, ranging from 3 to 113 months.\u003c/p\u003e\n\u003cp\u003eTable 3 provides an analysis of various initial presentation factors and their correlation with the growth of choroidal nevus into melanoma. It was observed that 43% of males and 57% of females did not progress to melanoma. Gender did not show a significant difference in terms of transformation risk (p = 0.662). However, the presence of symptoms (p \u0026lt; 0.001), orange pigment (p \u0026lt; 0.001), and a height greater than 2mm (p \u0026lt; 0.001) were significantly associated with the transformation to CM.\u003c/p\u003e\n\u003cp\u003eThe multivariate analysis revealed that the variable \u0026apos;Orange pigment\u0026apos; had a coefficient (B) of 4.331, with a standard error of 1.589 and a statistically significant odds ratio (OR) of 76.031, suggesting a notably higher likelihood of transformation in cases with orange pigment. The variable \u0026apos;Height \u0026gt; 2mm\u0026apos; had a coefficient (B) of 4.980, standard error of 1.477, and an OR of 145.480, indicating a significantly increased risk of transformation for lesions exceeding 2mm in height. The \u0026apos;Symptoms\u0026apos; variable, with a coefficient (B) of 1.952 and an OR of 7.046, demonstrated an association with transformation risk, though it did not reach conventional statistical significance (Table 4).\u003c/p\u003e\n\u003cp\u003eThe Cox and Snell R-squared coefficient was calculated as 0.292, indicating that the model accounts for approximately 29.2% of the variability in lesion transformation. This suggests that while the factors of orange pigment, height greater than 2mm, and symptoms are significant predictors, other unaccounted factors may also influence the progression to choroidal melanoma.\u003c/p\u003e"},{"header":"DISCUSION","content":"\u003cp\u003eOur study has elucidated that a lesion height exceeding 2 mm, as ascertained through ultrasonography (US), coupled with the presence of orange pigment, are the exclusive statistically significant risk factors for the transformation of SMCL into CM. This revelation is congruent with preceding scholarly inquiries, which have identified a lesion thickness surpassing 2 mm as a pivotal risk factor in such malignant transformations (references 3, 5, 6). Complementary studies have further delineated risk factors including subretinal fluid, symptomatic presentation, orange pigment, proximity to the optic disc, ultrasonographic hollowness, and the absence of a halo, all contributing to the transformation of SMCL into CM. Moreover, a synthesis of features discerned via multimodal imaging has been recognized as prognostic of SMCL progression to CM.[3, 5, 6]\u003c/p\u003e\n\u003cp\u003eThe seminal research conducted by Augsburger et al.[7]\u0026nbsp;was at the forefront of exploring risk factors in these lesions. Their analysis revealed that certain characteristics, notably a base size exceeding 5 mm, a height greater than 1.5 mm, juxtapapillary location, symptomatology, presence of orange pigment, and subretinal fluid, were significantly correlated with an augmented risk of lesion growth. These initial findings have been substantiated through ensuing, larger-scale retrospective analyses.[8]\u003c/p\u003e\n\u003cp\u003eIn the ambit of the Collaborative Ocular Melanoma Study (COMS)[9], a prospective investigation discerned that the existence of orange pigment, the absence of drusen, and adjacent alterations in the retinal pigment epithelium (RPE) were indicative of an elevated risk of growth in LCMPT. However, this study did not establish any associations with the proximity to the optic nerve or the presence of subretinal fluid.\u003c/p\u003e\n\u003cp\u003eThe investigative efforts of Shields et al.[10]\u0026nbsp;have identified a compendium of factors predictive of melanoma genesis, encompassing increased lesion thickness, subretinal fluid, symptoms, orange pigment, proximity to the optic disc, ultrasonographic hollowness, and the absence of a halo. Furthermore, it was determined that the annual rate of malignant transformation from CN to CM is approximately 1 in 8,845, with an increasing propensity with advancing age.[2, 11]\u0026nbsp;The identification of these risk factors is imperative for clinicians in the meticulous monitoring of patients with CN, thereby facilitating the identification of individuals at an elevated risk of developing CM.\u003c/p\u003e\n\u003cp\u003eThe scholarly article by Harbour et al.[12]\u0026nbsp;leveraged a validated genomic biomarker to evaluate risk factors and their correlation with the transformation of these lesions. Focusing on clinical and pathological characteristics such as tumour size and thickness, presence of retinal detachment, orange pigment, drusen, RPE fibrosis, atrophy, visual symptoms, and documented tumour growth, the study deduced that no singular clinical feature or amalgamation thereof is pathognomonic for the transformation of these lesions into melanoma. Specifically, a definitive clinical or pathological profile signifying malignant conversion was not identified. Nonetheless, patient age and tumour thickness emerged as potentially indicative of small choroidal melanocytic tumours with a higher likelihood of possessing a class 2 genomic profile, associated with malignant progression. Further corroboration from an additional study[3]\u0026nbsp;emphasized the significance of cytogenetic analysis as an instrumental tool in the assessment and management of LCMPT transformation cases, with prevalent chromosomal alterations such as gains on chromosomes 6p, 8q, 11q, and losses on chromosome 3, predominantly observed in melanomas of higher grade and larger dimensions. A comprehensive summary of the studies pertinent to this subject matter is succinctly encapsulated in Table 5, which offers a consolidated overview of the various research endeavours undertaken in this domain.\u003c/p\u003e\n\u003cp\u003eNotwithstanding, our study is subject to certain limitations, including a relatively modest sample size and a follow-up period that may not comprehensively capture all instances of SMCL transformation into CM. The retrospective nature of this study may inherently introduce biases into the findings.\u003c/p\u003e\n\u003cp\u003eDespite these limitations, our study contributes valuable insights into the risk factors for the transformation of CN into CM, which are instrumental in identifying CNs warranting rigorous monitoring or therapeutic intervention.[12]\u0026nbsp;The study also accentuates the pivotal role of US in detecting CNs predisposed to transformation into CM.[13]\u003c/p\u003e\n\u003cp\u003eIn summary, our research corroborates the critical importance of identifying risk factors for the transformation of CN into CM. Such identification enables clinicians to more effectively surveil patients with CN and discern those with an increased risk of developing CM. Future investigations are warranted to validate these findings and to unearth additional risk factors for the transformation of SMCL into CM.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eConflicts of Interest Statement: We declare that we have no conflicts of interest.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS.G., M.B. and L.F. wrote the main manuscript text and E.M., M.B. recollected data, P.S. and M.P prepared tables. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJager MJ, Shields CL, Cebulla CM, Abdel-Rahman MH, Grossniklaus HE, Stern MH, Carvajal RD, Belfort RN, Jia R, Shields JA, Damato BE (2020) Uveal melanoma. 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Ophthalmology 113: 887\u0026ndash;888 e881 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ophtha.2006.01.047\u003c/span\u003e\u003cspan address=\"10.1016/j.ophtha.2006.01.047\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarbour JW, Paez-Escamilla M, Cai L, Walter SD, Augsburger JJ, Correa ZM (2019) Are Risk Factors for Growth of Choroidal Nevi Associated With Malignant Transformation? Assessment With a Validated Genomic Biomarker. Am J Ophthalmol 197: 168\u0026ndash;179 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ajo.2018.08.045\u003c/span\u003e\u003cspan address=\"10.1016/j.ajo.2018.08.045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGass JD (1977) Problems in the differential diagnosis of choroidal nevi and malignant melanomas. The XXXIII Edward Jackson Memorial Lecture. Am J Ophthalmol 83: 299\u0026ndash;323 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/ten.2005.11.1254\u003c/span\u003e\u003cspan address=\"10.1089/ten.2005.11.1254\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh AD, Mokashi AA, Bena JF, Jacques R, Rundle PA, Rennie IG (2006) Small choroidal melanocytic lesions: features predictive of growth. Ophthalmology 113: 1032\u0026ndash;1039 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ophtha.2006.01.053\u003c/span\u003e\u003cspan address=\"10.1016/j.ophtha.2006.01.053\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLane AM, Egan KM, Kim IK, Gragoudas ES (2010) Mortality after diagnosis of small melanocytic lesions of the choroid. Arch Ophthalmol 128: 996\u0026ndash;1000 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archophthalmol.2010.166\u003c/span\u003e\u003cspan address=\"10.1001/archophthalmol.2010.166\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMashayekhi A, Siu S, Shields CL, Shields JA (2011) Slow enlargement of choroidal nevi: a long-term follow-up study. 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Saudi J Ophthalmol 32: 28\u0026ndash;32 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.sjopt.2018.02.004\u003c/span\u003e\u003cspan address=\"10.1016/j.sjopt.2018.02.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarous CL, Shields CL, Yu MD, Dalvin LA, Ancona-Lezama D, Shields JA (2019) Malignant transformation of choroidal nevus according to race in 3334 consecutive patients. Indian J Ophthalmol 67: 2035\u0026ndash;2042 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/ijo.IJO_1217_19\u003c/span\u003e\u003cspan address=\"10.4103/ijo.IJO_1217_19\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDalvin LA, Shields CL, Ancona-Lezama DA, Yu MD, Di Nicola M, Williams BK, Jr., Lucio-Alvarez JA, Ang SM, Maloney SM, Welch RJ, Shields JA (2019) Combination of multimodal imaging features predictive of choroidal nevus transformation into melanoma. Br J Ophthalmol 103: 1441\u0026ndash;1447 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bjophthalmol-2018-312967\u003c/span\u003e\u003cspan address=\"10.1136/bjophthalmol-2018-312967\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaval V, Luo S, Zabor EC, Singh AD (2021) Small Choroidal Melanoma: Correlation of Growth Rate with Pathology. Ocul Oncol Pathol 7: 401\u0026ndash;410 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000517203\u003c/span\u003e\u003cspan address=\"10.1159/000517203\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZabor EC, Raval V, Luo S, Pelayes DE, Singh AD (2022) A Prediction Model to Discriminate Small Choroidal Melanoma from Choroidal Nevus. Ocul Oncol Pathol 8: 71\u0026ndash;78 DOI \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000521541\u003c/span\u003e\u003cspan address=\"10.1159/000521541\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Tumor characteristics and results of multimodal imaging tests.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" style=\"margin-right: calc(30%); width: 70%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.60377358490566%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDEMOGRAPHIC FEATURES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"53.39622641509434%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTAL (n=218)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"53.39622641509434%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eIris color\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003edark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003ebright\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor features\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" rowspan=\"3\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEye affected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eright\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e47.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eleft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e52.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eboth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" rowspan=\"3\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePigmentation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003edark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eamelanotic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eboth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" rowspan=\"3\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocalization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eposterior pole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e82.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eperipheral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eequator\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" rowspan=\"2\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eProximity to the optic disk \u0026lt;3 mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.516007532956685%\" rowspan=\"2\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHalo nevus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.741996233521657%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e93.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eIMAGING FEATURES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.890459363957597%\" rowspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eOCT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.98939929328622%\" rowspan=\"2\"\u003e\n \u003cp\u003eSubretinal fluid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.445229681978798%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.674911660777386%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e73.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.57627118644068%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"45.42372881355932%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e26.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.022770398481974%\" rowspan=\"2\"\u003e\n \u003cp\u003eChoroidal neovascularization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.550284629981025%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.426944971537%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e92.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.57627118644068%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"45.42372881355932%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.022770398481974%\" rowspan=\"2\"\u003e\n \u003cp\u003eRPE detachment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.550284629981025%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.426944971537%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.57627118644068%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"45.42372881355932%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.022770398481974%\" rowspan=\"2\"\u003e\n \u003cp\u003eDrusen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.550284629981025%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.426944971537%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e42.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.57627118644068%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"45.42372881355932%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e57.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.890459363957597%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.98939929328622%\" rowspan=\"2\"\u003e\n \u003cp\u003eOrange Pigment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.445229681978798%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.674911660777386%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e74.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.57627118644068%\" valign=\"top\" style=\"width: 34.0234%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"45.42372881355932%\" valign=\"top\" style=\"width: 14.9052%;\"\u003e\n \u003cp\u003e25.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Relevant parameters in choroidal nevi with three or more risk factors.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.60777385159011%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEAN (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.60777385159011%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003e69\u0026nbsp;\u0026plusmn;\u0026nbsp;15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.60777385159011%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIOP (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003e14.4\u0026nbsp;\u0026plusmn;\u0026nbsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.60777385159011%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisual acuity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003e0.76\u0026nbsp;\u0026plusmn;\u0026nbsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eLongitudinal base (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e7.70 \u0026nbsp;\u0026plusmn; \u0026nbsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eLongitudinal height (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.45\u0026plusmn;\u0026nbsp;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e.\u0026nbsp;Analysis of Factors at Initial Presentation Predicting Growth of Choroidal Nevus into Melanoma.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo Growth into melanoma (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrowth into melanoma (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" valign=\"top\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e43.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e57.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIris\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eDark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e74.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e70.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eBright\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e25.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e30.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePigmentation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003ePigmented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e87.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e77.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"3\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eAmelanotic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e4.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e11.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e8.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e11.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocalization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003ePeripheral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e14.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e10.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"3\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eEquatorial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e3.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003ePosterior Pole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e82.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e90.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaterality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e47.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e40.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e52.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e60.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePVD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e61.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"3\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eComplet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e36.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eParcial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e1.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e83.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e40.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e16.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e60.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrange Pigment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e72.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e10.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e27.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e90.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbscence Halo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e5.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.455\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e94.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3mm Optic Disk\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e67.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e60.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e32.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e40.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo drusas\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e47.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e20.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e53.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e80.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e92.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e7.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubretinal fluid\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;OCT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e74.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e25.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHollow echogenicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e86.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e75.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e13.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight \u0026gt;2mm\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e86.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e22.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e13.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e77.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBase \u0026gt;5mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e7.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e93.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKappa anglen\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e79.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e20.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchogenicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eBaja\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e28.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e28.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"5\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eMedia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e25.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e57.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eAlta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e21.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eMedia-Alta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e21.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eMedia-Baja\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e4.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e14.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulse\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.241830065359476%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e98.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.30718954248366%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" rowspan=\"2\" style=\"width: 11.4277%;\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.954198473282442%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.07888040712468%\" valign=\"top\" style=\"width: 22.0052%;\"\u003e\n \u003cp\u003e1.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.966921119592875%\" valign=\"top\" style=\"width: 16.8403%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Results of the logistic regression model, dependent variable: Transformation to choroidal melanoma\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"566\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.691358024691358%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81657848324515%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.876543209876543%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.924162257495592%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% C.I. para EXP(B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eInferior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eSuperior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.691358024691358%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrange Pigment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e4,331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81657848324515%\" valign=\"top\"\u003e\n \u003cp\u003e1,589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.876543209876543%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e76,031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e3,373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e1713,572\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.691358024691358%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight \u0026gt; 2mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e4,980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81657848324515%\" valign=\"top\"\u003e\n \u003cp\u003e1,477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.876543209876543%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e145,480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e8,043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e2631,384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.691358024691358%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e1,952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81657848324515%\" valign=\"top\"\u003e\n \u003cp\u003e1,221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.876543209876543%\" valign=\"top\"\u003e\n \u003cp\u003e0,110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e7,046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e0,644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e77,123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.691358024691358%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e-8,276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.81657848324515%\" valign=\"top\"\u003e\n \u003cp\u003e2,147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.876543209876543%\" valign=\"top\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.462081128747796%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e. Comparative Summary of Studies on the Transformation of Small Choroidal Melanocytic Lesions to Melanoma\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStudy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSample Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluated Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMain Findings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAugsburger et al.\u003c/strong\u003e\u003cstrong\u003e[7]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDemographics (age, sex, race), Visual Acuity (VA), lesion size, presence of Retinal Detachment (RD), location, Orange Pigment (OP), drusen.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e- Lesion height, juxtapapillary location, symptoms, OP, and Subretinal Fluid (SRF) correlate with higher growth risk.\u003c/p\u003e\n \u003cp\u003e- Drusen suggest a state of lesion inactivity.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCOMS\u003c/strong\u003e\u003cstrong\u003e[9]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLesion height and base, OP, drusen, changes in Retinal Pigment Epithelium (RPE).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e- OP, absence of drusen, and changes in the RPE are related to the growth risk of SCML.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSingh et al\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e[14]\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDemographics, tumour size and location, SCML characteristics (orange pigment, drusen, SRF, CNV).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRisk factors for growth:\u003c/p\u003e\n \u003cp\u003e- Height \u0026gt;2mm\u003c/p\u003e\n \u003cp\u003e- Male sex\u003c/p\u003e\n \u003cp\u003e- \u0026lt;3mm to foveola\u003c/p\u003e\n \u003cp\u003e- Symptoms\u003c/p\u003e\n \u003cp\u003e- Orange pigment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eShields et al.\u003c/strong\u003e\u003cstrong\u003e[10]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAge, symptoms, base, height, and pigmentation of SCML, presence of OP, atrophy or hyperplasia of the RPE, drusen, SRF.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e- Clinical characteristics do not differ by age of presentation.\u003c/p\u003e\n \u003cp\u003e- Older patients had more lesions per eye, drusen, and greater thickness compared to younger patients.\u003c/p\u003e\n \u003cp\u003e- Symptomatic SCML more likely to be located beneath the foveola, have subfoveal fluid, and be non-pigmented.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLane, Egan et al.\u003c/strong\u003e\u003cstrong\u003e[15]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDemographics, involved eye, tumour size, symptoms.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMortality rate from metastasis at 5, 10, and 15 years (average follow-up of 8.4 years):\u003c/p\u003e\n \u003cp\u003e- Indeterminate Melanocytic Lesions (IML): 0%, 1%, 3%\u003c/p\u003e\n \u003cp\u003e- Choroidal Melanoma (CM): 2%, 5%, 7%\u003c/p\u003e\n \u003cp\u003e- No SCML patient died from metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMashayekhi et al.\u003c/strong\u003e\u003cstrong\u003e[16]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDemographics, base and height of SCML, presence of SRF, OP, drusen, atrophy, hyperplasia, metaplasia.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31% of SCML showed slight size increase without clinical evidence of transformation.\u003c/p\u003e\n \u003cp\u003e- Growth frequency inversely related to patient age.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eShields et al.\u003c/strong\u003e\u003cstrong\u003e[17]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDemographics, height and base, chromosomes 3, 6, and 8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSCML with rapid transformation into CM within 1 year are more likely to demonstrate a high-risk cytogenetic profile (risk of metastatic disease) compared to those with slow transformation.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMarous et al.\u003c/strong\u003e\u003cstrong\u003e[18]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDemographics, clinical characteristics, imaging features, and transformation rate by race.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e- Transformation risk did not differ by race.\u003c/p\u003e\n \u003cp\u003e- Caucasians with nevus growth had lower risk of presenting acoustic hollowness on ultrasound.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHarbour, Paez-Escamilla et al.\u003c/strong\u003e\u003cstrong\u003e[12]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRisk of transformation by increase in height in mm.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEach increase in thickness showed a transformation risk (HR) of:\u003c/p\u003e\n \u003cp\u003e- 4.7 for thin lesions\u003c/p\u003e\n \u003cp\u003e- 35.7 for medium lesions\u003c/p\u003e\n \u003cp\u003e- 52.0 for thick lesions.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDalvin et al.\u003c/strong\u003e\u003cstrong\u003e[19]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHeight and base, SRF, symptoms, OP, void in US.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e- 6 risk factors for transformation identified by multimodal imaging.\u003c/p\u003e\n \u003cp\u003e- Transformation risk is 1% with no risk factors and approaches 100% with specific combinations of 3 or more risk factors.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRaval et al.\u003c/strong\u003e\u003cstrong\u003e[20]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAge, sex, laterality, tumour dimensions, tumour location, presence of orange pigment, subretinal fluid, drusen, atrophy of the retinal pigment epithelium.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eChoroidal melanocytic lesions showing a defined growth rate can be clinically diagnosed as SCM without the need for biopsy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eZabor et al.\u003c/strong\u003e\u003cstrong\u003e[21]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSRF, height, drusen, OP, distance to the Optic Nerve (ON).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e- Distance to ON \u0026gt;3mm and drusen are associated with a lower probability of CM.\u003c/p\u003e\n \u003cp\u003e- SRF, OP are associated with a higher probability of CM.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOur study\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDemographics, affected eye, symptoms, VA, OP, size, distance of lesion to ON.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eThe presence of orange pigment and height \u0026gt; 2 mm are significantly predictive of transformation.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Choroidal melanoma, Melanocytic lesions, Risk factors, Retrospective study, Literature review","lastPublishedDoi":"10.21203/rs.3.rs-3927201/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3927201/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis research aimed to identify critical risk factors for the malignant transformation of small melanocytic choroidal lesions (SMCL)\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective longitudinal study was conducted on 218 SMCL cases at the University Hospital of Santiago de Compostela from January 2013 to January 2023. Patients were selected based on their diagnosis of SMCL and their undergoing of comprehensive multimodal imaging such as optical coherence tomography, ultrasonography, and fundus autofluorescence. The primary focus was on evaluating demographic data, symptomatic presentations, and detailed imaging features.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe cohort consisted of 43% males and 57% females, with a mean age of 69 years. Notably, 19% of the lesions were symptomatic, and 25.5% exhibited orange pigment. Approximately 33% of the tumours were proximate to the optic disc. Multivariate analysis revealed orange pigment presence and a lesion height greater than 2 mm as significant predictors of transformation. The Cox and Snell R-squared coefficient of 0.292 indicated that these factors accounted for about 29.2% of the variability in lesion transformation. The average follow-up period was 52 months, during which 4.6% of the SMCLs evolved into CM.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study highlights the substantial role of lesion height exceeding 2 mm and the presence of orange pigment as key risk factors for the transformation of SMCL into CM. These findings are instrumental in aiding clinicians to identify and monitor high-risk patients, enabling early and potentially more effective interventions. Future research is essential to further explore these risk factors and to establish a more comprehensive understanding of SMCL progression to CM.\u003c/p\u003e","manuscriptTitle":"The Potential of a Small Melanocytic Lesion to Transform into Choroidal Melanoma: A Retrospective Study and Literature Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-08 13:07:08","doi":"10.21203/rs.3.rs-3927201/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"488198fd-ae46-4df5-b9d5-416bace0edab","owner":[],"postedDate":"February 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-24T12:14:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-08 13:07:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3927201","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3927201","identity":"rs-3927201","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}