Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society · 2016
Ocular Myasthenia Gravis: Toward a Risk of Generalization Score and Sample Size Calculation for a Randomized Controlled Trial of Disease Modification.
СтатьяМногоцентровое исследованиеРандомизированное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Wong Sui H, Petrie Aviva, Plant Gordon T
Аннотация
BACKGROUND: There is currently no prognostic test to determine the risk of developing generalized myasthenia gravis (GMG) risk in patients who first present with ocular disease. Most studies that report risk factors are flawed by the inclusion of patients on immunosuppression, which is likely to reduce the risk.
OBJECTIVE: To create a prognostic score to predict the risk of GMG.
METHODS: Multicenter retrospective cohort of patients with ocular myasthenia gravis for minimum 3 months, untreated with immunosuppression for minimum 2 years or until GMG onset.
RESULTS: One hundred one (57 female) patients were included, with median follow-up of 8.4 years (2-42) from disease onset. Thirty-one developed GMG at median of 1.31 years (3.5 months-20.2 years); 19 occurred within 2 years. Univariable logistic regression analysis produced 3 significant predictors (P < 0.10), adjusted odds ratios in a multivariable logistic model (χ P = 0.01) with multiple imputations for missing data: seropositivity, 5.64 (95% CI, 1.45-21.97); presence of 1 or more comorbidities including autoimmune disorders, 6.49 (95% CI, 0.78-53.90); thymic hyperplasia, 5.41 (95% CI, 0.39-75.43). Prognostic score was derived from the coefficients of the logistic model: sum of the points (1 point for the presence of each of the above predictive factors), classified "low risk" if ≤1 and "high risk" if ≥2. Predicted probabilities were 0.07 (SD, 0.03) for low risk and 0.39 (SD, 0.09) for high risk. Negative predictive value was 91% (95% CI, 79-98), positive predictive value was 38% (95% CI, 23-54), sensitivity was 79% (95% CI, 54-94), specificity was 63% (95% CI, 50-74), area under receiver operating characteristic curve was 0.74 (95% CI, 0.64-0.85).
CONCLUSIONS: In this preliminary study, we have shown by proof of principle that it is possible to stratify risk of GMG: an approach that may allow us to better counsel patients at diagnosis, complement decision-making, and move us toward addressing the question of modifying GMG risk in high-risk patients. Furthermore, the effect of comorbidities is novel and demands further elucidation.
OBJECTIVE: To create a prognostic score to predict the risk of GMG.
METHODS: Multicenter retrospective cohort of patients with ocular myasthenia gravis for minimum 3 months, untreated with immunosuppression for minimum 2 years or until GMG onset.
RESULTS: One hundred one (57 female) patients were included, with median follow-up of 8.4 years (2-42) from disease onset. Thirty-one developed GMG at median of 1.31 years (3.5 months-20.2 years); 19 occurred within 2 years. Univariable logistic regression analysis produced 3 significant predictors (P < 0.10), adjusted odds ratios in a multivariable logistic model (χ P = 0.01) with multiple imputations for missing data: seropositivity, 5.64 (95% CI, 1.45-21.97); presence of 1 or more comorbidities including autoimmune disorders, 6.49 (95% CI, 0.78-53.90); thymic hyperplasia, 5.41 (95% CI, 0.39-75.43). Prognostic score was derived from the coefficients of the logistic model: sum of the points (1 point for the presence of each of the above predictive factors), classified "low risk" if ≤1 and "high risk" if ≥2. Predicted probabilities were 0.07 (SD, 0.03) for low risk and 0.39 (SD, 0.09) for high risk. Negative predictive value was 91% (95% CI, 79-98), positive predictive value was 38% (95% CI, 23-54), sensitivity was 79% (95% CI, 54-94), specificity was 63% (95% CI, 50-74), area under receiver operating characteristic curve was 0.74 (95% CI, 0.64-0.85).
CONCLUSIONS: In this preliminary study, we have shown by proof of principle that it is possible to stratify risk of GMG: an approach that may allow us to better counsel patients at diagnosis, complement decision-making, and move us toward addressing the question of modifying GMG risk in high-risk patients. Furthermore, the effect of comorbidities is novel and demands further elucidation.