Exploring the predictive value of the evoked potentials score in MS within an appropriate patient population: a hint for an early identification of benign MS?

Abstract

Background: The prognostic value of evoked potentials (EPs) in multiple sclerosis (MS) has not been fully established. The correlations between the Expanded Disability Status Scale (EDSS) at First Neurological Evaluation (FNE) and the duration of the disease, as well as between EDSS and EPs, have influenced the outcome of most previous studies. To overcome this confounding relations, we propose to test the prognostic value of EPs within an appropriate patient population which should be based on patients with low EDSS at FNE and short disease duration.

Methods: We retrospectively selected a sample of 143 early relapsing remitting MS (RRMS) patients with an EDSS < 3.5 from a larger database spanning 20 years. By means of bivariate logistic regressions, the best predictors of worsening were selected among several demographic and clinical variables. The best multivariate logistic model was statistically validated and prospectively applied to 50 patients examined during 2009-2011.

Results: The Evoked Potentials score (EP score) and the Time to EDSS 2.0 (TT2) were the best predictors of worsening in our sample (Odds Ratio 1.10 and 0.82 respectively, p=0.001). Low EP score (below 15-20 points), short TT2 (lower than 3-5 years) and their interaction resulted to be the most useful for the identification of worsening patterns. Moreover, in patients with an EP score at FNE below 6 points and a TT2 greater than 3 years the probability of worsening was 10% after 4-5 years and rapidly decreased thereafter.

Conclusions: In an appropriate population of early RRMS patients, the EP score at FNE is a good predictor of disability at low values as well as in combination with a rapid buildup of disability. Interestingly, an EP score at FNE under the median together with a clinical stability lasting more than 3 years turned out to be a protective pattern. This finding may contribute to an early identification of benign patients, well before the term required to diagnose Benign MS (BMS).

Figure 1

ROC curve resulting from the logistic regression model. The area under the curve (AUC = 0.81) shows the sensitivity and specificity corresponding to different cut-off points of the prediction of clinical worsening (defined by patients reaching the threshold of EDSS 3.5). The best cut-off point defined by the maximum of Youden’s index corresponds to a sensitivity of 0.738 and a specificity of 0.693.

Figure 2

Distribution of predicted probabilities for EP score and TT2. A sampling plot drawn from the logistic regression model showing how the predicted probabilities (PP) of clinical worsening are distributed along the EP score scale (with TT2 held constant at the mean). A sample of EP values and their corresponding PP is reported below the graph. Shaded area represents 95% CI.

Figure 3

Distribution of predicted probabilities (PP) for EP score and TT2. A sampling plot drawn from the logistic regression model, showing how the predicted probabilities of clinical worsening are distributed along the TT2 variable (x-axis = yrs; with the EP score held constant at the mean). A sample of TT2 values and their corresponding PP is reported below the graph. Shaded area represents 95% CI.

Figure 4

Plot of predicted probabilities (Y-axis) vs. the EP score (X-axis). The dotted line represents patients with TT2 > 3 yrs; the solid line represents patients with TT2 ≤ 3 yrs. The difference between the curves is largest at the origin of the EP axis and tends to decrease as the EP values grow until it eventually becomes negligible at approximately an EP score of 20.

Figure 5

Plot of predicted probabilities (Y-axis) vs. TT2 (X-axis). The dotted line represents patients with an EP score ≤ 5; the solid line represents patients with an EP score > 5. The difference between the curves is largest at the origin of the TT2 axis and decreases as TT2 exceeds 4–5 years.

Figure 6

Correlations between EDSS and EP scores in the last 6 years literature. The correlations between EDSS and EP scores reflect the researchers’ choice of patients selection criteria. 1: Kallmann et al. 2006 [2] group 1, F_EDSS =2.0, range (0–4). 2: Jung et al. 2008 [4] F_EDSS = 1.5, range(0–3). 3: this study, F_EDSS = 1.5, range(0–3). 4: Leocani et al. 2006 [3], F_EDSS = 3.5, range (1–8). 5: Invernizzi et al. 2011 [5], F_EDSS = 3.0, range(0–6.5). 6: Kallmann et al. 2006 [2] group 2, F_EDSS =3.5, range(0–7).F_EDSS= first EDSS assessment.