Validating Predictors of Disease Progression in a Large Cohort of Primary-Progressive Multiple Sclerosis Based on a Systematic Literature Review

<div><p>Background</p><p>New agents with neuroprotective or neuroregenerative potential might be explored in primary-progressive Multiple Sclerosis (PPMS) - the MS disease course with leading neurodegenerative pathology. Identification of patients with a high short-term risk for progression may minimize study duration and sample size. Cohort studies reported several variables as predictors of EDSS disability progression but findings were partially contradictory.</p><p>Objective</p><p>To analyse the impact of published predictors on EDSS disease progression in a large cohort of PPMS patients.</p><p>Methods</p><p>A systematic literature research was performed to identify predictors for disease progression in PPMS. Individual case data from the Sylvia Lawry Centre (SLC) and the Hamburg MS patient database (HAPIMS) was pooled for a retrospective validation of these predictors on the annualized EDSS change.</p><p>Results</p><p>The systematic literature analysis revealed heterogeneous data from 3 prospective and 5 retrospective natural history cohort studies. Age at onset, gender, type of first symptoms and early EDSS changes were available for validation. Our pooled cohort of 597 PPMS patients (54% female) had a mean follow-up of 4.4 years and mean change of EDSS of 0.35 per year based on 2503 EDSS assessments. There was no significant association between the investigated variables and the EDSS-change.</p><p>Conclusion</p><p>None of the analysed variables were predictive for the disease progression measured by the annualized EDSS change. Whether PPMS is still unpredictable or our results may be due to limitations of cohort assessments or selection of predictors cannot be answered. Large systematic prospective studies with new endpoints are needed.</p></div

Observed communication competences and reliability.

<p>Item range 0–4: 0 = skill not observed, 4 = skill executed to a high standard; InterRR = inter-rater reliability, based on 26 consultations IntraRR  = intra-rater reliability, based on 15 consultations (Correlation coefficients are based on Spearman).</p

Relationship of OPTION and SDM-Q.

<p>Each point represents one consultation. Data are given separately for physicians 1 to 3 and for the whole sample (physician 1: n = 36, physician 2: n = 23, physician 3: n = 14, physician 4 n = 3). Correlations are indicated by Spearman's rho.</p

Consultation sample.

<p>MS = multiple sclerosis, GP = general practitioner.</p

Inter-relations of MAPPIN'SDM foci.

<p>The table shows Pearson correlation coefficients of pairwise related judgements by MAPPIN'SDM different measurement foci. Abbreviations are explained in detail in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034849#pone-0034849-t001" target="_blank">table 1</a>.</p

MAPPIN'SDM overview.

<p>The table illustrates the organization of the MAPPIN'SDM inventory by indicating the constituting elements for the seven foci of measurement. Each of which represents a separate view on the communication and is supposed to apply the identical set of 15 SDM indicators.</p

Comparison of OPTION and MAPPIN'SDM.

<p>Set of indicators of shared decision making of MAPPIN'SDM compared to that of the OPTION scale.</p

Relationship of OPTION and DCS.

<p>Each point represents one consultation. Data are given separately for physicians 1 to 3 and for the whole sample (physician 1: n = 36, physician 2: n = 23, physician 3: n = 14, physician 4 n = 3). Correlations are indicated by Spearman's rho.</p

Flow of participants through umbrella trial and nested cohort trial.

<p>Flow of participants through umbrella trial and nested cohort trial.</p

Association between Early and Late EDSS-Progression.

<p>Delta-EDSS in the first two years after baseline and delta-EDSS from year three on, delta-EDSS = annualized difference between first and last EDSS assessment, Spearman's rank correlation  =  −0.0445, p = 0.6536.</p