Factors associated with time from first-symptoms to diagnosis and treatment initiation of Multiple Sclerosis in Switzerland

Abstract

Background: Recent studies emphasise the importance of timely diagnosis and early initiation of disease-modifying treatment in the long-term prognosis of multiple sclerosis.

Objectives: The objective of this study was to investigate factors associated with extended time to diagnosis and time to disease-modifying treatment initiation in the Swiss Multiple Sclerosis Registry.

Methods: We used retrospective data (diagnoses 1996-2017) of the survey-based Swiss Multiple Sclerosis Registry and fitted logistic regression models (extended time to diagnosis ≥2 years from first symptoms, extended time to disease-modifying treatment initiation ≥1 year from diagnosis) with demographic and a priori defined variables.

Results: Our study, based on 996 persons with multiple sclerosis, suggests that 40% had an extended time to diagnosis, and extended time to disease-modifying treatment initiation was seen in 23%. Factors associated with extended time to diagnosis were primary progressive multiple sclerosis (odds ratio (OR) 5.09 (3.12-8.49)), diagnosis setting outside of hospital (neurologist (private practice) OR 1.54 (1.16-2.05)) and more uncommon first symptoms (per additional symptom OR 1.17 (1.06-1.30)). Older age at onset (per additional 5 years OR 0.84 (0.78-0.90)) and gait problems (OR 0.65 (0.47-0.89)) or paresthesia (OR 0.72 (0.54-0.95)) as first symptoms were associated with shorter time to diagnosis. Extended time to disease-modifying treatment initiation was associated with older age at diagnosis (per additional 5 years OR 1.18 (1.09-1.29)). In more recent years, time to diagnosis and time to disease-modifying treatment initiation tended to be shorter.

Conclusions: Even in recent periods, substantial and partially systematic variation regarding time to diagnosis and time to disease-modifying treatment initiation remains. With the emerging paradigm of early treatment, the residual variation should be monitored carefully.

Keywords: Registries; age of onset; disease-modifying treatment; logistic models; retrospective studies; time to diagnosis.

Figures

Figure 1.

Flow chart showing study population. The first set concerns the time between the first symptoms and diagnosis (1365 to 990) (column 2 in Table 1). The second set is the time between diagnosis and disease-modifying treatment start (1059 to 872) (column 3 in Table 1). CDMS: clinically definite multiple sclerosis.

Figure 2.

Cumulative incidence of multiple sclerosis diagnoses curve displaying the time between first symptoms and diagnosis. The y axis shows the percentage of the whole sample (n=996) that is diagnosed within a certain time frame (years on xaxis). The table underneath the graph displays the number of people who are still ‘at risk’, so not yet diagnosed, at a given time after the first symptoms. The dashed line shows the median, which is at 1.1 years.

Figure 3.

Extended time between first symptoms and diagnosis (≥2 years) model displayed in a forest plot. The odds ratios (ORs) and 95% confidence intervals (CIs) of the individual factors are shown on a log2 scale and the point estimates are stated at the right side of the plot. Values higher than 1 indicate an association with extended time, below 1 with shorter time. The reference levels of the factors are (from top to bottom, variable in brackets): type of MS: relapsing-onset MS (primary progressive MS), sex: female (male), diagnosis period: 1996–2000 (diagnosis period: 2001–2005, 2006–2010, 2011–2015, 2016–2017), diagnosis setting: neurologist (hospital) (neurologist (private practice), general practitioner) and absence of the stated first symptoms (gait problems first symptom, paresthesia first symptom). diag.: diagnosis; pract.: practice; FS: first symptoms. The results are displayed on a log2 scale to give the positive and negative factors the same weight.

Figure 4.

Cumulative incidence of disease-modifying treatment (DMT) initiation curve displaying the time between diagnosis and first DMT initiation. The y axis names the percentage of the whole sample (n=872) that is under DMT within a certain time frame (years on x axis). The table underneath the graph displays the number of people who are still ‘at risk’, so not yet treated with DMT, at a given time after diagnosis. The dashed line shows the median, which is at 2 months.

Figure 5.

Extended time between diagnosis and first disease-modifying treatment (DMT) initiation (1 or more years) model displayed in a forest plot. The odds ratios (ORs) and 95% confidence intervals (CIs) of the individual factors are shown on a log2 scale and the point estimates stated at the right side of the plot. Values higher than 1 indicate an association with extended time, below 1 with shorter time. The reference levels of the factors are (from top to bottom, variable in brackets): sex: female (male), diagnosis period 1996–2000 (2001–2005, 2006–2010, 2011–2015, 2016). diag.: diagnosis; pract.: practice; FS: first symptoms. The results are displayed on a log2 scale to give the positive and negative factors the same weight.