Administrative data for observational research in multiple sclerosis: Opportunities and challenges

Building and validating trend-based multiple sclerosis case definitions: a population-based cohort study for Manitoba, Canada

OBJECTIVE

This study aims to (1) build and validate model-based case definitions for multiple sclerosis (MS) that use trends (ie, trend-based case definitions) and (2) to apply dynamic classification to identify the average number of data years needed for classification (ie, average trend needed).

DESIGN

Retrospective cohort study design.

PARTICIPANTS

608 MS cases and 59 620 MS non-cases.

SETTING

Data from 1 April 2004 to 31 March 2022 were obtained from the Manitoba Population Research Data Repository. MS case status was ascertained from homecare records and linked to health data. Trend-based case definitions were constructed using multivariate generalised linear mixed models applied to annual numbers of general and specialist physician visits, hospitalisations and MS healthcare contacts or medication dispensations. Dynamic classification, which ascertains cases and non-cases annually, was used to estimate mean classification time. Classification accuracy performance measures, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), proportion correctly classified (PCC) and F1-scores, were compared for trend-based case definitions and a deterministic case definition of 3+MS healthcare contacts or medication dispensations.

RESULTS

When applied to the full study period, classification accuracy performance measure estimates for all case definitions exceeded 0.90, except sensitivity and PPV for the trend-based dynamic case definition (0.88, 0.64, respectively). PCC was high for all case definitions (0.94-0.99); F1-scores were lower for the trend-based case definitions compared with the deterministic case definition (0.74-0.93 vs 0.96). Dynamic classification identified 5 years as the average trend needed. When applied to the average trend windows, accuracy estimates for trend-based case definitions were lower than the estimates from the full study period (sensitivity: 0.77-0.89; specificity: 0.90-0.97; PPV: 0.54-0.81; NPV: 0.97-0.99; F1-score: 0.64-0.84). Accuracy estimates for the deterministic case definition remained high, except sensitivity (0.42-0.80). F1-score was variable (0.59-0.89).

CONCLUSIONS

Trend-based and deterministic case definitions classifications were similar to a population-based clinician assessment reference standard for multiple measures of classification accuracy. However, accuracy estimates for both trend-based and deterministic case definitions varied as the years of data used for classification were reduced. Dynamic classification appears to be a viable option for identifying the average trend needed for trend-based case definitions.

Psychiatric Comorbidity During the Prodromal Period in Patients With Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Psychiatric morbidity is common after a multiple sclerosis (MS) diagnosis. However, little is known about psychiatric comorbidity during the prodromal phase (before MS onset). To compare the prevalence and relative burden of psychiatric morbidity in individuals with MS with matched controls before MS onset.

METHODS

Using linked administrative and clinical data from British Columbia, Canada, we identified cases with MS through a validated algorithm or from neurologist-diagnosed MS clinic attendees. Cases were matched by age, sex, and geographical location with up to 5 general population controls. We identified psychiatric morbidity through a validated definition and determined its prevalence in cases/controls in the 5 years before the first demyelinating claim of cases with MS ("administrative cohort") or symptom onset ("clinical cohort") and estimated case/control prevalence ratios with 95% CIs. We also compared the yearly number of physician visits for psychiatric morbidity, visits to psychiatrists, psychiatric-related admissions, and psychotropic dispensations pre-MS onset in cases/controls regardless of whether psychiatric morbidity algorithm was fulfilled using negative binomial regression fitted through generalized estimating equations; results were reported as adjusted rate ratios with 95% CIs. We assessed yearly trends through interaction terms between cases/controls and each year pre-MS onset.

RESULTS

The administrative cohort comprised 6,863/31,865 cases/controls; the clinical cohort comprised 966/4,534 cases/controls. Over the entire 5-year period pre-MS onset, 28.0% (1,920/6,863) of cases and 14.9% (4,738/31,865) of controls (administrative cohort) had psychiatric morbidity, as did 22.0% (213/966) of clinical cases and 14.1% (638/4,534) controls. Psychiatric morbidity prevalence ratios ranged from 1.58; 95% CI 1.38-1.81 (clinical cohort) to 1.91; 95% CI 1.83-2.00 (administrative cohort). In the administrative cohort, health care use was higher for cases in each year pre-MS onset (all 95% CIs >1); physician visits were 78% higher in year 5 pre-MS onset and 124% 1 year before; visits to psychiatrists were 132% higher in year 5 and 146% in year 1; hospitalizations were 129% higher in year 5 and 197% in year 1; and prescription dispensations were 72% higher in year 5 and 100% in year 1. Results were not significant in the clinical cohort.

DISCUSSION

Psychiatric morbidity represents a significant burden before MS onset and may be a feature of the MS prodrome.