Trajectory of health care resources among adults stopping or reducing treatment frequency of botulinum toxin for chronic migraine treatment in Alberta, Canada.

OBJECTIVE: Understand health resource, medication use, and cost of adults with chronic migraine who received guideline-recommended onabotulinumtoxinA (botulinum toxin) treatment frequency and then continued or reduced/stopped. BACKGROUND: Botulinum toxin may be a beneficial treatment for chronic migraine; the trajectory of health resources utilization among those with continued or reduced/stopped use is unclear. METHODS: A retrospective population-based cohort study utilizing administrative data from Alberta, Canada (2012-2020), was performed. A cohort of adults who received ≥5 botulinum toxin treatment cycles for chronic migraine over 18 months (6-month run-in; 1-year pre-index period) were grouped into those who (1) continued use (≥3 treatments/year), or (2) stopped or reduced use (stopped for 6 months then received 0 or 1-2 treatments/year, respectively) over a 1-year post-index period. Health resources and medication use were described, and pre-post costs were assessed. A second cohort that received ≥3 treatments/year immediately followed by 1 year of stopped or reduced use was considered in sensitivity analysis. RESULTS: Pre-post health resource, medication use, and costs were similar among those with continued use (n = 3336). Among those who stopped or reduced use (n = 1099; 756 stopped, 343 reduced), health resource, medication use, and costs were lower in the post- (total median per-person cost [IQR]: all-cause $4851 [$8090]; migraine-related $835 [$1915]) versus pre- (all-cause $6096 [$7207]; migraine-related $2995 [$1950]) index period (estimated cost ratios [95% CI]: total all-cause 0.86 [0.79, 0.95]; total migraine-related 0.44 [0.40, 0.48]). In the second cohort (n = 3763), return to continued use (≥3 treatments/year) occurred in up to 70.4% in those with reduced use. CONCLUSIONS: Of adults treated with botulinum toxin for chronic migraine, 75.2% had continued use, stable health resource and medication use, and costs over a 2 year period. In those that stopped/reduced use, the observed lower health resource and migraine medication use may indicate improved symptom control, but the resumption of guideline-recommended treatment intervals after reduced use was common.

Characteristics of Adults with Migraine in Alberta, Canada: A Population-Based Study.

BACKGROUND: Migraine, including episodic migraine (EM) and chronic migraine (CM), is a common neurological disorder that imparts a substantial health burden. OBJECTIVE: Understand the characteristics and treatment of EM and CM from a population-based perspective. METHODS: This retrospective population-based cross-sectional study utilized administrative data from Alberta. Among those with a migraine diagnostic code, CM and EM were identified by an algorithm and through exclusion, respectively; characteristics and migraine medication use were examined with descriptive statistics. RESULTS: From 79,076 adults with a migraine diagnostic code, 12,700 met the criteria for CM and 54,686 were considered to have EM. The majority of migraineurs were female, the most common comorbidity was depression, and individuals with CM had more comorbidities than EM. A larger proportion of individuals with CM versus EM were dispensed acute (80.6%: CM; 63.4%: EM) and preventative (58.0%: CM; 28.9%: EM) migraine medications over 1 year. Among those with a dispensation, individuals with CM had more acute (13.6 ± 32.2 vs. 4.6 ± 10.9 [mean ± standard deviation], 95% confidence interval [CI] 7.7-8.3), and preventative (12.6 ± 43.5 vs. 5.0 ± 12.6, 95% CI 6.9-8.4) migraine medication dispensations than EM, over 1-year. Opioids were commonly used in both groups (proportion of individuals dispensed an opioid over 1-year: 53.1%: CM; 25.7%: EM). CONCLUSIONS: Individuals with EM and CM displayed characteristics and medication use patterns consistent with other reports. Application of this algorithm for CM may be a useful and efficient means of identifying subgroups of migraine using routinely collected health data in Canada.

Health resource utilization and cost before versus after initiation of second-generation long-acting injectable antipsychotics among adults with schizophrenia in Alberta, Canada: a retrospective, observational single-arm study.

BACKGROUND: Long-acting injectable (LAI) antipsychotics, along with community treatment orders (CTOs), are used to improve treatment effectiveness through adherence among individuals with schizophrenia. Understanding real-world medication adherence, and healthcare resource utilization (HRU) and costs in individuals with schizophrenia overall and by CTO status before and after second generation antipsychotic (SGA)-LAI initiation may guide strategies to optimize treatment among those with schizophrenia. METHODS: This retrospective observational single-arm study utilized administrative health data from Alberta, Canada. Adults (≥ 18 years) with schizophrenia who initiated a SGA-LAI (no use in the previous 2-years) between April 1, 2014 and March 31, 2016, and had ≥ 1 additional dispensation of a SGA-LAI were included; index date was the date of SGA-LAI initiation. Medication possession ratio (MPR) was determined, and paired t-tests were used to examine mean differences in all-cause and mental health-related HRU and costs (Canadian dollars), comprised of hospitalizations, physician visits, emergency department visits, and total visits, over the 2-year post-index and 2-year pre-index periods. Analyses were stratified by presence or absence of an active CTO during the pre-index and/or post-index periods. RESULTS: Among 1,211 adults with schizophrenia who initiated SGA-LAIs, 64% were males with a mean age of 38 (standard deviation [SD] 14) years. The mean overall antipsychotic MPR was 0.39 (95% confidence interval [CI] 0.36, 0.41) greater during the 2-year post-index period (0.84 [SD 0.26]) compared with the 2-year pre-index period (0.45 [SD 0.40]). All-cause and mental health-related HRU and costs were lower post-index versus pre-index (p < 0.001) for hospitalizations, physician visits, emergency department visits, and total visits; mean total all-cause HRU costs were $33,788 (95% CI -$38,993, -$28,583) lower post- versus pre-index ($40,343 [SD $68,887] versus $74,131 [SD $75,941]), and total mental health-related HRU costs were $34,198 (95%CI -$39,098, -$29,297) lower post- versus pre-index ($34,205 [SD $63,428] versus $68,403 [SD $72,088]) per-patient. Forty-three percent had ≥ 1 active CTO during the study period; HRU and costs varied according to CTO status. CONCLUSIONS: SGA-LAIs are associated with greater medication adherence, and lower HRU and costs however the latter vary according to CTO status.

Inferring the true number of SARS-CoV-2 infections in Japan.

INTRODUCTION: In Japan, as of December 31, 2021, more than 1.73 million laboratory-confirmed cases have been reported. However, the actual number of infections is likely to be under-ascertained due to the epidemiological characteristics such as mild and subclinical infections and limited testing availability in the early days of the pandemic. In this study, we infer the true number of infections in Japan between January 16, 2020, and December 31, 2021, using a statistical modelling framework that combines data on reported cases and fatalities. METHODS: We used reported COVID-19 deaths and age-specific infection fatality ratios (IFR) to impute the true number of infections. Estimates of IFR were informed from published studies and were adjusted to reflect the effects of pharmaceutical interventions, mass vaccination, and evolving variants. To account for the uncertainty in IFR, we sampled values from relevant distributions. RESULTS: We estimated that as of December 31, 2021, 3.07 million (CrI: 2.05-4.24 million) people had been infected in Japan, which is 1.77 times higher than the 1.73 million reported cases. Our meta-analysis confirmed that these findings were consistent with the intermittent seroprevalence studies conducted in Japan. CONCLUSIONS: We have estimated that a substantial number of COVID-19 infections in Japan were unreported, particularly in adults. Our approach provides a more realistic assessment of the true underlying burden of COVID-19. The results of this study can be used as fundamental components to strengthen population health control and surveillance measures.

Incidence and prevalence, and medication use among adults living with dermatomyositis: an Alberta, Canada population-based cohort study.

Dermatomyositis is a rare disease characterized by progressive muscle weakness and skin rashes. Estimates of incidence and prevalence are fundamental measures in epidemiology, but few studies have been conducted on dermatomyositis. To address this knowledge gap, we conducted a population-based study to determine the contemporary incidence (between 2013 and 2019) and prevalence (2019) of adults living with dermatomyositis using administrative health data in Alberta, Canada. We also described disease-related medication use, as there are very few approved medications for the treatment of dermatomyositis, and no Canadian therapeutic guidelines. The average age- and sex-standardized annual incidence of dermatomyositis was 2.8-3.0 cases per 100,000 adults, and prevalence was 28.6 cases per 100,000 adults, which is greater than reported in other cohorts. Dermatomyositis-related medication use decreased from 73% in the first year to 46% in the eighth year after diagnosis. Glucocorticoids were the most commonly used drug class, often taken concurrently with various immunomodulatory agents; this medication use aligns with empirically-based recommendations and the few therapeutic guidelines for dermatomyositis. Considering that Alberta may have one of the highest rates of dermatomyositis among adults, further research on the burden of disease is warranted for planning within the health care system.

A machine learning approach to predict ethnicity using personal name and census location in Canada.

BACKGROUND: Canada is an ethnically-diverse country, yet its lack of ethnicity information in many large databases impedes effective population research and interventions. Automated ethnicity classification using machine learning has shown potential to address this data gap but its performance in Canada is largely unknown. This study conducted a large-scale machine learning framework to predict ethnicity using a novel set of name and census location features. METHODS: Using census 1901, the multiclass and binary class classification machine learning pipelines were developed. The 13 ethnic categories examined were Aboriginal (First Nations, Métis, Inuit, and all-combined)), Chinese, English, French, Irish, Italian, Japanese, Russian, Scottish, and others. Machine learning algorithms included regularized logistic regression, C-support vector, and naïve Bayes classifiers. Name features consisted of the entire name string, substrings, double-metaphones, and various name-entity patterns, while location features consisted of the entire location string and substrings of province, district, and subdistrict. Predictive performance metrics included sensitivity, specificity, positive predictive value, negative predictive value, F1, Area Under the Curve for Receiver Operating Characteristic curve, and accuracy. RESULTS: The census had 4,812,958 unique individuals. For multiclass classification, the highest performance achieved was 76% F1 and 91% accuracy. For binary classifications for Chinese, French, Italian, Japanese, Russian, and others, the F1 ranged 68-95% (median 87%). The lower performance for English, Irish, and Scottish (F1 ranged 63-67%) was likely due to their shared cultural and linguistic heritage. Adding census location features to the name-based models strongly improved the prediction in Aboriginal classification (F1 increased from 50% to 84%). CONCLUSIONS: The automated machine learning approach using only name and census location features can predict the ethnicity of Canadians with varying performance by specific ethnic categories.

Asthma and wheezing are associated with depression and anxiety in adults: an analysis from 54 countries.

Background. Asthma and depression are important public-health concerns worldwide. While some epidemiologic studies have shown asthma and wheezing to be associated with depression and anxiety, the patterns are unclear at the multinational level due to the lack of cross-study comparability. Our study examined the associations of self-reported asthma diagnosis and current wheezing with self-reported depression diagnosis and 30-day anxiety using an international survey. Methods. Using the 2002 World Health Survey, a standardized international survey conducted by the WHO, we estimated the associations between diagnosed asthma and current wheezing with diagnosed depression and 30-day anxiety via multiple logistic regressions for 54 countries worldwide. Results. Diagnosed depression and 30-day anxiety were associated with diagnosed asthma in 65% and 40% of the countries, respectively. Diagnosed depression and 30-day anxiety were associated with current wheezing in 83% and 82% of the countries, respectively. Conclusions. The association between asthma and depression was generally seen at the global level. These results indicated the importance of addressing the asthma-depression comorbidity as public-health and clinical management priorities, in order to improve the overall health of the countries.