Prevalence of multiple sclerosis in the Lazio region, Italy: use of an algorithm based on health information systems

Impact of adherence to disease-modifying drugs in multiple sclerosis: A study on Italian real-world data

BACKGROUND

Multiple Sclerosis (MS) is a chronic inflammatory disease of the central nervous system requiring complex diagnostic and therapeutic management. Treatment with Disease Modifying Drugs (DMDs) is aimed at reducing relapse rate and disease disability. Few real-world, population-based data are available on the impact of adherence on relapse rate. The objective of this study was to assess the impact of adherence to DMDs on relapses in a real-world Italian setting.

METHODS

Population-based cohort study. People with MS (PwMS) older than 18 years and residing in the Emilia-Romagna region, Northern Italy, were identified through administrative databases using a validated algorithm. A Cox regression model with a time-varying exposure was performed to assess the association between level of adherence to DMDs and relapses over a 5-year period.

RESULTS

A total of 2,528 PwMS receiving a first prescription of DMDs between 2015 and 2019 were included (average age of 42, two-thirds female). Highly adherent PwMS had a 25 % lower hazard of experiencing moderate or severe relapses than non-adherent PwMS (Hazard Ratio 0.75, 95 % CI 0.58 to 0.98), after adjusting for age and sex. Several sensitivity analyses supported the main result.

CONCLUSION

The results of our study support the hypothesis that a high level of DMD adherence in MS is associated with a lower risk of moderate or severe relapse. Therefore, choosing the DMD with which to start drug treatment and recommending adherence to treatment appear to be crucial aspects involving both physicians and patients.

Advantages and limitations of experimental autoimmune encephalomyelitis in breaking down the role of the gut microbiome in multiple sclerosis

Since the first model of experimental autoimmune encephalomyelitis (EAE) was introduced almost a century ago, there has been an ongoing scientific debate about the risks and benefits of using EAE as a model of multiple sclerosis (MS). While there are notable limitations of translating EAE studies directly to human patients, EAE continues to be the most widely used model of MS, and EAE studies have contributed to multiple key breakthroughs in our understanding of MS pathogenesis and discovery of MS therapeutics. In addition, insights from EAE have led to a better understanding of modifiable environmental factors that can influence MS initiation and progression. In this review, we discuss how MS patient and EAE studies compare in our learning about the role of gut microbiome, diet, alcohol, probiotics, antibiotics, and fecal microbiome transplant in neuroinflammation. Ultimately, the combination of rigorous EAE animal studies, novel bioinformatic approaches, use of human cell lines, and implementation of well-powered, age- and sex-matched randomized controlled MS patient trials will be essential for improving MS patient outcomes and developing novel MS therapeutics to prevent and revert MS disease progression.

Shift of multiple sclerosis onset towards older age

OBJECTIVE

To explore whether age at onset increased over time despite a shortened interval from the initial clinical demyelinating event to the diagnosis of multiple sclerosis (MS), as promoted by updated diagnostic criteria.

METHODS

This was an independent, multicentre, retrospective study based on data from 4345 patients with relapsing-onset MS attending three tertiary MS Clinics in Italy. After stratifying the year of MS onset into four periods (<1991, 1991-2000, 2001-2010, 2011-2021), we analysed the temporal trends in age at onset and interval from onset to diagnosis; we then explored the female-to-male ratio and onset location across different classes of age at onset.

RESULTS

We observed an increased mean age at onset, and a shortened mean interval to diagnosis over time (p<0.0001). Accordingly, there were more MS onsets at the older age classes of 40-49, 50-59 and ≥60 years (p<0.0001). In cases with age at onset ≥40 years, we also found an increased female-to-male ratio (p=0.007), more frequent spinal cord (p=0.0004) and less frequent supratentorial onset (p=0.008).

CONCLUSION

Our study shows a forward shift towards an older age at onset of MS, thus suggesting considerable thought on the place-in-therapy of most currently used disease-modifying treatments, and on the standard of care to an older population.

Homozygosity Haplotype and Whole-Exome Sequencing Analysis to Identify Potentially Functional Rare Variants Involved in Multiple Sclerosis among Sardinian Families

Multiple Sclerosis (MS) is a complex multifactorial autoimmune disease, whose sex- and age-adjusted prevalence in Sardinia (Italy) is among the highest worldwide. To date, 233 loci were associated with MS and almost 20% of risk heritability is attributable to common genetic variants, but many low-frequency and rare variants remain to be discovered. Here, we aimed to contribute to the understanding of the genetic basis of MS by investigating potentially functional rare variants. To this end, we analyzed thirteen multiplex Sardinian families with Immunochip genotyping data. For five families, Whole Exome Sequencing (WES) data were also available. Firstly, we performed a non-parametric Homozygosity Haplotype analysis for identifying the Region from Common Ancestor (RCA). Then, on these potential disease-linked RCA, we searched for the presence of rare variants shared by the affected individuals by analyzing WES data. We found: (i) a variant (43181034 T > G) in the splicing region on exon 27 of CUL9; (ii) a variant (50245517 A > C) in the splicing region on exon 16 of ATP9A; (iii) a non-synonymous variant (43223539 A > C), on exon 9 of TTBK1; (iv) a non-synonymous variant (42976917 A > C) on exon 9 of PPP2R5D; and v) a variant (109859349-109859354) in 3'UTR of MYO16.

Multiple sclerosis epidemiological trends in Italy highlight the environmental risk factors

Italy is definitely a high-risk country for multiple sclerosis (MS). Over the last 50 years, several epidemiological studies, including longitudinal surveys, have disclosed that MS incidence and prevalence in Italy mainland and Islands (Sardinia and Sicily) have progressively increased, picturing a semi-parabolic curve. Based on the comprehensive scrutiny of 58 papers, we conclude that the latitude risk gradient does not fit to the Italian map of MS. The genetic heterogeneity of the Italian ethnicities, that likely forms the basis of MS predisposition, does not account for the dramatic increase of MS incidence and prevalence observed in Italy over the last half century that, rather, seems better explained by the effect of environmental factors.

The TRACTOR Project: TRACking and MoniToring Occupational Risks in Agriculture Using French Insurance Health Data (MSA)

OBJECTIVES

A vast data mining project called 'TRACking and moniToring Occupational Risks in agriculture' (TRACTOR) was initiated in 2017 to investigate work-related health events among the entire French agricultural workforce. The goal of this work is to present the TRACTOR project, the challenges faced during its implementation, to discuss its strengths and limitations and to address its potential impact for health surveillance.

METHODS

Three routinely collected administrative health databases from the National Health Insurance Fund for Agricultural Workers and Farmers (MSA) were made available for the TRACTOR project. Data management was required to properly clean and prepare the data before linking together all available databases.

RESULTS

After removing few missing and aberrant data (4.6% values), all available databases were fully linked together. The TRACTOR project is an exhaustive database of agricultural workforce (active and retired) from 2002 to 2016, with around 10.5 million individuals including seasonal workers and farm managers. From 2012 to 2016, a total of 6 906 290 individuals were recorded. Half of these individuals were active and 46% had at least one health event (e.g. declared chronic disease, reimbursed drug prescription) during this 5-year period.

CONCLUSIONS

The assembled MSA databases available in the TRACTOR project are regularly updated and represent a promising and unprecedent dataset for data mining analysis dedicated to the early identification of current and emerging work-related illnesses and hypothesis generation. As a result, this project could help building a prospective integrated health surveillance system for the benefit of agricultural workers.

Estimating the prevalence and incidence of treated type 2 diabetes using prescription data as a proxy: A stepwise approach on Iranian data

AIMS

Type 2 diabetes is a serious health challenge, and large-scale studies on its prevalence in Iran are lacking. In pharmacoepidemiology, case-finding can be done by reviewing the prescription databases for specific drug(s) prescribed for a disease. We aimed to determine the prevalence and incidence of type 2 diabetes in Fars province, Iran, using prescription data and a stepwise approach to ascertain the results.

METHODS

A dataset of 3,113 insured individuals aged ≥35 years were selected. Their Prescription Data Centre records were reviewed for all drugs frequently used in controlling type 2 diabetes available in the Iranian pharmacopeia. Then we used a stepwise method for case-finding. In step one, each individual with a positive drug history for type 2 diabetes was labeled as an individual with diabetes. The next two steps were implemented for ascertainment of step one estimations.

RESULTS

Prevalence of type 2 diabetes based on prescription, internist opinion, and phone call verification in 2015 and 2016 was 9.3% and 10.3%, 8.5% and 9.8%, and 7.2% and 8.7%, respectively. An incidence of 1.9% was determined for 2016.

CONCLUSIONS

We obtained a realistic estimation of prevalence and incidence of treated type 2 diabetes, using prescription data which are large-scale, low cost, and real-time.

Impact of the COVID-19 pandemic on access to healthcare services amongst patients with multiple sclerosis in the Lazio region, Italy

BACKGROUND AND PURPOSE

Multiple sclerosis (MS) is a complex chronic, autoimmune inflammatory disease involving multidisciplinary assessments and interventions. Access to outpatient specialist and home healthcare services was explored during the pandemic outbreak and the lockdown amongst MS patients in the Lazio region. Adherence to disease-modifying therapies (DMTs) is also described.

METHODS

A population-based study was conducted using regional healthcare administrative databases. A validated algorithm was used to identify MS cases over the period 2011-2018. The numbers of specialist and home-based services were compared between 2019 and 2020. The medication possession ratio was used to measure adherence to DMTs.

RESULTS

A total of 9380 MS patients were identified (68% women). A decline in the number of outpatient care services between March and June 2020 compared to the previous year was observed, in particular for rehabilitation (-82%), magnetic resonance imaging (-56%) and neurological specialist services (-91%). Important year-to-year variations were observed in May and June 2020 in home-based nursing and medical care (-91%) and motor re-education services (-74%). Adherence to DMTs was higher in the first 4 months of 2019 compared to the same period of 2020 (67.1% vs. 57.0%).

CONCLUSIONS

A notable disruption of rehabilitative therapy and home-based services as well as in DMT adherence was observed. Since the pandemic is still ongoing and interruption of healthcare services could have a major impact on MS patients, it is necessary to monitor access of MS patients to healthcare resources in order to ensure adequate treatments, including rehabilitative therapies.

Use of geographical information systems in multiple sclerosis research: A systematic scoping review

INTRODUCTION

Geographical information system (GIS) and spatial analysis have an emerging role in the understanding and management of health-related outcomes. However, there is a knowledge gap about the extent to which GIS has supported multiple Sclerosis (MS) research. Therefore, this review aimed to explore the types of GIS applications and the complexity of their visualisation in MS research.

METHODS

A systematic scoping review was conducted based on York's five-stage framework. PubMed, Scopus and Web of Science were searched for relevant studies published between 2000 and 2020 using a comprehensive search strategy based on the main concepts related to GIS and MS. Grounded, inductive analysis was conducted to organize studies into meaningful application areas. Further, we developed a tool to assess the visualisation complexity of the selected papers.

RESULTS

Of 3,723 identified unique citations, 42 papers met our inclusion criteria for the final review. One or more of the following types of GIS applications were reported by these studies: (a) thematic mapping (37 papers); (b) spatial cluster detection (16 papers); (c) risk factors detection (16 papers); and (d) health access and planning (two papers). In the majority of studies (88%), the score of visualisation complexity was relatively low: three or less from the range of zero to six.

CONCLUSIONS

Although the number of studies using GIS techniques has dramatically increased in the last decade, the use of GIS in the areas of MS access and planning is still under-researched. Additionally, the capacity of GIS in visualising complex nature of MS care system is not yet fully investigated.

Validation of an Algorithm to Detect Multiple Sclerosis Cases in Administrative Health Databases in Piedmont (Italy): An Application to the Estimate of Prevalence by Age and Urbanization Level

INTRODUCTION

Italy is considered a high-risk country for multiple sclerosis (MS). Exploiting electronic health archives (EHAs) is highly useful to continuously monitoring the prevalence of the disease, as well as the care delivered to patients and its outcomes. The aim of this study was to validate an EHA-based algorithm to identify MS patients, suitable for epidemiological purposes, and to estimate MS prevalence in Piedmont (North Italy).

METHODS

MS cases were identified, in the period between January 1, 2012 and December 31, 2017, linking data from 4 different sources: hospital discharges, drug prescriptions, exemptions from co-payment to health care, and long-term care facilities. Sensitivity of the algorithm was tested through record linkage with a cohort of 656 neurologist-confirmed MS cases; specificity was tested with a cohort of 2,966,293 residents presumably not affected by MS. Undercount was estimated by a capture-recapture method. We calculated crude, and age- and gender-specific prevalence. We also calculated age-adjusted prevalence by level of urbanization of the municipality of residence.

RESULTS

On December 31, 2017, the algorithm identified 8,850 MS cases. Sensitivity was 95.9%, specificity was 99.97%, and the estimated completeness of ascertainment was 91.9%. The overall prevalence, adjusted for undercount, was 152 per 100,000 among men and 286 among women; it increased with increasing age and reached its peak value in the 45- to 54-year class, followed by a progressive reduction. The age-adjusted prevalence of residents in cities was 15% higher than in those living in the countryside.

DISCUSSION/CONCLUSION

We validated an algorithm based on EHAs to identify cases of MS for epidemiological use. The prevalence of MS, adjusted for undercount, was among the highest in Italy. We also found that the prevalence was higher in highly urbanized areas.

No evidence of disease activity-3 (NEDA-3) status in patients with relapsing remitting multiple sclerosis: Evidence from Saudi cohort receiving mainly Interferon

BACKGROUND

No evidence of disease activity (NEDA) is a composite surrogate assessing the responsiveness to various disease-modifying treatments (DMTs) in patients with relapsing and remitting multiple sclerosis (RRMS), addressing clinical as well as radiological disease activity. Despite the rising prevalence of multiple sclerosis in Saudi Arabia (SA), there is a lack of evidence focusing on this important aspect in the management of RRMS. This study aimed to identify the prevalence of NEDA-3 status achievement in patients with RRMS on DMTs (mainly the interferon) and to describe the factors affecting its attainment.

METHOD

This was a retrospective, cross-sectional study carried out at King Fahd University Hospital after obtaining institutional ethical approval. The electronic records of 119 patients diagnosed with RRMS were reviewed. Clinical manifestations at initial presentation, relapse after starting treatment, disability progression, and development of new lesions on follow-up magnetic resonance imaging were all documented to assess NEDA-3 status. Data were analyzed using Statistical Package for Social Sciences, version 22.

RESULTS

NEDA-3 status was achieved in 41 (33.6%) patients. The female-to-male ratio for all patients was 1.5:1. Interferon (IFN) was the most commonly prescribed DMT. NEDA-3 status was achieved in 30.9% of patients receiving IFN. Mean baseline Expanded Disability Status Scale in patients who did not achieve NEDA-3 was 2.8±1.8. Patients with ataxia (P = <0.001), sphincter disturbances (P=0.002) and infra-tentorial brain lesions (P=0.03) were less likely to achieve NEDA-3 status. Involvement of pyramidal, cerebellar and more than one system at initial presentation was more frequent in patients who could not achieve NEDA-3 status (P=0.002) CONCLUSION: Less than one third of total patients on IFN as DMT could achieve NEDA-3 status in our cohort of patients which is in agreement with the literature published in the West. We could not properly asses NEDA-3 status for other DMTs in our center due to the very small sample size of patients on these DMTs, and recommend future studies including larger number of patients on DMTs other than IFN. Significant differences were identified between the two groups of patients with respect to attainment of NEDA-3 status, which requires further verification by multicenter prospective studies.

Development and validation of a clinical risk score to predict the risk of SARS-CoV-2 infection from administrative data: A population-based cohort study from Italy

BACKGROUND

The novel coronavirus (SARS-CoV-2) pandemic spread rapidly worldwide increasing exponentially in Italy. To date, there is lack of studies describing clinical characteristics of the people at high risk of infection. Hence, we aimed (i) to identify clinical predictors of SARS-CoV-2 infection risk, (ii) to develop and validate a score predicting SARS-CoV-2 infection risk, and (iii) to compare it with unspecific scores.

METHODS

Retrospective case-control study using administrative health-related database was carried out in Southern Italy (Campania region) among beneficiaries of Regional Health Service aged over than 30 years. For each person with SARS-CoV-2 confirmed infection (case), up to five controls were randomly matched for gender, age and municipality of residence. Odds ratios and 90% confidence intervals for associations between candidate predictors and risk of infection were estimated by means of conditional logistic regression. SARS-CoV-2 Infection Score (SIS) was developed by generating a total aggregate score obtained from assignment of a weight at each selected covariate using coefficients estimated from the model. Finally, the score was categorized by assigning increasing values from 1 to 4. Discriminant power was used to compare SIS performance with that of other comorbidity scores.

RESULTS

Subjects suffering from diabetes, anaemias, Parkinson's disease, mental disorders, cardiovascular and inflammatory bowel and kidney diseases showed increased risk of SARS-CoV-2 infection. Similar estimates were recorded for men and women and younger and older than 65 years. Fifteen conditions significantly contributed to the SIS. As SIS value increases, risk progressively increases, being odds of SARS-CoV-2 infection among people with the highest SIS value (SIS = 4) 1.74 times higher than those unaffected by any SIS contributing conditions (SIS = 1).

CONCLUSION

Conditions and diseases making people more vulnerable to SARS-CoV-2 infection were identified by the current study. Our results support decision-makers in identifying high-risk people and adopting of preventive measures to minimize the spread of further epidemic waves.

Incidence, prevalence and mortality of systemic sclerosis in Italy: a nationwide population-based study using administrative health data

To study incidence, prevalence and mortality of systemic sclerosis (SSc) in Italy, assessing epidemiological differences between men and women and in distinct age groups. We performed a nationwide population-based study using administrative health data from regional co-payment exemption registries. Patients entitled with SSc-specific co-payment exemption were included. Fourteen of the 20 Italian regions contributed data covering a population of over 45 million individuals. Crude annual incidence rate, annual prevalence, crude annual mortality rate and standardised mortality ratio (SMR) were calculated. In 2016, the overall crude incidence rate of SSc was 18.5 (95% CI 16.9-20.2) per million per year. Incidence rate was 31.0 (95% CI 28.1-34.1) per million in women, and 4.3 (95% CI 3.2-5.6) per million in men. Peak incidence was observed in the age range 55-69 years. Overall annual prevalence was 306.1 (95% CI 301.1-311.2) per million. Prevalence was 530.8 (95% CI 521.5-540.2) per million in women and 67.8 (95% CI 64.4-71.3) per million in men, with a female to male ratio of 7.8:1. Highest prevalence was observed in the range 70-84 years. Crude annual mortality rate was 27.9 (95% CI 24.9-31.1) per 1000 patients. Overall SMR in patients with SSc was 2.8 (95% CI 1.9-3.8). SMR was 3.8 (95% CI 2.9-5.1) in men and 2.6 (95% CI 1.8-3.6) in women. We provided updated estimates on epidemiology of SSc in Italy. Our findings on incidence, prevalence and mortality of SSc are consistent with previously published literature.

Multiple Sclerosis in the Campania Region (South Italy): Algorithm Validation and 2015-2017 Prevalence

We aim to validate a case-finding algorithm to detect individuals with multiple sclerosis (MS) using routinely collected healthcare data, and to assess the prevalence of MS in the Campania Region (South Italy). To identify individuals with MS living in the Campania Region, we employed an algorithm using different routinely collected healthcare administrative databases (hospital discharges, drug prescriptions, outpatient consultations with payment exemptions), from 1 January 2015 to 31 December 2017. The algorithm was validated towards the clinical registry from the largest regional MS centre (n = 1460). We used the direct method to standardise the prevalence rate and the capture-recapture method to estimate the proportion of undetected cases. The case-finding algorithm including individuals with at least one MS record during the study period captured 5362 MS patients (females = 64.4%; age = 44.6 ± 12.9 years), with 99.0% sensitivity (95% CI = 98.3%, 99.4%). Standardised prevalence rate per 100,000 people was 89.8 (95% CI = 87.4, 92.2) (111.8 for females [95% CI = 108.1, 115.6] and 66.2 for males [95% CI = 63.2, 69.2]). The number of expected MS cases was 2.7% higher than cases we detected. We developed a case-finding algorithm for MS using routinely collected healthcare data from the Campania Region, which was validated towards a clinical dataset, with high sensitivity and low proportion of undetected cases. Our prevalence estimates are in line with those reported by international studies conducted using similar methods. In the future, this cohort could be used for studies with high granularity of clinical, environmental, healthcare resource utilisation, and pharmacoeconomic variables.

Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems

Background

Estimating CKD prevalence is difficult. Information on CKD prevalence is rather scanty in Italy and available figures come from surveys in selected geographical areas. Administrative data have been already demonstrated to be an effective tool in estimating the epidemiological burden of diseases, however there is limited experience in literature as far as CKD is concerned.

Methods

The aim of this study is to develop an algorithm based on regional Health Administrative Databases to identify individuals with CKD and provide estimates of disease prevalence in Lazio Region (Italy); about 5.500.000 inhabitants in 2017. A population-level analysis based on a record-linkage strategy using data from Health Administrative Databases has been applied in Lazio Region. CKD cases were identified between January 1, 2012 and December 31, 2017 using Outpatient Specialist Service Information System, Hospital Discharge Registry, Ticket Exemption Registry and Drug Dispensing Registry. Age-specific and standardized prevalence rates were calculated by gender. CKD cases were classified as higher and lower severity.

Results

The algorithm identified 99,457 individuals with CKD (mean age 71 years, 55.8% males). The exclusive contributions of each regional source used were: 35,047 (35.2%) from Outpatient Specialist Service Information System, 27,778 (27.9%) from Hospital Discharge Registry, 4143 (4.2%) from Ticket Exemption Registry and 463 (0.5%) from Drug Dispensing Registry; 5.1% of cases were found in all databases. The standardized prevalence rate at December 31, 2017 was 1.76, 2.06% for males and 1.50% for females. The prevalence increased with age, rising from 0.33% (age 0–18) up to 14.18% (age 85+) among males and from 0.25% up to 8.18% among females. The proportion of CKD individuals with lower severity disease was 78.7% in both genders.

Conclusions

The proposed algorithm represents a novel tool to monitor the burden of CKD disease, that can be used by the regional government to guide the development and implementation of evidence-based pathways of care for CKD patients. The high prevalence of people with CKD of lower severity should be carefully considered in order to promote diagnosis and optimal management at early stages.

Population size estimation with interval censored counts and external information: Prevalence of multiple sclerosis in Rome

We discuss Bayesian log-linear models for incomplete contingency tables with both missing and interval censored cells, with the aim of obtaining reliable population size estimates. We also discuss use of external information on the censoring probability, which may substantially reduce uncertainty. We show in simulation that information on lower bounds and external information can each improve the mean squared error of population size estimates, even when the external information is not completely accurate. We conclude with an original example on estimation of prevalence of multiple sclerosis in the metropolitan area of Rome, where five out of six lists have interval censored counts. External information comes from mortality rates of multiple sclerosis patients.

Increasing prevalence of multiple sclerosis in Tuscany, Italy

BACKGROUND AND RATIONALE

An increase of prevalence and incidence of multiple sclerosis (MS) has been reported in several countries, especially taking into account a long-term evaluation. This increasing trend often reflects improved case identification and ascertainment due to the refinement of diagnostic criteria. The aim of this study was to update the prevalence rate of MS in Tuscany (central Italy) as of 2017, and to assess if there has been an increasing trend of prevalence in this Region considering a short period of analysis, from 2014 to 2017.

METHODS

To capture prevalent cases, a case-finding algorithm based on administrative data, previously created and validated, was used. As data sources, we considered hospital discharge records, drug-dispensing records, disease-specific exemptions from copayment to health care, home and residential long-term care, and inhabitant registry.

RESULTS

As of January 1, 2017, 7809 cases were identified, of which 69.4% were females and 30.6% were males. Considering temporal variation, an increasing trend was observed, with standardized rates rising from 189.2 in 2014 to 208.7 per 100,000 in 2017.

CONCLUSIONS

Results confirm that prevalence increases every year, probably mainly due to the difference between incidence and mortality, resulting in an increasing trend. Moreover, administrative data may accurately identify MS patients in a routinary way and monitor this cohort along disease care pathways.

Change in multiple sclerosis prevalence over time in Australia 2010–2017 utilising disease-modifying therapy prescription data

Objective:

Determine the prevalence of multiple sclerosis (MS) in Australia in 2017 using MS-specific disease-modifying therapy (DMT) prescription data and estimate the change in prevalence from 2010.

Methods:

DMT prescriptions were extracted from Australia’s Pharmaceutical Benefits Scheme (PBS) data for January–December 2017. Percentages of people with MS using DMTs (DMT penetrance) were calculated using data from the Australian MS Longitudinal Study. Prevalence was estimated by dividing the total number of monthly prescriptions by 12 (except alemtuzumab), adjusted for DMT penetrance and Australian population estimates. Prevalences in Australian states/territories were age-standardised to the Australian population. Comparisons with 2010 prevalence data were performed using Poisson regression.

Results:

Overall DMT penetrance was 64%, and the number of people with MS in Australia in 2017 was 25,607 (95% confidence interval (CI): 24,874–26,478), a significant increase of 4324 people since 2010 ( p < 0.001). The prevalence increased significantly from 95.6/100,000 (2010) to 103.7/100,000 (2017), with estimates highest in Tasmania in 2017 (138.7/100,000; 95% CI: 137.2–140.1) and lowest in Queensland (74.6/100,000; 95% CI: 73.5–75.6). From 2010 to 2017 using the median latitudes for each state/territory, the overall latitudinal variation in MS prevalence was an increase of 3.0% per degree-latitude.

Conclusion:

Consistent with global trends, Australia’s MS prevalence has increased; this probably reflecting decreased mortality, increased longevity and increased incidence.

Prevalence of multiple sclerosis in Sardinia: A systematic cross-sectional multi-source survey

Background:

Partial surveys in sub-regions of Sardinia have suggested a high prevalence of multiple sclerosis (MS) on the island, relative to other Mediterranean populations. We assessed the island-wide prevalence of MS and its detailed distribution in Sardinia.

Methods:

The study population consisted of 5677 MS patients, 1735 men and 3942 women, living in Sardinia. Neurologists retrospectively examined electronic and paper-based records of patients with a diagnosis of MS. The data were then linked to the administrative health information systems. Crude, age-, and sex-specific prevalence estimates of disease were calculated.

Results:

The overall age-adjusted MS prevalence was 330 per 100,000 (95% confidence interval (CI) 321–338) in individuals older than 15 years, 447 in women (95% CI 433–461), and 205 in men (95% CI 195–214). The prevalence was highest in the Ogliastra and Nuoro districts, respectively, 425 (95% CI 372–478) and 419 (95% CI 387–451), and lowest in the Olbia-Tempio district, 217 (95% CI 195–239). Most cases had relapsing–remitting MS (79.3%), 16.3% had secondary-progressive MS, and 4.4% had primary-progressive MS.

Conclusion:

These prevalence are among the highest reported so far worldwide. They provide estimates for comparative analyses in other populations and are essential for public health interventions.

The Prevalence of Multiple Sclerosis in the Metropolitan Area of Rome: A Capture-Recapture Analysis

BACKGROUND

Limited data are available on the prevalence of multiple sclerosis (MS) in central Italy. The objective of this study is to estimate MS prevalence in the metropolitan area of Rome.

METHODS

We used the capture-recapture method to calculate prevalence estimates in the study area. The selected prevalence day was December 31, 2015. A total of 1,007 patients, with a definite diagnosis of MS according to the revised McDonald's criteria, were considered for crude, age- and sex-specific prevalence estimation.

RESULTS

The overall crude prevalence rate was 146.2 cases per 100,000 (95% CI 119.9-172.5). A higher prevalence rate was recorded in females (194.1, 95% CI 149.6-238.6) than in males (93.0, 95% CI 67.2-118.8) with a female to male ratio of 1.8. Age-specific prevalence peaked in the 25-34 , 35-44 and 45-54 years class; moreover, it was found to increase up to the 45-54 years age group in females and the 35-44 years age group in males, decreasing thereafter.

CONCLUSION

The results confirm that the metropolitan area of Rome is a high-risk area for MS.

Epidemiology of Multiple Sclerosis in Austria

BACKGROUND

To assess the incidence rate and prevalence ratio of multiple sclerosis (MS) in Austria.

METHODS

Hospital discharge diagnosis and MS-specific immunomodulatory treatment prescriptions from public health insurances, covering 98% of Austrian citizens with health insurance were used to extrapolate incidence and prevalence numbers based on the capture-recapture method.

RESULTS

A total of 1,392,629 medication prescriptions and 40,956 hospitalizations were extracted from 2 data sources, leading to a total of 13,205 patients. The incidence rate and prevalence ratio of MS in Austria based on the capture-recapture method were 19.5/100,000 person-years (95% CI 14.3-24.7) and 158.9/100,000 (95% CI 141.2-175.9), respectively. Female to male ratio was 1.6 for incidence and 2.2 for prevalence.

CONCLUSIONS

Incidence rates and prevalence ratios of MS in our study are within the upper range of comparable studies across many European countries as well as the United States.

Identifying Relapses in Multiple Sclerosis Patients through Administrative Data: A Validation Study in the Lazio Region, Italy

BACKGROUND

Relapse is frequently considered an outcome measure of disease activity in relapsing-remitting multiple sclerosis (MS). The objectives of this study were to identify relapse episodes in patients with MS in the Lazio region using health administrative databases and to evaluate the validity of the algorithm using patients enrolled at MS treatment centers.

METHODS

MS cases were identified in the period between January 1, 2006 and December 31, 2009 using data from regional Health Information Systems (HIS). An algorithm based on HIS was used to identify relapse episodes, and patients recruited at MS centers were used to validate the algorithm. Positive and negative predictive values (PPV, NPV) and the Cohen's kappa coefficient were calculated.

RESULTS

The overall MS population identified through HIS consisted of 6,094 patients, of whom 67.1% were female and the mean age was 41.5. Among the MS patients identified by the algorithm, 2,242 attended the centers and 3,852 did not. The PPV was 58.9%, the NPV was 76.3%, and the kappa was 0.36.

CONCLUSIONS

The proposed algorithm based on health administrative databases does not seem to be able to reliably detect relapses; however, it may be a helpful tool to detect healthcare utilization, and therefore to identify the worsening condition of a patient's health.

Prevalence, incidence and associated comorbidities of treated hypothyroidism: an update from a European population

OBJECTIVE

Estimates of the prevalence of hypothyroidism in unselected populations date from the late 1990s. We present an update on the prevalence and incidence of overt hypothyroidism in Piedmont, northwest Italy and examine the association between hypothyroidism and multiple chronic comorbidities.

DESIGN AND METHODS

Data were obtained from drug prescription and hospital discharge databases. Individuals who had received at least two levothyroxine prescriptions in 2012 were defined as having hypothyroidism; those who had undergone thyroidectomy or I¹³¹ irradiation in the previous 5 years were defined as having iatrogenic hypothyroidism and those who had either obtained exemption from treatment co-payment or had been discharged from hospital with a chronic comorbidity (diabetes and connective tissue diseases) were identified as having one of these conditions.

RESULTS

The overall crude prevalence was 31.1/1000 (2.3/1000 for iatrogenic hypothyroidism) and the overall crude incidence was 7/1000. The average daily dose of thyroxine (122 µg) roughly corresponded to 1.7 µg/kg. There was a strong association between hypothyroidism and diabetes (type 1, type 2 or gestational) and with autoimmune diseases, with the odds ratio ranging from 1.43 (1.02-1.99) for psoriatic arthritis to 4.99 (3.06-8.15) for lupus erythematosus.

CONCLUSIONS

As compared with previous estimates, the prevalence of hypothyroidism rose by about 35%, driven mainly by non-iatrogenic forms. The increase may be due to either population aging or improved diagnostic capability or both. The frequent co-occurrence of hypothyroidism with other multiple chronic conditions characterizes it more as a comorbidity rather than an isolated chronic disease.

Multiple Sclerosis Epidemiology in Europe

Multiple sclerosis is characterized by a non-homogeneous distribution around the world. Some authors in past described a latitude gradient, with increasing risk from the equator to North and South Poles, but this theory is still controversial. Regarding Europe, there are many articles in the literature concerning the epidemiology of this disease but, unfortunately, they are not always comparable due to different methodologies, they do not cover all countries in the continent, and most of them reported data of small areas and rarely at a national level. In 2012 there were 20 national registries that could help to describe the epidemiology of the disease and, in addition, there is an European Register for Multiple Sclerosis that collect data from already existing national or regional MS registries and databases. Another valid alternative to obtain epidemiological data, also at national level, in a routinely and cost-saving way is through administrative data that are of increasing interest in the last years.