Comparison of performances of SIREN or MFSRS in stroke risk prediction in an African environment

Stroke is the second leading cause of death and the third leading cause of disability-adjusted life years (DALYs) lost worldwide [1, 2]. The incidence and mortality of stroke differ between countries, ethnic groups, races, and geographical regions [3]. Over the past three to four decades, the burden of stroke has reduced in high-income countries (due to improvements in prevention, acute stroke care, and neurorehabilitation) [4, 5] but has increased in low- and middle-income countries [1] with incidence rates in the latter now exceeding those in the former [1, 4, 6, 7]. The World Health Organization (WHO) had earlier estimated that by the year 2030, 80% of all strokes will occur in low-and-middle-income countries such as Nigeria [8]. In Nigeria, several population-based studies point to high incidence (0.6–1.63 per 1000 persons) and prevalence (1.14–14.6 per 1000 persons) rates of stroke in different regions of the country [9‐12]. In general, the global number of stroke survivors and the global burden of stroke have increased [6, 13]. This is attributable to population growth, aging, improved stroke care, and increased prevalence of modifiable risk factors of stroke [6, 13].

The risk factors of stroke could be classified into modifiable and non-modifiable risk factors [14, 15]. The modifiable risk factors are dynamic as more and more of these modifiable risk factors emerge as time goes by [16]. Ninety percent of all strokes are caused by modifiable risk factors [17, 18] with hypertension, apolipoprotein, current smoking, poor diet, physical inactivity, abdominal obesity, psychosocial factors, cardiac problems, high alcohol consumption, and diabetes mellitus accounting for 91.5% and 87.1% of the population-attributable risk for ischemic and hemorrhagic stroke in the INTERSTROKE study (conducted in 32 countries including Nigeria) [19]. Hence, the overwhelming majority of strokes can be prevented through awareness, control of blood pressure, and lifestyle changes (healthy diet, physical activity, and smoking cessation) [18]. Consequently, rating and controlling of risk factors of stroke have been an important focus of stroke prevention globally, and have led to the formulation of stroke risk evaluation algorithms [14, 20].

In the literature, there are four available stroke risk evaluation algorithms: the Modified Framingham Stroke Risk Score (MFSRS), the QStroke, the Stroke Riskometer™, and more recently, the Stroke Investigative Research and Educational Network (SIREN) [3, 21]. The MFSRS, the QStroke, and the Stroke Riskometer were developed in high-income countries and were therefore tailor-made to suit individuals in these countries. However, with the nature and strength of stroke risk factors varying across races, ethnic groups, and geographical locations [22, 23], these risk assessment algorithms may not perform equally effectively across geographical locations and races. Due to some subtle evidence about the existing evaluation algorithm not being entirely suitable for African environment, Akpa et al. [3] developed the SIREN, a stroke risk score that was designed to accommodate the major stroke risk factors in African environments [3, 24] with Nigeria being one of the countries involved in the development. In addition to the factors (age, sex, dyslipidaemia, blood pressure, and diabetic status) explored in the MFSRS, the SIREN also included other factors deemed important in the African environments (which include sugar, salt, meat, and leafy vegetable consumption, physical inactivity, stress, waist-hip ratio, history and status of cardiac disease, educational attainment, and income level). Apart from the developers, no study seemed to have utilized the SIREN in Nigeria.

Although an accurate assessment of stroke risk factors in each region and population group of the world is important, the benefits of international or interregional comparison of these risk factors can also not be overemphasized. Understandably, this comparison can easily be engendered by a uniformity of risk assessment tools. Though some shortcomings of the MFSRS have been reported, it is still the most popular, utilized, and well-accepted stroke risk prediction score, thereby making it a suitable candidate for this international comparison [25, 26]. The MFSRS has been reported not to factor in modifiable risk factors indigenous to Africans [22] with no study on its applicability and performance in an African environment being available for reference. There seems to be no Nigerian population-based study that has utilized the MFSRS. However, previous Nigerian studies have revealed that the MFSRS/FSRS can be sensitive in differentiating risk scores between different pathological groups [27, 28]. This study was therefore designed to determine the level of convergence in outcomes between the MFSRS and the SIREN in a community in Nigeria. It was hypothesized that the correlation between the MFSRS and the SIREN will be moderate.

This study aimed to compare the performance of the MFSRS and the SIREN in the assessment of stroke risk factors in an African (Nigerian) environment. The MFSRS was developed in a high-income country and has been a tool frequently used for the comparison of stroke risks across countries and continents [25, 26]. On the other hand, the SIREN was primarily developed for usage in low-and middle-income African countries [3]. It may be apt to compare the performances of these instruments in an African environment as this may give a better perspective and engender more understanding of stroke risk data emanating from Africa.

Present results revealed that stroke risks were highly prevalent in the present sample. This agrees with several reports about the continuous increase of stroke in African countries [6]. The most prevalent risk factors among the present participants were hypertriglyceridemia, raised waist-hip ratio, physical inactivity, psychological stress, hypertension, sugar consumption, poor income, and failure to consume leafy vegetables. Hypertension, poor diet, physical inactivity, and abdominal obesity were among the ten risk factors of stroke that accounted for 91.5% and 87.1% of the population-attributable risk for ischemic and hemorrhagic stroke in the multinational INTERSTROKE study [19]. The high prevalence of stroke risk factors in this study was further buttressed by the risk estimate of 34.5% by the SIREN. However, the MFSRS gave a low risk estimate (6.0%) and prevalence (16.0%) which is lower than stroke risks from Asian and European studies [38, 39] that had utilized the MFSRS. The MFSRS has been reported to likely underestimate stroke risks from Africa [40].

Results suggest that there may be significant differences in the rating of the SIREN and the MFSRS in the setting of this study. For example, only three out of the six stroke risks accounted for in the MFSRS made the list of the ten most prevalent risk factors in this study with the eight others being the factors only considered in the SIREN. Also, smoking status given a high priority in the MFSRS was lowly prevalent and lowly ranked risk by the SIREN in the present study while meat consumption, low income level, non-consumption of leafy vegetables, physical inactivity, and so on that were not taken cognizance of in the MFSRS were the seemingly most impactful risks in the present results according to the SIREN. Hypertriglyceridemia, hypertension, age, diabetes status, and low HDL usually accounted for in the MFSRS occupied the first, third, seventh, fourteenth, and sixteenth positions on the SIREN scale. This may be suggesting some levels of discordance in the performances of these two algorithms in the studied environment. The perceived discordance is buttressed by the presence of poor correlation between the total scores on the SIREN and the MFSRS. Some questions may thus emanate from these findings. Could the MFSRS and SIREN be respectively underestimating and overestimating stroke risks in African environments? Could there be a need to modify one or the two algorithms to more accurately assess the risks of stroke in Africa, and thus engender a more credible international comparison? Could the MFSRS justifiably have an African version that will vary from the one used in high-income countries? Consequently, there may be a yearning for further large African-centred quality control studies to ascertain this in order to improve the credibility ratings of stroke risks coming from Africa. However, the literature seems to agree with the estimates from the SIREN in the present study. The high stroke risk estimate by the SIREN in the present study is in concordance with previous reports of high risks in low-and middle-income countries [6]. On the other hand, the prevalence of stroke risks accounted for by the MFSRS in the present study was lower than the prevalence figures from higher economies [38, 39]. Furthermore, the fact that the SIREN was primarily developed for use in African countries might suggest that it would perform better than the MFSRS in the African environment.

The proportion of young adults recorded in this study reflects the pattern of Nigerian population distribution [41]. However, the educational attainment and employment rate in this study were far higher than the generality of Nigerians. This could be attributable to real improvements in the educational attainment of the population because Anambra State had been occupying a top position in education among the 36 states of Nigeria within the last 15 years [42]. The purported increase in educational attainment would understandably increase the chances of getting employed. Being a commercial centre, it may be easy to understand why the majority of the population were traders.

The present study was not without limitations. Though this was a population-based study, a larger sample size that was not restricted to a single Nigerian community might have given more power to this study. However, the fact that the two algorithms were applied among the same African population can still give some level of credence to the revealed discordance between the algorithms in an African setting. Furthermore, the quality of this study would have been improved further if some potential participants did not decline participation in the study due to erroneous fear of using their blood sample for diabolism, a usual belief in the setting of this study.

Stroke risks were highly prevalent in the sampled Nigerian population with hypertriglyceridemia, raised waist-hip ratio, hypercholesterolemia, physical inactivity, psychological stress, hypertension, sugar consumption, poor income, and failure to consume leafy vegetables being the most prevalent risk factors. The poor correlation between the two algorithms and the fact that risk factors not accounted for in the MFSRS were among the most impactful according to the SIREN rating suggested some significant levels of disagreement between the two algorithms. From the literature and the global present trend of stroke risk, the MFSRS seemed to underestimate stroke risks in the present population while the SIREN seemed to agree with the literature thus suggesting that the latter might be a better predictor of stroke risks than the former in an African environment. Despite this, there is a need for large African-based quality control studies to determine the lapses (if there is any) in one or the two algorithms to improve the quality of stroke risk data emanating from Africa. Before then, there may be a need to apply caution while interpreting stroke risk estimates from Africa using these algorithms.