Summary of key findings
We have developed and validated QStroke, which is a new algorithm to identify patients at high risk of ischaemic stroke based on contemporaneous primary care data from the UK. Although QStroke has been designed to be used in all patients without a history of stroke or transient ischaemic attack, we envisage that its primary use will be in the subset of patients with atrial fibrillation for whom anticoagulation is considered.
QStroke incorporates established risk factors for stroke or transient ischaemic attack, many of which are absent from existing stroke risk assessment tools. QStroke includes age, sex, deprivation, ethnicity, body mass index, systolic blood pressure, total cholesterol:HDL cholesterol ratio, smoking status (five levels), diabetes type, congestive cardiac failure, coronary heart disease, rheumatoid arthritis, chronic kidney disease, treated hypertension, valvular heart disease, and family history of premature coronary heart disease.
Comparison with existing risk prediction scores
We tested the performance of QStroke in a separate cohort of patients without stroke or transient ischaemic attack and demonstrated good levels of discrimination and calibration and improved performance compared with the Framingham stroke risk score.
We also tested QStroke in the subset of patients with atrial fibrillation, for whom anticoagulation might be indicated. We compared the performance of QStroke with both CHADS2 and CHA2DS2VASc in patients without a prior stroke to ensure a fair comparison between the scores. We found some indication of improved performance on all measures of discrimination, although confidence intervals were wide. The comparison between QStroke and CHADS2 is important since the use of CHADS2 is currently incentivised as an indicator in the primary care Quality and Outcomes Framework and is used to determine which patients require anticoagulation. We also demonstrated some evidence of improved performance of QStroke compared with the newer CHA2DS2VASc, although this was less marked. None the less, we think the difference between performance of QStroke and CHA2DS2VASc could be important for those patients who are reclassified with QStroke and for whom advice on treatment with anticoagulation might change. For example, patients at high predicted risk on QStroke but classified as low risk on CHA2DS2VASc might require anticoagulation. Conversely, the patients classified as high risk with CHA2DS2VASc but low predicted risk with QStroke might be able to avoid unnecessary anticoagulation.
We have not provided definite comment on what threshold of absolute risk should be used for intervention, as that would include cost effectiveness analyses, which are outside the scope of this study. Ideally the review of a risk score is best judged around a risk threshold. This can be appropriate for other scores such as QRISK2 determining whether to intervene with primary prevention of cardiovascular disease. When determining whether to intervene with primary prevention of cardiovascular disease, the current 10 year risk threshold is 20%, making comparisons of different risk scores such as QRISK2 around this threshold appropriate. Stroke prevention in the population with atrial fibrillation has not yet reached this level of sophistication. The currently accepted risk scores, such as those of CHADS2, have not described their outputs in terms of absolute risk of stroke, and, as such, there is no consensus regarding a risk threshold. In contrast, QStroke calculates the absolute risk of stroke and so, unlike CHADS2, is able to inform future debate around what threshold is appropriate to intervene with oral anticoagulation. Choice of threshold is a complex area dependent on many variables relating to clinical outcomes and service costs, and to do justice to the complexity, we consider it should be the subject of a separate paper. We have, however, provided analyses using a range of thresholds of risk which can be used to help inform future analyses and guidelines
The results of our validation statistics for CHA2
VASc and CHADS2
in patients with atrial fibrillation are broadly similar to those reported using another UK GP database25
and a Danish registry cohort.14
Both studies showed improved performance of CHA2
VASc compared with CHADS2.
The Danish study additionally showed that CHA2
VASc was better for identifying those at low and intermediate risk.14
Our results, however, are not directly comparable with those of the Danish study as that study included venous thromboembolism in the definition of the outcome, whereas our study included only stroke and transient ischaemic attack.14
VASc, and CHADS2
tended to perform better in men with atrial fibrillation compared with women with atrial fibrillation, which deserves further study.
Implications for clinical practice
Whilst the new QStroke algorithm is more complex than CHA2DS2VASc or CHADS2, it has several advantages. It includes weighting for ethnicity and deprivation, which should help avoid widening health inequalities. The algorithm uses routinely collected data, which means it can be easily and regularly updated to reflect changes in populations, improvements in data quality, advances in knowledge, and evolving guidelines. The algorithms can also be implemented in primary care since the data are already present in the clinical computer systems. QStroke will work both in populations with atrial fibrillation and those without atrial fibrillation—though the immediate clinical use might be for risk stratification among patients with atrial fibrillation, QStroke can still inform other patients of their specific risk of stroke or transient ischaemic attack as part of their general cardiovascular risk assessment.
QStroke has also been designed to be integrated into UK general practice clinical computer systems, where the risk factors are already recorded and used to calculate closely related scores such as QRISK2. Much of the apparent complexity relating to additional variables and interactions can be incorporated into the software using data already entered into each patient’s electronic health record. There are only three variables in QStroke (congestive cardiac failure, coronary heart disease, and valvular heart disease) that are not in QRISK2. Where possible we used the definitions from the Quality and Outcomes Framework, which should simplify its implementation. QRISK2 is integrated into all four UK GP clinical computer systems, and QStroke can be implemented in a similar way. For example, clinicians can use structured templates within the consultation to calculate a patient’s risk and use the information to inform treatment decisions. It can also be used in “batch processing” mode to calculate an estimated risk for all eligible patients registered with a practice so that patients with the highest risk can be recalled. Additionally, QStroke could easily be integrated in the GRASP-AF tool (Guidance on Risk Assessment and Stroke Prevention in Atrial Fibrillation), which is a primary care database interrogation tool designed to help identify possible candidates for anticoagulation from practice lists.29
Another advantage of QStroke compared with either CHA2DS2VASc or CHADS2 is that it gives an absolute measure of stroke risk which can more easily be explained to a patients (for example, “Of 100 people like you, X are likely to have a stroke or transient ischaemic attack within the next 10 years”), rather than a simple integer that has no direct interpretation of absolute stroke risk. Should a tool be developed that quantifies absolute risk of bleeding with anticoagulation, it will be possible to do a more direct assessment of risk of stroke in patients compared with potential risk and benefits of anticoagulation, thus providing better information for patients to make an informed choice. This is important since anticoagulation treatment is usually life long, and the risk of bleeding increases with increasing age.
QStroke has not been designed be used in patients with atrial fibrillation who have had a previous stroke, since all such patients should be prescribed anticoagulation and an estimation of risk will not affect the clinical decision. To ensure a fair comparison, we compared the performance of QStroke against CHADS2 and CHA2DS2VASc only in patients with atrial fibrillation who were free from stroke. However, removing the patients already receiving treatment may result in the higher risk patients being removed from the cohort, which might then result in an underestimation of risk in patients with atrial fibrillation overall.
The methods to derive and validate this model are the same as those used for the original development of QRISK2 and a range of other risk prediction tools. The strengths and limitations of the approach have already been discussed in detail,4
including information on multiple imputation of missing data. In summary, key strengths include size, duration of follow-up, representativeness, and lack of selection, recall, and respondent bias. UK general practices have good levels of accuracy and completeness in recording clinical diagnoses and prescribed drugs.35
We think our study has good face validity since it has been conducted in the setting where most patients in the UK are assessed, treated, and followed up. Limitations include lack of formally adjudicated outcomes, information bias, and potential for bias due to missing data. Our database has linked cause of death from the UK Office of National Statistics, and our study is therefore likely to have picked up most cases of stroke or transient ischaemic attack, thereby minimising ascertainment bias. Patients who die of stroke in hospital will have stroke or transient ischaemic attack recorded on their death certificate and therefore will be included on the linked cause of death data. Other patients who have stroke or transient ischaemic attack diagnosed in hospital who do not die will have the information recorded in hospital discharge letters which are sent to the patients’ general practice and then entered into each patient’s electronic record. We excluded people without a valid deprivation score since this group may represent a more transient population where follow-up for stroke could be unreliable or unrepresentative. Their deprivation scores are unlikely to be missing at random so we did not think it would be appropriate to impute them.
The present validation has been done on a completely separate set of practices and individuals to those which were used to develop the score, although the practices all use the same clinical computer system (EMIS, the computer system used by 55% of UK general practices). An independent validation study would be a more stringent test and should be done, but when such independent studies have examined other risk algorithms,6
they have demonstrated similar performance compared with the validation in the QResearch database.5
This QStroke model has been developed using data from England and Wales and includes UK derived ethnicities and a postcode-based deprivation score. It is therefore not immediately applicable for clinical use in international settings without some modification of the UK-specific risk factors and validation in the setting in which it is intended to be used.
We have developed and validated a new algorithm to predict risk of stroke. QStroke shows some improvement over current risk scoring methods, CHADS2 and CHA2DS2VASc, for patients with atrial fibrillation for whom anticoagulation may be required. QStroke also provides an accurate measure of absolute stroke risk in the general population of patients free of stroke or transient ischaemic attack, as shown by its performance in a separate validation cohort. Further research is needed to evaluate the clinical outcomes and cost effectiveness of using these algorithms in primary care.
What is already known on this topic
- Methods to identify patients at high or low risk of stroke are needed to identify patients for whom interventions may be required, especially those with atrial fibrillation for whom anticoagulation might be needed
- Current methods for risk scoring, such as CHADS2 and CHA2DS2VASc, are not based on a statistical model, do not include many established risk factors, nor provide absolute risk estimates of stroke
What this study adds
- We have developed a new algorithm to quantify absolute risk of primary stroke which includes established risk factors and which is designed to work with the QRISK2 cardiovascular disease algorithm
- QStroke provides a valid measure of absolute stroke risk in the general population of patients free of stroke or transient ischaemic attack as shown by its performance in a separate validation cohort
- QStroke shows some improvement on current risk scoring methods, CHADS2 and CHA2DS2VASc, for the subset of patients with atrial fibrillation for whom anticoagulation may be required
- Further research is needed to evaluate the clinical outcomes and cost effectiveness of using these algorithms in primary care