Derivation and validation of the QStatin algorithm to predict the risks and benefits of taking statins
What is the aim of the study and why is it important?
QStatin is a risk prediction algorithm which calculates an individual’s risk of cataract, myopathy, acute renal failure and liver dysfunction taking account of their individual risk factors such as age, sex, ethnicity, clinical values and diagnoses. The outcomes are identified according to clinical codes recorded on the primary care record or the linked mortality or hospital record. The research describing the derivation and validation of the algorithm has been published in the BMJ.
QStatin is used to quantify an individual’s risk in order to prioritise and inform decisions regarding interventions to lower risk. It is updated regularly to ensure the algorithms remain calibrated to the current population since the incidence of disease and the prevalence of risk factors changes over time. The updates also enable the algorithm to take account of improvements to data quality (for example increases in the completeness of recording of risk factors such as ethnicity or laboratory values) and also allows adaptations to any changes which might be required to improve the predictive power of the tool or the population to which is applied.
Location of research
Date on which research approved
Project reference ID
Generic ethics approval reference
Are all data accessed are in anonymised form?
Brief summary of the dataset to be released (including any sensitive data)
Risk factors for unintended effects of statin medication linked to both the outcomes and prescription data for statins
No external funding
Professor Julia Hippisley-Cox, Professor Carol Coupland
Individualising the risks of statins in men and women in England and Wales: population-based cohort study
Authors: Hippisley-Cox J, Coupland C
Ref: Heart 2010; 96: 939-947
http://www.qresearch.org/Public_Documents/JHC Heart 2010.pdf
Unintended effects of statins in men and women in England and Wales: population based cohort study using the QResearch database
Authors: Hippisley-Cox J, Coupland C.
Ref: BMJ 2010; 340: c2197 (online first)
http://www.qresearch.org/Public_Documents/Hippisley-Cox BMJ 2010.pdf