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. 2016 Jun 28:353:i3283.
doi: 10.1136/bmj.i3283.

Impact of statin related media coverage on use of statins: interrupted time series analysis with UK primary care data

Anthony Matthews  1 , Emily Herrett  1 , Antonio Gasparrini  2 , Tjeerd Van Staa  3 , Ben Goldacre  1 , Liam Smeeth  1 , Krishnan Bhaskaran  1
Affiliations

Impact of statin related media coverage on use of statins: interrupted time series analysis with UK primary care data

Anthony Matthews et al. BMJ. .

Abstract

Objective: To quantify how a period of intense media coverage of controversy over the risk:benefit balance of statins affected their use.

Design: Interrupted time series analysis of prospectively collected electronic data from primary care.

Setting: Clinical Practice Research Datalink (CPRD) in the United Kingdom.

Participants: Patients newly eligible for or currently taking statins for primary and secondary cardiovascular disease prevention in each month in January 2011-March 2015.

Main outcome measures: Adjusted odds ratios for starting/stopping taking statins after the media coverage (October 2013-March 2014).

Results: There was no evidence that the period of high media coverage was associated with changes in statin initiation among patients with a high recorded risk score for cardiovascular disease (primary prevention) or a recent cardiovascular event (secondary prevention) (odds ratio 0.99 (95% confidence interval 0.87 to 1.13; P=0.92) and 1.04 (0.92 to 1.18; P=0.54), respectively), though there was a decrease in the overall proportion of patients with a recorded risk score. Patients already taking statins were more likely to stop taking them for both primary and secondary prevention after the high media coverage period (1.11 (1.05 to 1.18; P<0.001) and 1.12 (1.04 to 1.21; P=0.003), respectively). Stratified analyses showed that older patients and those with a longer continuous prescription were more likely to stop taking statins after the media coverage. In post hoc analyses, the increased rates of cessation were no longer observed after six months.

Conclusions: A period of intense public discussion over the risks:benefit balance of statins, covered widely in the media, was followed by a transient rise in the proportion of people who stopped taking statins. This research highlights the potential for widely covered health stories in the lay media to impact on healthcare related behaviour.

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Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: AG received grants from Medical Research Council, during the conduct of the study, and personal fees from University of Umea, unrelated to the submitted work; TVS received personal fees from GSK, Roche, and Sanofi for presenting on methods for pragmatic trials and grant funding from GSK unrelated to the submitted work; BG received grants from the Laura and John Arnold Foundation, Wellcome Trust, and the Health Foundation and receives additional income from speaking, writing, and broadcasting on problems in science and medicine; LS reports grants from Wellcome Trust and British Heart Foundation during the conduct of the study, grants from Wellcome Trust, Medical Research Council, National Institute for Health Research and the European Union outside the submitted work, personal fees from GSK for advisory work unrelated to the submitted work, grant funding from GSK for academic research unrelated to the submitted work, acts as an unpaid steering committee chair for AstraZeneca for a randomised trial unrelated to the submitted work, and is a trustee of the British Heart Foundation; KB received grants from British Heart Foundation, Wellcome Trust, and Royal Society during the conduct of the study, and grant funding from Medical Research Council and National Institute for Health Research unrelated to the submitted work

Figures

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Fig 1 Primary analyses evaluating step change in proportion of patients initiating and stopping statin for primary and secondary prevention of cardiovascular disease after exposure period (October 2013 to March 2014). Model used interrupted time series analysis with generalised linear model with binomial error structure, with break points at beginning and end of exposure period. Models allowed for change in level of proportion of patients initiating/stopping statin. Odds ratios therefore relate to relative change in odds of initiating/stopping statins after exposure period, in comparison with expected change based on pre-exposure predictions. In A and B denominators are patients with opportunity to initiate statin each month within study period, and numerators are patients who did initiate statin after indication. In C and D denominators are patients with statin prescription ending each month within study period, and numerators are patients who did not renew that prescription and hence were defined as stopping. Solid lines and shaded confidence intervals relate to linear predictions of log odds and 95% CI of event, respectively, calculated from model and converted into probabilities. Dotted lines are extrapolation of pre-exposure linear predictions of log odds converted to probabilities, to give hypothetical proportions of post-exposure period under counterfactual scenario of no changes after exposure
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Fig 2 Stratified cessation analyses evaluating step change in proportion of patients stopping statin for primary and secondary prevention of cardiovascular disease after exposure period (October 2013 to March 2014). Models used interrupted time series analysis with generalised linear model with binomial error structure, with break points at beginning and end of exposure period. Models allowed for change in level of proportion of patients stopping statin. Odds ratios therefore relate to relative change in odds of stopping statins after exposure period, in comparison with expected change based on pre-exposure predictions
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Fig 3 Post hoc cessation analysis evaluating step change in proportion of patients stopping statin for primary and secondary prevention of cardiovascular disease, with post-exposure period stratified into ≤6 and >6 months. Denominators are patients with statin prescription ending each month within study period, and numerators are patients who did not renew that prescription and hence were defined as stopping. Models used interrupted time series analysis with generalised linear model with binomial error structure, with break points at beginning and end of exposure period. Models allowed for change in level of proportion of patients stopping statin. Odds ratios therefore relate to relative change in odds of stopping statins after for each 6 month section exposure period, in comparison with expected change based on pre-exposure predictions. Solid lines and shaded confidence intervals relate to linear predictions of log odds and 95% CI of event, respectively, calculated from model and converted into probabilities. Dotted lines are extrapolation of pre-exposure linear predictions of log odds converted to probabilities, to give hypothetical proportions of post-exposure period under counterfactual scenario of no changes after exposure
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Fig 4 Post hoc analyses evaluating step change in proportion of recorded 10 year risk scores for cardiovascular disease in each category after exposure period (October 2013-March 2014), using denominator of total number of patients under follow-up each month in CPRD. Denominators are all patients under follow-up in CPRD each month within study period, and numerators are patients that had recorded 10 year risk score for cardiovascular disease within each category in that month. Models used interrupted time series analysis with generalised linear model with binomial error structure, with break points at beginning and end of exposure period. Models allowed for change in level of proportion of patients with a recorded cardiovascular risk score. Odds ratios therefore relate to relative change in odds of having a recorded risk score after the exposure period, in comparison with expected change based on pre-exposure predictions. Solid lines and shaded confidence intervals relate to linear predictions of log odds and 95% CI of event, respectively, calculated from model and converted into probabilities. Dotted lines are extrapolation of pre-exposure linear predictions of log odds converted to probabilities, to give hypothetical proportions of post-exposure period under counterfactual scenario of no changes after exposure
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