Regression discontinuity analysis for pharmacovigilance: statin example reflected trial findings showing little evidence of harm.

Lauren Scott, Maria Theresa Redaniel, Matthew Booker, Rupert A Payne, Kate Tilling

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Article in Journal of clinical epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lauren ScottNational Institute for Health Research Applied Research Collaboration West, University Hospitals Bristol and Weston NHS Foundation Trust, 9th Floor, Whitefriars, Lewins Mead, Bristol, BS1 2NT, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK.

Maria Theresa RedanielNational Institute for Health Research Applied Research Collaboration West, University Hospitals Bristol and Weston NHS Foundation Trust, 9th Floor, Whitefriars, Lewins Mead, Bristol, BS1 2NT, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK. Electronic address: theresa.redaniel@bristol.ac.uk.

Matthew BookerCentre for Academic Primary Care, Bristol Medical School, Canynge Hall, University of Bristol, 39 Whatley Road, Bristol, BS8 2PS, UK.

Rupert A PayneCentre for Academic Primary Care, Bristol Medical School, Canynge Hall, University of Bristol, 39 Whatley Road, Bristol, BS8 2PS, UK.

Kate TillingNational Institute for Health Research Applied Research Collaboration West, University Hospitals Bristol and Weston NHS Foundation Trust, 9th Floor, Whitefriars, Lewins Mead, Bristol, BS1 2NT, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK; MRC Integrative Epidemiology Unit, Bristol Medical School, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

Funding

Department of Health NIHR200181Medical Research Council MC_UU_00011/3

6 · The paper itself

Abstract

objectivesThe study aims to explore the use of regression discontinuity analysis (RDA) to examine effects of prescription of statins on total cholesterol and adverse outcomes (type 2 diabetes, rhabdomyolysis and myopathy, myalgia and myositis, liver disease, CVD, and mortality). STUDY DESIGN AND

settingWe conducted a prospective cohort study using the Clinical Practice Research Datalink including patients with QRISK scores of 10 to 30 in 2010 to 2013 who were last followed-up in October 2016. Comparing patients with QRISK≥20 and QRISK<20, we explored RDA assumptions, provided proof of concept analyses (total cholesterol as outcome), and investigated the effect of statins prescription on adverse outcomes.

resultRDA confirmed statin prescription reduced total cholesterol (Mean difference (MD) -1.33 mmol/L, 95%Confidence Interval (CI) -1.93 to -0.73). RDA provided little evidence for adverse effects on diabetes, myalgia and myositis, liver disease, CVD, or mortality. The RDA analysis findings are similar to RCT results. Findings from non-RDA analysis agree with published observational studies.

conclusionRDA can be used with large routine clinical datasets to provide evidence on effects of medications which are prescribed according to a threshold. Testable RDA assumptions were satisfied, but confidence intervals were wide, partly due to the low compliance with the prescribing threshold.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2Hydroxymethylglutaryl-CoA Reductase InhibitorsMyositisCholesterolHumansMyalgiaPharmacovigilanceProspective StudiesCholesterolHydroxymethylglutaryl-CoA Reductase InhibitorsCardiovascular diseaseEpidemiologyHealth services researchQRISK scoreRegression discontinuity analysisStatins

Identifiers

PMID34648942

DOI10.1016/j.jclinepi.2021.10.003

PMCPMC8982642

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