Evidence map›Paper›PMID 28705147›Full record

Trial reportBMC medical research methodology2017

Sample size re-estimation in paired comparative diagnostic accuracy studies with a binary response.

Gareth P J McCray, Andrew C Titman, Paula Ghaneh, Gillian A Lancaster

Abstract readClinical TrialComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

4 authors.

Gareth P J McCrayInstitute of Primary Care and Health Sciences, Keele University, David Weatherall Building, Stoke-on-Trent, ST5 5BG, UK. g.mccray@keele.ac.uk.ORCID http://orcid.org/0000-0002-0728-5171
Andrew C TitmanDepartment of Mathematics and Statistics, Lancaster University, Fylde College, Lancaster, LA14YF, UK.
Paula GhanehInstitute of Translational Medicine, University of Liverpool, Cedar House, L69 3GE, Ashton St, Liverpool, L3 5PS, UK.
Gillian A LancasterInstitute of Primary Care and Health Sciences, Keele University, David Weatherall Building, Stoke-on-Trent, ST5 5BG, UK.

Funding

Cancer Research UK 11883Cancer Research UK 15957Cancer Research UK 16186Cancer Research UK 16812Cancer Research UK 17680Cancer Research UK 8968Department of Health 08/29/02
6 · The paper itself

Abstract

backgroundThe sample size required to power a study to a nominal level in a paired comparative diagnostic accuracy study, i.e. studies in which the diagnostic accuracy of two testing procedures is compared relative to a gold standard, depends on the conditional dependence between the two tests - the lower the dependence the greater the sample size required. A priori, we usually do not know the dependence between the two tests and thus cannot determine the exact sample size required. One option is to use the implied sample size for the maximal negative dependence, giving the largest possible sample size. However, this is potentially wasteful of resources and unnecessarily burdensome on study participants as the study is likely to be overpowered. A more accurate estimate of the sample size can be determined at a planned interim analysis point where the sample size is re-estimated.

methodsThis paper discusses a sample size estimation and re-estimation method based on the maximum likelihood estimates, under an implied multinomial model, of the observed values of conditional dependence between the two tests and, if required, prevalence, at a planned interim. The method is illustrated by comparing the accuracy of two procedures for the detection of pancreatic cancer, one procedure using the standard battery of tests, and the other using the standard battery with the addition of a PET/CT scan all relative to the gold standard of a cell biopsy. Simulation of the proposed method illustrates its robustness under various conditions.

resultsThe results show that the type I error rate of the overall experiment is stable using our suggested method and that the type II error rate is close to or above nominal. Furthermore, the instances in which the type II error rate is above nominal are in the situations where the lowest sample size is required, meaning a lower impact on the actual number of participants recruited.

conclusionWe recommend multinomial model maximum likelihood estimation of the conditional dependence between paired diagnostic accuracy tests at an interim to reduce the number of participants required to power the study to at least the nominal level.

trial registrationISRCTN ISRCTN73852054 . Registered 9th of January 2015. Retrospectively registered.

Indexed as

Sample SizeAdultAlgorithmsComputer SimulationFemaleHumansLikelihood FunctionsMaleMatched-Pair AnalysisModels, StatisticalPancreatic NeoplasmsPositron Emission Tomography Computed TomographyReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityTreatment OutcomeDiagnostic accuracyInterim analysisSample-size re-estimationSensitivitySpecificityStudy design

Identifiers

PMID28705147
PMCPMC5513326

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.