Evidence map›Paper›PMID 23824468›Full record

ArticleTheoretical medicine and bioethics2013

Monitoring in clinical trials: benefit or bias?

Cecilia Nardini

Abstract read
PubMed Publisher
In one paragraph

Article in Theoretical medicine and bioethics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

1 author.

Cecilia NardiniIstituto Europeo di Oncologia (IEO), University of Milan, Campus IFOM-IEO, Via Adamello 16, 20139, Milan, Italy. cecilia.nardini@ieo.eu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring ongoing clinical trials for early signs of effectiveness is an option for improving cost-effectiveness of trials that is becoming increasingly common. Alongside the obvious advantages made possible by monitoring, however, there are some downsides. In particular, there is growing concern in the medical community that trials stopped early for benefit tend to overestimate treatment effect. In this paper, I examine this problem from the point of view of statistical methodology, starting from the observation that the overestimation is caused by the statistical method adopted. Consequently, I argue that some modifications can and should be made to the present statistical framework in order not to miss the advantages the possibility of monitoring can grant.

Indexed as

Bayes TheoremResearch DesignBiasClinical Trials as TopicCost-Benefit AnalysisEarly Termination of Clinical TrialsHumansReproducibility of ResultsTreatment Outcome

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.