Evidence map›Paper›PMID 29368033›Full record

ArticlePharmaceutical research2018

Development and performance of npde for the evaluation of time-to-event models.

M Cerou, M Lavielle, K Brendel, M Chenel, E Comets

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Pharmaceutical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

M CerouINSERM, CIC 1414, 35700, Rennes, France. marc.cerou@inserm.fr.ORCID http://orcid.org/0000-0001-6792-2526
M LavielleInria Saclay & CMAP, Ecole Polytechnique, Palaiseau, France.
K BrendelDivision of Clinical Pharmacokinetics and Pharmacometrics, Institut de Recherches Internationales Servier, Suresnes, France.
M ChenelDivision of Clinical Pharmacokinetics and Pharmacometrics, Institut de Recherches Internationales Servier, Suresnes, France.
E CometsINSERM, CIC 1414, 35700, Rennes, France.

Funding

Servier CIFRE ANRT 2016/0729
6 · The paper itself

Abstract

purposeNormalised prediction distribution errors (npde) are used to graphically and statistically evaluate mixed-effect models for continuous responses. In this study, our aim was to extend npde to time-to-event (TTE) models and evaluate their performance.

methodsLet V denote a dataset with censored TTE observations. The null hypothesis (H

resultsType I error was found to be close to the expected 5% significance level for all sample sizes tested. The npde were able to detect misspecifications in the baseline hazard as well as in the link between the longitudinal variable and the survival function. The ability to detect model misspecifications increased as the difference in the shape of the survival function became more apparent. As expected, the power also increased as the sample size increased. Imputing the censored events tended to decrease the percentage of rejections.

conclusionsWe have shown that npde can be readily extended to TTE data and that they perform well with an adequate type I error.

Indexed as

Clinical Trials as TopicData Interpretation, StatisticalNonlinear DynamicsBiomarkersDatasets as TopicMonte Carlo MethodSoftwareSurvival AnalysisTime FactorsTreatment OutcomeBiomarkersmodel evaluationnpdePSAtime-to-event

Identifiers

What OpenQuestion holds

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Registered trials

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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.