ReviewDeutsches Arzteblatt international2024
Recognizing Statistical Problems in Reports of Clinical Trials: a Readers' Aid. Part 33 of a Series on Evaluation of Scientific Publications.
Review in Deutsches Arzteblatt international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundReaders of clinical trial reports should be able to critically evaluate the design, results, and conclusions of the trial. There are internationally accepted guidelines that define methodological standards for trial planning, statistical methods, and the display and interpretation of the results. Publications may nonetheless contain erroneous findings and interpretations.
methodsStatistical errors can arise in the planning of the trial, the analysis and display of the results, as well as in the interpretation of p-values and treatment effects in experimental and observational clinical trials. A useful aid for readers of medical publications should include a description of the potential statistical problems without complex theoretical background information. With this aim, we discuss certain major types of statistical error that the reader should be familiar with in order to be able to interpret the conclusions of these publications more easily.
resultsStatistical errors can already arise at an early stage through the choice of the wrong question to be addressed or the wrong population to be analyzed; such errors will inevitably have consequences. Before the start of any clinical trial, a primary endpoint must be defined, the sample size must be calculated, and the trial must be appropriately registered (among other requirements). With regard to the analysis, readers should for example take into account whether a statistical analysis plan with an intention-to-treat analysis existed for the study in question. They must be able to recognize erroneous methods of displaying and comparing data, confounding, as well as incorrect interpretations of p-values, and should take these problems into account when interpreting the findings. The problem of invalid causal inferences is not restricted to observational studies.
conclusionStatistical errors do, indeed, arise. They should be detected as early as possible in various test instances. Nonetheless, readers should be able to judge independently whether the published clinical trial reflects meticulous and correct trial planning, appropriate display of the trial's results, and a proper, reasoned interpretation of the findings. The published checklists are a good aid for this purpose.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.