ArticleAnnals of oncology : official journal of the European Society for Medical Oncology2017
Statistical controversies in cancer research: using standardized effect size graphs to enhance interpretability of cancer-related clinical trials with patient-reported outcomes.
Article in Annals of oncology : official journal of the European Society for Medical Oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Non-pharmacological therapies for patients with lymphangioleiomyomatosis: a systematic review and meta-analysis.Frontiers in rehabilitation sciences · 2026Review
- Comparison of statistical methods for the analysis of patient-reported outcomes (PROs), particularly the Short-Form 36 (SF-36), in randomised controlled trials (RCTs) using standardised effect size (SES): an empirical analysis.Health and quality of life outcomes · 2025Article
- Innovations in research and clinical care using patient-generated health data.CA: a cancer journal for clinicians · 2020Review
- Exploring perceptions of meaningfulness in visual representations of bivariate relationships.PeerJ · 2019Article
- Guidance for using pilot studies to inform the design of intervention trials with continuous outcomes.Clinical epidemiology · 2018Article
- Challenges to interpreting patient reported outcomes in clinical trials: author rejoinder.Annals of translational medicine · 2017Article
- Challenges of interpreting patient reported outcomes from clinical trials.Annals of translational medicine · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Patient reported outcomes (PROs) are becoming increasingly important in cancer studies, particularly with the emphasis on patient centered outcome research. However, multiple PROs, using different scales, with different directions of favorability are often used within a trial, making interpretation difficult. To enhance interpretability, we propose the use of a standardized effect size graph, which shows all PROs from a study on the same figure, on the same scale. Plotting standardized effects with their 95% confidence intervals (CIs) on a single graph clearly showing the null value conveys a comprehensive picture of trial results. We demonstrate how to create such a graph using data from a randomized controlled trial that measured 12 PROs at two time points. The 24 effect sizes and CIs are shown on one graph and clearly indicate that the intervention is effective and sustained.
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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.