Evidence map›Paper›PMID 29067214›Full record

ArticleESMO open2017

Detailed statistical assessment of the characteristics of the ESMO Magnitude of Clinical Benefit Scale (ESMO-MCBS) threshold rules.

Urania Dafni, Dimitris Karlis, Xanthi Pedeli, Jan Bogaerts, George Pentheroudakis, Josep Tabernero, Christoph C Zielinski, Martine J Piccart, Elisabeth G E de Vries, Nicola Jane Latino and 2 more

Open access · goldAbstract read
In one paragraph

Article in ESMO open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
19.8field-weighted citation impact, top 1% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 10 institutions in 7 countries.

Urania DafniLaboratory of Biostatistics, School of Health Sciences, National and Kapodistrian, University of Athens, Athens, Greece.
Dimitris KarlisDepartment of Statistics, Athens University of Economics and Business, Athens, Greece.
Xanthi PedeliFrontier Science Foundation-Hellas, Athens, Greece.
Jan BogaertsMethodology Direction, EORTC Headquarters, Brussels, Belgium.
George PentheroudakisDepartment of Medical Oncology, Ioannina University Hospital, Ioannina, Greece.
Josep TaberneroDepartment of Medical Oncology, Vall d'Hebron University Hospital, Barcelona, Spain.
Christoph C ZielinskiDivision of Oncology, Medical University Vienna, Vienna, Austria.
Martine J PiccartJules Bordet Institute, Universite Libre de Bruxelles, Bruxelles, Belgium.
Elisabeth G E de VriesDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Nicola Jane LatinoESMO Head Office, European Society for Medical Oncology, Lugano, Switzerland.
Jean-Yves DouillardESMO Head Office, European Society for Medical Oncology, Lugano, Switzerland.
Nathan I ChernyDepartment of Medical Oncology, Cancer Pain and Palliative Medicine Service, Shaare Zedek Medical Center, Jerusalem, Israel.
European Society for Medical Oncology · CHFrontier Science Foundation-Hellas · GRAthens University of Economics and Business · GREuropean Organisation for Research and Treatment of Cancer · BEInstitut Jules Bordet · BEMedical University of Vienna · ATShaare Zedek Medical Center · ILUniversity Hospital of Ioannina · GRUniversity of Groningen · NLVall d'Hebron Hospital Universitari · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe European Society for Medical Oncology (ESMO) has developed the ESMO Magnitude of Clinical Benefit Scale (ESMO-MCBS), a tool to assess the magnitude of clinical benefit from new cancer therapies. Grading is guided by a dual rule comparing the relative benefit (RB) and the absolute benefit (AB) achieved by the therapy to prespecified threshold values. The ESMO-MCBS v1.0 dual rule evaluates the RB of an experimental treatment based on the lower limit of the 95%CI (LL95%CI) for the hazard ratio (HR) along with an AB threshold. This dual rule addresses two goals: inclusiveness: not unfairly penalising experimental treatments from trials designed with adequate power targeting clinically meaningful relative benefit; and discernment: penalising trials designed to detect a small inconsequential benefit.

methodsBased on 50 000 simulations of plausible trial scenarios, the sensitivity and specificity of the LL95%CI rule and the ESMO-MCBS dual rule, the robustness of their characteristics for reasonable power and range of targeted and true HRs, are examined. The per cent acceptance of maximal preliminary grade is compared with other dual rules based on point estimate (PE) thresholds for RB.

resultsFor particularly small or particularly large studies, the observed benefit needs to be relatively big for the ESMO-MCBS dual rule to be satisfied and the maximal grade awarded. Compared with approaches that evaluate RB using the PE thresholds, simulations demonstrate that the MCBS approach better exhibits the desired behaviour achieving the goals of both inclusiveness and discernment.

conclusionsRB assessment using the LL95%CI for HR rather than a PE threshold has two advantages: it diminishes the probability of excluding big benefit positive studies from achieving due credit and, when combined with the AB assessment, it increases the probability of downgrading a trial with a statistically significant but clinically insignificant observed benefit.

Indexed as

Clinical BenefitESMO-MCBSEvaluation of Clinical BenefitThreshold Rule

Identifiers

PMID29067214
PMCPMC5640101
OpenAlexW2761635936

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.