Evidence map›Paper›PMID 32474426›Full record

ArticleBMJ open2020

Characteristics and interpretation of subgroup analyses based on tumour characteristics in randomised trials testing target-specific anticancer drugs: design of a systematic survey.

Stefan Schandelmaier, Andreas M Schmitt, Amanda K Herbrand, Dominik Glinz, Hannah Ewald, Matthias Briel, Gordon H Guyatt, Lars G Hemkens, Benjamin Kasenda

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 95% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 3 institutions in 3 countries.

Stefan SchandelmaierInstitute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland s.schandelmaier@gmail.com.ORCID 0000-0002-8429-0337
Andreas M SchmittDepartment of Medical Oncology, University Hospital Basel, Basel, Switzerland.
Amanda K HerbrandDepartment of Medical Oncology, University Hospital Basel, Basel, Switzerland.
Dominik GlinzInstitute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland.
Hannah EwaldUniversity Medical Library, University of Basel, Basel, Switzerland.
Matthias BrielInstitute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland.
Gordon H GuyattDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.
Lars G HemkensInstitute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland.
Benjamin KasendaDepartment of Medical Oncology, University Hospital Basel, Basel, Switzerland.
University of Basel · CHUniversity Hospital of Basel · CHImpact · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTarget-specific anticancer drugs are under rapid development. Little is known, however, about the risk of administering target-specific drugs to patients who have tumours with molecular alterations or other characteristics that can make the drug ineffective or even harmful. An increasing number of randomised clinical trials (RCTs) investigating target-specific anticancer drugs include subgroup analyses based on tumour characteristics. Such subgroup analyses have the potential to be more credible and influential than subgroup analyses based on traditional factors such as sex or tumour stage. In addition, they may more frequently lead to qualitative subgroup effects, that is, show benefit in one but harm in another subgroup of patients (eg, if the tumour characteristic makes the drug ineffective or even enhance tumour growth). If so, subgroup analyses based on tumour characteristics would be highly relevant for patient safety. The aim of this study is to systematically assess the frequency and characteristics of subgroup analyses based on tumour characteristics, the frequency of qualitative subgroup effects, their credibility, and the interpretations that investigators and guidelines developers report. METHODS AND ANALYSIS: We will perform a systematic survey of 433 RCTs testing the effect of target-specific anticancer drugs. Teams of methodologically trained investigators and oncologists will identify eligible studies, extract relevant data and assess the credibility of putative subgroup effects using a recently developed formal instrument. We will systematically assess how trial investigators interpret apparent subgroup effects based on tumour characteristics and the extent to which they influence subsequent practice guidelines. Our results will provide empirical data characterising an increasingly used type of subgroup analysis in cancer trials and its potential impact on precision medicine to predict benefit or harm. ETHICS AND DISSEMINATION: Formal ethical approval is not required for this study. We will disseminate the findings in a peer-reviewed and open-access journal publication.

Indexed as

Antineoplastic AgentsNeoplasmsSurveys and QuestionnairesHumansAntineoplastic Agentsoncologyprecision medicinerandomised controlled trialsstatistics & research methodssubgroup analysissystematic survey of studies

Identifiers

PMID32474426
PMCPMC7264639
OpenAlexW3031248945

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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.