Evidence map›Paper›PMID 30181174›Full record

Trial reportBlood2018

RNA-seq of newly diagnosed patients in the PADIMAC study leads to a bortezomib/lenalidomide decision signature.

Michael A Chapman, Jonathan Sive, John Ambrose, Claire Roddie, Nicholas Counsell, Anna Lach, Mahnaz Abbasian, Rakesh Popat, Jamie D Cavenagh, Heather Oakervee and 20 more

Open access · bronzeAbstract readClinical Trial, Phase II
In one paragraph

Trial report in Blood, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Construction of a treatment response prediction model for multiple myeloma based on multi-omics and machine learning.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

30 authors at 16 institutions in 3 countries.

Michael A ChapmanDepartment of Haematology, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-8342-0606
Jonathan SiveDepartment of Haemato-oncology, St. Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
John AmbroseBill Lyons Informatics Centre, UCL Cancer Institute, University College London, London, United Kingdom.
Claire RoddieDepartment of Haematology, University College London Hospitals, London, United Kingdom.
Nicholas CounsellCancer Research UK and UCL Cancer Trials Centre, London, United Kingdom.
Anna LachDepartment of Haematology, UCL Cancer Institute, University College London, London, United Kingdom.
Mahnaz AbbasianDepartment of Haematology, UCL Cancer Institute, University College London, London, United Kingdom.
Rakesh PopatDepartment of Haematology, University College London Hospitals, London, United Kingdom.
Jamie D CavenaghDepartment of Haemato-oncology, St. Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
Heather OakerveeDepartment of Haemato-oncology, St. Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
Matthew J StreetlyDepartment of Haematology, Guys and St. Thomas' Hospital, London, United Kingdom.
Stephen ScheyDepartment of Haematology, Kings College Hospital, London, United Kingdom.
Mickey KohDepartment of Haematology, St. George's Hospital, London, United Kingdom.
Fenella WillisDepartment of Haematology, St. George's Hospital, London, United Kingdom.
Andres E VirchisDepartment of Haematology, Royal Free London, Barnet and Chase Farm Hospitals, London, United Kingdom.
Josephine CroweDepartment of Haematology, Royal United Hospitals Bath, Bath, United Kingdom.
Michael F QuinnDepartment of Haematology, Belfast City Hospital, Belfast, United Kingdom.
Gordon CookDepartment of Haematology, St. James's University Hospital, Leeds, United Kingdom.
Charles R CrawleyDepartment of Haematology, Addenbrookes Hospital, Cambridge, United Kingdom.
Guy PrattCentre for Clinical Haematology, University Hospitals Birmingham, Birmingham, United Kingdom.
Mark CookCentre for Clinical Haematology, University Hospitals Birmingham, Birmingham, United Kingdom.
Nivette BraganzaCancer Research UK and UCL Cancer Trials Centre, London, United Kingdom.
Toyin AdedayoCancer Research UK and UCL Cancer Trials Centre, London, United Kingdom.
Paul SmithCancer Research UK and UCL Cancer Trials Centre, London, United Kingdom.
Laura Clifton-HadleyCancer Research UK and UCL Cancer Trials Centre, London, United Kingdom.
Roger G OwenHaematological Malignancy Diagnostic Service, St. James' University Hospital, Leeds, United Kingdom.
Pieter SonneveldErasmus Medical Centre, Rotterdam, The Netherlands; and.
Jonathan J KeatsIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ.
Javier HerreroBill Lyons Informatics Centre, UCL Cancer Institute, University College London, London, United Kingdom.ORCID 0000-0001-7313-717X
Kwee YongDepartment of Haematology, UCL Cancer Institute, University College London, London, United Kingdom.
Cancer Research UK · GBUniversity College London · GBSt Bartholomew's Hospital · GBNIHR Surgical Reconstruction and Microbiology Research Centre · GBRoyal London Hospital · GBSt George's Hospital · GBSt James's University Hospital · GBAddenbrooke's Hospital · GBErasmus University Rotterdam · NLKing's College Hospital · GBRoyal United Hospital · GBSt Thomas' Hospital · GBThe Royal Free Hospital · GBTranslational Genomics Research Institute · USUniversity of Cambridge · GBUniversity of Ulster · GB

Funding

Cancer Research UK C416/A18088Cancer Research UK C416/A25145Wellcome Trust
6 · The paper itself

Abstract

Improving outcomes in multiple myeloma will involve not only development of new therapies but also better use of existing treatments. We performed RNA sequencing on samples from newly diagnosed patients enrolled in the phase 2 PADIMAC (Bortezomib, Adriamycin, and Dexamethasone Therapy for Previously Untreated Patients with Multiple Myeloma: Impact of Minimal Residual Disease in Patients with Deferred ASCT) study. Using synthetic annealing and the large margin nearest neighbor algorithm, we developed and trained a 7-gene signature to predict treatment outcome. We tested the signature in independent cohorts treated with bortezomib- and lenalidomide-based therapies. The signature was capable of distinguishing which patients would respond better to which regimen. In the CoMMpass data set, patients who were treated correctly according to the signature had a better progression-free survival (median, 20.1 months vs not reached; hazard ratio [HR], 0.40; confidence interval [CI], 0.23-0.72;

Indexed as

Antineoplastic AgentsAntineoplastic Combined Chemotherapy ProtocolsBortezomibDexamethasoneDoxorubicinHumansKaplan-Meier EstimateLenalidomideMachine LearningMultiple MyelomaMutationProportional Hazards ModelsSequence Analysis, RNATranscriptomeTreatment OutcomeUnited StatesAntineoplastic AgentsBortezomibDexamethasoneDoxorubicinLenalidomide

Identifiers

PMID30181174
PMCPMC6310235
OpenAlexW2892371354

What OpenQuestion holds

Textmetadata
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.