Evidence map›Paper›PMID 34332931›Full record

ArticleThe Lancet. Digital health2021

The use of a next-generation sequencing-derived machine-learning risk-prediction model (OncoCast-MPM) for malignant pleural mesothelioma: a retrospective study.

Marjorie G Zauderer, Axel Martin, Jacklynn Egger, Hira Rizvi, Michael Offin, Andreas Rimner, Prasad S Adusumilli, Valerie W Rusch, Mark G Kris, Jennifer L Sauter and 2 more

Abstract read
In one paragraph

Article in The Lancet. Digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
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

23 citing papers in PubMed.

  1. Article
  2. Article
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  4. Review
  5. Review
  6. Article
  7. Article
  8. Developing Novel Genomic Risk Stratification Models in Soft Tissue and Uterine Leiomyosarcoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Article
  9. Review
  10. Review
  11. Review
  12. Novel Genomic Risk Stratification Model for Primary Gastrointestinal Stromal Tumors (GIST) in the Adjuvant Therapy Era.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Multimodality Therapy in Patients With Primary Pericardial Mesothelioma.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2022
    Article
  17. IsolatedCancers · 2022
    Article
  18. Article
  19. Review
  20. Article
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

12 authors.

Marjorie G ZaudererThoracic Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA. Electronic address: zauderem@mskcc.org.
Axel MartinBiostatistics Service, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Jacklynn EggerDruckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Hira RizviDruckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Michael OffinThoracic Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA.
Andreas RimnerDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Prasad S AdusumilliThoracic Surgery, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Valerie W RuschThoracic Surgery, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Mark G KrisThoracic Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA.
Jennifer L SauterDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Marc LadanyiDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Ronglai ShenBiostatistics Service, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
SURGICAL ONCOLOGY RESEARCH TRAINING PROGRAMT32CA009501 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Babak J Mehrara · 1985 to 2026
$7.7M
A phase I/II combination immunotherapy clinical trial: mesothelin-targeted chimeric antigen receptor T cells and checkpoint blockade agent in pleural mesotheliomaR01CA235667 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI ADUSUMILLI, PRASAD S. · 2019 to 2024
$3.6M
Image-guided irreversible electroporation directed CAR T-cell delivery to solid tumorsR01CA236615 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI ADUSUMILLI, PRASAD S., SOLOMON, STEPHEN BARNETT · 2018 to 2022
$2.0M
Imaging the efficacy of TRAIL-enhanced cancer immunotherapyR21CA213139 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI ADUSUMILLI, PRASAD S., PONOMAREV, VLADIMIR · 2017 to 2018
$413k
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA235667NCI NIH HHS R01 CA236615NCI NIH HHS R21 CA213139NCI NIH HHS T32 CA009501
6 · The paper itself

Abstract

backgroundCurrent risk stratification for patients with malignant pleural mesothelioma based on disease stage and histology is inadequate. For some individuals with early-stage epithelioid tumours, a good prognosis by current guidelines can progress rapidly; for others with advanced sarcomatoid cancers, a poor prognosis can progress slowly. Therefore, we aimed to develop and validate a machine-learning tool-known as OncoCast-MPM-that could create a model for patient prognosis.

methodsWe did a retrospective study looking at malignant pleural mesothelioma tumours using next-generation sequencing from the Memorial Sloan Kettering Cancer Center-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT). We collected clinical, pathological, and routine next-generation sequencing data from consecutive patients with malignant pleural mesothelioma treated at the Memorial Sloan Kettering Cancer Center (New York, NY, USA), as well as the MSK-IMPACT data. Together, these data comprised the MSK-IMPACT cohort. Using OncoCast-MPM, an open-source, web-accessible, machine-learning risk-prediction model, we integrated available data to create risk scores that stratified patients into low-risk and high-risk groups. Risk stratification of the MSK-IMPACT cohort was then validated using publicly available malignant pleural mesothelioma data from The Cancer Genome Atlas (ie, the TCGA cohort).

findingsBetween Feb 15, 2014, and Jan 28, 2019, we collected MSK-IMPACT data from the tumour tissue of 194 patients in the MSK-IMPACT cohort. The median overall survival was higher in the low-risk group than in the high-risk group as determined by OncoCast-MPM (30·8 months [95% CI 22·7-36·2] vs 13·9 months [10·7-18·0]; hazard ratio [HR] 3·0 [95% CI 2·0-4·5]; p<0·0001). No single factor or gene alteration drove risk differentiation. OncoCast-MPM was validated against the TCGA cohort, which consisted of 74 patients. The median overall survival was higher in the low-risk group than in the high-risk group (23·6 months [95% CI 15·1-28·4] vs 13·6 months [9·8-17·9]; HR 2·3 [95% CI 1·3-3·8]; p=0·0019). Although stage-based risk stratification was unable to differentiate survival among risk groups at 3 years in the MSK-IMPACT cohort (31% for early-stage disease vs 30% for advanced-stage disease; p=0·90), the OncoCast-MPM-derived 3-year survival was significantly higher in the low-risk group than in the high-risk group (40% vs 7%; p=0·0052).

interpretationOncoCast-MPM generated accurate, individual patient-level risk assessment scores. After prospective validation with the TCGA cohort, OncoCast-MPM might offer new opportunities for enhanced risk stratification of patients with malignant pleural mesothelioma in clinical trials and drug development.

fundingUS National Institutes of Health/National Cancer Institute.

Indexed as

High-Throughput Nucleotide SequencingMachine LearningAgedCohort StudiesFemaleHumansLung NeoplasmsMaleMesothelioma, MalignantMiddle AgedNeoplasm StagingNew YorkPleural NeoplasmsPrognosisRetrospective StudiesRisk

Identifiers

PMID34332931
PMCPMC8459747

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LicenceCC BY-NC-ND
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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.