Evidence map›Paper›PMID 42133899›Full record

ArticleJCO precision oncology2026

Multimodal Impact of Number of Metastases and Genetic Alterations on Survival in Metastatic Non-Small Cell Lung Cancer.

N Ari Wijetunga, Nikhil P Mankuzhy, Emily S Lebow, Lillian A Boe, Luke R G Pike, Adam J Schoenfeld, Narek Shaverdian, Tafadzwa L Chaunzwa, David R Jones, Jamie E Chaft and 6 more

Abstract read
In one paragraph

Article in JCO precision oncology, 2026. 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
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.

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

16 authors.

N Ari WijetungaDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0002-8518-4691
Nikhil P MankuzhyDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0001-9004-7598
Emily S LebowDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.
Lillian A BoeDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0001-6279-9987
Luke R G PikeDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0001-9622-7442
Adam J SchoenfeldDepartment of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0002-2644-1416
Narek ShaverdianDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0002-0294-8749
Tafadzwa L ChaunzwaDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0001-7216-159X
David R JonesDepartment of Surgery, Thoracic Surgery Service, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0002-3318-0146
Jamie E ChaftDepartment of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0002-5838-9982
Charles M RudinDepartment of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0001-5204-3465
Mark G KrisDepartment of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY.
Helena A YuDepartment of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0002-0377-9510
Jason C ChangDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0002-1705-1870
Puneeth IyengarDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0000-0003-3740-7915
Daniel R GomezDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY.ORCID 0009-0003-8617-3868

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

purposeOligometastatic disease (OMD) is an intermediate state of metastatic disease in which metastasis-directed therapy (MDT) may improve outcomes. The classification of OMD is inconsistent, typically defined by number of metastases without considering tumor biologic characteristics. To help optimize patient selection for MDT, we analyzed integrated genomic sequencing results from patients with metastatic non-small cell lung cancer (NSCLC). MATERIALS AND

methodsPatients with metastatic NSCLC who had molecular sequencing through a validated institutional assay (MSK-IMPACT) were included. The number and location of metastases were manually annotated (assigned 1-10 and >10). Individual gene variant scores were analyzed by gene length and patient mutation burden. Analysis was completed in R and included maximally selected rank statistics, agglomerative hierarchical clustering, and the chi-square test for independence.

resultsIn total, 844 patients had clinical data, tissue sequencing, and annotated imaging for analysis. Of these, 635 had >10 metastases (75.2%), and 209 had 1-10 metastases (24.8%). The cutpoint that maximized overall survival (OS) was four metastases, and six mutation signatures were identified. For patients with 1-4 metastases,

conclusionThe cutpoint that maximized difference in OS was four metastases, but incorporating genetic alteration information modified this criterion. These findings were proof of principle that integrating multimodal data beyond number of lesions can better identify patients with metastatic NSCLC who may be candidates for MDT.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedMutationNeoplasm Metastasis

Identifiers

PMID42133899
PMCPMC13182819

What OpenQuestion holds

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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.