Evidence map›Paper›PMID 33009371›Full record

ArticleNature communications2020

Real-world data from a molecular tumor board demonstrates improved outcomes with a precision N-of-One strategy.

Shumei Kato, Ki Hwan Kim, Hyo Jeong Lim, Amelie Boichard, Mina Nikanjam, Elizabeth Weihe, Dennis J Kuo, Ramez N Eskander, Aaron Goodman, Natalie Galanina and 12 more

Registry-linked trialAbstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07346209 (STudy of Real-world Individualized Precision-oncology), which is not on this map. Cited by 183 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
183citing papers in PubMed, 2 pooled it
–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.

NCT07346209 phase2not yet recruitingnot on this mapstarted 2026, after this paper: background citation

STudy of Real-world Individualized Precision-oncology

TypeinterventionalSponsorUniversity of California, San DiegoRan2026 to 2031Enrolled280ConditionsMetastatic Cancer, Unresectable CarcinomaArmsMolecularly matched therapy, Standard of care
3 · Its place in the literature

Who cites it

183 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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123 more citing papers are in PubMed but not listed here.

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

22 authors.

Shumei Kato *Center for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA. smkato@ucsd.edu.ORCID http://orcid.org/0000-0003-1193-1815
Ki Hwan Kim *Center for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA. floresta405@gmail.com.
Hyo Jeong LimCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Amelie BoichardCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Mina NikanjamCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Elizabeth WeiheDepartment of Radiology, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Dennis J KuoDivision of Pediatric Hematology-Oncology, Rady Children's Hospital-San Diego, University of California San Diego School of Medicine, San Diego, CA, USA.ORCID http://orcid.org/0000-0003-4154-0057
Ramez N EskanderCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Aaron GoodmanCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Natalie GalaninaCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Paul T FantaCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Richard B SchwabCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Rebecca ShatskyCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Steven C PlaxeCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Andrew SharabiCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Edward StitesIntegrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-3783-7336
Jacob J AdashekDepartment of Internal Medicine, University of South Florida, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.ORCID http://orcid.org/0000-0003-4272-312X
Ryosuke OkamuraCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.ORCID http://orcid.org/0000-0001-7352-8621
Suzanna LeeCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Scott M LippmanCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Jason K SicklickCenter for Personalized Cancer Therapy and Division of Surgical Oncology, Department of Surgery, UC San Diego Moores Cancer Center, La Jolla, CA, USA.
Razelle KurzrockCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center, La Jolla, CA, USA.

Funding

VIRAL MALIGNANCYP30CA023100 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DIANE M SIMEONE · 1985 to 2026
$124.9M
Viral Vector Core (VVC)P30CA014195 · NCI · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI Ye Zheng · 1985 to 2026
$82.8M
NCI NIH HHS P30 CA014195NCI NIH HHS P30 CA023100
6 · The paper itself

Abstract

Next-generation sequencing (NGS) can identify novel cancer targets. However, interpreting the molecular findings and accessing drugs/clinical trials is challenging. Furthermore, many tumors show resistance to monotherapies. To implement a precision strategy, we initiated a multidisciplinary (basic/translational/clinical investigators, bioinformaticians, geneticists, and physicians from multiple specialties) molecular tumor board (MTB), which included a project manager to facilitate obtaining clinical-grade biomarkers (blood/tissue NGS, specific immunohistochemistry/RNA expression including for immune-biomarkers, per physician discretion) and medication-acquisition specialists/clinical trial coordinators/navigators to assist with medication access. The MTB comprehensively reviewed patient characteristics to develop N-of-One treatments implemented by the treating physician's direction under the auspices of a master protocol. Overall, 265/429 therapy-evaluable patients (62%) were matched to ≥1 recommended drug. Eighty-six patients (20%) matched to all drugs recommended by MTB, including combinatorial approaches, while 38% received physician's choice regimen, generally with unmatched approach/low degree of matching. Our results show that patients who receive MTB-recommended regimens (versus physician choice) have significantly longer progression-free (PFS) and overall survival (OS), and are better matched to therapy. High (≥50%) versus low (<50%) Matching Score therapy (roughly reflecting therapy matched to ≥50% versus <50% of alterations) independently correlates with longer PFS (hazard ratio [HR], 0.63; 95% confidence interval [CI], 0.50-0.80; P < 0.001) and OS (HR, 0.67; 95% CI, 0.50-0.90; P = 0.007) and higher stable disease ≥6 months/partial/complete remission rate (52.1% versus 30.4% P < 0.001) (all multivariate). In conclusion, patients who receive MTB-based therapy are better matched to their genomic alterations, and the degree of matching is an independent predictor of improved oncologic outcomes including survival.

Indexed as

AdolescentAdultAgedAged, 80 and overAntineoplastic AgentsChildChild, PreschoolCirculating Tumor DNADisease-Free SurvivalFemaleGenome, HumanHumansMaleMiddle AgedNeoplasmsPrecision MedicineAntineoplastic AgentsCirculating Tumor DNA

Identifiers

PMID33009371
PMCPMC7532150

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Registered trials

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.