Evidence map›Paper›PMID 36469316›Full record

ArticleJAMA network open2022

Concordance Between Recommendations From Multidisciplinary Molecular Tumor Boards and Central Consensus for Cancer Treatment in Japan.

Yoichi Naito, Kuniko Sunami, Hidenori Kage, Keigo Komine, Toraji Amano, Mitsuho Imai, Takafumi Koyama, Daisuke Ennishi, Masashi Kanai, Hirotsugu Kenmotsu and 15 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

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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

25 authors at 14 institutions in 1 country.

Yoichi NaitoDepartment of General Internal Medicine, National Cancer Center Hospital East, Kashiwa, Japan.
Kuniko SunamiDepartment of Laboratory Medicine, National Cancer Center Hospital, Tokyo, Japan.
Hidenori KageDepartment of Next-Generation Precision Medicine Development Laboratory, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Keigo KomineDepartment of Medical Oncology, Tohoku University Hospital, Sendai, Japan.
Toraji AmanoDivision of Clinical Cancer Genomics, Hokkaido University Hospital, Sapporo, Japan.
Mitsuho ImaiGenomics Unit, Keio University School of Medicine, Tokyo, Japan.
Takafumi KoyamaDepartment of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan.
Daisuke EnnishiDepartment of Hematology and Oncology, Okayama University Hospital, Okayama, Japan.
Masashi KanaiDepartment of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Hirotsugu KenmotsuDivision of Thoracic Oncology, Shizuoka Cancer Center, Shizuoka, Japan.
Takahiro MaedaDivision of Precision Medicine, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan.
Sachi MoritaDepartment of Clinical Oncology and Chemotherapy, Nagoya University Hospital, Nagoya, Japan.
Daisuke SakaiCenter for Cancer Genomics and Personalized Medicine, Osaka University, Suita, Japan.
Kousuke WatanabeDepartment of Clinical Laboratory, The University of Tokyo Hospital, Tokyo, Japan.
Hidekazu ShirotaDepartment of Medical Oncology, Tohoku University Hospital, Sendai, Japan.
Ichiro KinoshitaDivision of Clinical Cancer Genomics, Hokkaido University Hospital, Sapporo, Japan.
Masashiro YoshiokaDepartment of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Nobuaki MamesayaDivision of Thoracic Oncology, Shizuoka Cancer Center, Shizuoka, Japan.
Mamoru ItoDivision of Precision Medicine, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan.
Shinji KohsakaSection of Knowledge Integration, Center for Cancer Genomics and Advanced Therapeutics, National Cancer Center, Tokyo, Japan.
Yusuke SaigusaDepartment of Biostatistics, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Kouji YamamotoDepartment of Biostatistics, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Makoto HirataDepartment of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo, Japan.
Katsuya TsuchiharaDivision of Translational Informatics, National Cancer Center Exploratory Oncology Research and Clinical Trial Center, Tokyo, Japan.
Takayuki YoshinoDepartment of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan.
Hokkaido University Hospital · JPNational Cancer Center Hospital East · JPKyoto University · JPKyushu University · JPShizuoka Cancer Center · JPTohoku University Hospital · JPTokyo National Hospital · JPYokohama City University · JPJapan Clinical Cancer Research Organization · JPKeio University · JPNagoya University Hospital · JPOkayama University Hospital · JPOsaka University · JPUniversity of Tokyo Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Quality assurance of molecular tumor boards (MTBs) is crucial in cancer genome medicine. Objective: To evaluate the concordance of recommendations by MTBs and centrally developed consensus treatment recommendations at all 12 leading institutions for cancer genomic medicine in Japan using 50 simulated cases. Design, Setting, and Participants: This was a prospective quality improvement study of 50 simulated cancer cases. Molecular tumor boards from 12 core hospitals independently recommended treatment for 50 cases blinded to the centrally developed consensus treatment recommendations. The study's central committee consisted of representatives from all 12 core hospitals in Japan who selected the 50 simulated cases from The Cancer Genome Atlas database, including frequently observed genomic alterations. The central committee recommended centrally developed consensus treatment. The concordance rate for genomically matched treatments between MTBs and centrally developed consensus treatment recommendations was evaluated. Data analysis was conducted from January 22 to March 3, 2021. Exposures: Simulated cases of cancer. Main Outcomes and Measures: The primary outcome was concordance, defined as the proportion of recommendations by MTBs concordant with centrally developed consensus treatment recommendations. A mixed-effects logistic regression model, adjusted for institutes as a random intercept, was applied. High evidence levels were defined as established biomarkers for which the treatment was ready for routine use in clinical practice, and low evidence levels were defined as biomarkers for genomically matched treatment that were under investigation. Results: The Clinical Practice Guidance for Next-Generation Sequencing in Cancer Diagnosis and Treatment (edition 2.1) was used for evidence-level definition. The mean concordance between MTBs and centrally developed consensus treatment recommendations was 62% (95% CI, 57%-65%). Each MTB concordance varied from 48% to 86%. The concordance rate was higher in the subset of patients with colorectal cancer (100%; 95% CI, 94.0%-100%), ROS1 fusion (100%; 95% CI, 85.5%-100%), and high evidence level A/R (A: 88%; 95% CI, 81.8%-93.0%; R:100%; 95% CI, 92.6%-100%). Conversely, the concordance rate was lower in cases of cervical cancer (11%; 95% CI, 3.1%-26.1%), TP53 mutation (16%; 95% CI, 12.5%-19.9%), and low evidence level C/D/E (C: 30%; 95% CI, 24.7%-35.9%; D: 25%; 95% CI, 5.5%-57.2%; and E: 18%; 95% CI, 13.8%-23.0%). Multivariate analysis showed that evidence level (high [A/R] vs low [C/D/E]: odds ratio, 4.4; 95% CI, 1.8-10.8) and TP53 alteration (yes vs no: odds ratio, 0.06; 95% CI, 0.03-0.10) were significantly associated with concordance. Conclusions and Relevance: The findings of this study suggest that genomically matched treatment recommendations differ among MTBs, particularly in genomic alterations with low evidence levels wherein treatment is being investigated. Sharing information on matched therapy for low evidence levels may be needed to improve the quality of MTBs.

Indexed as

NeoplasmsPractice Guidelines as TopicConsensusHumansJapanProspective StudiesQuality Improvement

Identifiers

PMID36469316
PMCPMC9855299
OpenAlexW4311554414

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.