Evidence map›Paper›PMID 37181287›Full record

ArticleSovremennye tekhnologii v meditsine2022

CRAC (Clinical Relevance of Alterations in Cancer): a Knowledge Base for the Selection of Molecularly Matched Therapy for Solid Tumors.

A A Lebedeva, A I Kavun, E M Veselovsky, V A Mileyko, M V Ivanov

Open access · diamondAbstract read
In one paragraph

Article in Sovremennye tekhnologii v meditsine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 58% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Review
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

5 authors at 1 institution in 1 country.

A A LebedevaHead of Data Interpretation Group; Oncoatlas LLC, 31 Malaya Nikitskaya St., Moscow, 121069, Russia.
A I KavunSenior Data Interpreter; Oncoatlas LLC, 31 Malaya Nikitskaya St., Moscow, 121069, Russia.
E M VeselovskyTechnology Development and Integration Specialist; Oncoatlas LLC, 31 Malaya Nikitskaya St., Moscow, 121069, Russia.
V A MileykoDirector; Oncoatlas LLC, 31 Malaya Nikitskaya St., Moscow, 121069, Russia.
M V IvanovHead of the Research and Development Department; Oncoatlas LLC, 31 Malaya Nikitskaya St., Moscow, 121069, Russia; Researcher, School of Living Systems; Moscow Institute of Physics and Technology (National Research University), 9 Institutskiy per., Dolgoprudny, Moscow Region, 141701, Russia.
Moscow Power Engineering Institute · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multigene testing using NGS (next-generation sequencing) provides a large amount of information and can detect multiple molecular alterations. Subsequent clinical interpretation is a time-consuming process necessary to select a treatment strategy. Existing databases often contain inconsistent information and are not regularly updated. The use of ESCAT levels of evidence requires a deep understanding of the nature of alterations and does not answer the question of which therapy option to select when multiple biomarkers with the same level of evidence are detected. To address these issues, we created the Clinical Relevance of Alterations in Cancer (CRAC) database on the relevance of detected alterations in specific genes, which are often analyzed as part of NGS panels. The team of oncologists and biologists assigned a CRAC score from 1 to 10 to each biomarker (a type of genomic alteration characteristic of specific genes) for 15 malignancies; an average score was entered into the database. CRAC scores are a numerical reflection of the following factors: therapy availability and the prospects of drug treatment with experimental drugs for patients with a particular type of tumor. A total of 134 genes and 15 of the most common tumor types have been selected for CRAC. The biomarker-nosology associations with CRAC scores in the range of 1-3 are the most frequent (n=2719 out of 3495; 77.8%), the least frequent ones (n=52 out of 3495; 1.5%) are with the highest CRAC scores 9 and 10. To estimate the practical effectiveness of the CRAC database, 208 reports on comprehensive molecular profiling were retrospectively analyzed; the applicability of CRAC was compared with the ESCAT level of evidence system. The highest CRAC scores corresponded to the ESCAT maximum levels of evidence: the range of scores 8-10 corresponded to evidence levels I and II. No biomarker within the same level of evidence was represented by the same CRAC score; the largest range of CRAC scores was observed for biomarkers of levels evidence IIIA and IV - from 2 to 10 and from 1 to 9, respectively. The use of CRAC scores allowed to identify additional 95 alterations with CRAC scores of 1-5 in the studied patients. The developed database is available at: https://crac.oncoatlas.ru/.

Indexed as

Clinical RelevanceNeoplasmsHumansKnowledge BasesPrecision MedicineRetrospective Studiesclinical interpretationdatabasemolecularly matched therapyNGSprecision oncology

Identifiers

PMID37181287
PMCPMC10171055
OpenAlexW4312199624

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.