Evidence map›Paper›PMID 34101093›Full record

ArticleJournal of neuro-oncology2021

Combination chemotherapy versus temozolomide for patients with methylated MGMT (m-MGMT) glioblastoma: results of computational biological modeling to predict the magnitude of treatment benefit.

Michael Castro, Anusha Pampana, Aftab Alam, Rajan Parashar, Swaminathan Rajagopalan, Deepak Anil Lala, Kunal Ghosh Ghosh Roy, Sayani Basu, Annapoorna Prakash, Prashant Nair and 7 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuro-oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 10 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

17 authors at 1 institution in 3 countries.

Michael CastroPersonalized Cancer Medicine PLLC, 1735 S Hayworth Ave., Los Angeles, CA, USA. michael.castro@personalizedcancermedicine.us.ORCID http://orcid.org/0000-0003-0421-1027
Anusha PampanaCellworks Group, Inc., S. San Francisco, CA, USA.
Aftab AlamCellworks Group, Inc., S. San Francisco, CA, USA.
Rajan ParasharCellworks Group, Inc., S. San Francisco, CA, USA.
Swaminathan RajagopalanCellworks Group, Inc., S. San Francisco, CA, USA.
Deepak Anil LalaCellworks Group, Inc., S. San Francisco, CA, USA.
Kunal Ghosh Ghosh RoyCellworks Group, Inc., S. San Francisco, CA, USA.
Sayani BasuCellworks Group, Inc., S. San Francisco, CA, USA.
Annapoorna PrakashCellworks Group, Inc., S. San Francisco, CA, USA.
Prashant NairCellworks Group, Inc., S. San Francisco, CA, USA.
Vishwas JosephCellworks Group, Inc., S. San Francisco, CA, USA.
Ashish AgarwalCellworks Group, Inc., S. San Francisco, CA, USA.
Poornachandra GCellworks Group, Inc., S. San Francisco, CA, USA.
Liptimayee BehuraCellworks Group, Inc., S. San Francisco, CA, USA.
Shruthi KulkarniCellworks Group, Inc., S. San Francisco, CA, USA.
Nikita Ray ChoudharyCellworks Group, Inc., S. San Francisco, CA, USA.
Shweta KapoorCellworks Group, Inc., S. San Francisco, CA, USA.
Cellworks Research (India) · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA randomized trial in glioblastoma patients with methylated-MGMT (m-MGMT) found an improvement in median survival of 16.7 months for combination therapy with temozolomide (TMZ) and lomustine, however the approach remains controversial and relatively under-utilized. Therefore, we sought to determine whether comprehensive genomic analysis can predict which patients would derive large, intermediate, or negligible benefits from the combination compared to single agent chemotherapy.

methodsComprehensive genomic information from 274 newly diagnosed patients with methylated-MGMT glioblastoma (GBM) was downloaded from TCGA. Mutation and copy number changes were input into a computational biologic model to create an avatar of disease behavior and the malignant phenotypes representing hallmark behavior of cancers. In silico responses to TMZ, lomustine, and combination treatment were biosimulated. Efficacy scores representing the effect of treatment for each treatment strategy were generated and compared to each other to ascertain the differential benefit in drug response.

resultsDifferential benefits for each drug were identified, including strong, modest-intermediate, negligible, and deleterious (harmful) effects for subgroups of patients. Similarly, the benefits of combination therapy ranged from synergy, little or negligible benefit, and deleterious effects compared to single agent approaches.

conclusionsThe benefit of combination chemotherapy is predicted to vary widely in the population. Biosimulation appears to be a useful tool to address the disease heterogeneity, drug response, and the relevance of particular clinical trials observations to individual patients. Biosimulation has potential to spare some patients the experience of over-treatment while identifying patients uniquely situated to benefit from combination treatment. Validation of this new artificial intelligence tool is needed.

Indexed as

Brain NeoplasmsGlioblastomaAntineoplastic Agents, AlkylatingAntineoplastic Combined Chemotherapy ProtocolsArtificial IntelligenceDNA Modification MethylasesDNA Repair EnzymesDrug Therapy, CombinationHumansLomustineOvertreatmentPharmaceutical PreparationsTemozolomideTumor Suppressor ProteinsAntineoplastic Agents, AlkylatingDNA Modification MethylasesDNA Repair EnzymesLomustineMGMT protein, humanPharmaceutical PreparationsTemozolomideTumor Suppressor ProteinsArtificial intelligence (AI)BiosimulationComputational biological modelingGlioblastoma (GBM)O6-methylguanine-DNA methyl-transferase (MGMT)Precision medicine

Identifiers

PMID34101093
PMCPMC8280043
OpenAlexW3167493674

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.