Evidence map›Paper›PMID 26659358›Full record

ArticlePloS one2015

Multi-Scale Agent-Based Multiple Myeloma Cancer Modeling and the Related Study of the Balance between Osteoclasts and Osteoblasts.

Minna Qiao, Dan Wu, Michelle Carey, Xiaobo Zhou, Le Zhang

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Correlations of DKK1 with pathogenesis and prognosis of human multiple myeloma.Cancer biomarkers : section A of Disease markers · 2019
    Article
  5. Article
  6. Review
  7. Article
  8. Article
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.

Minna QiaoCollege of Computer and Information Science, Southwest University, Chongqing, P. R. China.
Dan WuDepartment of Radiology, Wake Forest University School of Medicine, Winston Salem, United States of America.
Michelle CareyDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, United States of America.
Xiaobo ZhouDepartment of Radiology, Wake Forest University School of Medicine, Winston Salem, United States of America.
Le ZhangCollege of Computer and Information Science, Southwest University, Chongqing, P. R. China.

Funding

Virology/Immunology CoreP30AI078498 · NIAID · UNIVERSITY OF ROCHESTER · PI DEWHURST, STEPHEN · 2008 to 2018
$14.6M
Modelling the Growth of the MIC Niche at the System LevelU01CA166886 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ZHOU, XIAOBO · 2012 to 2016
$2.2M
NCI NIH HHS U01 CA166886NCI NIH HHS U01 CA166886-01NIAID NIH HHS HHSN272201000055CNIAID NIH HHS P30 AI078498NIAID NIH HHS P30AI078498
6 · The paper itself

Abstract

RESEARCH

backgroundCurrently, multiple myeloma is the second most common hematological malignancy in the U.S., constituting 1% of all cancers. With conventional treatment, the median survival time is typically 3-4 years, although it can be extended to 5-7 years or longer with advanced treatments. Recent research indicated that an increase in osteoclast (OC) activity is often associated withmultiple myeloma (MM) and that a decrease inosteoblast (OB) activity contributesto the osteolytic lesions in MM. Normally, the populations of OCs and OBs are inequilibrium, and an imbalance in this statecontributes to the development of lesions. RESEARCH PROCEDURES: A multi-scale agent-based multiple myeloma model was developed to simulate the proliferation, migration and death of OBs and OCs. Subsequently, this model was employed to investigate the efficacy of thethree most commonly used drugs for MM treatment under the following two premises: the reduction in the progression of MM and the re-establishment of the equilibrium between OCs and OBs. RESEARCH PURPOSES: The simulated results not only demonstrated the capacity of the model to choose optimal combinations of the drugs but also showed that the optimal use of the three drugs can restore the balance between OCs and OBs as well as kill MMs. Furthermore, the drug synergism analysis function of the model revealed that restoring the balance between OBs and OCs can significantly increase the efficacy of drugs against tumor cells.

Indexed as

Models, BiologicalModels, StatisticalAminoglycosidesAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic AgentsCell DeathCell DifferentiationCell MovementCell ProliferationEnediynesGene Expression Regulation, NeoplasticGlucocorticoidsHumansIntercellular Signaling Peptides and ProteinsMultiple MyelomaAminoglycosidesAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic AgentsBHQ880C 1027DKK1 protein, humanEnediynesGlucocorticoidsIntercellular Signaling Peptides and ProteinsRANK LigandReceptor Activator of Nuclear Factor-kappa BTNFRSF11A protein, humanTNFSF11 protein, humanTumor Necrosis Factor-alpha

Identifiers

PMID26659358
PMCPMC4676611

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.