ArticlePloS one2015
Multi-Scale Agent-Based Multiple Myeloma Cancer Modeling and the Related Study of the Balance between Osteoclasts and Osteoblasts.
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.
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.
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.
Who cites it
8 citing papers in PubMed.
- Screening and Analysis of Core Genes for Osteoporosis Based on Bioinformatics Analysis and Machine Learning Algorithms.Indian journal of orthopaedics · 2024Article
- The bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous drug resistant disease.Nature communications · 2024Article
- Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution.Current opinion in systems biology · 2019Article
- Correlations of DKK1 with pathogenesis and prognosis of human multiple myeloma.Cancer biomarkers : section A of Disease markers · 2019Article
- A Retrospective Analysis: A Novel Index Predicts Survival and Risk-Stratification for Bone Destruction in 419 Newly Diagnosed Multiple Myelomas.OncoTargets and therapy · 2019Article
- Searching Synergistic Dose Combinations for Anticancer Drugs.Frontiers in pharmacology · 2018Review
- Developing an Agent-Based Drug Model to Investigate the Synergistic Effects of Drug Combinations.Molecules (Basel, Switzerland) · 2017Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
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
Identifiers
What OpenQuestion holds
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.