Evidence map›Paper›PMID 26316014›Full record

ArticleScientific reports2015

Mathematical Modelling and Prediction of the Effect of Chemotherapy on Cancer Cells.

Hamidreza Namazi, Vladimir V Kulish, Albert Wong

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

9 citing papers in PubMed, 56 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Review
  6. Computational modeling of therapy on pancreatic cancer in its early stages.Biomechanics and modeling in mechanobiology · 2020
    Article
  7. Dynamics of Breast Cancer under Different Rates of Chemoradiotherapy.Computational and mathematical methods in medicine · 2019
    Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Hamidreza NamaziSchool of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.
Vladimir V KulishSchool of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.
Albert WongDepartment of Radiotherapy, Oncology and Palliative care, Sarawak General Hospital, Kuching, Malaysia.
Nanyang Technological University · SGSarawak General Hospital · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a class of diseases characterized by out-of-control cells' growth which affect DNAs and make them damaged. Many treatment options for cancer exist, with the primary ones including surgery, chemotherapy, radiation therapy, hormonal therapy, targeted therapy and palliative care. Which treatments are used depends on the type, location, and grade of the cancer as well as the person's health and wishes. Chemotherapy is the use of medication (chemicals) to treat disease. More specifically, chemotherapy typically refers to the destruction of cancer cells. Considering the diffusion of drugs in cancer cells and fractality of DNA walks, in this research we worked on modelling and prediction of the effect of chemotherapy on cancer cells using Fractional Diffusion Equation (FDE). The employed methodology is useful not only for analysis of the effect of special drug and cancer considered in this research but can be expanded in case of different drugs and cancers.

Indexed as

Models, BiologicalAdultAntineoplastic AgentsDiffusionDNA DamageDrug Delivery SystemsFemaleHumansMaleNeoplasmsAntineoplastic Agents

Identifiers

PMID26316014
PMCPMC4552002
OpenAlexW1275652294

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.