Cancer as a System Dysfunction

Saeed, Khalid; Ryder, Elizabeth F.; Manning, Amity L.

doi:10.3390/systems9010014

Cited by 3 publications

(6 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…People were the primary unit being modeled in 50% of the studies (n = 16) [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49], while 16% modeled patient experience or behavior (n = 5) [50][51][52][53][54]. Other primary units modeled include cells (n = 4; 13%) [33, [55][56][57], environmental contaminants (n = 4; 13%) [58][59][60][61], currency (n = 2; 6%) [62,63], and web search queries (n = 1; 3%) [64]. The abstracted characteristics of all studies included in this review are available in S1 Table . Study topics were clustered around several themes: Eight studies (25%) focused on cancer screening, each of which focused on a different type of cancer or associated condition (e.g., Lynch syndrome, anal dysplasia).…”

Section: Plos Onementioning

confidence: 99%

“…As seen in Fig 5, our search yielded studies relating to all stages in the cancer control continuum: fourteen (44%) related to treatment [33-37, 45, 49, 51, 53-57, 63], eleven (34%) to prevention [35,39,40,43,47,48,52,58,60,61,64], ten (31%) to detection [35-38, 41-44, 46, 62], eight (25%) to etiology [35,39,48,52,[57][58][59]61], four (13%) to diagnosis [35][36][37]51], and one (3%) to survivorship [50]. The majority of studies (n = 21; 66%) related most significantly to one focus area in the cancer control continuum, while seven (22%) related to two areas [39,43,44,48,52,58,61], two (6%) related to three areas [36,37] and one (3%) related to five [35].…”

Section: Study Topics Across the Cancer Control Continuummentioning

confidence: 99%

“…Studies pertaining to etiology or prevention most often related to other focus areas (typically each other), while studies related to treatment most often related to only that area. Only one study included etiology and treatment [57]. Detection was evenly split between single and multiple focus areas.…”

Section: Study Topics Across the Cancer Control Continuummentioning

confidence: 99%

“…The majority of studies spanning etiology or prevention (62%) related to either environmental pollution or tobacco / e-cigarettes [39,40,47,52,[58][59][60][61]. Five treatment studies related to chemotherapy [33, [55][56][57], one of which included etiology [57]. Of the ten studies discussing detection, no two related to screening for the same type of cancer.…”

Section: Study Topics Across the Cancer Control Continuummentioning

confidence: 99%

See 3 more Smart Citations

System dynamics modeling for cancer prevention and control: A systematic review

Kenzie,

Seater,

Wakeland

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

Cancer prevention and control requires consideration of complex interactions between multilevel factors. System dynamics modeling, which consists of diagramming and simulation approaches for understanding and managing such complexity, is being increasingly applied to cancer prevention and control, but the breadth, characteristics, and quality of these studies is not known. We searched PubMed, Scopus, APA PsycInfo, and eight peer-reviewed journals to identify cancer-related studies that used system dynamics modeling. A dual review process was used to determine eligibility. Included studies were assessed using quality criteria adapted from prior literature and mapped onto the cancer control continuum. Characteristics of studies and models were abstracted and qualitatively synthesized. 32 studies met our inclusion criteria. A mix of simulation and diagramming approaches were used to address diverse topics, including chemotherapy treatments (16%), interventions to reduce tobacco or e-cigarettes use (16%), and cancer risk from environmental contamination (13%). Models spanned all focus areas of the cancer control continuum, with treatment (44%), prevention (34%), and detection (31%) being the most common. The quality assessment of studies was low, particularly for simulation approaches. Diagramming-only studies more often used participatory approaches. Involvement of participants, description of model development processes, and proper calibration and validation of models showed the greatest room for improvement. System dynamics modeling can illustrate complex interactions and help identify potential interventions across the cancer control continuum. Prior efforts have been hampered by a lack of rigor and transparency regarding model development and testing. Supportive infrastructure for increasing awareness, accessibility, and further development of best practices of system dynamics for multidisciplinary cancer research is needed.

show abstract

Section: Plos Onementioning

confidence: 99%

Section: Study Topics Across the Cancer Control Continuummentioning

confidence: 99%

Section: Study Topics Across the Cancer Control Continuummentioning

confidence: 99%

Section: Study Topics Across the Cancer Control Continuummentioning

confidence: 99%

See 2 more Smart Citations

System dynamics modeling for cancer prevention and control: A systematic review

Kenzie,

Seater,

Wakeland

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Within the cancer systems biology paradigm, the system structures can be separated into five networks including the gene regulatory network, molecular network, cellular network, organ network, and clinical and research network. The systems dynamics process aims to understand how cancer as a complex system of abnormal cell growth behaves and changes over time from an initial set of conditions [ 14 ]. The cancer control method of systems biology relies on modulating the state of the cell to limit cancer growth or induce apoptosis to validate potential therapeutic options [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Clinical Network Systems Biology: Traversing the Cancer Multiverse

Mambetsariev

Fricke

Gruber

et al. 2023

JCM

View full text Add to dashboard Cite

In recent decades, cancer biology and medicine have ushered in a new age of precision medicine through high-throughput approaches that led to the development of novel targeted therapies and immunotherapies for different cancers. The availability of multifaceted high-throughput omics data has revealed that cancer, beyond its genomic heterogeneity, is a complex system of microenvironments, sub-clonal tumor populations, and a variety of other cell types that impinge on the genetic and non-genetic mechanisms underlying the disease. Thus, a systems approach to cancer biology has become instrumental in identifying the key components of tumor initiation, progression, and the eventual emergence of drug resistance. Through the union of clinical medicine and basic sciences, there has been a revolution in the development and approval of cancer therapeutic drug options including tyrosine kinase inhibitors, antibody–drug conjugates, and immunotherapy. This ‘Team Medicine’ approach within the cancer systems biology framework can be further improved upon through the development of high-throughput clinical trial models that utilize machine learning models, rapid sample processing to grow patient tumor cell cultures, test multiple therapeutic options and assign appropriate therapy to individual patients quickly and efficiently. The integration of systems biology into the clinical network would allow for rapid advances in personalized medicine that are often hindered by a lack of drug development and drug testing.

show abstract

Smart Cities from the Perspective of Systems

Ammara

Rasheed

Mansoor

et al. 2022

Systems

View full text Add to dashboard Cite

Modern cities are complex adaptive systems in which there is a lot of dependency and interaction between the various stakeholders, components, and subsystems. The use of digital Information and Communications Technology (ICT) has opened up the vision of smart cities in which the city dwellers can have a better quality of life and the city can be better organized and managed. The deployment of ICT solutions, however, does not automatically or invariably improve the quality of living of the citizens. Analyzing cities as complex systems with various interacting sub-systems can help us understand urban dynamics and the fate of smart cities. We will be able to analyze various policy interventions and ascertain their effectiveness and anticipate potential unintended consequences. In this paper, we discuss how smart cities can be viewed through the lens of systems thinking and complex systems and provide a comprehensive review of related techniques and methods. Along with highlighting the science of cities in light of historic urban modeling and urban dynamics, we focus on shedding light on the smart city complex systems. Finally, we will describe the various challenges of smart cities, discuss the limitations of existing models, and identify promising future directions of work.

show abstract

Cancer as a System Dysfunction

Cited by 3 publications

References 22 publications

System dynamics modeling for cancer prevention and control: A systematic review

System dynamics modeling for cancer prevention and control: A systematic review

Clinical Network Systems Biology: Traversing the Cancer Multiverse

Smart Cities from the Perspective of Systems

Contact Info

Product

Resources

About