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Modeling the pathway of breast cancer in the Middle East

Asmaa Amer

Asmaa Amer

  • School of Mathematics and Statistics, Central China Normal UniversityWuhan, China
  • Faculty of Science, Mathematics Department, Menoufia UniversityEgypt
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Amer, Asmaa
, 
Ahmed Nagah

Ahmed Nagah

  • School of Mathematics and Statistics, Central China Normal UniversityWuhan, China
  • Faculty of Science, Mathematics Department, Zagazig UniversityEgypt
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Nagah, Ahmed
, 
Mojeeb AL-Rahman El-Nor Osman

Mojeeb AL-Rahman El-Nor Osman

School of Mathematics and Statistics, Central China Normal UniversityWuhan, China
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Osman, Mojeeb AL-Rahman El-Nor
 and 
Abdul Majid

Abdul Majid

School of Mathematics and Statistics, Central China Normal UniversityWuhan, China
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Majid, Abdul
  
Nov 19, 2021
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Published Online: Nov 19, 2021
Page range: 147 - 166
Received: Nov 20, 2019
Accepted: Apr 11, 2021
DOI: https://doi.org/10.2478/amns.2021.2.00050
Keywords
© 2023 Asmaa Amer et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Incidence of breast cancer in four member countries (Egypt, Jordan, Cyprus and Israel (Arabs and Jews)) of the Middle East Cancer Consortium (MECC) and USA.
Incidence of breast cancer in four member countries (Egypt, Jordan, Cyprus and Israel (Arabs and Jews)) of the Middle East Cancer Consortium (MECC) and USA.

Fig. 2

A schematic representation of k-stage model (k = 2,3, …) for carcinogenesis. N denotes the normal progenitor cells. Ii(i = 2,3, …,k) denotes the compartments of intermediate cells, μi(i = 1,2, …,k) are the mutation rates per cell per year of normal progenitor cells and compartment of intermediate cells, and γi(i = 1,2, …,k) are the net growth rates per cell per year. M denotes the malignant cells.
A schematic representation of k-stage model (k = 2,3, …) for carcinogenesis. N denotes the normal progenitor cells. Ii(i = 2,3, …,k) denotes the compartments of intermediate cells, μi(i = 1,2, …,k) are the mutation rates per cell per year of normal progenitor cells and compartment of intermediate cells, and γi(i = 1,2, …,k) are the net growth rates per cell per year. M denotes the malignant cells.

Fig. 3

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Egypt from 2008 to 2011 under hypothesis one. The blue line represents the model and red stars represent the data from Egypt.
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Egypt from 2008 to 2011 under hypothesis one. The blue line represents the model and red stars represent the data from Egypt.

Fig. 4

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Jordan from 1996 to 2001 under hypothesis one. The blue line represents the model and red stars represent the data from Jordan.
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Jordan from 1996 to 2001 under hypothesis one. The blue line represents the model and red stars represent the data from Jordan.

Fig. 5

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Cyprus from 1998 to 2001 under hypothesis one. The blue line represents the model and red stars represent the data from Cyprus.
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Cyprus from 1998 to 2001 under hypothesis one. The blue line represents the model and red stars represent the data from Cyprus.

Fig. 6

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Arabs) from 1996 to 2001 under hypothesis one. The blue line represents the model and red stars represent data from Israel (Arabs).
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Arabs) from 1996 to 2001 under hypothesis one. The blue line represents the model and red stars represent data from Israel (Arabs).

Fig. 7

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Jews) from 1996 to 2001 under hypothesis one. The blue line represents the model and red stars represent data from Israel (Jews).
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Jews) from 1996 to 2001 under hypothesis one. The blue line represents the model and red stars represent data from Israel (Jews).

Fig. 8

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Egypt under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent data from Egypt.
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Egypt under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent data from Egypt.

Fig. 9

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Jordan under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent the data from Jordan.
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Jordan under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent the data from Jordan.

Fig. 10

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Cyprus under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent the data from Cyprus.
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Cyprus under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent the data from Cyprus.

Fig. 11

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Arabs) under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent data from Israel (Arabs).
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Arabs) under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent data from Israel (Arabs).

Fig. 12

The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Jews) under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent data from Israel (Jews).
The simulation of the probability of age-specific incidence rates of all races per 100,000 females for breast cancer in Israel (Jews) under hypothesis two that all mutation rates are equal. The blue line represents the model and red stars represent data from Israel (Jews).
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