Between 1998 and 2009 the age adjusted cumulative incidence of cancer in the six countries was 119,000 [18] . The reported breast cancer cases were 14,700 cases or 12% of all cancers, and the reported ovarian cancer cases were 2265, or 1.9% of all cancers. Figure 1 shows the relationship between the log-count (natural logarithm of the number of cases) of breast cancer cases and the log-midpoint of age. As can be see, the rates and the rates of changes are clearly divided into two distinct phases separated at about age 49. The first phase represents the early years of reproductive life, and the second phase represents the post-menopausal years. This trend in phase (1) is in agreement with the suggestion of Lilienfeld and Johnson [19] that the incidence increases by the same rate with each increment of age. The constancy of the rate of change in phase 1) is of quantitative importance because if the rate of change remains the same in the age groups 35, 40, and 50, the lifetime and incidence of breast cancer in AGS would be more than doubled in the next 12 years to follow. In phase 2), the decline in incidence as women ages increase is shown.

We therefore decided to model the relationship between incidence and age separately for each phase of age (phase (1) = age less than 49, and Phase (2) = when age is above 49). Figure 2 & Figure 3 depict this relationship. The relationship between age and ovarian cancer incidence are shown in Figure 4 and Figure 5.

The relationship between age and the number of breast cancer (BC) cases for phase (1) is adequately modeled by a simple linear regression model. An indicative of the goodness of fit of this relationship is the value of the

Figure 1. Cumulative breast cancer cases over the period 1998-2009 for all ages.

Figure 2. Cumulative count of breast cancer for the period 1998-2009 for phase (1).

Figure 3. Incidence of breast cancer for the age phase (2).

Figure 4. Incidence of ovarian cancer for the age periods above below 50 years of age.

Figure 5. Incidence of ovarian cancer for the age periods above 50 years.

coefficient of determination R^{2}. Values of the coefficient of determination above 70% indicate a good fit, and this is the case except for Qatar and Kuwait. Since our focus is on young women we shall give special attention to the relationship between age and the count in phase (1). Using SPSS version 20, we fitted the relationship [20] :

(1)

The results are presented in Table 5. Now we need to verify the hypothesis of homogeneity of the rates of change in the number of breast cancer cases with respect age. This hypothesis can be tested using the Cochran’s Chi-square test defined as follows:

First, we define, where. The chi-square test is:

And the hypothesis of homogeneity of rates of change is established when p-value of the above Q-statistics is above 5%. For BC cases the results are summarized in Table 7. We may conclude that all the AGS have the same rate of change in BC cases since all the p-values are above the cut-off value 5% of the type I error rate. The common estimate of the rates of change in BC count with respect to age are, and for phases (1) and (2) respectively.

The pattern of relationship between the OC incidence and age is similar to the relationship between BC and age as can be seen in Table 6. There is increase in the incidence rate with age in phase (1) and a decrease in the rates in phase (2). The results are shown in Table 4. Except for the country of Qatar, there is an excellent fit for the linear model in phase (1), and a very poor fit in phase (2). Similarly, the homogeneity test is accepted and the p-values are reported in Table 7. The common rates of change in the OC incidence with respect to age are, and for phases (1) and (2) respectively.

Homogeneity of rate of change in number of cancer cases among the 6 countries was established separately for each phase and for BC, and OC.

5. Discussion

Cancer poses a major threat to public health worldwide, and incidence rates have increased in most countries

Table 5. Rates of change in BC count for the two phases of age.

Table 6. Rates of change in OC count for two phases of age.

Table 7. Results of testing homogeneity of rates of change in cancer counts with respect to age. P-values above 0.05 indicate that the hypothesis of homogeneity is supported by the data.

since 1990. The trend is a particular threat to developing nations with health systems that are ill-equipped to deal with complex and expensive cancer treatments. The annual update provided by the national cancer registries on the regional burden of cancer will provide all stakeholders with timely estimates to guide policy efforts in cancer prevention, screening, treatment, and palliation. Together with the registry of cancer incidence there is a need for an integrated system of surveillance of the associated risk factors. Therefore one can monitor the correlation between the trend of increase/decrease in the risk factors and the trend of increase/decrease in the cancer incidence. Therefore a systematic investigation of cancer pattern and trends in the AGS over the next decades become feasible, and such information will help the council of health ministers for the design, implementation, the evaluation, and intervention in the AGS.

Acknowledgements

The authors are thankful for the constructive comments made by anonymous reviewer.

Conflict of Interest

The authors declare that they have no conflict of interest.

Cite this paper

Sarah Al-Gahtani,Suhair Abozaid,Elham Al-Nami,Leen Merie,Ayana Al-Yousef,Mohamed M. Shoukri, (2016) Breast and Ovarian Cancer in Young Women of the Arabian Gulf Region: Relationship to Age. *Open Journal of Epidemiology*,**06**,173-182. doi: 10.4236/ojepi.2016.63019

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NOTES

^{*}Corresponding author.