Limits...
Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China.

Fei X, Christakos G, Lou Z, Ren Y, Liu Q, Wu J - Sci Rep (2016)

Bottom Line: The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions.Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data.The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

View Article: PubMed Central - PubMed

Affiliation: College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China.

ABSTRACT
Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008-2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008-2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

No MeSH data available.


Related in: MedlinePlus

Plots of the space-time covariances of the TC incidence and BC incidence distributions, (a) , and (b) , respectively. Circles denote experimental (sample) covariance values, whereas continuous (color) surfaces and continuous lines denote the fitted theoretical models.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4920092&req=5

f7: Plots of the space-time covariances of the TC incidence and BC incidence distributions, (a) , and (b) , respectively. Circles denote experimental (sample) covariance values, whereas continuous (color) surfaces and continuous lines denote the fitted theoretical models.

Mentions: Interestingly, the geographical variations of the and distributions of each one of the five years considered (Figs 5a–e and 6a–e) showed some small differences, which were due to corresponding differences in the disease prediction error maps (vs. ), which, in turn, were due to the different TC and BC datasets as well as to the different space-time covariances, and , used in TC and BC incidence prediction. Indeed, the different shapes of the two space-time incidence covariances can be clearly seen in Fig. 7a,b (the spatial TC correlation range is much longer than the BC correlation range, implying stronger geographical dependence between TC incidences than between BC incidences, the TC incidence variance is smaller than that of BC incidence, implying less local TC variation than BC variation, etc.). These differences between the incidence covariances can affect the results of BME prediction of the TC and BC incidences across space-time.


Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China.

Fei X, Christakos G, Lou Z, Ren Y, Liu Q, Wu J - Sci Rep (2016)

Plots of the space-time covariances of the TC incidence and BC incidence distributions, (a) , and (b) , respectively. Circles denote experimental (sample) covariance values, whereas continuous (color) surfaces and continuous lines denote the fitted theoretical models.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4920092&req=5

f7: Plots of the space-time covariances of the TC incidence and BC incidence distributions, (a) , and (b) , respectively. Circles denote experimental (sample) covariance values, whereas continuous (color) surfaces and continuous lines denote the fitted theoretical models.
Mentions: Interestingly, the geographical variations of the and distributions of each one of the five years considered (Figs 5a–e and 6a–e) showed some small differences, which were due to corresponding differences in the disease prediction error maps (vs. ), which, in turn, were due to the different TC and BC datasets as well as to the different space-time covariances, and , used in TC and BC incidence prediction. Indeed, the different shapes of the two space-time incidence covariances can be clearly seen in Fig. 7a,b (the spatial TC correlation range is much longer than the BC correlation range, implying stronger geographical dependence between TC incidences than between BC incidences, the TC incidence variance is smaller than that of BC incidence, implying less local TC variation than BC variation, etc.). These differences between the incidence covariances can affect the results of BME prediction of the TC and BC incidences across space-time.

Bottom Line: The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions.Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data.The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

View Article: PubMed Central - PubMed

Affiliation: College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China.

ABSTRACT
Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008-2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008-2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

No MeSH data available.


Related in: MedlinePlus