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Multicenter Study
. 2023 Jan 6;13(1):303.
doi: 10.1038/s41598-023-27547-x.

Future world cancer death rate prediction

Oleg Gaidai  1 , Ping Yan  1 , Yihan Xing  2
Affiliations
Multicenter Study

Future world cancer death rate prediction

Oleg Gaidai et al. Sci Rep. .

Abstract

Cancer is a worldwide illness that causes significant morbidity and death and imposes an immense cost on global public health. Modelling such a phenomenon is complex because of the non-stationarity and complexity of cancer waves. Apply modern novel statistical methods directly to raw clinical data. To estimate extreme cancer death rate likelihood at any period in any location of interest. Traditional statistical methodologies that deal with temporal observations of multi-regional processes cannot adequately deal with substantial regional dimensionality and cross-correlation of various regional variables. Setting: multicenter, population-based, medical survey data-based biostatistical approach. Due to the non-stationarity and complicated nature of cancer, it is challenging to model such a phenomenon. This paper offers a unique bio-system dependability technique suited for multi-regional environmental and health systems. When monitored over a significant period, it yields a reliable long-term projection of the chance of an exceptional cancer mortality rate. Traditional statistical approaches dealing with temporal observations of multi-regional processes cannot effectively deal with large regional dimensionality and cross-correlation between multiple regional data. The provided approach may be employed in numerous public health applications, depending on their clinical survey data.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Map of the world with countries and cancer deaths. All world countries were studied in this paper.
Figure 2
Figure 2
Example of how two example processes, X and Y, are merged to create a new synthetic vector R→.
Figure 3
Figure 3
Annual cancer annual death cases. Left: as % of local population per country and year. Right: in per cent as 195D vector R→. Scaled by Eq. (9) in per cent of the corresponding country population.
Figure 4
Figure 4
Death rate prediction. 100 years return level extrapolation of pkλ towards critical level (indicated by a star) in per cent of the local population. Extrapolated 95% CI indicated by dotted lines. Percentage of the local population on the horizontal axis.
Figure 5
Figure 5
Cancer global statistics. Left: SODP plot. Middle: TODP, Right: FODP.
See this image and copyright information in PMC

References

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