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July 2012 Vol. 1 Issue 6
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Misiri H
Edriss A
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Global Advanced Research Journal
of Medicine and Medical Sciences
July 2012 Vol. 1(6), pp. 154-162
Copyright © 2012 Global Advanced
Research Journals
Full Length Research Paper
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Age at cancer diagnosis in Malawi
Humphrey Misiri1,2 * and Abdi
Edriss3
1Department
of Biostatistics, Institute of Basic Medical
Sciences, University of Oslo, Oslo, Norway.
2Department
of Community Health, College of Medicine, Blantyre,
Malawi.
3Bunda
College, University of Malawi, Lilongwe, Malawi.
*Corresponding author E-mail:
hmisiri@gmail.com,
humphrey.misiri@medisin.uio.no ; Tel/Cell:
+265-888-342-864: Fax: +265-1874-700
Accepted 28 June, 2012
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Abstract |
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Cancer which is one of the leading causes of death
worldwide is emerging as a serious public health
problem in Malawi due to the AIDS pandemic. Research
has shown that HIV causes the syndrome of premature
aging and accelerates carcinogenesis. The objective
of this study was to describe age at cancer
diagnosis and to fit the age distribution of
childhood and adult cancer diagnosis in Malawi. We
therefore fitted the normal, gamma, lognormal and
inverse Gaussian probability distributions to the
data for the 1996–2005 period from the Malawi
National Cancer Registry and selected the model of
best fit using the Akaike Information Criterion.
Additionally, a finite mixture distribution of
lognormals was also fitted to the data. According to
the analysis for this study, the median ages at
diagnosis are at most 42 years for AIDS-defining
cancers and at least 46 years for non-AIDS defining
cancers. Furthermore, the ages at childhood and
adult cancer diagnosis follow lognormal
distributions and the distribution of age at cancer
diagnosis (all cancers) is a finite mixture
distribution of lognormals with estimated mixing
proportions equal to 0.071 and 0.929. The estimated
means of the mixture distribution are 5.1 and 45.1
years and the corresponding estimated standard
deviations are 1.211 and 2.842 years. This analysis
suggests that age at cancer diagnosis in Malawi is
relatively low and has a bimodal distribution.
Therefore, to achieve maximum impact, cancer
prevention and control activities should target the
15-50 year age range.
Keywords:
cancer, diagnosis, AIC, finite mixture.
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