PubMed · 15306819
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Paul Smaglik. 2004-08-12. Making the switch.. https://doi.org/10.1038/nj7001-811a
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Time-to-event regression is a frequent tool in biomedical research. In clinical trials this time is usually measured from the beginning of the study. The same approach is often adopted in the analysis of longitudinal observational studies. However, in recent years there has appeared literature making a case for the use of the date of birth as a starting point, and thus utilize age as the time-to-event. In this paper, we explore different types of age-scale models and compare them with time-on-study models in terms of the estimated regression coefficients they produce. We consider six proportional hazards regression models that differ in the choice of time scale and in the method of adjusting for the years before the study. By considering the estimating equations of these models as well as numerical simulations we conclude that correct adjustment for the age at entry is crucial in reducing bias of the estimated coefficients. The unadjusted age-scale model is inferior to any of the five other models considered, regardless of their choice of time scale. Additionally, if adjustment for age at entry is made, our analyses show very little to suggest that there exists any practically meaningful difference in the estimated regression coefficients depending on the choice of time scale. These findings are supported by four practical examples from the Framingham Heart Study.
Disease expression in hereditary nonpolyposis colorectal cancer (HNPCC) cannot be readily explained by mutation site in the respective DNA mismatch repair genes associated with this disorder. One explanation is the role of modifying genes that can either promote or prevent disease development on a background of increased risk. Two single nucleotide polymorphisms in MDM2 and TP53 have been shown to be associated with younger ages of disease onset in HNPCC (TP53) and Li-Fraumeni syndrome (MDM2). In this study 220 HNPCC patients were examined, from Australia and Poland, all characterized at the molecular level to determine the frequency of the MDM2 SNP309 T>G and to assess its influence on disease expression. The results were then pooled with the results of a previous study to assess the combined influence of the MDM2 SNP309 T>G and TP53 SNP R72P. A significant difference was observed between CRC patients and unaffected MMR gene mutation carriers over the age of 45 years (p = 0.01). The unaffected MMR gene mutation carriers over the age of 45 years who carry the G allele have a reduced risk of developing CRC. The results indicate that the MDM2 SNP309, alone or in combination with TP53 R72P, does not influence age of diagnosis of CRC in individuals with HNPCC. In conclusion, the data indicates the G allele of MDM2 SNP309 might have a protective effect on disease development in HNPCC patients and that age of diagnosis of CRC is not associated with MDM2 SNP309 or TP53 R72P either as single SNPs or combined.
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