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Comparison between parametric and semi-parametric cox models in modeling transition rates of a multi-state model: application in patients with gastric cancer undergoing surgery at the Iran cancer institute.
- Source :
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Asian Pacific journal of cancer prevention : APJCP [Asian Pac J Cancer Prev] 2014 Jan; Vol. 14 (11), pp. 6751-5. - Publication Year :
- 2014
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Abstract
- Background: Research on cancers with a high rate of mortality such as those occurring in the stomach requires using models which can provide a closer examination of disease processes and provide researchers with more accurate data. Various models have been designed based on this issue and the present study aimed at evaluating such models.<br />Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. Cox-Snell Residuals and Akaike Information Criterion were used to compare parametric and semi-parametric Cox models in modeling transition rates among different states of a multi-state model. R 2.15.1 software was used for all data analyses.<br />Results: Analysis of Cox-Snell Residuals and Akaike Information Criterion for all probable transitions among different states revealed that parametric models represented a better fitness. Log-logistic, Gompertz and Log-normal models were good choices for modeling transition rate for relapse hazard (state 1?state 2), death hazard without a relapse (state 1?state 3) and death hazard with a relapse (state 2?state 3), respectively.<br />Conclusions: Although the semi-parametric Cox model is often used by most cancer researchers in modeling transition rates of multi- state models, parametric models in similar situations- as they do not need proportional hazards assumption and consider a specific statistical distribution for time to occurrence of next state in case this assumption is not made - are more credible alternatives.
Details
- Language :
- English
- ISSN :
- 2476-762X
- Volume :
- 14
- Issue :
- 11
- Database :
- MEDLINE
- Journal :
- Asian Pacific journal of cancer prevention : APJCP
- Publication Type :
- Academic Journal
- Accession number :
- 24377600
- Full Text :
- https://doi.org/10.7314/apjcp.2013.14.11.6751