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Articles 1 - 3 of 3
Full-Text Articles in Medicine and Health Sciences
Nonparametric And Semiparametric Inference For Models Of Tumor Size And Metastasis, Debashis Ghosh
Nonparametric And Semiparametric Inference For Models Of Tumor Size And Metastasis, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
There has been some recent work in the statistical literature for modelling the relationship between the size of primary cancers and the occurrences of metastases. While nonparametric methods have been proposed for estimation of the tumor size distribution at which metastatic transition occurs, their asymptotic properties have not been studied. In addition, no testing or regression methods are available so that potential confounders and prognostic factors can be adjusted for. We develop a unified approach to nonparametric and semiparametric analysis of modelling tumor size-metastasis data in this article. An equivalence between the models considered by previous authors with survival data …
Individualized Predictions Of Disease Progression Following Radiation Therapy For Prostate Cancer., Jeremy Taylor, Menggang Yu, Howard M. Sandler
Individualized Predictions Of Disease Progression Following Radiation Therapy For Prostate Cancer., Jeremy Taylor, Menggang Yu, Howard M. Sandler
The University of Michigan Department of Biostatistics Working Paper Series
Background: Following treatment for localized prostate cancer, men are monitored with serial PSA measurements. Refining the predictive value of post-treatment PSA determinations may add to clinical management and we have developed a model that predicts for an individual patient future PSA values and estimates the time to future clinical recurrence.
Methods: Data from 934 patients treated for prostate cancer between 1987 and 2000 were used to develop a comprehensive statistical model to fit the clinical recurrence events and pattern of PSA data. A logistic regression model was used for the probability of cure, non-linear hierarchical mixed models were used for …
Individual Prediction In Prostate Cancer Studies Using A Joint Longitudinal-Survival-Cure Model, Menggang Yu, Jeremy Taylor, Howard M. Sandler
Individual Prediction In Prostate Cancer Studies Using A Joint Longitudinal-Survival-Cure Model, Menggang Yu, Jeremy Taylor, Howard M. Sandler
The University of Michigan Department of Biostatistics Working Paper Series
For monitoring patients treated for prostate cancer, Prostate Specific Antigen (PSA) is measured periodically after they receive treatment. Increases in PSA are suggestive of recurrence of the cancer and are used in making decisions about possible new treatments. The data from studies of such patients typically consist of longitudinal PSA measurements, censored event times and baseline covariates. Methods for the combined analysis of both longitudinal and survival data have been developed in recent years, with the main emphasis being on modeling and estimation. We analyze data from a prostate cancer study that has been extended by adding a mixture structure …