Bayesian semi-parametric modeling for mixed proportional hazard models with right censoring

2006 ◽  
Vol 76 (7) ◽  
pp. 719-728 ◽  
Author(s):  
John W. Lau
Keyword(s):  
Parametric Modeling ◽  
Right Censoring ◽  
Hazard Models ◽  
Proportional Hazard ◽  
Proportional Hazard Models ◽  
Mixed Proportional Hazard Models

SEMI-NONPARAMETRIC INTERVAL-CENSORED MIXED PROPORTIONAL HAZARD MODELS: IDENTIFICATION AND CONSISTENCY RESULTS

2008 ◽  
Vol 24 (3) ◽  
pp. 749-794 ◽  
Author(s):  
Herman J. Bierens
Keyword(s):  
Legendre Polynomials ◽  
Unobserved Heterogeneity ◽  
Unit Interval ◽  
Hazard Models ◽  
Nonparametric Identification ◽  
Proportional Hazard ◽  
Proportional Hazard Models ◽  
Consistency Results ◽  
Interval Censored ◽  
Mixed Proportional Hazard Models

In this paper I propose estimating distributions on the unit interval semi-nonparametrically using orthonormal Legendre polynomials. This approach will be applied to the interval-censored mixed proportional hazard (ICMPH) model, where the distribution of the unobserved heterogeneity is modeled semi-nonparametrically. Various conditions for the nonparametric identification of the ICMPH model are derived. I will prove general consistency results for M-estimators of (partly) non-euclidean parameters under weak and easy-to-verify conditions and specialize these results to sieve estimators. Special attention is paid to the case where the support of the covariates is finite.

scholarly journals LAMB1 Is Related to the T Stage and Indicates Poor Prognosis in Gastric Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382110049
Author(s):  
Tao Ran ◽  
ZhiJi Chen ◽  
LiWen Zhao ◽  
Wei Ran ◽  
JinYu Fan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Poor Prognosis ◽  
Hazard Models ◽  
Proportional Hazard ◽  
Kegg Analysis ◽  
Proportional Hazard Models ◽  
Cox Proportional Hazard ◽  
Kaplan Meier ◽  
Cox Proportional Hazard Models ◽  
Gastric Cancer Patients

Background and Objective: Gastric cancer (GC) is a common tumor malignancy with high incidence and poor prognosis. Laminin is an indispensable component of basement membrane and extracellular matrix, which is responsible for bridging the internal and external environment of cells and transmitting signals. This study mainly explored the association of the LAMB1 expression with clinicopathological characteristics and prognosis in gastric cancer. Methods: The expression data and clinical information of gastric cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG). And we analyzed the relationship between LAMB1 expression and clinical characteristics through R. CIBERSORTx was used to calculate the absolute score of immune cells in gastric tumor tissues. Then COX proportional hazard models and Kaplan-Meier curves were performed to evaluate the role of LAMB1 and its influence on prognosis in gastric cancer patients. Finally, GO and KEGG analysis were applied for LAMB1-related genes in gastric cancer, and PPI network was constructed in Cytoscape software. Results: In the TCGA cohort, patients with gastric cancer frequently generated LAMB1 gene copy number variation, but had little effect on mRNA expression. Both in the TCGA and ACRG cohorts, the mRNA expression of LAMB1 in gastric cancer tissues was higher than it in normal tissues. All patients were divided into high expression group and low expression group according to the median expression level of LAMB1. The elevated expression group obviously had more advanced cases and higher infiltration levels of M2 macrophages. COX proportional hazard models and Kaplan-Meier curves revealed that patients with enhanced expression of LAMB1 have a worse prognosis. GO/KEGG analysis showed that LAMB1-related genes were enriched in PI3K-Akt signaling pathway, focal adhesion, ECM-receptor interaction, etc. Conclusions: The high expression of LAMB1 in gastric cancer is related to the poor prognosis of patients, and it may be related to microenvironmental changes in tumors.

scholarly journals Low rather than high mean corpuscular volume is associated with mortality in Japanese patients under hemodialysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hirokazu Honda ◽  
Miho Kimachi ◽  
Noriaki Kurita ◽  
Nobuhiko Joki ◽  
Masaomi Nangaku
Keyword(s):  
Mean Corpuscular Volume ◽  
Japanese Patients ◽  
Cubic Spline ◽  
Hazard Models ◽  
Proportional Hazard ◽  
Corpuscular Volume ◽  
Proportional Hazard Models ◽  
Cox Proportional Hazard ◽  
All Cause Mortality ◽  
Cox Proportional Hazard Models

Abstract Recent studies have reported that high mean corpuscular volume (MCV) might be associated with mortality in patients with advanced chronic kidney disease (CKD). However, the question of whether a high MCV confers a risk for mortality in Japanese patients remains unclear. We conducted a longitudinal analysis of a cohort of 8571 patients using data derived from the Japan Dialysis Outcomes and Practice Patterns Study (J-DOPPS) phases 1 to 5. Associations of all-cause mortality, vascular events, and hospitalization due to infection with baseline MCV were examined via Cox proportional hazard models. Non-linear relationships between MCV and these outcomes were examined using restricted cubic spline analyses. Associations between time-varying MCV and these outcomes were also examined as sensitivity analyses. Cox proportional hazard models showed a significant association of low MCV (< 90 fL), but not for high MCV (102 < fL), with a higher incidence of all-cause mortality and hospitalization due to infection compared with 94 ≤ MCV < 98 fL (reference). Cubic spline analysis indicated a graphically U-shaped association between baseline MCV and all-cause mortality (p for non-linearity p < 0.001). In conclusion, a low rather than high MCV might be associated with increased risk for all-cause mortality and hospitalization due to infection among Japanese patients on hemodialysis.

scholarly journals Performance of two formal tests based on martingales residuals to check the proportional hazard assumption and the functional form of the prognostic factors in flexible parametric excess hazard models

Biostatistics ◽  
2017 ◽  
Vol 18 (3) ◽  
pp. 505-520
Author(s):  
Coraline Danieli ◽  
Nadine Bossard ◽  
Laurent Roche ◽  
Aurelien Belot ◽  
Zoe Uhry ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Analysis ◽  
Functional Form ◽  
Cancer Registries ◽  
Parametric Modeling ◽  
Diagnostic Tools ◽  
Hazard Models ◽  
Proportional Hazard ◽  
Proportional Hazard Assumption ◽  
Net Survival

Summary Net survival, the one that would be observed if the disease under study was the only cause of death, is an important, useful, and increasingly used indicator in public health, especially in population-based studies. Estimates of net survival and effects of prognostic factor can be obtained by excess hazard regression modeling. Whereas various diagnostic tools were developed for overall survival analysis, few methods are available to check the assumptions of excess hazard models. We propose here two formal tests to check the proportional hazard assumption and the validity of the functional form of the covariate effects in the context of flexible parametric excess hazard modeling. These tests were adapted from martingale residual-based tests for parametric modeling of overall survival to allow adding to the model a necessary element for net survival analysis: the population mortality hazard. We studied the size and the power of these tests through an extensive simulation study based on complex but realistic data. The new tests showed sizes close to the nominal values and satisfactory powers. The power of the proportionality test was similar or greater than that of other tests already available in the field of net survival. We illustrate the use of these tests with real data from French cancer registries.

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