Browsing by Subject "Survival Analysis"

Now showing 1 - 3 of 3
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    Regulation of Stat5 by FAK and PAK1 in Oncogenic FLT3 and KIT driven Leukemogenesis
    (Elsevier B.V., 2014-11-20) Chatterjee, Anindya; Ghosh, Joydeep; Ramdas, Baskar; Mali, Raghuveer Singh; Martin, Holly; Kobayashi, Michihiro; Vemula, Sasidhar; Canela, Victor H.; Waskow, Emily R.; Visconte, Valeria; Tiu, Ramon V.; Smith, Catherine C.; Shah, Neil; Bunting, Kevin D.; Boswell, H. Scott; Liu, Yan; Chan, Rebecca J.; Kapur, Reuben; Department of Pediatrics, IU School of Medicine
    Oncogenic mutations of FLT3 and KIT receptors are associated with poor survival in patients with acute myeloid leukemia (AML) and myeloproliferative neoplasms (MPN) and currently available drugs are largely ineffective. Although Stat5 has been implicated in regulating several myeloid and lymphoid malignancies, how precisely Stat5 regulates leukemogenesis, including its nuclear translocation to induce gene transcription is poorly understood. In leukemic cells, we show constitutive activation of focal adhesion kinase (FAK), whose inhibition represses leukemogenesis. Downstream of FAK, activation of Rac1 is regulated by RacGEF Tiam1, whose inhibition prolongs the survival of leukemic mice. Inhibition of the Rac1 effector PAK1 prolongs the survival of leukemic mice in part by inhibiting the nuclear translocation of Stat5. These results reveal a leukemic pathway involving FAK/Tiam1/Rac1/PAK1 and demonstrate an essential role for these signaling molecules in regulating the nuclear translocation of Stat5 in leukemogenesis.
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    Simultaneous variable selection for joint models of longitudinal and survival outcomes
    (Wiley Blackwell (Blackwell Publishing), 2015-03) He, Zangdong; Tu, Wanzhu; Wang, Sijian; Fu, Haoda; Yu, Zhangsheng; Department of Biostatistics, Richard M. Fairbanks School of Public Health
    Joint models of longitudinal and survival outcomes have been used with increasing frequency in clinical investigations. Correct specification of fixed and random effects is essential for practical data analysis. Simultaneous selection of variables in both longitudinal and survival components functions as a necessary safeguard against model misspecification. However, variable selection in such models has not been studied. No existing computational tools, to the best of our knowledge, have been made available to practitioners. In this article, we describe a penalized likelihood method with adaptive least absolute shrinkage and selection operator (ALASSO) penalty functions for simultaneous selection of fixed and random effects in joint models. To perform selection in variance components of random effects, we reparameterize the variance components using a Cholesky decomposition; in doing so, a penalty function of group shrinkage is introduced. To reduce the estimation bias resulted from penalization, we propose a two-stage selection procedure in which the magnitude of the bias is ameliorated in the second stage. The penalized likelihood is approximated by Gaussian quadrature and optimized by an EM algorithm. Simulation study showed excellent selection results in the first stage and small estimation biases in the second stage. To illustrate, we analyzed a longitudinally observed clinical marker and patient survival in a cohort of patients with heart failure.
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    Survival Analysis for the Association between Anti-hypertensive Medication and Time to Dementia with Competing Risk
    (2019-06) Hu, Xinhua Flora; Gao, Sujuan; Zhang, Ying; Katz, Barry P.
    Background: High blood pressure (HBP) is a common risk factor for dementia in elder population. Anti-hypertensive medications have been reported to associate with lower incidence rate of dementia in elder African Americans. The Apolipoprotein E (ApoE) epsilon 4 allele has been shown to be associated with both increased dementia and hypertension risk. However, previous studies had not examined the association between anti-hypertensive medications by ApoE status accounting for the competing risk from death. Methods: This is a prospective observational cohort study in 1236 community-dwelling hypertensive African Americans aged 65 years and older without dementia at baseline, with follow-up cognitive assessment and clinical evaluation for dementia diagnosis. Dementia-free mortality was considered as the competing risk. Of these, 707 participants were genotyped for ApoE status. Anti-hypertensive medication use was obtained from prescription records in the electronic medical records of the Indiana Network for Patient Care (INPC). Cox proportional cause-specific hazard (CSH) regression models were applied to assess the association between anti-hypertensive medication use and CSHs for dementia and death in ApoE epsilon 4 carriers and non-carriers separately. Key results: In ApoE epsilon 4 carriers, participants using anti-hypertensive medications had lower CSH of dementia compared to those not on anti-hypertensive medications before adjusting for blood pressure (BP) (hazard ratio (HR), 0.365; 95% CI, 0.170 – 0.785; p = 0.0099). The HR was no longer significant once BP control was adjusted (HR, 0.784; 95% CI, 0.197 – 3.123; p = 0.7303). Anti-hypertensive medications were not associated with dementia rate in non-carriers. In ApoE epsilon 4 non-carriers, participants on anti-hypertensive treatment showed significantly lower CSH of death compared to those not on mediations adjusting for covariates and BP control (HR, 0.237; 95% CI, 0.149 – 0.375; p < 0.0001). There was no significant association between anti-hypertensive medication use and death in ApoE epsilon 4 carriers. Conclusions: Anti-hypertensive medication was associated with lower dementia rate in ApoE epsilon 4 carriers and that rate was primarily mediated through BP control. In non-carriers, anti-hypertensive medication was significantly associated with lower mortality rate and this association appears to be independent of BP control.