Browsing by Author "Huang, Chiung-Yu"

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    Recurrent Event Data Analysis With Intermittently Observed Time-Varying Covariates
    (Wiley, 2016-08-15) Li, Shanshan; Sun, Yifei; Huang, Chiung-Yu; Follmann, Dean A.; Krause, Richard; Biostatistics, School of Public Health
    Although recurrent event data analysis is a rapidly evolving area of research, rigorous studies on estimation of the effects of intermittently observed time-varying covariates on the risk of recurrent events have been lacking. Existing methods for analyzing recurrent event data usually require that the covariate processes are observed throughout the entire follow-up period. However, covariates are often observed periodically rather than continuously. We propose a novel semiparametric estimator for the regression parameters in the popular proportional rate model. The proposed estimator is based on an estimated score function where we kernel smooth the mean covariate process. We show that the proposed semiparametric estimator is asymptotically unbiased, normally distributed and derive the asymptotic variance. Simulation studies are conducted to compare the performance of the proposed estimator and the simple methods carrying forward the last covariates. The different methods are applied to an observational study designed to assess the effect of Group A streptococcus (GAS) on pharyngitis among school children in India.
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    Updated Results of TBCRC026: Phase II Trial Correlating Standardized Uptake Value With Pathological Complete Response to Pertuzumab and Trastuzumab in Breast Cancer
    (American Society of Clinical Oncology, 2021) Connolly, Roisin M.; Leal, Jeffrey P.; Solnes, Lilja; Huang, Chiung-Yu; Carpenter, Ashley; Gaffney, Katy; Abramson, Vandana; Carey, Lisa A.; Liu, Minetta C.; Rimawi, Mothaffar; Specht, Jennifer; Storniolo, Anna Maria; Valero, Vicente; Vaklavas, Christos; Krop, Ian E.; Winer, Eric P.; Camp, Melissa; Miller, Robert S.; Wolff, Antonio C.; Cimino-Mathews, Ashley; Park, Ben H.; Wahl, Richard L.; Stearns, Vered; Medicine, School of Medicine
    Purpose: Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake value corrected for lean body mass (SULmax) on 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) would predict pathologic complete response (pCR) to pertuzumab and trastuzumab (PT). Patients and methods: Patients with stage II or III, estrogen receptor-negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percent change in SULmax by C1D15 predicting pCR is ≤ 0.65, with a one-sided type I error rate of 10%. Results: Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 22%. Receiver operator characteristic analysis of percent change in SULmax by C1D15 yielded an area under the curve of 0.72 (80% CI, 0.64 to 0.80; one-sided P = .12), which did not reject the null hypothesis. However, between patients who obtained pCR and who did not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 41.8%; P = .004) and SULmax reduction ≥ 40% was more prevalent (83% v 52%; P = .03; positive predictive value, 31%). Participants not obtaining a 40% reduction in SULmax by C1D15 were unlikely to obtain pCR (negative predictive value, 91%). Conclusion: Although the primary objective was not met, early changes in SULmax predict response to PT in estrogen receptor-negative and HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate tailoring of therapy in this setting.