Real‐Time Individual Predictions of Prostate Cancer Recurrence Using Joint Models
暂无分享,去创建一个
Yongseok Park | Donna P Ankerst | Tom Pickles | Jeremy M G Taylor | J. M. Taylor | D. Ankerst | L. Kestin | H. Sandler | T. Pickles | C. Proust-Lima | Howard Sandler | Scott Williams | Larry Kestin | Cecile Proust-Lima | Kyoungwha Bae | K. Bae | S. Williams | Yongseok Park
[1] Menggang Yu,et al. Individual Prediction in Prostate Cancer Studies Using a Joint Longitudinal Survival–Cure Model , 2008 .
[2] Paul Schellhammer,et al. Defining biochemical failure following radiotherapy with or without hormonal therapy in men with clinically localized prostate cancer: recommendations of the RTOG-ASTRO Phoenix Consensus Conference. , 2006, International journal of radiation oncology, biology, physics.
[3] Cécile Proust-Lima,et al. Determinants of change in prostate-specific antigen over time and its association with recurrence after external beam radiation therapy for prostate cancer in five large cohorts. , 2008, International journal of radiation oncology, biology, physics.
[4] Yan Wang,et al. Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome , 2001 .
[5] D. Ankerst,et al. Clinical monitoring based on joint models for longitudinal biomarkers and event times , 2006 .
[6] Douglas E Schaubel,et al. The effect of salvage therapy on survival in a longitudinal study with treatment by indication , 2010, Statistics in medicine.
[7] S. Zeger,et al. Joint analysis of longitudinal data comprising repeated measures and times to events , 2001 .
[8] Jeremy MG Taylor,et al. Validation of Biomarker-Based Risk Prediction Models , 2008, Clinical Cancer Research.
[9] R Henderson,et al. Joint modelling of longitudinal measurements and event time data. , 2000, Biostatistics.
[10] C. McCulloch,et al. Latent Class Models for Joint Analysis of Longitudinal Biomarker and Event Process Data , 2002 .
[11] Menggang Yu,et al. Individualized Predictions of Disease Progression Following Radiation Therapy for Prostate Cancer , 2005 .
[12] Scott Tyldesley,et al. Evaluation of the Houston biochemical relapse definition in men treated with prolonged neoadjuvant and adjuvant androgen ablation and assessment of follow-up lead-time bias. , 2003, International journal of radiation oncology, biology, physics.
[13] Cécile Proust-Lima,et al. Joint latent class models for longitudinal and time-to-event data: A review , 2014, Statistical methods in medical research.
[14] Menggang Yu,et al. JOINT LONGITUDINAL-SURVIVAL-CURE MODELS AND THEIR APPLICATION TO PROSTATE CANCER , 2004 .
[15] N. Obuchowski,et al. Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures , 2010, Epidemiology.
[16] Cécile Proust-Lima,et al. Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach. , 2009, Biostatistics.
[17] Dimitris Rizopoulos,et al. Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time‐to‐Event Data , 2011, Biometrics.