Real-Time Individual Predictions of Prostate Cancer Recurrence Using Joint Models

Biometrics

Volumn 69, Issue 1, 2013, Pages 206-213

  Taylor, Jeremy M G ^a   Park, Yongseok ^a   Ankerst, Donna P ^b,c   Proust Lima, Cecile ^d   Williams, Scott ^e   Kestin, Larry ^f   Bae, Kyoungwha ^g   Pickles, Tom ^h   Sandler, Howard ⁱ  

^a UNIVERSITY OF MICHIGAN SCHOOL OF PUBLIC HEALTH   (United States)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c UNIVERSITY OF TEXAS HEALTH SCIENCE CENTER AT SAN ANTONIO   (United States)

^d INSERM   (France)

^e PETER MACCALLUM CANCER CENTRE   (Australia)

^f 21ST CENTURY ONCOLOGY   (United States)

^g NOVARTIS PHARMA AG   (Switzerland)

^h BRITISH COLUMBIA CANCER AGENCY   (Canada)

ⁱ CEDARS SINAI MEDICAL CENTER   (United States)

Author keywords

Joint longitudinal survival model; Online calculator; Predicted probability; Prostate cancer; PSA

Indexed keywords

ANTIGENS; BAYESIAN NETWORKS; MARKOV PROCESSES; MATHEMATICAL INSTRUMENTS; MONTE CARLO METHODS; RADIOTHERAPY; RISK ASSESSMENT; RISK PERCEPTION; UROLOGY;

INDIVIDUAL PREDICTION; JOINT LONGITUDINAL-SURVIVAL MODEL; ONLINE CALCULATOR; PREDICTED PROBABILITY; PROSTATE CANCER RECURRENCE; PROSTATE CANCERS; PROSTATE SPECIFIC ANTIGEN; REAL- TIME; SURVIVAL MODEL; TRAINING DATASET;

DISEASES;

CANCER; DATA SET; MARKOV CHAIN; MONTE CARLO ANALYSIS; PREDICTION; PROBABILITY; REAL TIME;

PROSTATE SPECIFIC ANTIGEN;

ALGORITHM; ARTICLE; BAYES THEOREM; BLOOD; HUMAN; MALE; MONTE CARLO METHOD; PATHOLOGY; PREDICTIVE VALUE; PROBABILITY; PROSTATE TUMOR; STATISTICAL MODEL; SURVIVAL; TUMOR RECURRENCE;

ALGORITHMS; BAYES THEOREM; HUMANS; MALE; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; NEOPLASM RECURRENCE, LOCAL; PREDICTIVE VALUE OF TESTS; PROSTATE-SPECIFIC ANTIGEN; PROSTATIC NEOPLASMS; SURVIVAL ANALYSIS;

EID: 84875937581     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2012.01823.x     Document Type: Article

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