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Artificial Neural Network to Predict Skeletal Metastasis in Patients with Prostate Cancer

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Abstract

The application of an artificial neural network (ANN) in prediction of outcomes using clinical data is being increasingly used. The aim of this study was to assess whether an ANN model is a useful tool for predicting skeletal metastasis in patients with prostate cancer. Consecutive patients with prostate cancer who underwent the technetium-99m methylene diphosphate (Tc-99m MDP) whole body bone scintigraphies were retrospectively analyzed between 2001 and 2005. The predictors were the patient’s age and radioimmunometric serum PSA concentration. The outcome variable was dichotomous, either skeletal metastasis or non-skeletal metastasis, based on the results of Tc-99m MDP whole body bone scintigraphy. To assess the performance for classification model in clinical study, the discrimination and calibration of an ANN model was calculated. The enrolled subjects consisted of 111 consecutive male patients aged 72.41 ± 7.69 years with prostate cancer. Sixty-seven patients (60.4%) had skeletal metastasis based on the scintigraphic diagnosis. The final best architecture of neural network model was four-layered perceptrons. The area under the receiver-operating characteristics curve (0.88 ± 0.07) revealed excellent discriminatory power (p < 0.001) with the best simultaneous sensitivity (87.5%) and specificity (83.3%). The Hosmer–Lemeshow statistic was 6.74 (p = 0.08 > 0.05), which represented a good-fit calibration. These results suggest that an ANN, which is based on limited clinical parameters, appears to be a promising method in forecasting of the skeletal metastasis in patients with prostate cancer.

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Acknowledgement

This paper is in memorial of Mr. A-Tsai Lee, Dr. Jainn-Shiun Chiu’s maternal grandfather, who died from prostate cancer with skeletal metastasis on 20 October 2006.

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Authors and Affiliations

  1. Department of Nuclear Medicine, Buddhist Dalin Tzu Chi General Hospital, Chiayi, Taiwan

    Jainn-Shiun Chiu, Yuh-Feng Wang, Ling-Huei Wei & Jian-Guo Liao

  2. Division of Hematology and Oncology, Department of Internal Medicine, Buddhist Dalin Tzu Chi General Hospital, Chiayi, Taiwan

    Yu-Cheih Su

  3. Institute of Biomedical Informatics, National Yang Ming University, No. 155, Sec. 2, Linong St., Beitou District, Taipei City, 112, Taiwan

    Yu-Chuan Li

  4. Department of Medicine, College of Medicine, Tzu Chi University, Hualien, Taiwan

    Jainn-Shiun Chiu, Yuh-Feng Wang & Yu-Cheih Su

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  1. Jainn-Shiun Chiu
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Correspondence to Yu-Chuan Li.

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Chiu, JS., Wang, YF., Su, YC. et al. Artificial Neural Network to Predict Skeletal Metastasis in Patients with Prostate Cancer. J Med Syst 33, 91–100 (2009). https://doi.org/10.1007/s10916-008-9168-2

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  • DOI: https://doi.org/10.1007/s10916-008-9168-2

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