Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network

Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

doi:10.7150/jca.33945

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J Cancer 2019; 10(18):4189-4195. doi:10.7150/jca.33945 This issue Cite

Research Paper

Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network

Bogdan Obrzut^1,2, Maciej Kusy³, Andrzej Semczuk^4✉, Marzanna Obrzut¹, Jacek Kluska³

1. Medical Faculty, University of Rzeszow, Rejtana str. 16C, 35-959 Rzeszow, Poland
2. Department of Obstetrics and Gynecology, Provincial Clinical Hospital No. 2, Lwowska str. 60, 35-301 Rzeszow, Poland
3. Faculty of Electrical and Computer Engineering, Rzeszow University of Technology, Powstanców Warszawy avenue 12, 35-959 Rzeszow, Poland
4. II ND Department of Gynecology, Lublin Medical University, Jaczewski str. 8, 20-954, Lublin, Poland

Citation:

Obrzut B, Kusy M, Semczuk A, Obrzut M, Kluska J. Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network. J Cancer 2019; 10(18):4189-4195. doi:10.7150/jca.33945. https://www.jcancer.org/v10p4189.htm

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Abstract

Background: Toward the goal of predicting individual long-term cancer survival to guide treatment decisions, this study evaluated the ability of a probabilistic neural network (PNN), an established model used for decision-making in research and clinical settings, to predict the 10-year overall survival in patients with cervical cancer who underwent primary surgical treatment.

Patients and Method: The input dataset was derived from 102 patients with cervical cancer FIGO stage IA2-IIB treated by radical hysterectomy. We identified 4 demographic parameters, 13 tumor-related parameters, and 6 selected perioperative variables for each patient and performed computer simulations with DTREG software. The predictive ability of the model was determined on the basis of its error, sensitivity, and specificity, as well as area under the receiver operating characteristic curve. The results of the PNN predictive model were compared with those of logistic regression analysis and a single decision tree as reference models.

Results: The PNN model had very high predictive ability, with a sensitivity of 0.949, a specificity of 0.679, and an error rate of 12.5%. The PNN's area under the receiver operating characteristic curve was high, 0.809, a value greater than those for both logistic regression analysis and the single decision tree.

Conclusion: The PNN model effectively and reliably predicted 10-year overall survival in women with operable cervical cancer, and may therefore serve as a tool for decision-making process in cancer treatment.

Keywords: cervical cancer, 10-year overall survival, probabilistic neural network, survival prediction

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APA

Obrzut, B., Kusy, M., Semczuk, A., Obrzut, M., Kluska, J. (2019). Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network. Journal of Cancer, 10(18), 4189-4195. https://doi.org/10.7150/jca.33945.

ACS

Obrzut, B.; Kusy, M.; Semczuk, A.; Obrzut, M.; Kluska, J. Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network. J. Cancer 2019, 10 (18), 4189-4195. DOI: 10.7150/jca.33945.

NLM

CSE

Obrzut B, Kusy M, Semczuk A, Obrzut M, Kluska J. 2019. Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network. J Cancer. 10(18):4189-4195.

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