應用類神經網路預測鼻咽癌病人之五年存活狀態

Translated title of the contribution: Clinical Application of Artificial Neural Network in Predicting Five-Year Survival of Patients with Nasopharyngeal Carcinoma

Chong-Hao Cheng, Skye Hon-Giun Cheng, Hung-Wen Chiu

Research output: Contribution to journalArticle

Abstract

Purpose: This study wants to establish a prognostic prediction system by artificial neural network for individual patients with nasopharyngeal carcinoma.Materials and methods: In this study, the dataset are 1,114 patients with nasopharyngeal carcinoma in one cancer center during the year from 1990 to 2005. The chosen variables include age, sex, primary tumor, regional lymph nodes, biopsy, radiotherapy, chemotherapy, lactic dehydrogenase, alkaline phosphatase, smoking, and family history. The final dataset are 984 patients excluding 70 patients with any data columns missing and 60 patients with distant metastasis. Seventy-five percent of 984 patients are randomly selected and classified to training group. An artificial neural network is created by computer software to predict the five-year survival status of patients with nasopharyngeal carcinoma. The performance of prediction models will be evaluated according to parameters such as accuracy, sensitivity, specificity, and the area under receiver operating characteristic curve.Result: The average age of the patients is 45.45 years old, and the five-year overall survival rate is 77.74%. The optimized artificial neural network is MLP 34-5-2 which training performance is 92.00 and test performance is 87.80. Its accuracy is 90.96%, sensitivity is 93.73%, specificity is 81.27%, and area under the ROC curve is 0.95 for all patients. Its accuracy is 87.80%, sensitivity is 92.23%, specificity is 71.70%, and area under the ROC curve is 0.88 for test group.Conclusion: This study shows that the prognostic prediction system established by artificial neural network has the potential to predict the five-year survival status of individual patients with nasopharyngeal carcinoma. With more input data, the performance of prediction models is better than previous researches. But this prognostic prediction system still need further study to prove it could be used for clinical patients.
Original languageTraditional Chinese
Pages (from-to)191-197
Number of pages7
Journal放射治療與腫瘤學
Volume20
Issue number3
Publication statusPublished - 2013

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Survival
ROC Curve
Area Under Curve
Nasopharyngeal carcinoma
Alkaline Phosphatase
Neoplasms
Oxidoreductases
Milk
Radiotherapy
Software
Survival Rate
Lymph Nodes
Smoking
Neoplasm Metastasis
Biopsy
Drug Therapy
Sensitivity and Specificity
Research

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應用類神經網路預測鼻咽癌病人之五年存活狀態. / Cheng, Chong-Hao ; Cheng, Skye Hon-Giun ; Chiu, Hung-Wen.

In: 放射治療與腫瘤學, Vol. 20, No. 3, 2013, p. 191-197.

Research output: Contribution to journalArticle

Cheng, Chong-Hao ; Cheng, Skye Hon-Giun ; Chiu, Hung-Wen. / 應用類神經網路預測鼻咽癌病人之五年存活狀態. In: 放射治療與腫瘤學. 2013 ; Vol. 20, No. 3. pp. 191-197.
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title = "應用類神經網路預測鼻咽癌病人之五年存活狀態",
abstract = "目的:應用類神經網路建立鼻咽癌病人預後預測系統,提供個人化的存活狀況預測資訊。材料與方法:本研究篩選1990年至2005年間臺灣地區某癌症專科醫院臨床研究室資料庫的1,114位鼻咽癌病人,選用年齡、性別、腫瘤期別、原始腫瘤侵犯程度、淋巴結擴散狀態、病理細胞切片、放射治療方式、化學治療方式、乳酸脫氫脢指數、鹼性磷酸脢指數、過往吸菸習慣、 家族癌症病史等十二項變數,剔除變數資料欄位不全者70人以及60位遠端轉移者後,將整體樣本984人隨機挑選75{\%}為訓練樣本,建立類神經網路模型預測鼻咽癌病人五年存活狀態,並對25{\%}測試樣本的預測準確率、靈敏度、特異度和ROC曲線下面積進行評估及分析。結果:整體樣本平均年齡為45.45歲,五年整體存活率為77.74{\%},利用STATISTICA軟體使用多層次類神經網路方式建立起最佳化的預測模型為MLP 34-5-2,其訓練效能為92.00,測試效能為87.80。與原始病人存活狀態資料進行比對分析,整體樣本中對於個別病人的存活狀態預測準確率為90.96{\%},靈敏度和特異度分別為93.73{\%}及81.28{\%},ROC曲線下面積為0.95,如果單以測試組樣本來看,其預測準確率為87.80{\%},靈敏度和特異度分別為92.23{\%}及71.70{\%},ROC曲線下面積為0.88。結論:本研究運用類神經網路提供了一種預測個別鼻咽癌病人預後的方法,使用各項統計指標評估該類神經網路預測模型效能,顯示選用更多輸入變數資料的類神經網路,在預測個別鼻咽癌病人五年存活狀態的表現較先前研究為佳,但此方法是否適用於實際臨床病人仍有待進一步的評估與研究。",
keywords = "存活預測, 鼻咽癌, 類神經網路, Artificial neural networks, Nasopharyngeal carcinoma, Survival prediction",
author = "Chong-Hao Cheng and Cheng, {Skye Hon-Giun} and Hung-Wen Chiu",
year = "2013",
language = "繁體中文",
volume = "20",
pages = "191--197",
journal = "放射治療與腫瘤學",
issn = "1023-988x",
publisher = "台灣放射腫瘤學會",
number = "3",

}

TY - JOUR

T1 - 應用類神經網路預測鼻咽癌病人之五年存活狀態

AU - Cheng, Chong-Hao

AU - Cheng, Skye Hon-Giun

AU - Chiu, Hung-Wen

PY - 2013

Y1 - 2013

N2 - 目的:應用類神經網路建立鼻咽癌病人預後預測系統,提供個人化的存活狀況預測資訊。材料與方法:本研究篩選1990年至2005年間臺灣地區某癌症專科醫院臨床研究室資料庫的1,114位鼻咽癌病人,選用年齡、性別、腫瘤期別、原始腫瘤侵犯程度、淋巴結擴散狀態、病理細胞切片、放射治療方式、化學治療方式、乳酸脫氫脢指數、鹼性磷酸脢指數、過往吸菸習慣、 家族癌症病史等十二項變數,剔除變數資料欄位不全者70人以及60位遠端轉移者後,將整體樣本984人隨機挑選75%為訓練樣本,建立類神經網路模型預測鼻咽癌病人五年存活狀態,並對25%測試樣本的預測準確率、靈敏度、特異度和ROC曲線下面積進行評估及分析。結果:整體樣本平均年齡為45.45歲,五年整體存活率為77.74%,利用STATISTICA軟體使用多層次類神經網路方式建立起最佳化的預測模型為MLP 34-5-2,其訓練效能為92.00,測試效能為87.80。與原始病人存活狀態資料進行比對分析,整體樣本中對於個別病人的存活狀態預測準確率為90.96%,靈敏度和特異度分別為93.73%及81.28%,ROC曲線下面積為0.95,如果單以測試組樣本來看,其預測準確率為87.80%,靈敏度和特異度分別為92.23%及71.70%,ROC曲線下面積為0.88。結論:本研究運用類神經網路提供了一種預測個別鼻咽癌病人預後的方法,使用各項統計指標評估該類神經網路預測模型效能,顯示選用更多輸入變數資料的類神經網路,在預測個別鼻咽癌病人五年存活狀態的表現較先前研究為佳,但此方法是否適用於實際臨床病人仍有待進一步的評估與研究。

AB - 目的:應用類神經網路建立鼻咽癌病人預後預測系統,提供個人化的存活狀況預測資訊。材料與方法:本研究篩選1990年至2005年間臺灣地區某癌症專科醫院臨床研究室資料庫的1,114位鼻咽癌病人,選用年齡、性別、腫瘤期別、原始腫瘤侵犯程度、淋巴結擴散狀態、病理細胞切片、放射治療方式、化學治療方式、乳酸脫氫脢指數、鹼性磷酸脢指數、過往吸菸習慣、 家族癌症病史等十二項變數,剔除變數資料欄位不全者70人以及60位遠端轉移者後,將整體樣本984人隨機挑選75%為訓練樣本,建立類神經網路模型預測鼻咽癌病人五年存活狀態,並對25%測試樣本的預測準確率、靈敏度、特異度和ROC曲線下面積進行評估及分析。結果:整體樣本平均年齡為45.45歲,五年整體存活率為77.74%,利用STATISTICA軟體使用多層次類神經網路方式建立起最佳化的預測模型為MLP 34-5-2,其訓練效能為92.00,測試效能為87.80。與原始病人存活狀態資料進行比對分析,整體樣本中對於個別病人的存活狀態預測準確率為90.96%,靈敏度和特異度分別為93.73%及81.28%,ROC曲線下面積為0.95,如果單以測試組樣本來看,其預測準確率為87.80%,靈敏度和特異度分別為92.23%及71.70%,ROC曲線下面積為0.88。結論:本研究運用類神經網路提供了一種預測個別鼻咽癌病人預後的方法,使用各項統計指標評估該類神經網路預測模型效能,顯示選用更多輸入變數資料的類神經網路,在預測個別鼻咽癌病人五年存活狀態的表現較先前研究為佳,但此方法是否適用於實際臨床病人仍有待進一步的評估與研究。

KW - 存活預測

KW - 鼻咽癌

KW - 類神經網路

KW - Artificial neural networks

KW - Nasopharyngeal carcinoma

KW - Survival prediction

M3 - 文章

VL - 20

SP - 191

EP - 197

JO - 放射治療與腫瘤學

JF - 放射治療與腫瘤學

SN - 1023-988x

IS - 3

ER -