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研究生:許秀卿
研究生(外文):Hsiu-Ching Hsu
論文名稱:貝氏分析應用於生化指標在胃癌及癌前病變之早期偵測
論文名稱(外文):Biological Measures for Early Detection of Pre-invasive and Invasive Carcinoma of Gastrium: A Bayesian Approach
指導教授:陳秀熙陳秀熙引用關係
指導教授(外文):Hsiu-Hsi Chen
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:預防醫學研究所
學門:醫藥衛生學門
學類:醫學學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:134
中文關鍵詞:蒙地卡羅馬可夫鏈貝氏分析生化指標胃癌
外文關鍵詞:biological measuresMonte Carlo Markov ChainBayesian modelgastric cancer
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前言:最近部分研究以血清生化指標使用於胃癌篩檢,但是生化指標的切點在各個研究並無定論,尤其並沒有將年齡以及平衡偽陰性與偽陽性所決定的風險值列入考慮。

目的:以貝氏分析應用於胃癌及腸型化生之個別風險評估。

方法:將相關的生化指標以對數及平方根轉換使之符合常態分佈。透過貝氏方法進行單變項及雙變項分析。研究資料來自於馬祖地區所進行的胃癌及癌前病變社區篩檢,運用蒙地卡羅馬可夫鏈估計後驗風險比值及95%信賴區間。

結果:除了年齡因素,胃蛋白脢原I為診斷胃癌最重要的指標,其次為癌胚抗原,兩者具有邊緣統計上相關。在腸型化生以幽門螺旋桿菌感染分層,胃蛋白脢原I及胃蛋白脢原I/II比率為統計上顯著相關的因子。將上述因子進行單變項及雙變項分析,計算後驗風險比。再以預先訂定的風險值及效用比,求得適當的切點以及相對的敏感度及特異度。
結論:由方法學的角度而言,我們以貝氏分析模式進行個別胃癌及腸型化生的預測。由胃癌及癌前病變的篩檢角度而言,再以生化指標作為篩檢工具,對於切點的選擇本研究對於政策的擬定有很大幫助。
Background: The recently proposed serum marker for gastric cancer screening has been criticized by lacking of appropriate cutoff point determined by age and predetermined risk level related to the trade-off between false negative cases and false positive cases.

Objective: A Bayesian model was proposed to estimate individual risk for gastric cancer or intestinal metaplasia.

Methods: Univariate and bivariate analysis using Bayesian approach were developed assuming normal distributions after log or square transformation of relevant serum markers. This model was applied to data from community-based screening for gastric cancer or its precursor in Matzu. Monte Carlo Markov Chain (MCMC) simulation was applied to estimate posterior odds ratios and 95% confidence interval.

Results: In addition to age, PG I was selected the most important marker for ascertaining cancer and CEA was of borderline statistical significance. Similarly, PGI and PGI /PG II ratio were two significant factors for predicting IM after the stratification of the presence of HP infection. Posterior odds were all calculated for univariate and bivariate analysis. The selected cutoff points in relation to sensitivity and specificity given predetermined risk level and utility ratio were demonstrated.

Conclusions: From the methodological viewpoint, we developed a Bayesian model for individual risk prediction for gastric cancer or intestinal metaplasia. From the aspect of screening for gastric cancer or precursor, this approach plays an important role in mass screening for gastric cancer or its precursor with serum marker.
1 Introduction 1
1.1 Criticism on biological markers of screening for gastric cancer 1
1.2 Mass screening for gastric cancer and precursor with serum markers in Matzu 2

2 Literature Review 5
2.1 The role of H. pylori infection 5
2.2 Serum pepsinogen as a marker for gastric cancer and precancerous lesion 8

3. Material and Method 15
3.1 Study Subjects 15
3.2 Model Specification with Bayesian approach 16
3.2.1 Univariate analysis 16
3.2.2 Bivariate analysis 18
3.2.3 Marginal analysis 20
3.3 Optimal cutoff point by utility ratio 20
3.4 Bayesian inference with Markov Chain Monte Carlo (MCMC) simulation 22
3.4.1 Directed graphic model 23
3.4.2 Markov Chain Monte Carlo (MCMC) techniques 25
3.4.3 Gibbs Sampler 26

4. Results 29
4.1 Basic Findings 29
4.2 Risk prediction with PG I (Univariate analysis) 31
4.2.1 Gastric Cancer 31
4.2.2 Intestinal Metaplasia (IM) 32
4.3 Risk Prediction with PG I and CEA (Bivariate Analysis) 32
4.3.1 Gastric Cancer 32
4.3.2 Intestinal Metaplasia (IM) 33
4.4 The determination of optimal cutoff point 34

5. Discuss 37

Reference 41

Appendix 133



Figure List

Figure 2.1 Multi-scale model for gastric carcinogenesis 45
Figure 3.1 Flow chart of two-stage screening for gastric cancer 46
Figure 4.1.1 The distribution of age of cancer and non-cancer 47
Figure 4.1.2 The distribution of PGI of cancer and non-cancer 47
Figure 4.1.3 The distribution of PGII of cancer and non-cancer 48
Figure 4.1.4 The distribution of PGI /PGII ratio of cancer and non-cancer
48
Figure 4.1.5 The distribution of CEA of cancer and non-cancer 49
Figure 4.2.1 The distribution of age of IM and non-IM 49
Figure 4.2.2 The distribution of PGI of IM and non-IM 50
Figure 4.2.3 The distribution of PGII of cancer and non-cancer 50
Figure 4.2.4 The distribution of PGI /PGII ratio of IM and non-IM 51
Figure 4.2.5 The distribution of CEA of IM and non-IM 51
Figure 5.1 The distribution of score of cancer and non-cancer 52
Figure 5.2 ROC curve for cancer prediction 52
Figure 5.3 ROC curve for IM prediction 53

Table List

Table 2.1 Summary of epidemiological studies on the association between helicobacter pylori infection and the development of gastric cancer and precancerous lesions 55
Table 2.2 Summary of epidemiological studies of pepsinogen as a marker for gastric cancer or precancerous lesions 59
Table 4.1 The frequencies of demographic and biochemical variables by the presence of gastric cancer 68
Table 4.2 The frequencies of demographic and biochemical variables by the presence of intestinal metaplasia 69
Table 4.3 Frequency of demographic and biochemical variables by the presence of atrophic/superficial gastritis 70
Table 4.4.1 Posterior odds (1:n) of developing gastric cancer in Male given PGI level 71
Table 4.4.2 Posterior odds (1:n) of developing gastric cancer in females given PGI level 72
Table 4.4.3 Cumulative probability of developing gastric cancer in males less than certain PGI level 73
Table 4.4.4 Cumulative probability of developing gastric cancer in females less than certain PGI level 74
Table 4.5.1 Posterior odds of developing IM in HP seropositive 75
Table 4.5.2 Posterior odds of developing IM in HP seronegative 76

Table 4.5.3 Cumulative probability of developing IM in HP seropositive less than certain PGI level 77
Table 4.5.4 Cumulative probability of developing IM in HP seronegative less than certain PGI level 78
Table 4.6.1 Posterior odds of being gastric cancer given PGI and CEA for 30-34 y/o male 79
Table 4.6.2 Posterior odds of being gastric cancer given PGI and CEA for 35-39 y/o male 80
Table 4.6.3 Posterior odds of being gastric cancer given PGI and CEA for 40-44 y/o male 81
Table 4.6.4 Posterior odds of being gastric cancer given of PGI and CEA for 45-49 y/o male 82
Table 4.6.5 Posterior odds of being gastric cancer given of PGI and CEA for 50-54 y/o male 83
Table 4.6.6 Posterior odds of being gastric cancer given of PGI and CEA for 55-59 y/o male 84
Table 4.6.7 Posterior odds of being gastric cancer given of PGI and CEA for 60-64 y/o male 85
Table 4.6.8 Posterior odds of being gastric cancer given PGI and CEA for 65-69 y/o male 86
Table 4.6.9 Posterior odds of being gastric cancer given PGI and CEA for 70-74 y/o male 87
Table 4.6.10 Posterior odds of being gastric cancer given PGI and CEA for 75-79 y/o male 88
Table 4.6.11 Posterior odds of being gastric cancer given PGI and CEA for 80-84 y/o male 89

Table 4.6.12 Posterior odds of being gastric cancer given PGI and CEA for 85+ y/o male 90
Table 4.6.13 Posterior odds of being gastric cancer given PGI and CEA for 30-34 y/o female 91
Table 4.6.14 Posterior odds of being gastric cancer given PGI and CEA for 35-39 y/o female 92
Table 4.6.15 Posterior odds of being gastric cancer given PGI and CEA for 40-44 y/o female 93
Table 4.6.16 Posterior odds of being gastric cancer given PGI and CEA for 45-49 y/o female 94
Table 4.6.17 Posterior odds of being gastric cancer given of PGI and CEA for 50-54 y/o female 95
Table 4.6.18 Posterior odds of being gastric cancer given of PGI and CEA for 55-59 y/o female 96
Table 4.6.19 Posterior odds of being gastric cancer givenof PGI and CEA for 60-64 y/o female 97
Table 4.6.20 Posterior odds of being gastric cancer given PGI and CEA for 65-69 y/o female 98
Table 4.6.21 Posterior odds of being gastric cancer given PGI and CEA for 70-74 y/o female 99
Table 4.6.22 Posterior odds of being gastric cancer given PGI and CEA for 75-79 y/o female 100
Table 4.6.23 Posterior odds of being gastric cancer given PGI and CEA for 80-84 y/o female 101
Table 4.6.24 Posterior odds of being gastric cancer given PGI and CEA for 85+ y/o female 102
Table 4.7.1 Marginal posterior odds of developing cancer after adjustment for CEA in males 103
Table 4.7.2 Marginal posterior odds of developing cancer after adjustment for CEA in females 104
Table 4.8.1 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 30-34 years (HP seropositive) 105
Table 4.8.2 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 35-39 years (HP seropositive) 106
Table 4.8.3 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 40-44 years (HP seropositive) 107
Table 4.8.4 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 45-49 years (HP seropositive) 108
Table 4.8.5 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 50-54 years (HP seropositive) 109
Table 4.8.6 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 55-59 years (HP seropositive) 110
Table 4.8.7 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 60-64 years (HP seropositive) 111

Table 4.8.8 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 65-69 years (HP seropositive) 112
Table 4.8.9 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 70-74 years (HP seropositive) 113
Table 4.8.10 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 75-79 years (HP seropositive) 114
Table 4.8.11 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 80-84 years (HP seropositive) 115
Table 4.8.12 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 30-34 years (HP seronegative) 116
Table 4.8.13 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 35-39 years (HP seronegative) 117
Table 4.8.14 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 40-44 years (HP seronegative) 118
Table 4.8.15 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 45-49 years (HP seronegative) 119
Table 4.8.16 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 50-54 years (HP seronegative) 120
Table 4.8.17 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 55-59 years (HP seronegative) 121
Table 4.8.18 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 60-64 years (HP seronegative) 122
Table 4.8.19 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 65-69 years (HP seronegative) 123
Table 4.8.20 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 70-74 years (HP seronegative) 124
Table 4.8.21 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 75-79 years (HP seronegative) 125
Table 4.8.22 Posterior odds of developing IM with bivariate Bayesian analysis given PGI and PG ratio for age of 85+ years (HP seronegative) 126
Table 4.9.1 Marginal posterior odds of developing IM after adjustment for PG ratio (HP seropositive) 127
Table 4.9.2 Marginal posterior odds of developing IM after adjustment for PG ratio (HP seronegative) 128
Table 4.10.1 Determination of cut-off point for cancer screening given probability >1/1000 (Male) 129
Table 4.10.2 Determination of cut-off point for cancer screening given probability >1/1000 (Female) 129
Table 4.10.3 Determination of cut-off point for cancer screening given probability >1/2000 129
Table 4.10.4 Determination of cut-off point for cancer screening given probability >1/3000 130
Table 4.11.1 Determination of cut-off point for IM screening given probability >1/10 (HP seronegative) 130
Table 4.11.2 Determination of cut-off point for IM screening given probability >1/10 (HP seropositive) 130
Table 4.12.1 Determination of cut-off point for cancer screening given utility 131
Table 4.12.2 Determination of cut-off point for cancer IM screening given utility 131
Table 5.1 Logistic model prediction of cancer 131
Table 5.2 Comparison of the cancer predictive probability from two models 132
Kikuchi, S. et al. "Serum pepsinogen as a new marker for gastric carcinoma among young adults. Research Group on Prevention of Gastric Carcinoma among Young Adults." Cancer 73.11 (1994): 2695-702.
Kitahara, F. et al. "Accuracy of screening for gastric cancer using serum pepsinogen concentrations." Gut 44.5 (1999): 693-97.
Knight, T. et al. "Helicobacter pylori gastritis and serum pepsinogen levels in a healthy population: development of a biomarker strategy for gastric atrophy in high risk groups." Br.J.Cancer 73.6 (1996): 819-24.
Kodoi, A. et al. "Serum pepsinogen in screening for gastric cancer." J.Gastroenterol. 30.4 (1995): 452-60.
Kuipers, E. J. "In through the out door: serology for atrophic gastritis." Eur.J.Gastroenterol.Hepatol. 15.8 (2003): 877-79.
Lin, J. T. et al. "Serum levels of pepsinogen I and gastrin in gastric carcinoma: the influence of Helicobacter pylori infection and tumor characteristics." Hepatogastroenterology 40.6 (1993): 600-03.
Miki, K. et al. "Clinical application of serum pepsinogen I and II levels for mass screening to detect gastric cancer." Jpn.J.Cancer Res. 84.10 (1993): 1086-90.
Miki, K. et al. "Usefulness of gastric cancer screening using the serum pepsinogen test method." Am.J.Gastroenterol. 98.4 (2003): 735-39.
Nomura, A. et al. "Helicobacter pylori infection and gastric carcinoma among Japanese Americans in Hawaii." N.Engl.J.Med. 325.16 (1991): 1132-36.
Ohkuma, K., M. Okada, and H. Murayama. "Association of Helicobacter pylori infection with atrophic gastritis and intestinal metaplasia." J of Gastroenterol.Hepatol 15 (2000): 1105-12.
Parsonnet, J. et al. "Helicobacter pylori infection and the risk of gastric carcinoma." N.Engl.J.Med. 325.16 (1991): 1127-31.
Richard A.Johnson and Dean W.Wichern. APPLIED MULTIVARIATE STATISTICAL ANALYSIS. 2 ed. 1988.
So, J. B. et al. "Serum pepsinogen levels in gastric cancer patients and their relationship with Helicobacter pylori infection: a prospective study." Gastric.Cancer 5.4 (2002): 228-32.
Uemura, N. et al. "Helicobacter pylori infection and the development of gastric cancer." N.Engl.J.Med. 345.11 (2001): 784-89.
Vaananen, H. et al. "Non-endoscopic diagnosis of atrophic gastritis with a blood test. Correlation between gastric histology and serum levels of gastrin-17 and pepsinogen I: a multicentre study." Eur.J.Gastroenterol.Hepatol. 15.8 (2003): 885-91.
Varis, K. et al. "Serum pepsinogen I and serum gastrin in the screening of atrophic pangastritis with high risk of gastric cancer." Scand.J.Gastroenterol.Suppl 186 (1991): 117-23.
Varis, K. et al. "Implications of serum pepsinogen I in early endoscopic diagnosis of gastric cancer and dysplasia. Helsinki Gastritis Study Group." Scand.J.Gastroenterol. 35.9 (2000): 950-56.
Wu, M. S. et al. "Serum levels of pepsinogen I in healthy volunteers and patients with gastric ulcers and gastric carcinoma in Taiwan." J.Formos.Med.Assoc. 92.8 (1993): 711-16.
Xia, H. H. X. "Antral-type mucosa in the gastric incisura, body and fundus (Antralization): A link between helicobacter pylori infection and intestinal metaplasia." Am.J.Gastroenterol. 95 (2000): 114-21.
Yoshihara, M. et al. "Correlation of ratio of serum pepsinogen I and II with prevalence of gastric cancer and adenoma in Japanese subjects." Am.J.Gastroenterol. 93.7 (1998): 1090-96.
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