| Literature DB >> 29456570 |
Li-Ling Shen1, Chih-Hsin Muo2,3, Shan-Yu Su1,4, Donald E Morisky5.
Abstract
The Pap test diagnosed cervical dysplasia, which could recover to normal or progress to cervical cancer (CC), is an early stage of cell abnormality before CC. This case-control study analyzed the differences in the risk to develop CC between Chinese medicine (CM) users and nonusers among women who had ever been diagnosed as having cervical dysplasia. A total of 750 CC patients with a cervical dysplasia history were collected between 1998 and 2011 from National Health Insurance Research Database, and controls were women with cervical dysplasia history but did not develop CC. Adjusted odds ratio (aOR) for developing CC was assessed using multivariable logistic regression after adjusting for age, urbanization of residence, and occupation. The proportion of using CM among CC patients was lower than that among CC nonpatients, with an aOR of 0.8. By analyzing the relationship between CC development and the frequency of CM usage, the trend test revealed a significant decreasing trend for developing CC among high-frequency CM users. Moreover, the most frequently used single herb high-frequency was Rheum palmatum (Da-Huang). The usage of CM might be an effective complementary method to prevent uterine cervix from progressing to CC after cervical dysplasia has occurred.Entities:
Year: 2017 PMID: 29456570 PMCID: PMC5804104 DOI: 10.1155/2017/4082630
Source DB: PubMed Journal: Evid Based Complement Alternat Med ISSN: 1741-427X Impact factor: 2.629
Figure 1Flow chart for abstracting study subjects. NHIRD, National Health Insurance Research Database, and CC, cervical cancer.
Demographic factors of cervical cancer patients and nonpatients who had ever been diagnosed as cervical dysplasia.
| CC patients | CC nonpatients |
| |||
|---|---|---|---|---|---|
|
| % |
| % | ||
| Age, year | 0.99 | ||||
| 20–39 | 72 | 9.60 | 144 | 9.61 | |
| 40–49 | 202 | 26.9 | 404 | 27.0 | |
| 50–59 | 216 | 28.8 | 432 | 28.8 | |
| >59 | 260 | 34.7 | 518 | 34.6 | |
| Mean (SD) | 56.2 (13.2) | 56.0 (13.2) | 0.53 | ||
| Urbanization | 0.07 | ||||
| Urban | 424 | 56.5 | 906 | 60.5 | |
| Rural | 326 | 43.5 | 592 | 39.5 | |
| Occupation | <0.0001 | ||||
| Homemaker | 226 | 30.1 | 376 | 25.1 | |
| White collar | 210 | 28.0 | 562 | 37.5 | |
| Blue collar | 314 | 41.9 | 560 | 37.4 | |
Chi-square test and t-test. CC, cervical cancer.
Odds ratio for using CM in cervical cancer patients and nonpatients stratified by demographic subgroups.
| CC patients | CC nonpatients | ||||
|---|---|---|---|---|---|
|
| % |
| % | aOR (95% CI) | |
| CM usage | 149 | 19.9 | 359 | 24.0 | 0.80 (0.64–0.99) |
| Age, year | |||||
| 20–39 | 19 | 26.4 | 38 | 26.4 | 0.98 (0.51–1.89) |
| 40–49 | 43 | 21.3 | 112 | 27.7 | 0.71 (0.47–1.06) |
| 50–59 | 40 | 18.5 | 111 | 25.7 | 0.66 (0.44–0.99) |
| >60 | 47 | 18.0 | 98 | 18.9 | 0.95 (0.65–1.40) |
| Urbanization | |||||
| Urban | 88 | 20.8 | 226 | 24.9 | 0.81 (0.61–1.07) |
| Rural | 61 | 18.7 | 133 | 22.5 | 0.76 (0.54–1.08) |
| Occupation | |||||
| Homemaker | 41 | 18.1 | 86 | 22.9 | 0.73 (0.48–1.11) |
| White collar | 43 | 20.5 | 152 | 27.1 | 0.71 (0.48–1.04) |
| Blue collar | 65 | 20.7 | 121 | 21.6 | 0.92 (0.65–1.29) |
Adjusted for age, urbanization, and occupation. CC, cervical cancer; CM, Chinese medicine. p < 0.05 in the logistic regression model.
Adjusted odds ratio for using CM in cervical cancer patients and nonpatients among CM nonusers, low-frequency CM users, and high-frequency CM users.
| CC patients | CC nonpatients | aOR (95% CI) | |||
|---|---|---|---|---|---|
|
| % |
| % | ||
| CM nonuser | 601 | 80.1 | 1139 | 76.0 | 1.00 |
| CM users | |||||
| Low frequency | 73 | 9.73 | 164 | 11.0 | 0.86 (0.64–1.16) |
| High frequency | 76 | 10.1 | 195 | 13.0 | 0.74 (0.56–0.98) |
| | 0.03 | ||||
Adjusted for age, urbanization, and occupation. p < 0.05 in the logistic regression model.
Top ten CM singles and formulas prescribed for high-frequency CM users.
| % | Days/year | Daily dose (g) | |
|---|---|---|---|
| Single | |||
| | 2.20 | 67.60 | 0.51 |
| | 1.96 | 43.98 | 1.10 |
| | 1.89 | 34.60 | 1.12 |
| | 1.88 | 36.91 | 0.99 |
| | 1.70 | 45.20 | 1.39 |
| | 1.50 | 44.11 | 0.96 |
| | 1.47 | 33.81 | 1.07 |
| | 1.33 | 30.91 | 1.10 |
| | 1.21 | 26.48 | 0.95 |
| | 1.19 | 32.33 | 1.14 |
|
| |||
| Formula | |||
| Jia-wei-xiao-yao-san | 4.03 | 67.64 | 4.21 |
| Chuan-qiong-cha-tiao-san | 2.50 | 44.72 | 3.92 |
| Ge-gen-tang | 1.74 | 32.35 | 4.12 |
| Suan-zao-ren-tang | 1.67 | 41.28 | 3.77 |
| Tian-wang-bu-xin-dan | 1.55 | 43.56 | 3.67 |
| Du-huo-ji-sheng-tang | 1.54 | 40.27 | 4.66 |
| Zhi-gan-cao-tang | 1.53 | 42.96 | 3.51 |
| Shu-jing-huo-xie-tang | 1.50 | 34.45 | 4.59 |
| Xiang-sha-liu-jun-zi-tang | 1.50 | 43.48 | 4.02 |
| Ban-xia-xie-xin-tang | 1.48 | 32.41 | 3.69 |