| Literature DB >> 30717733 |
Yu-Chi Wang1, Jen-Huai Chiang2,3,4, Hsin-Cheng Hsu1,5, Chun-Hao Tsai6,7,8.
Abstract
BACKGROUND: There are no published studies regarding the efficacy of traditional Chinese medicine (TCM) for the prevention of osteoporotic fracture. Therefore, we conducted this nationwide, population-based cohort study to investigate the probable effect of TCM to decrease the fracture rate.Entities:
Keywords: National Health Insurance Research Database; Osteoporotic fracture; Traditional Chinese medicine
Mesh:
Substances:
Year: 2019 PMID: 30717733 PMCID: PMC6360787 DOI: 10.1186/s12906-019-2446-3
Source DB: PubMed Journal: BMC Complement Altern Med ISSN: 1472-6882 Impact factor: 3.659
Fig. 1The recruitment flowchart of subjects from the one million samples randomly selected from the National Health Insurance Research Database (NHIRD) in Taiwan. There were a total of 54,075 osteoporosis patients registered in the NHIRD, with 37,960 patients diagnosed between 2000 and 2010. After ruling out patients with missing information and aged > 18 years, as well as matching 1:1 by sex, age, diagnosis year of osteoporosis, and index year, both groups contained 804 patients
Characteristics of osteoporosis patients according to use of traditional Chinese medicine
| Variable | TCM | ||||
|---|---|---|---|---|---|
| No ( | Yes ( | ||||
| n | % | n | % | ||
| Gender | 0.99* | ||||
| Female | 615 | 76.49 | 615 | 76.49 | |
| Male | 189 | 23.51 | 189 | 23.51 | |
| Age group, year | 0.99* | ||||
| < 65 | 386 | 48.01 | 386 | 48.01 | |
| ≥ 65 | 418 | 51.99 | 418 | 51.99 | |
| Mean (SD) | 64.57 (11.08) | 64.48 (11.08) | 0.8813a | ||
| Urbanization level† | 0.0104* | ||||
| 1 (highest) | 207 | 25.75 | 240 | 29.85 | |
| 2 | 238 | 29.6 | 226 | 28.11 | |
| 3 | 106 | 13.18 | 134 | 16.67 | |
| 4 (lowest) | 253 | 31.47 | 204 | 25.37 | |
| Baseline comorbidity | |||||
| Alcohol-related disease | 4 | 0.5 | 1 | 0.12 | 0.3742b |
| Cancer | 45 | 5.6 | 22 | 2.74 | 0.0041* |
| Cardiovascular disease | 307 | 38.18 | 305 | 37.94 | 0.9182* |
| Chronic kidney disease | 25 | 3.11 | 25 | 3.11 | 0.99* |
| Chronic obstructive pulmonary disease | 188 | 23.38 | 241 | 29.98 | 0.0028* |
| Diabetes mellitus | 212 | 26.37 | 185 | 23.01 | 0.1184* |
| Dementia | 19 | 2.36 | 12 | 1.49 | 0.2043* |
| Depression | 44 | 5.47 | 54 | 6.72 | 0.2972* |
| Hyperlipidemia | 168 | 20.9 | 218 | 27.11 | 0.0035* |
| Hypertension | 447 | 55.6 | 416 | 51.74 | 0.1211* |
| Parkinson’s disease | 8 | 1 | 11 | 1.37 | 0.4887* |
| Interval between diagnosis and initial TCM use, mean (days) | 611 | ||||
| Follow-up time, mean (median; years) | 3.75 (2.86) | 5.38 (5.18) | |||
*Chi-Square Test, a t-test, bFisher’s exact test
†: The urbanization level was categorized into four levels based on the population density of the residential area, with level 1 as the most urbanized and level 4 as the least urbanized
Traditional Chinese medicine (TCM) included Chinese herbal remedies, acupuncture, and manipulative
Cox model with hazard ratios and 95% confidence intervals of fracture associated with TCM and covariates among osteoporosis patients
| Variable | Fracture no. ( | Crude* | Adjusted† | ||||
|---|---|---|---|---|---|---|---|
| HR | (95%CI) | p-value | HR | (95%CI) | |||
| TCM use | |||||||
| No | 193 | 1.00 | reference | 1.00 | reference | ||
| Yes | 130 | 0.50 | (0.4–0.63) | <.0001 | 0.47 | (0.37–0.59) | <.0001 |
| Gender | |||||||
| Female | 266 | 1.00 | reference | 1.00 | reference | ||
| Male | 57 | 0.78 | (0.59–1.04) | 0.0939 | 0.58 | (0.43–0.79) | 0.0004 |
| Age group, year | |||||||
| < 65 | 107 | 1.00 | reference | 1.00 | reference | ||
| ≥ 65 | 216 | 2.28 | (1.81–2.87) | <.0001 | 2.62 | (2.03–3.39) | <.0001 |
| Urbanization level | |||||||
| 1 (highest) | 73 | 1.00 | reference | 1.00 | reference | ||
| 2 | 94 | 1.28 | (0.94–1.73) | 0.1173 | 1.24 | (0.91–1.69) | 0.1665 |
| 3 | 52 | 1.46 | (1.02–2.08) | 0.0372 | 1.43 | (0.99–2.05) | 0.0534 |
| 4 (lowest) | 104 | 1.54 | (1.14–2.07) | 0.0049 | 1.31 | (0.97–1.77) | 0.0824 |
| Baseline comorbidity | |||||||
| Alcohol-related disease (Yes vs. No) | 4 | 5.20 | (1.94–13.96) | 0.0011 | 4.38 | (1.6–12.02) | 0.0041 |
| Cancer (Yes vs. No) | 9 | 0.83 | (0.43–1.61) | 0.5758 | 0.70 | (0.36–1.37) | 0.2979 |
| Cardiovascular disease (Yes vs. No) | 139 | 1.38 | (1.1–1.71) | 0.0046 | 1.07 | (0.83–1.38) | 0.5856 |
| Chronic kidney disease (Yes vs. No) | 9 | 1.22 | (0.63–2.36) | 0.5608 | 1.05 | (0.53–2.07) | 0.8909 |
| Chronic obstructive pulmonary (Yes vs. No)disease | 92 | 1.25 | (0.98–1.59) | 0.0759 | 1.20 | (0.93–1.54) | 0.1688 |
| Diabetes mellitus (Yes vs. No) | 87 | 1.20 | (0.94–1.54) | 0.1442 | 1.11 | (0.85–1.44) | 0.4518 |
| Dementia (Yes vs. No) | 6 | 1.62 | (0.72–3.64) | 0.2432 | 1.00 | (0.43–2.29) | 0.9909 |
| Depression (Yes vs. No) | 25 | 1.41 | (0.94–2.12) | 0.0972 | 1.62 | (1.05–2.5) | 0.0285 |
| Hyperlipidemia (Yes vs. No) | 62 | 0.79 | (0.6–1.04) | 0.0922 | 0.73 | (0.54–0.98) | 0.0352 |
| Hypertension (Yes vs. No) | 186 | 1.28 | (1.03–1.59) | 0.0292 | 0.92 | (0.72–1.19) | 0.5362 |
| Parkinson’s disease (Yes vs. No) | 5 | 1.25 | (0.52–3.02) | 0.6248 | 0.92 | (0.37–2.27) | 0.8498 |
Crude HR* represented relative hazard ratio; Adjusted HR† represented adjusted hazard ratio: mutually adjusted for TCM use, age, gender, urbanization level and baseline comorbidity in Cox proportional hazard regression
Fig. 2Kaplan–Meier curve of the difference between the TCM user and non-TCM user groups in the development of fracture
Hazard Ratios and 95% confidence intervals of fracture risk associated with cumulative use day of traditional Chinese herb medicine among osteoporosis patients
| TCM used (days per year) | N | No. of Event | Hazard Ratio (95% CI) | Hazard Ratio (95% CI) | ||
|---|---|---|---|---|---|---|
| Crude | Adjusted† | Crude | Adjusted† | |||
| Non-TCM users or Chinese herb users < 30 days per year | 1245 | 269 | 1(reference) | 1(reference) | – | – |
| Chinese herb users (≥ 30 days per year) ‡ | ||||||
| 30–180 days per year | 270 | 43 | 0.63 (0.46–0.87)** | 0.60 (0.43–0.84)** | 1(reference) | 1(reference) |
| 180 days per year | 93 | 11 | 0.42 (0.23–0.78)** | 0.37 (0.20–0.68)** | 0.65 (0.33–1.25) | 0.63 (0.32–1.24) |
Crude HR* represented relative hazard ratio; Adjusted HR† represented adjusted hazard ratio: mutually adjusted for age, gender, baseline comorbidity, and urbanization level in Cox proportional hazard regression
*p < 0.05, **p < 0.01, ***p < 0.001
Ten most common herbal formulas prescribed
| Herbal formula | Frequency | Number of person-days | Average daily dose | Average duration for prescription |
|---|---|---|---|---|
| (g) | (days) | |||
| Single Herb | ||||
| Eucommiae Cortex (Du-Zhong) | 803 | 10,832 | 1.2 | 13.5 |
| Salviaemiltiorrhizae Radix (Dan-shen) | 592 | 7850 | 1.3 | 13.3 |
| Chaenomelis Fructus (Mu-gua) | 520 | 6651 | 1.0 | 12.8 |
| Achuranthes (Huai-niu-xi) | 432 | 5181 | 1.1 | 12.0 |
| Dipsaci Radix (Xu-Duan) | 393 | 4701 | 1.3 | 12.0 |
| Sepiae Endoconcha (Haipiaoxiao) | 337 | 4476 | 1.4 | 13.3 |
| Corydalis Rhizoma (Yan-hu-suo) | 346 | 4284 | 1.5 | 12.4 |
| Spatholobi Caulis | 272 | 3570 | 1.4 | 13.1 |
| Testudinis Plastrum (Gui-ban) | 279 | 3477 | 0.9 | 12.5 |
| Drynariae Rhizoma (Gu sui-bu) | 259 | 3282 | 1.3 | 12.7 |
| Multiple Herb Formula | ||||
| Du Huo Ji Sheng Tang | 1109 | 13,795 | 5.7 | 12.4 |
| Gui Lu Er Xian Jiao | 433 | 8083 | 7.0 | 18.7 |
| Shu Jing Huo Xue Tang | 564 | 7427 | 4.6 | 13.2 |
| zuo Gui Wan | 516 | 5625 | 5.2 | 10.9 |
| ji Sheng Shen Qi Wan | 308 | 4478 | 5.1 | 14.5 |
| Zhi Bai Di Huang Yin | 322 | 4365 | 4.7 | 13.6 |
| Hu Qian Wan Without Hugu | 312 | 4211 | 7.2 | 13.5 |
| You Gui Wan | 302 | 3982 | 4.3 | 13.2 |
| Ma Zi Ren Wan | 219 | 3572 | 1.8 | 16.3 |
| Xiang Sha Liu Jun Zi Tang | 220 | 3423 | 4.2 | 15.6 |