The Effectiveness And Mechanism Of Tonifying Kidney And Spleen Method On Preventing And Treatment Of Myelosuppression Induced By Adjuvant Chemotherapy Of Colorectal Cancer Ⅵ
Sep 25, 2024
3.3 Quality evaluation of included literature
Among the included literature, the high risk of bias mainly exists in the implementation of blinding of subjects and experimental personnel, allocation concealment and incomplete data results. (1) Generation of random sequence: 24 studies mentioned the method of random sequence generation and were rated as "low risk"; the rest were "unclear risk of bias". (2) Allocation concealment: 2 studies used central randomization or envelope method for concealment and were rated as "low risk"; 7 studies used alternating allocation, medical record number allocation, etc. and were rated as "high risk"; the rest were "unclear risk of bias". (3) Blinding of subjects and researchers: All studies were blank-controlled and could not be blinded, so they were rated as "high risk". (4) Blinding of outcome assessors: None of the studies mentioned the use of blinding for outcome assessors. However, the outcome indicators of this study were all laboratory measurements, or were determined based on laboratory measurements as raw data. The outcome assessors judged that the outcomes would not be affected by the lack of blinding, so it was rated as "low risk"; (5) Incomplete outcome reporting: 8 studies reported missing data, the number of missing data between groups and the reasons were unbalanced, or inappropriate methods were used to handle missing data, so they were rated as "high risk", 24 studies had no missing data, and were rated as "low risk", and the rest were rated as "unclear risk of bias". (6) Selective reporting: None of the studies mentioned the relevant information of the study protocol registration, and were rated as "unclear risk of bias". (7) Other biases: All studies reported the comparability of baseline data, which was rated as "low risk". (Figure 1-2, Figure 1-3)

Figure 1-2 Evaluation of specific projects included in the study ROB

3.4 Meta-analysis results
3.4.1 Main outcome indicators
(1) Incidence of leukopenia
Nine studies 125-33 reported the incidence of leukopenia, 16 studies [34-49 reported the incidence of grade I/II/I/IV leukopenia, and another study [501 reported the incidence of grade I-II/III-IV leukopenia. After merging the data, it was found that the heterogeneity between the studies was not large (P=29%). The results of the meta-analysis showed that oral Chinese medicine can reduce the risk of leukopenia caused by adjuvant chemotherapy for colorectal cancer (RR=0.67, 95%CI[0.61,0.75], P<0.00001). (Figure 1-4)
| Events | Total | Events | Total | M-H, Fixed, 95% CI | M-H, Fixed, 95% CI | ||
|---|---|---|---|---|---|---|---|
| Wu Zhiqiang 2019 | 11 | 35 | 19 | 35 | 4.1% | 0.58 [0.33, 1.03] | |
| Liu Anbo 2020 | 7 | 32 | 15 | 32 | 3.2% | 0.47 [0.22, 0.99] | |
| Liu Linkang 2009 | 11 | 40 | 12 | 40 | 2.6% | 0.92 [0.46, 1.83] | |
| Lv Wanguo 2020 | 33 | 90 | 56 | 90 | 14.2% | 0.50 [0.37, 0.67] | |
| Wu Jianxin 2012 | 35 | 105 | 40 | 105 | 8.6% | 0.88 [0.61, 1.26] | |
| Zhou Yimin 2012 | 5 | 20 | 10 | 20 | 2.2% | 0.50 [0.21, 1.20] | |
| Zhou Gaoyun 2018 | 30 | 50 | 34 | 50 | 7.3% | 0.88 [0.66, 1.19] | |
| Sun Dandan 2017 | 7 | 40 | 12 | 40 | 2.6% | 0.58 [0.26, 1.33] | |
| Zheng Hao 2015 | 6 | 30 | 8 | 30 | 1.7% | 0.75 [0.30, 1.90] | |
| Xu Chunyan 2016 | 7 | 30 | 14 | 30 | 3.0% | 0.50 [0.24, 1.06] | |
| Cao Bo 2019 | 18 | 30 | 16 | 29 | 3.5% | 1.09 [0.70, 1.69] | |
| Li Lingchang 2009 | 3 | 15 | 10 | 15 | 2.2% | 0.10 [0.01, 0.69] | |
| Li Zhe 2012 | 4 | 20 | 9 | 20 | 1.9% | 0.44 [0.16, 1.21] | |
| Yang Hui 2012 | 12 | 37 | 13 | 36 | 2.8% | 0.90 [0.48, 1.70] | |
| Wang Fuxia 2013 | 10 | 30 | 17 | 29 | 3.7% | 0.57 [0.31, 1.03] | |
| Shi Tingting 2019 | 13 | 28 | 15 | 28 | 3.2% | 0.87 [0.51, 1.47] | |
| Xiao Ying 2018 | 10 | 20 | 15 | 20 | 3.2% | 0.67 [0.40, 1.11] | |
| Fan Binyan 2019 | 13 | 30 | 22 | 30 | 4.7% | 0.59 [0.37, 0.94] | |
| Dong Wangshao 2018 | 1 | 45 | 3 | 45 | 0.6% | 0.33 [0.04, 3.08] | |
| Xu Qianni 2016 | 13 | 26 | 20 | 25 | 4.4% | 0.63 [0.41, 0.96] | |
| Zheng Hao 2015 | 23 | 30 | 21 | 30 | 4.5% | 1.10 [0.81, 1.49] | |
| Zheng Wei 2010 | 18 | 26 | 23 | 24 | 5.2% | 0.72 [0.55, 0.95] | |
| Chen Li 2019 | 6 | 24 | 7 | 24 | 1.5% | 0.71 [0.26, 1.94] | |
| Chen Wenbo 2019 | 13 | 48 | 3 | 48 | 0.6% | 0.67 [0.12, 3.81] | |
| Chen Zhengwei 2020 | 12 | 50 | 23 | 505.0% | 0.52 | [0.29, 0.93] | |
| Gao Xiaomin 2015 | 8 | 28 | 15 | 27 | 3.3% | 0.51 [0.26, 1.01] | |
| ------------------- | -------- | ------- | -------- | ------- | -------- | --------------------- | --------------------- |
| Total (95% CI) | 959 | 952 | 100.0% | [0.61, 0.75] | |||
| Total events | 315 | 462 | |||||
| ------------------- | -------- | ------- | -------- | ------- | -------- | --------------------- | --------------------- |
| Heterogeneity: Chi² = 35.18, df = 25 (P = 0.08); I² = 29% | |||||||
| Test for overall effect: Z = 7.36 (P < 0.00001) |
Note: The forest plot is not included in this text-based table. The Risk Ratio column shows the numerical values, but the graphical representation is not possible in this format.
Figure 1-4 Meta-analysis of the incidence of leukopenia in traditional Chinese medicine + chemotherapy vs chemotherapy
The inverted funnel plot shows a symmetrical trend, which basically supports the results of the meta-analysis. (Figure 1-5)

Figure 1-5 Inverted funnel plot of meta-analysis of Chinese medicine + chemotherapy vs chemotherapy leukopenia
(2) Incidence of hemoglobin reduction
Four studies125.2728.51 reported the incidence of hemoglobin reduction, and 10 studies134.35.3740.42.4.47.48I reported the incidence of grade I/II/I/IV hemoglobin reduction. The combined data found that the heterogeneity between the studies was small (I²=0%): Meta-analysis results showed that oral Chinese medicine can reduce the risk of hemoglobin reduction caused by adjuvant chemotherapy for colorectal cancer (RR=0.75, 95%CI[0.63,0.89], P=0.0009). (Figure 1-6)
| Study or Subgroup | Experimental | | Control | | Weight | Risk Ratio | Risk Ratio |
| Events | Total | Events | Total | M-H, Fixed, 95% CI | M-H, Fixed, 95% CI | ||
|---|---|---|---|---|---|---|---|
| Liu Anbo 2020 | 3 | 32 | 6 | 32 | Not estimable | ||
| Zhou Yimin 2012 | 8 | 20 | 10 | 20 | 6.1% | 0.80 [0.40, 1.60] | |
| Zhou Gaoyun 2018 | 32 | 50 | 37 | 50 | 22.7% | 0.86 [0.66, 1.13] | |
| Xu Chunyan 2016 | 9 | 30 | 9 | 30 | 4.9% | 0.88 [0.36, 2.11] | |
| Li Zhe 2012 | 7 | 20 | 9 | 20 | 5.5% | 0.78 [0.36, 1.68] | |
| Shi Tingting 2019 | 7 | 28 | 14 | 28 | 8.6% | 0.50 [0.24, 1.05] | |
| Xiao Ying 2018 | 11 | 20 | 14 | 20 | 8.6% | 0.79 [0.48, 1.28] | |
| Fan Binyan 2019 | 15 | 30 | 17 | 30 | 10.4% | 0.88 [0.55, 1.42] | |
| Dong Wangshao 2018 | 2 | 45 | 2 | 45 | 1.2% | 1.00 [0.15, 6.79] | |
| Zheng Hao 2015 | 13 | 30 | 17 | 30 | 10.4% | 0.76 [0.46, 1.28] | |
| Zheng Wei 2010 | 26 | 24 | 2.5% | 1.15 [0.35, 3.80] | |||
| Liao Xue 2017 | 45 | 8 | 45 | 4.9% | 0.25 [0.06, 1.11] | ||
| Chen Zhengwei 2020 | 50 | 19 | 50 | 11.6% | 0.42 [0.20, 0.87] | ||
| Gao Xiaomin 2015 | 28 | 4 | 27 | 2.5% | 1.21 [0.36, 4.02] | ||
| ------------------- | -------- | ------- | -------- | ------- | -------- | --------------------- | --------------------- |
| Total (95% CI) | 454 | 421 | 100.0% | 0.75 [0.63, 0.89] | |||
| Total events | 125 | 169 | |||||
| ------------------- | -------- | ------- | -------- | ------- | -------- | --------------------- | --------------------- |
| Heterogeneity: Chi² = 8.68, df = 12 (P = 0.73); I² = 0% | |||||||
| Test for overall effect: Z = 3.32 (P = 0.0009) |






