Through collecting and synthesizing the paper concerning the method of dealing with heterogeneity in the meta analysis, to introduce the multi-levels statistical models, such as meta regression and baseline risk effect model based on random effects, and random effects model based on hierarchical bayes, and to introduce their application of controlling the meta analysis heterogeneity. The multi-levels statistical model will decompose the single random error in the traditional model to data structure hierarchical. Its fitting effect can not only make the meta-analysis result more robust and reasonable, but also guide clinical issues through the interpretation of association variable.
Objective To summarize the advancement of breast cancer stem cells and genotyping and analyze the correlation between the two. Methods Relevant literatures about breast cancer stem cells and genotyping, which were published recently were collected and reviewed. Results Cancer stem cell origin theory was supported by researches of correlation between breast cancer stem cells and genotyping, which also explained the complexity of intrinsic subtypes and heterogeneity of breast cancer. Conclusions A new way can be detected to study the formation mechanism and biological characteristics of breast cancer at the cellular and molecular level by researches of correlation between breast cancer stem cells and genotyping, which are expected to provide new strategies and tools for diagnosis and treatment of breast cancer.
【Abstract】 Objective To introduce the cl inical appl ication of heterogeneity (cattle) acellular dermal matrix(ADM)in the repair of mucosa defect otolaryngology. Methods From October 2006 to March 2007, 12 cases of mucosa defect was repaired with heterogeneity ADM after the surgery. There were 10 males and 2 females, aged 18-76 years. Defect was caused by deflection of nasal septum in 1 case, melanoma of front and midst basal is (capillary hemangioma) in 1 case, nasal vestibule angioma (T2N2M0)in 1 case, cancer of hypopharynx (T2N1M0) in 1 case, cancer of amygdale in 3 cases (2 of T2N0M0 and 1 of T3N1M0),cervical segments esophageal carcinoma in 1 case, and cancer of larynx in 4 cases (3 of T2N0M0 and 1 of T3N1M0). Results All these 12 cases were followed up for 6 months. The results of endoscope showed that heterogeneity ADM mingled with mucosa within 3 months after operation and the function was recovered. Pharynx fistula occurred in 1 case of hypopharynx cancer afterthe operation. After treatment of dressing change and antibiotics for 10 days, the wound healed, but after 2 months tumor recurred. All the patients were treated by radiation treatment. One case of amygdala cancer recurred and transferred to the neck after 2 months of radiation treatment. But 1 case of hypopharynx cancer died of massive haemorrhage after radiation treatment for 3 months. Conclusion Heterogeneity ADM can be easily obtained and it is a new method to repair mucosa defect. Theoperative procedure is easy to perform and worthwhile to be appl ied to cl inical operation.
Many meta-analysis studies evaluate rates as parameter to assess the overall estimate of effects. However, none of these studies address systematic approaches for the meta-analysis of rates. This paper outlines the conditions, analysis and software operation procedures for the meta-analysis of rates. It also compares different operation procedures of three types of commonly-used R software (Comprehensive Meta-Analysis, Stata and MetaAnalyst) through real application examples. The biggest challenge for the meta-analysis of rates is to determine whether rates can be pooled, and how to evaluate heterogeneity between studies' outcomes needs further discussion.
Objective To summarize the research progress of distributional heterogeneity of the molecular pathology characteristics in breast cancer. Methods The related literatures about the distribution of the molecular pathology characteristics in breast cancer were reviewed. Results The breast cancer had the same heterogeneity as other cancers. At the same time, the molecular pathology characteristics, such as estrogen receptor (ER), progesterone receptor (PR), Ki-67, and human epidermal growth factor receptor-2 (HER-2), had the distributional heterogeneity. The distributional heterogeneity of molecular pathology characteristics in breast cancer could effect the pathologic diagnosis, the treatment, and the prognosis. Conclusion Although there are some new techniques which were used to investigate the heterogeneity of breast cancer, but each way has some problems. The more attention should be paid to the research about the distributional heterogeneity of the molecular pathology characteristics in breast cancer.
Randomized controlled trials are the gold standard for evaluating the effects of medical interventions, primarily providing estimates of the average effect of an intervention in the overall study population. However, there may be significant differences in the effect of the same intervention across sub-populations with different characteristics, that is, treatment heterogeneity. Traditional subgroup analysis and interaction analysis tend to have low power to examine treatment heterogeneity or identify the sources of heterogeneity. With the recent development of machine learning techniques, causal forest has been proposed as a novel method to evaluate treatment heterogeneity, which can help overcome the limitations of the traditional methods. However, the application of causal forest in the evaluation of treatment heterogeneity in medicine is still in the beginning stage. In order to promote proper use of causal forest, this paper introduces its purposes, principles and implementation, interprets the examples and R codes, and highlights some attentions needed for practice.
Compared with traditional head to head meta-analysis, network meta-analysis has more confounding factors and difficulties to handle. Due to the mutual transitivity of evidence in network meta-analysis, heterogeneity may be brought into indirect meta-analysis. Hence, effective differentiation and correct handling of heterogeneity are being current focus. In order to ensure the reliability of the results of network meta-analysis, the concept of homogeneity is proposed and a series of methods are developed for differentiation and handling of homogeneity. Based on the extension of Bucher methods, current methods for differentiation and handling of homogeneity has extended to ten quantitative measures (eg., node analysis method, hypothesis tests, and two-step method). However, because of the differences and the focus of fundamental methodological theories as well as the limitation of statistics power, no highly-effective method has been worked out. Therefore, the exploration of highly-effective, simple and high-resolved methods are still needed.
The assumption of fixed-effects model is based on that the true effect of the each trial is same. However, the assumption of random-effects model is based on that the true effect of included trials is normal distributed. The total variance is equal to the sum of within-trial variance and between-trial variance under the random-effects model. There are many estimators of the between-trial variance. The aim of this paper is to give a brief introduction of the estimators of between-trial variance in trial sequential analysis for random-effects model.
Objective To investigate confidence interval estimation for the amount of heterogeneity in meta-analysis. Methods On the basis of BT’s method, the approximate Q-statistic distribution following linear transformation of Chi-square was applied to improve the accuracy of Q-statistic distribution, and to obtain the confidence interval for the amount of heterogeneity in meta-analysis. Results In case, the Q1 distribution obtained 95%CI 0.07 to 2.20, while the Q2 distribution obtained 95%CI 0.00 to 1.41; The proposed method Q2 narrowed down the range of confidence interval. Conclusion On account of improving the accuracy of Q-statistic distribution, the proposed method effectively strengthens the coverage probabilities of the confidence interval for the amount of heterogeneity. And the proposed method can also improve the precision of the confidence interval estimation for the amount of heterogeneity.
Objective To analyze the heterogeneity of systematic reviews (SRs)/Meta-analysis on traditional Chinese medicine (TCM), and explore strategies for addressing heterogeneity correctly during the process of conducting TCM related to systematic reviews (SRs). Methods Both electronic and hand searches were used to identify TCM SRs in CBM, CNKI, VIP database, and Chinese Journal of Evidence-Based Medicine. Two researchers performed data extracting and heterogeneity evaluation independently. Results A total of 115 TCM SRs were included, involving 17 types of diseases, among which the cardiovascular and cerebrovascular diseases were the most addressed (n=36, 31.30%). There were 35.65% (n=41) of SRs which integrated two or more types of studies; interventions of the included studies were inconsistent in 53.91% (n=62) of TCM SRs; control groups of the included studies were completely different in 60 (52.17%) SRs; and 8.7% (n=10) of SRs failed to investigate heterogeneity in the process of synthesis analysis. Conclusion The heterogeneity is common in TCM related to SRs, and the most addressed is clinical heterogeneity. Addressing heterogeneity incorrectly would downgrade the quality of TCM related to SRs.