Омела белая Viscum album Mistletoe
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- 2. Materials and Methods
- 2.2. Selection Criteria
- 2.3. Analysis of Data
- 2.4. Statistical Analysis
1. IntroductionComplementary and alternative medicine (CAM) has become increasingly popular over the last decades. According to Bausell et al., especially patients with chronic diseases increasingly seek for CAM-therapies [1]. With a growing amount of health information in the internet, physicians and therapists and patients are often not prepared to judge provided information of CAM health care approaches properly. Information dissemination of published evidence about the effectiveness of remedies and therapies therefore forms a necessary basis for shared decision making for patients and practitioners. In Europe, extracts from Viscum album (VA-E), the European white-berry mistletoe, are widely used to treat patients with cancer, in addition to patients with arthrosis, hypertension, arteriosclerosis, diabetes, and so forth [2] Historically, the intentions of mistletoe uses were manifold and conflicting in several cases (i.e., swellings or tumors, epilepsy, diseases of spleen and liver, labor pains, “weakness of the heart,” edema, eczema, ulcers of the feet, burns, and granulating wounds) [2]. In 1920, mistletoe extracts were introduced for the first time as a cancer treatment by Steiner (1861–1925) [3], the founder of anthroposophy. He recommended a drug extract produced in a complicated manufacturing process combining sap from mistletoe harvested in the winter and summer [4]. Based on his recommendations, several anthroposophical doctors have treated their cancer patients with these extracts within the last century. Meanwhile, clinical evaluations of mistletoe as an adjuvant cancer treatment have expanded. Recent scientific research has confirmed that mistletoe extracts induce apoptosis, stimulate immunocompetent cells, and protect the DNA of mononuclear cells (for review see [2, 5, 6]). Several experiments using tumor-bearing animals showed impressive reduction of tumor growth and/or increased survival with the application of mistletoe therapy (for review see [2, 5, 6]). There are several whole-plant extracts from Viscum album on the market which differ with respect to the extraction process and thus relative proportions of their constituents [7]. Due to this diversity of mistletoe products and their proportions of pharmacologically relevant constituents, the interpretation of clinical studies is difficult. Consequently it is not too surprising that preceding reviews on the clinical effects of mistletoe extracts in cancer patients, which summarizes a mixture of studies with different designs and plant extracts used, are conflicting in their results [6, 8–13]. Several of these reviews detected heterogeneity of studies with respect to the drug extracts used to treat the patients and thus are not suited to calculate reliable effects sizes. In fact, there are up to five different pharmaceutical processes of mistletoe extract preparation, and thus the pharmaceutical products show highly specific pattern of active components (i.e., pattern of cytotoxic mistletoe lectins, viscotoxins, etc.) [7]. To overcome this problem, we intended to determine the effectiveness of VA-E in the treatment of patients with cancer and focused on the most commonly used VA-E which is covered by a relatively large spectrum of published studies, the fermented plant extract Iscador (WELEDA AG, Switzerland). This whole-plant extract is produced from fresh leafy shoots and fruits of the summer and winter harvest, is rich on mistletoe lectins and viscotoxins [7, 14], and is recommended to be applied 2-3 times per week subcutaneously. While most clinical studies on the effects of VA-E focus on the survival of cancer patients, the effects on the patients' quality of life (QoL), which gains more and more importance as a relevant outcome variable in cancer therapy, received less consideration so far. Thus, we determined the effectiveness of the VA-E Iscador in the treatment of patients with cancer with respect to QoL-associated dimensions and analyzed the studies with respect to trials where patients of the control group received only standard care and no extra treatment. 2.1. Search StrategyBetween February and April 2008, we searched databases such as PubMed/Medline, the Excerpta Medica Database (EMBASE), the Cochrane Library, database of DIMDI (Deutsches Institut für Medizinische Dokumentation und Information), and CAMbase for clinical studies focusing on QoL-associated measures of cancer patients using Iscador extracts. Search terms were either “Iscador” and “study”, “mistletoe” and “study”, and “Viscum” and “study”. Finally we asked several experts for gray literature not listed in the above-mentioned databases, checked the reference lists of relevant articles and authors, and contacted the manufacturer of the VA-E. We performed an additional check for new studies in 2010, which did not reveal new results. 2.2. Selection CriteriaInclusion criteria were all controlled clinical studies (at least historic or literature) on parameters associated with quality of life in cancer patients treated with the VA-E Iscador, published in English or German language journals. Neither the experts in the field nor the manufacturer was aware of any other study published in French, Spanish, Chinese, or other languages. However, one study from Denmark was published in a Danish journal and in an English language journal, and thus we referred to both publications presenting data of the same study. We are not aware of unpublished studies on the effects of Iscador on QoL. We excluded field reports, case series, case reports, studies without a control group, abstracts which proceeded a full-length publication, translations of already published manuscripts, double publication of similar data (with the exception of the presentation of further data), internal reports, and unpublished manuscripts. 2.3. Analysis of DataTwo review authors independently assessed trials for inclusion in the review. They took part in the extraction of data and assessment of methodological quality and external validity. Disagreements were resolved by consensus. We graded the methodological quality of the studies by the following checklist (rater assessment): adequate description of the design (retrospective, prospective, retrolective, multicenter study, etc.), accrual (randomization, matched pairs, etc.), comparability of groups (controls and VA-E), description of dropouts, allocation concealment (analysis of concealed treatment allocation was difficult because most studies did not provide sufficient data to judge—either there were no statements or information was at least unclear), description of the intervention (dosage and duration of VA-E application), description of statistical analysis, and external validity (representative patients, relevant therapeutic concepts, generalization of results). Additionally we referred to the JADAD rating score which assesses randomization, blinding, and dropouts [15]. The reporting of the results adhered to the MOOSE [16] and QUOROM [17] guidelines. 2.4. Statistical AnalysisIf a trial was found to be eligible, assessments of its methodological quality were done independently by two reviewers (A. Büssing, T. Ostermann) and recorded on an especially predesigned data form together with the basic trial data and the extracted results. Allocation concealment was assessed in accordance with the Cochrane guidelines [18]:
Disagreements on methodological quality ratings were discussed by both assessors until they reached a consensus. Data were independently extracted by two persons (A. Büssing, T. Ostermann) and independently entered into a data form which was especially designed for trials on mistletoe by a third person (C. Raak). If the data entries differed, both reviewers were contacted to recheck the publications and were forced to come to a consensus, which could be reached in all cases. Data on the following details were extracted:
All data were separately analyzed for trials where patients of the control group received only standard care and no extra treatment (or placebo-controlled trials). QoL-associated outcome data (QoL questionnaires and scales: mean values and standard deviations, mean/median differences, effect estimates and confidence intervals, odds ratios, etc.) were extracted as they were given in the publication. They were converted into standardized mean differences (SMD) and their standard errors (STE) using standard formulas [18]. Effect sizes <0.5 indicate small effects and >0.8 large effects [19]. All studies were analysed in a single analysis, regardless of on what scale the results had originally been measured or reported. The association between sample size and trial results was graphically displayed in funnel plots, by plotting effect sizes on the horizontal axis (in a logarithmic scale) against their standard errors, or against the total patient numbers, on the vertical axis [20]. Funnel plots are adequate instruments to detect small study size effects, including publication bias. In the absence of bias, results from small studies should scatter widely at the bottom of the graph, with the spread narrowing among larger studies. Publication bias (and also lack of equipoise) may lead to asymmetrical funnel plots. Moreover, the asymmetry of the funnel plot was further explored by a weighted linear regression analysis (metaregression) which modeled the log SMD as a function of its standard error [21]. Weights were chosen inversely to the squared standard error. From this model, the asymmetry coefficient (AC) was estimated as the slope of the regression line. Heterogeneity between trials was assessed by standard χ²-tests and the I2 coefficient which measures the percentage of total variation across studies due to true heterogeneity rather than chance [22]. Overall estimates of the treatment effect were obtained from random-effect meta-analysis [23]. Additionally, from metaregression a predicted SMD was obtained for trials with a standard error as small as the smallest observed standard error of all included trials. The extent to which study-level variables were associated with SMDs was investigated by fitting multivariable metaregression models. The following variables were considered: standard error of SMD, tumor localization (breast, stomach, lung, colon, ovary, corpus, skin cancer yes/no), randomization (yes/no), and matched-pair comparison (yes/no)—due to the fact that all matched-pair studies were from the same source.
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