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Abstract

Background:

Breast cancer is the most common cancer type in women and quality of life an essential part of patients’ well-being. Although the treatment with mistletoe extracts is covered by multiple cancer guidelines and reviews, it is uncertain whether mistletoe extracts can improve the quality of life in breast cancer patients. We therefore performed a systematic review and meta-analysis on this topic.

Methods:

This systematic review included randomized clinical trials (RCTs) and non-randomized studies of intervention (NRSIs) comparing the quality of life in breast cancer patients treated with mistletoe extracts as add-on therapy to control groups treated conventionally. We searched previous systematic reviews and multiple databases until January 2023. We conducted a meta-analysis and assessed the risk of bias according to the Cochrane Handbook via RoB 2 and ROBINS-I and the certainty of evidence via GRADE, respectively.

Results:

Nine RCTs and 7 NRSIs with 833 and 2831 participants, respectively, were included. The pre-post changes for the quality of life resulted in a pooled standardized mean difference for RCTs of SMD = 0.61 (95% CI 0.47-0.75; P < .0001) and for retrospective NRSIs of SMD = 0.46 (95% CI 0.10-0.82; P = .01). The risk of bias was low to high for the RCTs and serious for all NRSIs. The certainty of evidence was moderate for RCTs and very low for NRSIs.

Discussion:

Our results indicate a clinically relevant, medium-sized effect of mistletoe extracts on the quality of life in breast cancer patients which may be based on the immunomodulating effects of mistletoe extracts during chemotherapy. The limitations of evidence include the risk of bias which is mainly caused by the difficulty of blinding. Further RCTs and real-world evidence need to confirm this result, especially in the setting of neoadjuvant chemotherapy and in breast cancer survivors.

Keywords

mistletoe breast cancer quality of life meta-analysis

Introduction

Breast cancer is the most frequent type of invasive cancer in women, with 2.3 million new cases worldwide in 2020.¹ Breast cancer and its standard medical treatment lead to an important decrease in quality of life (QoL), amounting to 19.6 million disability-adjusted life years globally for 2016.¹ QoL has been defined as “an overall general well-being that comprises objective descriptors and subjective evaluations of physical, material, social and emotional well-being together with the extent of personal development and purposeful activity, all weighted by a personal set of values.”^2,3 Apart from antineoplastic therapy, QoL in breast cancer patients is also influenced by multiple factors such as age, disease stage, and social and educational status.^4,5 In order to support QoL in breast cancer patients pharmacological and non-pharmacological interventions have been investigated.⁶

First developed by Wegman and Steiner, extracts from the European mistletoe (Viscum album L.) are authorized medicinal products with indications in supportive cancer care.^7,8 Mistletoe extracts (ME) are injected subcutaneously 2 to 3 times a week, during and beyond standard oncologic treatments.⁹ Recent meta-analyses of clinical studies concluded that application of ME produces a significant, medium-sized effect on QoL in cancer and may prolong survival.^10
-12 The most studied bioactive components are viscotoxins and lectins, but ME also contain other compounds such as flavonoids, phenolic acids and polysaccharides.¹³ One possible clinically observed mode of ME is immunomodulation, which may reduce inflammatory markers and the rate of neutropenia. This, together with a peripheral endorphin-release, may form the basis for an improvement of quality of life and reduction of side effects related to standard oncological therapies.^14,15 Further research is necessary, as modes of action are not fully elucidated due to the complexity of the bioactive compounds and since the phytochemical composition depends on the host tree and the way of pharmaceutical preparation¹³ Different preparations of ME (eg, Abnobaviscum, Helixor, Iscador, Iscucin, Lektinol) are used in clinical practice for various cancer entities, including breast cancer. Mistletoe therapy is individualized according to each patient’s clinical case and treatment response.¹⁶

ME are included in multiple guidelines,^17
-19 but certain aspects of their efficacy continue to be discussed. ME are noted in the recommendations of the German Working Group on Gynecological Oncology, the guidelines of the American Society of Integrative Oncology (endorsed by the American Society for Clinical Oncology) and of the German Cancer Society.^17
-19 In all 3 of these, ME are indicated as optional treatment to improve QoL of solid tumor patients. This indication comes with a level of evidence 1a, attributed to therapies assessed via systematic reviews of randomized clinical trials (RCTs).¹⁹ The main points of discussion are the lack of double-blinded RCTs and the heterogeneity of results.^20,21 The heterogeneity could be explained by the broadness of previous meta-analyses since none of the previous meta-analyses focused on 1 cancer entity only.^12,22 However, a subgroup analysis yielded smaller heterogeneities for breast or lung cancer studies when compared to all cancer types.¹² In addition, our earlier work included prospective studies only¹² and in turn neglected retrospective non-randomized studies of intervention (NRSIs) that may contribute to the evidence. This is particularly relevant in the light of a recent GRADE guideline regarding the integration of NRSIs into the assessment of evidence certainty²³ when no high level of evidential certainty from RCTs alone exists and NRSIs provide complementary data.²³ The latter is the case here since individualization is common among ME treatment and real-world data, as provided by NRSIs, are an important complement to RCTs in personalized medicine.²⁴

Therefore, the aim of this study is to systematically review the literature on ME treatment in breast cancer patients in order to synthesize both RCTs and NRSIs through meta-analysis and evidence assessment.

Methods

The review has been reported according to PRISMA,²⁵ and the protocol was registered with the PROSPERO database prior to analysis (CRD42023388900).

Literature Search

Studies were searched for in 2 previous systematic reviews.^12,22 In addition, Medline, Embase, the Cochrane Central Register of Controlled Trials, Clinicaltrials.gov, Google scholar, and the database of the Society for Cancer Research²⁶ were screened. Our search strategy combined the 3 terms “breast cancer,” “quality of life” and “mistletoe” including their synonyms and was adopted for each database. As an example, the search for Medline can be seen in the Supplemental (see Supplemental 1).

We included RCTs as well as NRSIs which compared breast cancer patients treated with ME to a control group. In case of insufficient data we contacted the authors of Oei et al for additional information.²⁷

Extraction

Data was extracted from each study independently by 2 reviewers (HW, ML) and covered the following items: lead author, year of publication, country where the study was conducted, patient characteristics (age, sex, number of patients in each arm), duration of study, type of study (interventional vs non-interventional, randomized vs non-randomized, blinded vs not blinded, single vs multi-center); additional therapy (eg, chemotherapy); number of drop-outs in each study arm; ME preparation (eg, Eurixor); control treatment (eg, placebo); effect size of primary outcomes plus standard deviation; applied instrument to measure primary outcomes; statistics according to intent-to-treat analysis (yes/no); sponsoring of study. Two reviewers (HW, ML) compared the independent extractions and resolved differences by discussion.

Bias Assessment

Risk of bias assessment was performed by 2 authors (HW, ML) according to the Cochrane handbook, that is, Rob-2 for RCTs and ROBINS-I for NRSIs.^28
-30

Statistical Analyses

Data from RCTs and from NRSIs were analyzed separately according to chapter 24 of the Cochrane Handbook.²⁸ The effect sizes are presented as standardized mean differences (SMD) of the changes from baseline to post-intervention between the verum and the control group for RCTs and NRSIs. Odds ratios (OR) were converted to SMD following the Hasselblad and Hedges and Hedges’ method if necessary.^31,32 The Mann Whitney statistics were transformed to SMD as described by Rahlfs et al.³³

The data were analyzed using R version 4.2.2 including the packages meta as well as Comprehensive Meta-Analysis V.2 to perform a meta-analysis in order to obtain a pooled estimate of the effect of ME on QoL. We assessed the heterogeneity between studies using the Cochrane Q test and quantified it by the index of heterogeneity (I²), the heterogeneity variance τ² and a prediction interval.^34,35 If I² was 50% or higher and the confidence interval of τ² did not contain 0, we applied a random-effect meta-analysis in accordance with the study protocol, otherwise we used a fixed-effect model. We conducted a meta-regression with RCTs and regressed the age of the patients, the study year, and the study duration on effect-size.

Sensitivity Analysis

Sensitivity analyses were conducted to examine the robustness of the results. To reduce heterogeneity, 2 prospective NRSIs^36,37 were not included in the main analyses, following Higgins et al²⁸ but added in the sensitivity analyses. In addition, we excluded 2 studies that measured self-regulation^37,38 and one study which applied ME i.v.,³⁹ respectively. If studies reported no validated scale for measuring QoL but multiple surrogate parameters,^40
-42 we used the measure with the highest comparability to the other effect sizes in the analyses (eg, symptom scores over performance status) and inserted other measures for sensitivity analyses.

Subgroup Analyses

Subgroup analyses were conducted for the following moderators: blinding status, tumor stage, ME preparation, and risk of bias.

Publication Bias

We checked for signs of a publication bias by examining funnel plots, Egger’s test⁴³ and Duval and Tweedie’s trim-and-fill procedure.⁴⁴

Certainty Assessment

The certainty of evidence was assessed with GRADE.⁴⁵ In short, the rating starts at “high” for RCTs and at “low” for NRSIs and can be rated down 1 or 2 levels for the 5 domains risk of bias, inconsistency, indirectness, imprecision, and publication bias. The quality of evidence can be rated up for NRSIs in case of large effect sizes, a dose-response gradient or if residual confounding supports inferences regarding the treatment effect.

Results

Study Selection and Characteristics

The literature search combined the search of database with the results of 2 earlier systematic reviews.^12,22 The search flow is shown in Figure 1.

Figure 1.

Search flow (*³⁷ with 2 cohorts (1 RCT and 1 NRSI) in 1 publication).

Sixteen studies presented in 15 publications have been included of which 9 are RCTs^{37
-39,46
-51} 7 are NRSIs.^{27,36,37,40
-42,52} One study included 2 cohorts with one being a RCT whereas the other is a NRSI.³⁷ Two RCTs were double-blinded^48,49 7 are unblinded. Two NRSIs were prospective^36,37 while the remaining 5 were retrospective. The characteristics of all studies are presented in Table 1.

Table 1.

Characteristics of Included Studies.

Reference	Country	Study type	Participants (N1 (N2); age)		Cancer stage	Intervention		QoL measurement
Reference	Country	Study type	Verum	Control	Cancer stage	Verum	Control	QoL measurement
Borrelli⁴⁶	Italy	RCT, single-center, unblinded	20 (20); n/a	10 (10); n/a	IV	ME (not specified), surgery, chemo	Water, surgery, chemo	Spitzer
Büssing et al³⁹	Germany	RCT, multi-center, unblinded	32 (32); 54.7	33 (31); 54.7	n/a	Iscador M spezial, chemo, radio	Chemo, radio	EORTC-QLQ-C30
Grossarth-Maticek and Ziegler³⁷	Germany	RCT, multi-center, unblinded, matched pairs	39 (38); 52.8	39 (38); 52.9	pT1a-3, pN0, M0	Iscador, conventional therapy	Conventional therapy	Self-regulation
Grossarth-Maticek and Ziegler³⁷	Germany	NRSI, multi-center, unblinded, matched pairs	97 (83); 52.2	97 (83); 52.2	pT1-3, pN0, M0	Iscador, conventional therapy	Conventional therapy	Self-regulation
Grossarth-Maticek and Ziegler³⁸	Germany	RCT, multi-center, unblinded, matched pairs	17 (17); 44.5	17 (17); 44.6	pT2-4, pN1-4, M0	Iscador, conventional therapy	Conventional therapy	Self-regulation
Heiny et al¹⁵	Germany	RCT, single-center, unblinded	25 (21); n/a	21 (19); n/a	IV	Eurixor, chemo	Chemo, infusion of saline solution	QoL scale based on FLIC, self-assessment
Semiglasov et al⁴⁸	Bulgaria, Russia, Ukraine	RCT, multi-center, blinded	67 (65); 44.6	70 (66); 43.5	pT1-3, pN0 N+, M0	Lektinol (PS76A), chemo	Placebo, chemo	GLQ-8, Spitzer
Semiglazov et al⁴⁹	Bulgaria, Russia, Ukraine	RCT, multi-center, blinded	176 (169); 46.4	176 (168); 45.9	pT1-3, pN0 N+, M0	Lektinol (PS76A), chemo	Placebo, chemo	FACT-G, GLQ-8, Spitzer
Tröger et al⁵⁰	Serbia	RCT, single-center, unblinded	30; 48.4	31; 50.8	pT1-3, pN0-2, M0	Iscador M spezial, chemo	Chemo	EORTC-QLQ-C30
Tröger et al⁵¹	Serbia	RCT, single-center, unblinded	34 (32); 50.4	31 (29); 50.8	pT1-3, pN0-2, M0	Helixor, chemo	Chemo	EORTC-QLQ-C30
Beuth et al⁴⁰	Germany	NRSI, multi-center, unblinded, retrospective	227 (167); 55.1	514 (514); 54.6	n/a	Helixor, radio-, chemo, hormone	Radio-, chemo, hormone	Clinician reported
Fritz et al⁵²	Germany	NRSI, multi-center, unblinded, retrospective	151 (23); 55.5	453 (77); 55.7	I-IV	Any ME, radio-, chemo, hormone	Radio-, chemo, hormone	EORTC-QLQ-C30
Loewe-Mesch³⁶	Germany	NRSI, single-center, unblinded	39 (33); 47.5	43 (33); 47.5	pT1-3, N0-N2; M0	Iscador M spezial, chemo	Chemo	EORTC-QLQ-C30
Oei et al²⁷	Germany	NRSI, single-center, unblinded, retrospective	129 (92); 56.4	190 (161); 60.7	Any stage	Any ME, conventional therapy	Conventional therapy	EORTC-QLQ-C30
Schmidt⁴¹	Germany	NRSI, multi-center, unblinded, retrospective	710 (615); 53	732 (669); 57	I-III	Any Iscador, radio-, chemo, hormone	Radio-, chemo, hormone	Clinician reported
Schumacher et al⁴²	Germany	NRSI, multi-center, unblinded, retrospective	219 (219); 60	470 (470); 64	I-III	Eurixor, radio-, chemo, hormone	Radio-, chemo, hormone	Clinician reported

Abbreviations: N1, total number of participants at baseline; N2, participants included in the meta-analyses, the age corresponds to N1.

Results of Synthesis

For RCTs, a fixed-effect meta-analysis was performed, shown in Figure 2. The estimated pooled effect size is SMD = 0.61 (95% CI 0.47-0.75). The between-study heterogeneity was estimated with I² = 12.3 % (95% CI 0.0%-54.1%). The heterogeneity variance was τ² = 0.01 (95% CI 0.000-0.13) and the prediction interval ranged from 0.31 to 0.86, indicating neither heterogeneity nor negative intervention effects for future studies. The sensitivity analyses (see Table 2) and the subgroup analyses (see Table 3) shows that the analysis is robust against alternative sets of conditions and in subdomains of the total population. There is a tendency for methodologically more rigorous studies to yield higher or equally high effect sizes compared to less rigorous ones. Blinded studies showed a tendency for a higher effect size (SMD = 0.69, 95% CI 0.38-0.97) than unblinded ones (SMD = 0.47, CI 0.27-0.68).

Figure 2.

Fixed-effect meta-analysis pooling standardized mean differences from RCT regarding the effect of mistletoe extracts versus control on quality of life in breast cancer patients.

Table 2.

Sensitivity Analyses for RCT and NRSI.

Moderator	N	SMD	95% CI		I ²	95% CI		z-Score	P-value	Tau²	95% CI		Prediction interval
RCT
Addition of 2 prospective NRSI^37,38	11	0.51	0.39	0.63	50%	0%	75%	8.19	.0001	0.04	0	0.19	−0.05	0.97
Exclusion of 1 study with i.v.⁴⁰	8	0.65	0.5	0.79	0%	0%	68%	8.73	.0001	0	0	0.1	0.46	0.83
Exclusion of self-regulation^38,39	7	0.62	0.47	0.77	33%	0%	72%	8.07	.0001	0.03	0	0.24	0.05	1.07
NRSI
Addition of 2 prospective NRSI^37,38	7	0.37	0.07	0.67	95%	92%	97%	2.43	.0149	0.14	0.05	0.71	−0.66	1.4
Karnofsky index instead of symptom score as QOL surrogate in 3 studies^41 -43	5	0.05	−0.11	0.22	5%	0%	80%	0.64	.5221	0.02	0	0.23	−0.55	0.72

Table 3.

Subgroup Analyses for RCT and NRSI.

RCT
Moderator	N	SMD	95% CI		I ²	95% CI		z-Score	P-value	Tau²	95% CI		Prediction interval
Blinding^a	W
Yes	2	0.69	0.38	0.97	57%	0%	90%	4.37	.0001	0.03	n/a	n/a	n/a	n/a
No	7	0.47	0.27	0.68	0%	0%	71%	4.5	.0001	0	0	0.15	0.20	0.74
Tumor stage
1-3	4	0.68	0.51	0.86	33%	0%	76%	7.63	.0001	0.03	0	0.63	−0.26	1.49
Including 4	4	0.57	0.31	0.82	0%	0%	85%	4.3	.0001	0	0	0.38	0	1.13
ME preparation^a
Iscador	4	0.39	0.13	0.64	0%	0%	85%	2.99	.003	0	0	0.55	−0.17	0.95
Lektinol	2	0.69	0.38	0.97	57%	0%	90%	4.37	.0001	0.03	n/a	n/a	n/a	n/a
Risk of bias
High	6	0.45	0.22	0.67	0%	0%	75%	3.89	.0001	0	0	0.25	0.13	0.77
Low or some concern	3	0.71	0.53	0.88	22%	0%	92%	7.86	.0001	0.01	0	1.05	−1.46	2.82
NRSI
Measurement
Clinician reported	3	0.58	−0.07	1.23	98%	97%	99%	1.76	.08	0.32	0.07	11.46	−7.76	8.93
EORTC-QLQ-C30	2	0.20	−0.03	0.42	0%	n/a	n/a	n/a	n/a	0	n/a	n/a	n/a	n/a

The 2 blinded studies are also geographically distinct, being conducted in Bulgaria, Russia and Ukraine.

For retrospective NRSIs, the pooled effect size has been calculated using a random-effect model, yielding a SMD = 0.46 (95% CI 0.1-0.82), as shown in Figure 3. The between-study heterogeneity was estimated with I² = 96.5 % (95% CI 94.1%-97.9%), the heterogeneity variance was τ² = 0.15 (95% CI 0.05-1.25) and the prediction interval ranged from −0.92 to 1.84. Thus, all 3 parameters reveal statistical heterogeneity regarding the NRSI analysis. A subgroup analysis, shown in Table 3, reveals that different types of measurement (self-reported vs clinician-reported) result in tendentially different effect sizes.

Figure 3.

Random-effect meta-analysis pooling standardized mean differences from NRSI regarding the effect of mistletoe extracts versus control on quality of life in breast cancer patients.

Meta-regression identified age of the patients as a potential predictor. The meta-regression model for the group of RCTs was not significant (P = .06), the negative slope indicates a linear decrease of QoL by 0.04 standard deviations for each additional year of age (Supplemental Figure 3). The meta-regression of study year on effect size was not significant and the relationship was a flat line (data not shown). A meta-regression of study duration on effect size yielded no significant effect as well.

Risk of Bias

For RCTs, the risk of bias was assessed with Cochrane’s ROB2 tool. Six studies had a “high” risk of bias, 2 resulted in an overall rating of “some concern,” and 1 study was assessed with a “low” risk of bias (see Figure 4 for a summary and Figure 5 for a domain- and study-specific view of the ratings). The subgroup analysis (Table 3) showed a tendency for larger effects for studies with low risk of bias or some concern (SMD = 0.71, 95% CI 0.53-0.88) compared to studies with high risk of bias (SMD = 0.45, 95% CI 0.22-0.67). The risk of bias of the NRSI was estimated using Cochrane’s ROBINS-1. The overall risk of bias was “serious” for all 6 studies (Figure 6).

Figure 4.

Summary of risk of bias assessment of RCTs with ROB2 as percentage (intention-to-treat).

Figure 5.

Details of risk of bias assessment of RCT according to Cochrane RoB 2 tool (intention-to-treat).

Figure 6.

Details of risk of bias assessment of NRSI according to Cochrane ROBINS-1 tool.

Reporting Biases

A possible publication bias was assessed for both RCTs and NRSIs by visual examination, by Egger’s test and by the Duval & Tweedie’s trim-and-fill procedure. For RCTs, the Egger’s test resulted in an intercept of I = −1.6 (95% CI −3.36-0.16) and is not significant (P = .068). Duval and Tweedie’s trim and fill procedure did not identify any study to the left, that is, to the more negative side of the mean effect size to be trimmed, but 4 to the right side, which would adjust the effect size more positively to SMD = 0.74. As it is unlikely that researchers would have missed publishing more positive studies, we see this as a support of a lack of publication bias. There was no indication for a visual funnel plot asymmetry (see Supplemental Figure S1 in the Supplemental). We used all 7 NRSIs for a publication bias analysis. Duval and Tweedie’s trim and fill method yielded no studies to be trimmed and filled to either direction of the mean, and Egger’s intercept test was not significant (I = 0.97 (95% CI −8.6-10.5; P = .8)), whereas visual inspection of the funnel plot (see Supplemental Figure S2 in the Supplemental) neither favors nor disfavors a publication bias.

Certainty of Evidence

The certainty of evidence was assessed with the GRADE approach. We downgraded the quality of evidence for the RCT analysis from “high” to “moderate” by one point due to the risk of bias. The risks of inconsistency, indirectness, imprecision, and publication bias were not downgraded. For NRSI, the certainty of evidence starts at “low” according to GRADE and was further downgraded to “very low” by one point regarding the risk of bias and for inconsistency.

Discussion

General Interpretation in Context of Other Evidence

Our analysis is, to our knowledge, the first meta-analysis to focus on the effect of ME on 1 cancer entity. We found a medium effect size of ME on the QoL of breast cancer patients with little heterogeneity between studies, compared to larger heterogeneity in an earlier study where different types of cancer were included in an overall meta-analysis.¹²

The magnitude of the effect size is comparable to, or larger than those of other interventions for breast cancer: Physical activity improves quality-of-life scores compared to control with a mean difference of 6.78 (95% CI 2.61-10.95) which corresponds to SMD = 0.08 (0.03-0.13) with a “probable” likelihood of causality.⁵³ Cognitive behavioral therapy (CBT) was reported to improve QoL with an SMD of 0.65 (95% CI 0.07-1.23) and a very low quality evidence in 1 study,⁵⁴ whereas Getu et al estimated an effect of SMD = 0.39 (95% Ci 0.12-0.66) and concluded that CBT is effective in improving the QoL of breast cancer patients. Compared to no therapy, yoga enhanced quality of life in breast cancer patients (SMD = 0.22 (95% CI 0.04-0.40)) with moderate-quality evidence.⁵⁵ Mindfulness interventions improved quality of life in breast cancer patients by SMD = 0.21.⁵⁶

Our findings suggest that the effect is robust: heterogeneity was low for the randomized studies, so a fixed effect model could be applied. There was no effect of the years the studies were conducted in on effect size, implying that methodological improvements that are assumed to be put in place over the years did not impact effect sizes. Effect sizes for blinded randomized studies, that is, methodologically more reliable studies were highest. However, this might be confounded with the fact that these studies were run in Russia, Bulgaria or Ukraine, where the effect size was SMD = 0.69 as opposed to studies run in Germany, Switzerland or Austria where effect size was SMD = 0.47. The advantage of studies performed in Eastern Europe may be that ME are much less known and could not be acquired in pharmacies, lowering the risk of unidentified application in the control groups. The ensuing lack of knowledge of side effects (eg, skin reactions) increases the probability that blinding was successful. Possibly lower health standards in Eastern Europe, with less supportive care, might suggest that the effect size shown in this setting is the “ME only” effect, while this effect is diminished in Western Europe, where patients have access to other supportive therapies. The effect size of all randomized studies is numerically higher (SMD = 0.61) than that of the non-randomized studies (SMD = 0.46), albeit not significant. Apparently, real world settings do not seem to increase the effectiveness of ME with regards to overall QoL. This might have to do with the fact that such real-world documentations are often more susceptible to implementation difficulties regarding QoL data-collection procedures and unidentified influences compared to randomized studies. Nonetheless, the NRSIs provide higher external validity by the real world setting and support the results deriving from RCTs that have inherently higher internal validity.

Limitations of the Evidence Included in the Review

Several limitations of the underlying evidence should be kept in mind. First, the reliability of measurement of QoL in breast cancer patients has improved strongly,⁶ but some of the included studies reported on parameters which can only be regarded as surrogates of QoL. While the exclusion of studies that measured “self-regulation” showed no substantial impact compared to the main RCT-analysis, the sensitivity analyses for NRSIs revealed that the alternation of surrogate parameters shifted the results into non-significance. One has to bear in mind, however, that the alternate effect measure was the Karnofsky index which is not a uniformly reliable QoL scale, and is applicable particularly for patients with terminal cancers,⁵⁷ while the majority of the patients in the NRSIs were in stages I-III.

Second, the included studies were heterogeneous regarding for example, tumor stages, QoL scales, blinding, and risk of bias. In contrast, the RCT-analysis showed no sign for between-study heterogeneity for all 3 statistical parameters. Third, the risk of bias was low in 1 RCT only, yet medium to high in 8 RCTs and serious for all NRSIs, respectively, which resulted in the downgrading of the quality of evidence according to GRADE. This risk of bias assessment is persistently rated as “medium” even in well-conducted ME studies, because of its therapy-inherent difficulty to blind the treatment. Subcutaneous injections of ME regularly lead to local skin reactions which makes them discernible, and active placebos that would mimic such irritations are normally not accepted by ethical committees or clinicians for ethical reasons. This should be borne in mind when assessing the RoB-status of the evidence.

Limitations of the Review Process

Our approach was to include both RCTs and NRSIs into the analysis in order to cover the clinical evidence from trials and real-world practice. This leads to unresolved issues regarding the GRADE approach,⁵⁸ since it remains unclear whether RCTs and NRSIs should be considered en bloc if the certainty of evidence is assessed and how the certainties of different study types are balanced out to achieve an overall assessment.^23,58 In practice, only very few reviews pool the evidence syntheses⁵⁹ which necessitates proper guiding.⁶⁰

Furthermore, the GRADE approach dictates to start the rating at a “high” level for RCTs and, as in the present case, at a “low” level for NRSIs.⁶¹ For RCTs, the certainty of evidence was assessed as “moderate” and for NRSI “very low.” Although the statistical results of our analysis needs to be seen in this light, it is also important to remember that the GRADE framework has been criticized to lack a theoretical and empirical basis showing that it helps therapists to make better treatment decisions for their patients.^62,63

Another limitation of the review process is that the adverse events and interactions with co-medications are not covered by this review. A recent analysis regarding the effects of ME on fatigue found few adverse events reported by studies that are also included here.²²

Since a recent comment questioned the usefulness of the I² statistics,⁶⁴ we calculated a prediction interval which provides a range in which future studies can be expected to fall based on the current evidence. For RCTs, it doesn’t include negative intervention effects [0.12; 0.93] which is further supported by our trim-and-fill analysis that indicated the true effect size to be even higher than that reported in the main analysis. The reliability of the trim-and-fill approach may be, however, limited due to the low number of included studies.

Implications for Practice, Policy, and Future Research

In general, the QoL of patients with breast cancer improved over the last decade⁶⁵ and our analysis indicates that compared with other potential interventions, ME may be an effective additional treatment which, due to their immunomodulating effects, may reduce side effects of other anti-cancer treatments. We feel that our data supports the inclusion of ME into current guidelines as optional additive treatments with a likely positive effect on QoL. These first results, with a low heterogeneity despite including different ME preparations, seem to confirm the current clinical practice that different ME preparations can be used for the same cancer entity.

Our results will need verification in light of future trials that overcome the above-mentioned limitations.⁶⁶ Future research should focus, in our view, on solid prospective real-world evidence in large cohorts of patients whose baseline status is well described such that predictive assessments and analyses can be calculated to figure out what types of patients, for example, which cancer stage and breast cancer subtype, will benefit from ME treatment. Also, such studies might be helpful in putting the evidence from randomized studies into context.⁶⁷ Particular attention should be paid to ME effects for breast cancer patients undergoing neoadjuvant chemotherapy and breast cancer survivors, as their numbers are increasing and no study in this setting could be found in this meta-analysis.

Supplemental Material

sj-docx-1-ict-10.1177_15347354231198074 – Supplemental material for Quality of Life in Breast Cancer Patients Treated With Mistletoe Extracts: A Systematic Review and Meta-Analysis

Supplemental material, sj-docx-1-ict-10.1177_15347354231198074 for Quality of Life in Breast Cancer Patients Treated With Mistletoe Extracts: A Systematic Review and Meta-Analysis by Martin Loef, Daniela Paepke and Harald Walach in Integrative Cancer Therapies

Footnotes

Availability of Data

Additional data of this study are available on request from the corresponding author.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The review has been supported by the “Stiftung Integrative Medizin & Pharmazie” (Stuttgart).

Data Support

We are grateful for additional data provided on request by Oei et al.²⁷

Protocol

The corresponding protocol was registered at PROSPERO with the number CRD42023388900.

ORCID iDs

Martin Loef

Harald Walach

Supplemental Material

Supplemental material for this article is available online.

References

Łukasiewicz

Czeczelewski

Forma

Baj

Sitarz

Stanisławek

Breast cancer-epidemiology, risk factors, classification, prognostic markers, and current treatment strategies-an updated review. Cancers. 2021;13:4287.

Felce

Perry

Quality of life: its definition and measurement. Res Dev Disabil. 1995;16:51-74.

Karimi

Brazier

Health, health-related quality of life, and quality of life: what is the difference?

Pharmacoeconomics. 2016;34:645-649.

Engel

Kerr

Schlesinger-Raab

Eckel

Sauer

Hölzel

Predictors of quality of life of breast cancer patients. Acta Oncol. 2003;42:710-718.

Safaee

Moghimi-Dehkordi

Zeighami

Tabatabaee

Pourhoseingholi

Predictors of quality of life in breast cancer patients under chemotherapy. Indian J Cancer. 2008;45:107-111.

Mokhtari-Hessari

Montazeri

Health-related quality of life in breast cancer patients: review of reviews from 2008 to 2018. Health Qual. Life Outcomes. 2020;18:338-425.

Kienle

GS.

The story behind mistletoe: a European remedy from anthroposophical medicine. Altern Ther Health Med. 1999;5:34-36.

Rostock

Die Misteltherapie in der Behandlung von Patienten mit einer Krebserkrankung. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2020;63:535-540.

Horneber

Bueschel

Huber

Linde

Rostock

Mistletoe therapy in oncology. Cochrane Database Syst Rev. 2008;2008:CD003297.

10.

Ostermann

Appelbaum

Poier

Boehm

Raak

Büssing

A systematic review and meta-analysis on the survival of cancer patients treated with a fermented Viscum album L. Extract (Iscador): an update of findings. Complement Med Res. 2020;27:260-271.

11.

Loef

Walach

Survival of cancer patients treated with non-fermented mistletoe extract: a systematic review and meta-analysis. Integr Cancer Ther. 2022;21:15347354221133561.

12.

Loef

Walach

Quality of life in cancer patients treated with mistletoe: a systematic review and meta-analysis. BMC Complement Med Ther. 2020;20:227-314.

13.

Kleszken

Timar

Memete

Miere

Vicas

SI.

On overview of bioactive compounds, biological and pharmacological effects of mistletoe (Viscum album L). Pharmacophore. 2022;13:10-26.

14.

Oei

Thronicke

Schad

Mistletoe and immunomodulation: insights and implications for anticancer therapies. Evid Based Complement Alternat Med. 2019;2019:1-6.

15.

Heiny

Albrecht

Beuth

Correlation of immune cell activities and beta-endorphin release in breast carcinoma patients treated with galactose-specific lectin standardized mistletoe extract. Anticancer Res. 1998;18:583-586.

16.

Wider

Rostock

Huntley

van Ackeren

Horneber

Mistletoe extracts for cancer treatment. Cochrane Database Syst Rev. 2022; CD014782. doi:10.1002/14651858.cd014782

17.

Lyman

Greenlee

Bohlke

, et al. Integrative therapies during and after breast cancer treatment: ASCO endorsement of the SIO clinical practice guideline. J Clin Oncol. 2018;36:2647-2655.

18.

Liedtke

Thill

Hanf

Schütz

, et al. AGO recommendations for the diagnosis and treatment of patients with early breast cancer: update 2014. Breast Care. 2014;9:189-200.

19.

Deutsche Krebsgesellschaft. Leitlinienprogramm Onkologie (Deutsche Krebsgesellschaft, Deutsche Krebshilfe, AWMF): Komplementärmedizin in der Behandlung von onkologischen PatientInnen, Langversion 1.1, 2021, AWMF Registernummer: 032/055OL. 2021. Accessed March 31, 2023, https://www.leitlinienprogramm-onkologie.de/leitlinien/komplementaermedizin/

20.

Schnell-Inderst

Steigenberger

Mertz

Otto

Flatscher-Thöni

Siebert

. Additional Treatment With Mistletoe Extracts for Patients With Breast Cancer Compared to Conventional Cancer Therapy Alone–Efficacy and Safety, Costs and Cost-Effectiveness, Patients and Social Aspects, and Ethical Assessment. DIMDI; 2021:0-80.

21.

Staupe

Buentzel

Keinki

Buentzel

Huebner

Systematic analysis of mistletoe prescriptions in clinical studies. J. Cancer Res. Clin. Oncol. 2023;149:5559-5571.

22.

Pelzer

Loef

Martin

Baumgartner

Cancer-related fatigue in patients treated with mistletoe extracts: a systematic review and meta-analysis. Support. Care Cancer. 2022;30:6405-6418.

23.

Cuello-Garcia

Santesso

Morgan

, et al. GRADE guidance 24 optimizing the integration of randomized and non-randomized studies of interventions in evidence syntheses and health guidelines. J Clin Epidemiol. 2022;142:200-208.

24.

Ramagopalan

Simpson

Sammon

Can real-world data really replace randomised clinical trials?

BMC Med. 2020;18:13-22.

25.

Page

McKenzie

Bossuyt

, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev. 2021;10:89-11.

26.

Society for Cancer Research. Literatursuche. 2021. Accessed December 15, 2022. www.vfk.ch/informationen/literatursuche/

27.

Oei

Thronicke

Kröz

von Trott

Schad

Matthes

Impact of oncological therapy and Viscum album L treatment on cancer-related fatigue and internal coherence in nonmetastasized breast cancer patients. Integr Cancer Ther. 2020;19:1534735420917211.

28.

Higgins

JPT

Thomas

Chandler

Cumpston

MLT

Page

(eds.). Cochrane Handbook for Systematic Reviews of Interventions Version 6. The Cochrane Collaboration; 2019.

29.

Sterne

Savović

Page

, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366:l4898. doi:10.1136/bmj.l4898

30.

Sterne

Hernán

Reeves

, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016;355:i4919. doi:10.1136/bmj.i4919

31.

Hasselblad

Hedges

LV.

Meta-analysis of screening and diagnostic tests. Psychol Bull. 1995;117:167-178.

32.

Chinn

A simple method for converting an odds ratio to effect size for use in meta-analysis. Stat Med. 2000;19:3127-3131.

33.

Rahlfs

Zimmermann

Lees

KR.

Effect size measures and their relationships in stroke studies. Stroke. 2014;45:627-633.

34.

Higgins

JPT

Thompson

SG.

Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539-1558.

35.

Harrer

Cuijpers

Furukawa

Ebert

DD.

Doing Meta-Analysis With R: A Hands-On Guide. Chapman & Hall/CRC Press; 2021.

36.

Loewe-Mesch

Kuehn

Borho

, et al. Adjuvante simultane Mistel-/Chemotherapie bei Mammakarzinom – Einfluss auf immunparameter, Lebensqualität und Verträglichkeit. Complement Med Res. 2008;15:22-30.

37.

Grossarth-Maticek

Ziegler

Prospective controlled cohort studies on long-term therapy of breast cancer patients with a mistletoe preparation (Iscador^®). Complement Med Res. 2006;13:285-292.

38.

Grossarth-Maticek

Ziegler

Randomised and non-randomised prospective controlled cohort studies in matched-pair design for the long-term therapy of breast cancer patients with a mistletoe preparation (Iscador): a re-analysis. Eur J Med Res. 2006;11:485-495.

39.

Büssing

Bückner

Enser-Weis

, et al. Modulation of chemotherapy-associated immunosuppression by intravenous application of Viscum album L. Extract (Iscador): a randomised phase II study. Eur J Integr Med. 2008;1:2-3.

40.

Beuth

Schneider

Schierholz

JM.

Impact of complementary treatment of breast cancer patients with standardized mistletoe extract during aftercare: a controlled multicenter comparative epidemiological cohort study. Anticancer Res. 2008;28:523-527.

41.

Schmidt

NE.

Die postoperative komplementäre Therapie des primären Mammakarzinom mit lektinnormiertem Mistelextrakt - eine epidemiologische, kontrollierte retrolektive Kohortenstudie. Charité – Universitätsmedizin; 2007.

42.

Schumacher

Schneider

Reich

, et al. Influence of postoperative complementary treatment with lectin-standardized mistletoe extract on breast cancer patients. A controlled epidemiological multicentric retrolective cohort study. Anticancer Res. 2003;23:5081-5087.

43.

Egger

Davey Smith

Schneider

Minder

Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629-634.

44.

Duval

Tweedie

Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56:455-463.

45.

Guyatt

Oxman

Schünemann

Tugwell

Knottnerus

GRADE guidelines: a new series of articles in the Journal of Clinical Epidemiology. J Clin Epidemiol. 2011;64:380-382.

46.

Borrelli

Evaluation of the quality of life in breast cancer patients undergoing lectin standardized mistletoe therapy. Minerva Med. 2001;92:105-107.

47.

Heiny

Additive Therapie mit standardisiertem Mistelextrakt reduziert die Leukopenie und verbessert die Lebensqualität von Patientinnen mit fortgeschrittenem Mammakarzinom unter palliativer Chemotherapie (VEC-Schema). Krebsmed. 1991;12:1-14.

48.

Semiglasov

Stepula

Dudov

Lehmacher

Mengs

The standardised mistletoe extract PS76A2 improves QoL in patients with breast cancer receiving adjuvant CMF chemotherapy: a randomised, placebo-controlled, double-blind, multicentre clinical trial. Anticancer Res. 2004;24:1293-1302.

49.

Semiglazov

Stepula

Dudov

Schnitker

Mengs

Quality of life is improved in breast cancer patients by standardised mistletoe extract PS76A2 during chemotherapy and follow-up: a randomised, placebo-controlled, double-blind, multicentre clinical trial. Anticancer Res. 2006;26:1519-1529.

50.

Tröger

Jezdić

Ždrale

Tišma

Hamre

Matijašević

Quality of life and neutropenia in patients with early stage breast cancer: a randomized pilot study comparing additional treatment with mistletoe extract to chemotherapy alone. J Artic Breast Cancer Bas Clin Res. 2009;3:35-45.

51.

Tröger

Ždrale

Tišma

Matijašević

Additional therapy with a mistletoe product during adjuvant chemotherapy of breast cancer patients improves quality of life: an open randomized clinical pilot trial. J Artic Evid Complement Altern Med. 2014;2014:1-9. doi:10.1155/2014/430518

52.

Fritz

Dippon

Mueller

, et al. Is mistletoe treatment beneficial in invasive breast cancer? A new approach to an unresolved problem. Anticancer Res. 2018;38:1585-1593.

53.

Aune

Markozannes

Abar

, et al. Physical activity and health-related quality of life in women with breast cancer: a meta-analysis. JNCI Cancer Spectr. 2022;6:ac072.

54.

Jassim

Whitford

Hickey

Carter

Psychological interventions for women with non-metastatic breast cancer. Cochrane Database Syst Rev. 2015;CD008729. doi: 10.1002/14651858.CD008729

55.

Getu

Chen

Panpan

Mboineki

Dhakal

The effect of cognitive behavioral therapy on the quality of life of breast cancer patients: a systematic review and meta-analysis of randomized controlled trials. Qual Life Res. 2021;30:367-384.

56.

Haller

Winkler

Klose

Dobos

Kümmel

Cramer

Mindfulness-based interventions for women with breast cancer: an updated systematic review and meta-analysis. Acta Oncol. 2017;56:1665-1676.

57.

Timmermann

‘Just give me the best quality of life questionnaire’: the Karnofsky scale and the history of quality of life measurements in cancer trials. Chronic Illn. 2013;9:179-190.

58.

Schünemann

Cuello

Akl

, et al. GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence. J Clin Epidemiol. 2019;111:105-114.

59.

Cuello-Garcia

Morgan

Brozek

, et al. A scoping review and survey provides the rationale, perceptions, and preferences for the integration of randomized and nonrandomized studies in evidence syntheses and GRADE assessments. J Clin Epidemiol. 2018;98:33-40.

60.

Schwingshackl

Nagavci

Stadelmaier

, et al. Pooling of cohort studies and RCTs affects GRADE certainty of evidence in nutrition research. J Clin Epidemiol. 2022;147:151-159.

61.

Balshem

Helfand

Schünemann

, et al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol. 2011;64:401-406.

62.

Mercuri

Gafni

The evolution of GRADE (part 2): still searching for a theoretical and/or empirical basis for the GRADE framework. J Eval Clin Pract. 2018;24:1211-1222.

63.

Mercuri

Gafni

The evolution of GRADE (part 3): a framework built on science or faith?

J Eval Clin Pract. 2018;24:1223-1231.

64.

Borenstein

In a meta-analysis, the I-squared statistic does not tell us how much the effect size varies. J Clin Epidemiol. 2022;152:281-284.

65.

AGO Mamma. Komplementäre Therapie. 2022. Accessed March 16, 2023, https://www.ago-online.de/fileadmin/ago-online/downloads/_leitlinien/kommission_mamma/2022/Einzeldateien_Literatur/AGO_2022D_23_Komplementaermedizin_REF.pdf

66.

Bryant

Duncan

Feder

Huntley

AL.

A pilot study of the mistletoe and breast cancer (MAB) trial: a protocol for a randomised double-blind controlled trial. Pilot Feasibility Stud. 2022;8:1-8.

67.

Walach

Loef

Using a matrix-analytical approach to synthesizing evidence solved incompatibility problem in the hierarchy of evidence. J Clin Epidemiol. 2015;68:1251-1260.

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