Mistletoe Extracts during the Oncological Perioperative Period: A Systematic Review and Meta-Analysis of Human Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: We aim to evaluate the safety and efficacy of mistletoe extract (ME) use during the oncological perioperative period. METHODS: Details registered a priori on PROSPERO (CRD42018086168). RESULTS: Seven RCTs (comprising 663 participants in nine reports) and three nonrandomized studies were included. In five RCTs, ME was evaluated as adjunctive care and the control group had no additional intervention, whereas in two RCTs, ME was compared head-to-head against common cancer treatments (i.e., etoposide or bacillus Calmette-Guérin) with the intervention groups not receiving standard care. Meta-analyses found no evidence for a difference between ME and no added therapy for mortality and recurrence (RR, 95% CI: 1.00, 0.79-1.27; and 1.03, 0.79-1.33, respectively). Two RCTs reported beneficial effects of ME on immune cells, specifically natural killer cells, in colorectal cancer, and one RCT reported quality of life improvement. Two RCTs reported ME discontinuations due to adverse events and grade 3/4 toxicities. Nevertheless, no safety signals were detected from these 10 studies. Quality appraisal revealed a substantial risk of bias. CONCLUSIONS: Preliminary data are encouraging for mistletoe extracts, particularly in the context of colorectal cancer. However, the evidence is limited by the number of studies, an evaluation of different outcomes, and methodological limitations. Further high-quality research is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.032 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".