Astragalus-containing Chinese herbal combinations for advanced non-small-cell lung cancer: a meta-analysis of 65 clinical trials enrolling 4751 patients
Bibliographic record
Abstract
Jean Jacques Dugoua1, Ping Wu2, Dugald Seely3, Oghenowede Eyawo4, Edward Mills4,51Graduate Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Canada; 2Shanghai Hospital #4, Shanghai, China; 3Department of Clinical Epidemiology, Canadian College of Naturopathic Medicine; 4Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada; 5Faculty of Health Sciences, University of Ottawa, Ottawa, CanadaBackground: Non-small-cell lung cancer (NSCLC) is a leading cause of death. Interventions to reduce mortality in patients with NSCLC represent a patient-important field of research. Little is known about interventions used outside the Western world for NSCLC. One intervention widely used in Asia is astragalus-based herbal preparations.Methods: We conducted a comprehensive systematic review of all published randomized clinical trials (RCTs) evaluating astragalus-based herbal preparations in NSCLC patients. We searched independently, in duplicate, 6 English language electronic databases and 2 Chinese-language databases. We abstracted data independently, in duplicate on studies reporting of methods, survival outcomes, tumor responses, and performance score responses. We applied a random-effects meta-analysis and report outcomes as relative risks (RR) with 95% confidence intervals (CIs).Results: We included 65 RCTs enrolling 4751 patients. All trials included the herbal preparations plus platinum-based chemotherapy versus chemotherapy alone. We pooled 7 studies (n = 529) reporting on survival at 6 months and found a pooled RR of 0.54 (95% CI, 0.45 to 0.65, P ≤ 0.0001). We included 20 trials in (n = 1520) for survival at 12 months and found a pooled RR of 0.65 (95% CI, 0.54 to 0.79, P ≤ 0.0001). This effect was consistent at 24 and 36 months. When we applied a composite endpoint of any tumor treatment response we pooled data from 57 trials and found a pooled RR of 1.35 in favor of herbal treatment (95% CI, 1.26 to 1.44, P ≤ 0.0001). Statistical heterogeneity was low across trials.Limitations: The quality of reporting the RCTs was generally poor. There is also reason to believe that studies reported as randomized may not be.Conclusions: We found a large treatment effect of adding astragalus-based herbal treatment to standard chemotherapy regimens. There is a pressing need for validation of these findings in well-conducted RCTs in a Western setting.Keywords: astralagus, non-small-cell lung cancer, herbal preparations
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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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.051 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".