Safety and efficacy of autologous cell vaccines in solid tumors: a systematic review and meta-analysis of randomized control trials
Bibliographic record
Abstract
We conducted a systematic review and meta-analysis of randomized control trials to formally assess the safety and efficacy of autologous whole cell vaccines as immunotherapies for solid tumors. Our primary safety outcome was number, and grade of adverse events. Our primary efficacy outcome was clinical responses. Secondary outcomes included survival metrics and correlative immune assays. We searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials for studies published between 1946 and August 2020 using any autologous whole cell product in the treatment of any solid tumor. The Cochrane Randomized Controlled Trial risk of bias tool was used to assess risk of bias. Eighteen manuscripts were identified with a total of 714 patients enrolled in control and 808 in vaccine arms. In 698 patients receiving at least one dose of vaccine, treatment was well tolerated with a total of 5 grade III or higher adverse events. Clinical response was reported in a minority (n = 2, 14%) of studies. Autologous cell vaccines were associated with improved overall (HR 1.28, 95% CI 1.01-1.63) and disease-free survival (HR 1.33, 95% CI 1.05-1.67) over thirteen and ten trials respectively. Where reported, immune assays correlated well with clinical outcomes. Our results suggest that autologous whole cell vaccination is safe and efficacious in increasing survival in patients undergoing treatment for solid tumors.Registration: PROSPERO CRD42019140187.
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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 | 0.025 | 0.062 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.030 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".