Risks and Benefits of Chimeric Antigen Receptor T-Cell (CAR-T) Therapy in Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Promising efficacy results of chimeric antigen receptor (CAR) T-cell therapy have been tempered by safety considerations. Our objective was to comprehensively summarize the efficacy and safety of CAR-T cell therapy in patients with relapsed or refractory hematologic or solid malignancies. MEDLINE, Embase, and the Cochrane Register of Controlled Trials (inception - November 21, 2017). Interventional studies investigating CAR-T cell therapy in patients with malignancies were included. Our primary outcome of interest was complete response (defined as the absence of detectable cancer). Two independent reviewers extracted relevant data, assessed risk of bias, and graded the quality of evidence using established methods. A total of 42 hematological malignancy studies and 18 solid tumor studies met were included (913 participants). Of 486 evaluable hematologic patients, 54.4% [95% CI, 42.5%-65.9%] experienced complete response in 27 CD19 CAR-T cell therapy studies. Of 65 evaluable hematologic patients, 24.4% [95% CI, 9.4%-50.3%] experienced complete response in seven non-CD19 CAR-T cell therapy studies. Cytokine release syndrome was experienced by 55.3% [95% CI, 40.3%-69.4%] of patients and neurotoxicity 37.2% [95% CI, 28.6%-46.8%] of patients with hematologic malignancies. Of 86 evaluable solid tumor patients, 4.1% [95% CI, 1.6%-10.6%] experienced complete response in eight CAR-T cell therapy studies. Limitations include heterogeneity of study populations, as well as high risk of bias of included studies. There was a strong signal for efficacy of CAR-T cell therapy in patients with CD19+ hematologic malignancies and no overall signal in solid tumor trials published to date. These results will help inform patients, physicians, and other stakeholders of the benefits and risks associated with CAR-T cell therapy.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.008 | 0.008 |
| 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) | 0.004 | 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".