Treatment outcomes for newly diagnosed, untreated <i>TP53</i>-mutated acute myeloid leukemia: A systematic review and meta-analysis.
Bibliographic record
Abstract
e19020 Background: TP53 mutations are present in 10%–15% of patients with acute myeloid leukemia (AML) and are associated with resistance to therapy and poor outcomes. Currently available frontline therapies for TP53-mutated ( TP53m) AML include intensive chemotherapy (IC), hypomethylating agents (HMA), and venetoclax combined with HMA (VEN+HMA). This systematic review and meta-analysis evaluated outcomes associated with IC, HMA, and VEN+HMA in newly diagnosed, untreated TP53m AML. Methods: EMBASE and MEDLINE were searched May 20, 2021 to identify studies of interest. Single-arm data on complete remission (CR), CR with incomplete hematologic recovery (CRi), median overall survival (mOS), event-free survival (EFS), and duration of response (DoR) were extracted and pooled for each treatment. Response rates were pooled using random-effects models; the median of medians method was used for time-related outcomes. Results: Of 3006 abstracts identified, 17 publications describing 12 studies met the inclusion criteria: 6 were randomized clinical trials (RCTs), 2 were single-arm trials, and 4 were retrospective studies. Outcomes are displayed in the Table. CR rate was highest with IC at 43% (95% CI, 30%, 56%), followed by VEN+HMA, 33% (22%, 47%), and HMA alone 21% (7%, 49%). Rates of CR/CRi were 49% (37%, 60%) for VEN+HMA, 46% (39%, 53%) for IC, and 13% (2%, 48%) for HMA alone. mOS was similarly low across the 3 treatments: IC, 6.5 months (N=155; 5.1, 8.5); VEN+HMA, 6.2 (N=73; 5.2, 7.2); HMA, 6.1 (N=34; 4.9, 7.2). Conclusions: CR, CR/CRi, and mOS were low across all treatments for patients with newly diagnosed, untreated TP53m AML. Addition of venetoclax to HMA showed a trend toward improved response vs HMA alone but not for mOS. There is a significant unmet need for more effective treatment for this very difficult-to-treat population. [Table: see text]
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".