Outcomes of patients with hematologic malignancies and COVID-19: a systematic review and meta-analysis of 3377 patients
Bibliographic record
Abstract
Outcomes for patients with hematologic malignancy infected with COVID-19 have not been aggregated. The objective of this study was to perform a systematic review and meta-analysis to estimate the risk of death and other important outcomes for these patients. We searched PubMed and EMBASE up to 20 August 2020 to identify reports of patients with hematologic malignancy and COVID-19. The primary outcome was a pooled mortality estimate, considering all patients and only hospitalized patients. Secondary outcomes included risk of intensive care unit admission and ventilation in hospitalized patients. Subgroup analyses included mortality stratified by age, treatment status, and malignancy subtype. Pooled prevalence, risk ratios (RRs), and 95% confidence intervals (CIs) were calculated using a random-effects model. Thirty-four adult and 5 pediatric studies (3377 patients) from Asia, Europe, and North America were included (14 of 34 adult studies included only hospitalized patients). Risk of death among adult patients was 34% (95% CI, 28-39; N = 3240) in this sample of predominantly hospitalized patients. Patients aged ≥60 years had a significantly higher risk of death than patients <60 years (RR, 1.82; 95% CI, 1.45-2.27; N = 1169). The risk of death in pediatric patients was 4% (95% CI, 1-9; N = 102). RR of death comparing patients with recent systemic anticancer therapy to no treatment was 1.17 (95% CI, 0.83-1.64; N = 736). Adult patients with hematologic malignancy and COVID-19, especially hospitalized patients, have a high risk of dying. Patients ≥60 years have significantly higher mortality; pediatric patients appear to be relatively spared. Recent cancer treatment does not appear to significantly increase the risk of death.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".