Long‐term risk of cardiovascular mortality in lymphoma survivors: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Cardiovascular disease has been identified as one of the late complications of cancer therapy. The purpose of this study was to quantify the long‐term risk of cardiovascular mortality among lymphoma survivors relative to that of the general population. A systematic review and meta‐analysis were conducted. Articles were identified in November 2016 by searching EMBASE, MEDLINE, and CINAHL databases. Observational studies were included if they assessed cardiovascular mortality in patients with lymphoma who survived for at least 5 years from time of diagnosis or if they had a median follow‐up of 10 years. A pooled standardized mortality ratio (SMR) was estimated using a DerSimonian and Laird random‐effects model. The Q and I2 statistics were used to assess heterogeneity. Funnel plots and Begg's and Egger's tests were used to evaluate publication bias. Of the 7450 articles screened, 27 studies were included in the systematic review representing 46 829 Hodgkin and 14 764 non‐Hodgkin lymphoma survivors. The pooled number of deaths attributable to cardiovascular disease among Hodgkin and non‐Hodgkin disease was estimated to be 7.31 (95% CI: 5.29‐10.10; I2 = 95.4%) and 5.35 (95% CI: 2.55‐11.24; I2 = 94.0%) times that of the general population, respectively. This association was greater among Hodgkin lymphoma survivors treated before the age of 21 (pooled SMR = 13.43; 95% CI: 9.22‐19.57; I2 = 78.9%). There was a high degree of heterogeneity and a high risk of bias due to confounding in this body of literature. Lymphoma survivors have an increased risk of fatal cardiovascular events compared to the general population and should be targeted for cardiovascular screening and prevention campaigns.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".