Precancer and cancer-associated depression and anxiety among older adults with blood cancers in the United States
Bibliographic record
Abstract
For patients with blood cancers, comorbid mental health disorders at diagnosis likely affect the entire disease trajectory, as they can interfere with disease information processing, lead to poor coping, and even cause delays in care. We aimed to characterize the prevalence of depression and anxiety in patients with blood cancers. Using the Surveillance, Epidemiology, and End Results-Medicare database, we identified patients ≥67 years old diagnosed with lymphoma, myeloma, leukemia, or myelodysplastic syndromes between 2000 and 2015. We determined the prevalence of precancer depression and anxiety and cancer-associated (CA) depression and anxiety using claims data. We identified factors associated with CA-depression and CA-anxiety in multivariate analyses. Among 75 691 patients, 18.6% had at least 1 diagnosis of depression or anxiety. Of the total cohort, 13.7% had precancer depression and/or precancer anxiety, while 4.9% had CA-depression or CA-anxiety. Compared with patients without precancer anxiety, those with precancer anxiety were more likely to have subsequent claims for CA-depression (odds ratio [OR] 2.98; 95% CI 2.61-3.41). Other factors associated with a higher risk of CA- depression included female sex, nonmarried status, higher comorbidity, and myeloma diagnosis. Patients with precancer depression were significantly more likely to have subsequent claims for CA-anxiety compared with patients without precancer depression (OR 3.01; 95% CI 2.63-3.44). Female sex and myeloma diagnosis were also associated with CA-anxiety. In this large cohort of older patients with newly diagnosed blood cancers, almost 1 in 5 suffered from depression or anxiety, highlighting a critical need for systematic mental health screening and management for this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".