Characteristics and Correlates of Dyspnea in Patients with Advanced Cancer
Bibliographic record
Abstract
BACKGROUND: Dyspnea is a very distressing symptom present in the vast majority of patients with advanced cancer. There are limited data on the characteristics and correlates of dyspnea in this population. The purpose of this study was to characterize dyspnea, explore the differences between breakthrough and continuous presentations, and to determine factors associated with its intensity. METHODS: Prospective observational study among 70 patients with dyspnea referred to a palliative care service. Dyspnea was assessed using the Edmonton Symptom Assessment System (ESAS, 0-10) and the Oxygen Cost Diagram (OCD). Oximetry, pulmonary function tests, Hospital Anxiety and Depression Scale (HADS), and a detailed systematic evaluation of daily characteristics of dyspnea were performed. Other symptoms were recorded using the ESAS. RESULTS: Of 30 patients, 70 (43%) were female, median age was 58 (range, 28-87), and the most frequent cancer diagnosis were lung (31/70; 44%) and urologic (15/70; 21%). Constant dyspnea occurred in 27 of 70 (39%) patients, with 14 of 70 (20%) presenting breakthrough episodes. Breakthrough-only dyspnea occurred in 43 of 70 (61%). The majority of patients with breakthrough episodes (39/57; 68%) presented fewer than 5 episodes daily, most frequently lasting for less than 10 minutes (50/57; 88%). In univariate analyses ESAS dyspnea was associated with fatigue (p < 0.0001), sleep (p = 0.002), anxiety (p = 0.006), depression (p = 0.01), sensation of well-being (p = 0.03), and with OCD (p = 0.001). In multivariate analysis, ESAS dyspnea was associated with fatigue (p = 0.001), forced expiratory volume (p = 0.004), pain (p = 0.01), and depression (p = 0.03). Dyspnea intensity significantly interfered with activities (general activity, p = 0.01, mood, p = 0.02, walking ability, p = 0.04, normal work p = 0.04, and enjoyment of life, p = 0.01). CONCLUSION: Dyspnea in patients with advanced cancer more frequently had breakthrough characteristics, was of very short duration, and interfered with daily activities.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".