A literature review of symptom clusters in patients with breast cancer
Bibliographic record
Abstract
The aim of this article is to present a review reporting empirically determined symptom clusters in breast cancer patients. We conducted a literature search on symptom clusters in breast cancer patients using PubMed, MEDLINE, EMBASE and CINAHL. Studies examining the presence of predetermined clusters were excluded. The five relevant studies identified were published between 2005 and 2009. The five studies differed from each other by statistical methodology, by the number of symptom clusters produced and by the symptoms comprising the clusters. Symptom clusters extracted between the five studies varied from one to four, while the number of symptoms in a cluster ranged from two to five. One study examining symptom clusters between different patient groups and a second study examining clusters across a time trajectory had certain reproducible clusters comprising similar symptoms. There were no clusters across different studies that contained the same symptoms, although the single symptom of fatigue was present in a cluster in all five studies and depression/psychological distress was noted in four of the studies. Nausea and appetite were the only two symptoms that associated together across three of the five studies; however, they were not the only two symptoms in those clusters. Methodological disparities include different patient populations between and within studies, different statistical methods, varying assessment tools and time points, with the majority of studies employing more than one symptom tool. Although there were common symptoms assessed across the five studies, no common symptom clusters could be derived from these reports. This lack of commonality may result from the disparities in subpopulations of patients, assessment tools, and analytical and methodological approaches. As symptom cluster research continues to develop towards a clearer consensus on guidelines, the findings of symptom clusters may provide clinically valuable information regarding diagnosis, prognostication, prioritizing and managing symptoms in breast cancer patients.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".