The Quality of Life and Psychosocial Implications of Cancer-Related Lower-Extremity Lymphedema: A Systematic Review of the Literature
Bibliographic record
Abstract
Lower-extremity lymphedema (LEL) is a progressive, lifelong complication of cancer that places a substantial burden upon cancer survivors’ quality of life (QOL) and psychosocial well-being. Despite its prevalence, cancer-related LEL is inconsistently diagnosed, treated, and poorly recognized by health care professionals. The purpose of this systematic review was to summarize and appraise the quantitative literature evaluating the impact of cancer-related LEL on patients’ psychosocial well-being and QOL. Three databases (PubMed, PROQuest, and Scopus) were searched for observational research articles published before May 1st, 2020. Twenty-one articles were eligible (cross-sectional (n = 16), prospective cohort designs (n = 3), and retrospective cohort designs (n = 2)). The majority of studies reported a negative relationship between cancer-related LEL and global QOL and/or one or more psychosocial domains including (1) physical and functional; (2) psycho-emotional; (3) social, relational and financial. A greater number of LEL symptoms and higher LEL severity were associated with poorer QOL. Although the evidence to date suggests a negative relationship between cancer-related LEL and patients’ QOL and psychosocial well-being, there is a substantial need for longitudinal analyses to examine the directionality and temporality of this effect in order to inform cancer survivorship care modelling and improve patient outcomes after cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".