Efficacy of Community-involved Hospice Care for Patients with Advanced Cancer: a Meta-analysis
Bibliographic record
Abstract
Background Community-based intervention is an important part of palliative care for advanced cancer patients. However, its role in the health management of advanced cancer patients remains to be supported by medical evidence. Objective To evaluate the efficacy of community-involved hospice care for patients with advanced cancer. Methods Wanfang Data Knowledge Service Platform, CNKI, VIP were searched by using Chinese keywords such as "community" "medical model" and "advanced cancer", Cochrane Library, PubMed and Web of Science were searched by using English keywords such as "Community-based" "Model of Palliative Care" "Advanced Cancer" "Quality of Life", to obtain randomized controlled trials (RCTs) related to the efficacy of community-involved hospice care from 2007-01-01 to 2022-05-10 by using Cochrane system evaluation method on 2022-05-22. The quality of RCTs meeting the inclusion criteria was evaluated, and the valid information was extracted for meta-analysis. Results A total of 11 RCTs in English and 9 RCTs in Chinese were included in the study, involving 2 356 and 1 238 patients, respectively. Meta-analysis showed that compared with routine cancer care, community-involved hospice care could improve quality of life and symptom severity in patients with advanced cancer, demonstrated by increasing Functional Assessment of Chronic Illness Therapy-Palliative Care scale socre〔MD (95%CI) =3.77 (0.83, 6.71) , P=0.01〕and Quality of Life Instruments for Cancer Patients scale total score〔MD (95%CI) =12.53 (2.36, 22.69) , P=0.02〕, reducing Functional Assessment of Cancer Therapy scale total score〔MD (95%CI) =-2.61 (-3.53, -1.70) , P<0.01〕 and Edmonton Symptom Assessment System score〔MD (95%CI) =-2.45 (-4.70, -0.20) , P=0.03〕. However, the improvement of community-involved hospice care on depressive symptoms and overall survival rates of patients remains controversial, and its effect on economic indicators such as admission rates, hospitalization days/numbers needs to be further explored. Conclusion Community-involved hospice care can improve the quality of life and symptom severity of patients with advanced cancer, however, its improvement in hospice care in the depressive symptoms and overall survival rates of the patients remains controversial, and its improvement in economic indicators such as admission rate and hospital stay/inpatients admissions remains to be further explored.
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.075 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".