Quality of life among cancer inpatients 80 years and older: a systematic review
Bibliographic record
Abstract
OBJECTIVE: The aim of this systematic review was to summarize and assess the literature on quality of life (QoL) among cancer patients 80 years and older admitted to hospitals and what QoL instruments have been used. METHODS: We searched systematically in Medline, Embase and Cinahl. Eligibility criteria included studies with any design measuring QoL among cancer patients 80 years and older hospitalized for treatment (surgery, chemotherapy or radiation therapy). EXCLUSION CRITERIA: studies not available in English, French, German or Spanish. We screened the titles and abstracts according to a predefined set of inclusion criteria. All the included studies were assessed according to the Critical Appraisal Skills Programme checklists, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement checklist was used to ensure rigor in conducting and reporting. This systematic review was registered in PROSPERO (CRD42017058290). RESULTS: We included 17 studies with 2005 participants with various cancer diagnoses and Classification of Malignant Tumors stages (TNM). The included studies used a range of different QoL instruments and had different aims and outcomes. Both cancer-specific and generic instruments were used. Only one of the 17 studies used an age-specific instrument. All the studies included patients 80 years and older in their cohort, but none specifically analyzed QoL outcomes in this particular subgroup. Based on findings in the age-heterogeneous population (age range 20-100 years), QoL seems to be correlated with the type of diagnosed carcinoma, length of stay, depression and severe symptom burden. CONCLUSION: We were unable to find any research directly exploring QoL and its determinants among cancer patients 80 years and older since none of the included studies presented specific analysis of data in this particular age subgroup. This finding represents a major gap in the knowledge base in this patient group. Based on this finding, we strongly recommend future studies that include this increasingly important and challenging patient group to use valid age- and diagnosis-specific QoL instruments.
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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".