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Record W1620409176 · doi:10.1155/2007/150126

Cancer Pain and Depression: A Systematic Review of Age‐Related Patterns

2007· review· en· W1620409176 on OpenAlexafffund
Lucia Gagliese, Lynn R. Gauthier, Gary Rodin

Bibliographic record

VenuePain Research and Management · 2007
Typereview
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsToronto General HospitalCancer Care OntarioYork UniversityUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsDepression (economics)MedicineCancerInclusion and exclusion criteriaSystematic reviewMEDLINEQuality of life (healthcare)PsychiatryClinical psychologyAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Pain is a common and debilitating symptom experienced by cancer patients of all ages. Cancer pain is associated with elevated levels of depression; however, age-related patterns in this relationship remain unclear. This information is important to provide effective palliation of pain and depression to the growing numbers of older cancer patients. OBJECTIVE: To provide a systematic review of the literature regarding age-related patterns in the intensity or prevalence of depression among cancer patients with pain. METHODS: Medical and psychological literature databases were searched to identify eligible studies. The methodological quality and outcomes of the studies were compiled and systematically reviewed. RESULTS: Five articles, describing four studies, met the inclusion and exclusion criteria. Due to high levels of cross-study methodological variability, a qualitative review was undertaken. Three of the four studies did not find evidence for age-related patterns in depression. The fourth study found that depression increased with age. CONCLUSION: The weight of the evidence suggests that younger and older cancer patients with pain report comparable levels of depression. However, this conclusion remains preliminary due to the methodological limitations of the available studies. Research is needed to more adequately address this important issue.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.113
GPT teacher head0.444
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations40
Published2007
Admission routes2
Has abstractyes

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