Examining the potential relationship between multidisciplinary cancer care and patient survival: An international literature review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The aim of this review is to examine the relationship between multidisciplinary cancer care and patient survival. METHODS: A literature review was undertaken between January 1950 and September 2009. Included studies described multidisciplinary cancer care and its relation to patient survival. Multidisciplinary care was defined as involvement of a team of clinical and allied specialists whose intent is individualized patient management. Studies were critically appraised for internal and external validity. All study designs were included. RESULTS: Twenty-one studies met eligibility criteria for this review, including two systematic reviews, one abstract, and 18 original studies. Pooling of results was not possible due to heterogeneity of patient populations, disease sites, measured outcomes, and follow-up periods. Twelve studies (one prospective and six retrospective cohort studies, five before-after series) reported statistically significant association between multidisciplinary care and patient survival. CONCLUSIONS: Due to methodological limitations, this review is unable to assert a causal relationship between multidisciplinary care and patient survival. In order to better evaluate this relationship, the oncology community must first accept a common definition of multidisciplinary care. Future efforts can then elucidate which aspects of multidisciplinary care impact survival, with consideration of confounding patient and tumour factors.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".