Multidisciplinary Care of Breast Cancer Patients: A Scoping Review of Multidisciplinary Styles, Processes, and Outcomes
Bibliographic record
Abstract
Background: Clinical practice guidelines recommend a multidisciplinary approach to cancer care that brings together all relevant disciplines to discuss optimal disease management. However, the literature is characterized by heterogeneous definitions and few reviews about the processes and outcomes of multidisciplinary care. The objective of this scoping review was to identify and classify the definitions and characteristics of multidisciplinary care, as well as outcomes and interventions for patients with breast cancer. Methods: A systematic search for quantitative and qualitative studies about multidisciplinary care for patients with breast cancer was conducted for January 2001 to December 2017 in the following electronic databases: medline, embase, PsycInfo, and cinahl. Two reviewers independently applied our eligibility criteria at level 1 (title/abstract) and level 2 (full-text) screening. Data were extracted and synthesized descriptively. Results: The search yielded 9537 unique results, of which 191 were included in the final analysis. Two main types of multidisciplinary care were identified: conferences and clinics. Most studies focused on outcomes of multidisciplinary care that could be variously grouped at the patient, provider, and system levels. Research into processes tended to focus on processes that facilitate implementation: team-working, meeting logistics, infrastructure, quality audit, and barriers and facilitators. Summary: Approaches to multidisciplinary care using conferences and clinics are well described. However, studies vary by design, clinical context, patient population, and study outcome. The heterogeneity of the literature, including the patient populations studied, warrants further specification of multidisciplinary care practice and systematic reviews of the processes or contexts that make the implementation and operation of multidisciplinary care effective.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".