Survivorship Care for People Affected by Advanced or Metastatic Cancer: MASCC-ASCO Standards and Practice Recommendations
Bibliographic record
Abstract
PURPOSE: People with advanced or metastatic cancer and their caregivers may have different care goals and face unique challenges compared with those with early-stage disease or those nearing the end of life. These Multinational Association for Supportive Care in Cancer (MASCC)-ASCO standards and practice recommendations seek to establish consistent provision of quality survivorship care for people affected by advanced or metastatic cancer. METHODS: A MASCC-ASCO expert panel was formed. Standards and recommendations relevant to the provision of quality survivorship care for people affected by advanced or metastatic cancer were developed through conducting (1) a systematic review of unmet supportive care needs; (2) a scoping review of cancer survivorship, supportive care, and palliative care frameworks and guidelines; and (3) an international modified Delphi consensus process. RESULTS: A systematic review involving 81 studies and a scoping review of 17 guidelines and frameworks informed the initial standards and recommendations. Subsequently, 77 experts (including eight people with lived experience) across 33 countries (33% were low- to middle-resource countries) participated in the Delphi study and achieved ≥94.8% agreement for seven standards, (1) Person-Centered Care; (2) Coordinated and Integrated Care; (3) Evidence-Based and Comprehensive Care; (4) Evaluated and Communicated Care; (5) Accessible and Equitable Care; (6) Sustainable and Resourced Care; and (7) Research and Data-Driven Care, and ≥84.2% agreement across 45 practice recommendations. CONCLUSION: Standards of survivorship care for people affected by advanced or metastatic cancer are provided. These MASCC-ASCO standards support optimization of health outcomes and care experiences by providing guidance to stakeholders (health care professionals, leaders, and administrators; governments and health ministries; policymakers; advocacy agencies; cancer survivors and caregivers). Practice recommendations may be used to facilitate future research, practice, policy, and advocacy efforts.Additional information is available at www.mascc.org, www.asco.org/standards and www.asco.org/survivorship-guidelines.
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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 | 0.150 | 0.226 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.010 | 0.015 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".