Integrative Oncology Care of Symptoms of Anxiety and Depression in Adults With Cancer: Society for Integrative Oncology–ASCO Guideline
Bibliographic record
Abstract
PURPOSE: To provide evidence-based recommendations to health care providers on integrative approaches to managing anxiety and depression symptoms in adults living with cancer. METHODS: The Society for Integrative Oncology and ASCO convened an expert panel of integrative oncology, medical oncology, radiation oncology, surgical oncology, palliative oncology, social sciences, mind-body medicine, nursing, methodology, and patient advocacy representatives. The literature search included systematic reviews, meta-analyses, and randomized controlled trials published from 1990 through 2023. Outcomes of interest included anxiety or depression symptoms as measured by validated psychometric tools, and adverse events. Expert panel members used this evidence and informal consensus with the Guidelines into Decision Support methodology to develop evidence-based guideline recommendations. RESULTS: The literature search identified 110 relevant studies (30 systematic reviews and 80 randomized controlled trials) to inform the evidence base for this guideline. RECOMMENDATIONS: Recommendations were made for mindfulness-based interventions (MBIs), yoga, relaxation, music therapy, reflexology, and aromatherapy (using inhalation) for treating symptoms of anxiety during active treatment; and MBIs, yoga, acupuncture, tai chi and/or qigong, and reflexology for treating anxiety symptoms after cancer treatment. For depression symptoms, MBIs, yoga, music therapy, relaxation, and reflexology were recommended during treatment, and MBIs, yoga, and tai chi and/or qigong were recommended post-treatment. DISCUSSION: Issues of patient-health care provider communication, health disparities, comorbid medical conditions, cost implications, guideline implementation, provider training and credentialing, and quality assurance of natural health products are discussed. While several approaches such as MBIs and yoga appear effective, limitations of the evidence base including assessment of risk of bias, nonstandardization of therapies, lack of diversity in study samples, and lack of active control conditions as well as future research directions are discussed.Additional information is available at 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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".