Evaluation of Managing Cancer and Living Meaningfully (CALM) in people with advanced non-small cell lung cancer treated with immunotherapies or targeted therapies: protocol for a single-arm, mixed-methods pilot study
Bibliographic record
Abstract
INTRODUCTION: People with advanced non-small cell lung cancer (NSCLC) treated with immunotherapies (IT) or targeted therapies (TT) may have improved outcomes in a subset of people who respond, raising unique psychological concerns requiring specific attention. These include the need for people with prolonged survival to reframe their life plans and tolerate uncertainty related to treatment duration and prognosis. A brief intervention for people with advanced cancer, Managing Cancer and Living Meaningfully (CALM), could help people treated with IT or TT address these concerns. However, CALM has not been specifically evaluated in this population. This study aims to evaluate the acceptability and feasibility of CALM in people with advanced NSCLC treated with IT or TT and obtain preliminary evidence regarding its effectiveness in this population. METHODS AND ANALYSIS: Twenty people with advanced NSCLC treated with IT or TT will be recruited from Peter MacCallum Cancer Centre, Melbourne, Australia. Participants will complete three to six sessions of CALM delivered over 3-6 months. A prospective, single-arm, mixed-methods pilot study will be conducted. Participants will complete outcome measures at baseline, post-intervention, 3 months and 6 months, including Patient Health Questionnaire, Death and Dying Distress Scale, Functional Assessment of Cancer Therapy General and Clinician Evaluation Questionnaire. The acceptability of CALM will be assessed using patient experiences surveys and qualitative interviews. Feasibility will be assessed by analysis of recruitment rates, treatment adherence and intervention delivery time. ETHICS AND DISSEMINATION: Ethics approval has been granted by the Peter MacCallum Cancer Centre Human Research Ethics Committee (HREC/82047/PMCC). Participants with cancer will complete a signed consent form prior to participation, and carers and therapists will complete verbal consent. Results will be made available to funders, broader clinicians and researchers through conference presentations and publications. If CALM is found to be acceptable in this cohort, this will inform a potential phase 3 trial.
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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 | 0.030 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".