Comparative effectiveness of interventions for cancer treatment–related cognitive impairment in adult cancer survivors: protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Cancer treatment-related cognitive impairment (CTRCI) can substantially reduce the quality of life of cancer survivors. Many treatments of CTRCI have been evaluated in randomized controlled trials (RCTs), including psychological interventions, pharmacologic interventions, and other therapies. There is a pressing need to establish the benefits and harms of previously studied CTRCI treatments. The proposed systematic review and network meta-analyses will assess the relative efficacy and safety of competing interventions for the management of CTRCI. METHODS: In consultation with the review team, an experienced medical information specialist will draft electronic search strategies for MEDLINE®, Embase, CINAHL, PsycINFO, and the Cochrane Trials Registry. We will seek RCTs of interventions for the treatment of CTRCI in adults with any cancer, except cancers/metastases of the central nervous system. Due to the anticipated high search yields, dual independent screening of citations will be expedited by use of an artificial intelligence/machine learning tool. The co-primary outcomes of interest will be subjective and objective cognitive function. Secondary outcomes of interest will include measures of quality of life, mental and physical health symptoms, adherence to treatment, and harms (overall and treatment-related harms and harms associated with study withdrawal), where feasible, random-effects meta-analyses and network meta-analyses will be pursued. We will address the anticipated high clinical and methodological heterogeneity through meta-regressions, subgroup analyses, and/or sensitivity analyses. DISCUSSION: The proposed systematic review will deliver a robust comparative evaluation of the efficacy and safety of existing therapies for the management of CTRCI. These findings will inform clinical decisions, identify evidence gaps, and identify promising therapies for future evaluation in RCTs.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.030 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".