Call for standardization in assessment and reporting of muscle and adipose change using computed tomography analysis in oncology: A scoping review
Bibliographic record
Abstract
Abstract Investigators are increasingly measuring skeletal muscle (SM) and adipose tissue (AT) change during cancer treatment to understand impact on patient outcomes. Recent meta‐analyses have reported high heterogeneity in this literature, representing uncertainty in the resulting estimates. Using the setting of palliative‐intent chemotherapy as an exemplar, we aimed to systematically summarize the sources of variability among studies evaluating SM and AT change during cancer treatment and propose standards for future studies to enable reliable meta‐analysis. Studies that measured computed tomography‐defined SM and/or AT change in adult patients during palliative‐intent chemotherapy for solid tumours were included, with no date or geographical limiters. Of 2496 publications screened by abstract/title, 83 were reviewed in full text and 38 included for extraction, representing 34 unique cohorts across 8 tumour sites. The timing of baseline measurement was frequently defined as prior to treatment , while endpoint timing ranged from 6 weeks after treatment start to time of progression . Fewer than 50% specified the actual time interval between measurements. Measurement error was infrequently discussed (8/34). A single metric (cm 2 /m 2 , cm 2 or %) was used to describe SM change in 18/34 cohorts, while multiple metrics were presented for 10/34 and no descriptive metrics for 6/34. AT change metrics and sex‐specific reporting were available for 10/34 cohorts. Associations between SM loss and overall survival were evaluated in 24 publications, with classification of SM loss ranging from any loss to >14% loss over variable time intervals. Age and sex were the most common covariates, with disease response in 50% of models. Despite a wealth of data and effort, heterogeneity in study design, reporting and statistical analysis hinders evidence synthesis regarding the severity and outcomes of SM and AT change during cancer treatment. Proposed standards for study design include selection of homogenous cohorts, clear definition of baseline/endpoint timing and attention to measurement error. Standard reporting should include baseline SM and AT by sex, actual scan interval, SM and AT change using multiple metrics and visualization of the range of change observed. Reporting by sex would advance understanding of sexual dimorphism in SM and AT change. Evaluating the impact of tissue change on outcomes requires adjustment for relevant covariates and concurrent disease response. Adoption of these standards by researchers and publishers would alter the current paradigm to enable meta‐analysis of future studies and move the field towards meaningful application of SM and AT change to clinical care.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".