Body composition is prognostic and predictive of ipilimumab activity in metastatic melanoma
Bibliographic record
Abstract
Abstract Background Body composition is minimally investigated in an immunotherapy era. Specific body composition signals such as myosteatosis may reflect aspects of patients' immunology and thereby their ability to respond to immunotherapies. Ipilimumab is a key checkpoint inhibitor in metastatic melanoma. As an antibody, it may also be more accurately dosed using body composition parameters rather than weight alone. This retrospective study aimed to investigate body composition‐based dosing and outcomes. Methods Pretreatment computed tomography images from metastatic melanoma, ipilimumab‐treated patients from 2009 to 2014 were used to measure myosteatosis [skeletal muscle radiographic density or SMD, in Hounsfield units (HU)] and surface area (cm2) as previously described. Cut point analysis determined whether a level of ipilimumab dose and myosteatosis demonstrated differences in progression‐free (PFS) and overall survival (OS). Secondary endpoints included objective response rates and toxicities. Results Of 121 identified, 97 patients were evaluable. Baseline demographics included 56 years median age, 60% male participants, and 23.7% with BRAF mutations. SMD analysis identified cut‐offs of SMD < 42 in those with BMI < 25 kg/m2 and <20 HU in those with BMI ≥ 25 kg/m2, respectively. Low SMD patients had poorer median PFS [2.4 vs. 2.7 months, hazard ratio (HR) 1.76, P = 0.008] and OS (5.4 vs. 17.5 months, HR 2.47, P = 0.001), which remained significant in multivariate modelling. High SMD patients had more immune‐related adverse events, better objective response rates (17.9 vs. 3.3%, P = 0.051), and lower baseline neutrophil‐to‐lymphocyte ratio (21 vs. 39%, P = 0.049). Separately, patients receiving <2.03 mg/cm2 had improved median PFS (3.0 vs. 2.6 months, HR 1.88, P = 0.02) and OS (14.9 vs. 5.7 months, HR 1.98, P = 0.01). Conclusions Low SMD and receiving >2.03 mg/cm2 are prognostic of poorer melanoma outcomes post ipilimumab. SMD may identify patients with flawed immunology and predict who may better respond to such therapy. Ipilimumab dosing by skeletal muscle index stands in contrast to weight‐based dosing and may demonstrate a more accurate method of antibody dosing.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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 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".