Sarcopenia and Adipopenia Are Independent Prognostic Factors in Patients with Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Background: The response to treatment and overall survival of patients with acute myeloid leukemia (AML) are heterogeneous. A number of prognostic factors related to patient and tumor characteristics have been described for AML, including age, performance status, and karyotype. The depletion of skeletal muscle (sarcopenia) and adipose tissue (adipopenia) are known to be associated with unfavorable prognosis in patients with some malignant diseases including lymphoma. Here, we studied the impact of sarcopenia and adipopenia on clinical outcomes of adult AML. Patients and Methods: We retrospectively analyzed 70 patients with adult AML (age ≥ 18 years) who received chemotherapy at Gifu University Hospital between December 2004 and September 2014. Skeletal muscle and adipose tissue were measured by the analysis of CT images at the L3 level before treatment. CT images were analyzed using SliceOMatic version 4.3 software (TomoVision, Montreal, QB, Canada), which enables specific tissue demarcation using previously reported Hounsfield unit (HU) thresholds. The CT HU thresholds were -29 to 150 for skeletal muscles and -190 to -30 and -50 to -150 for subcutaneous and visceral adipose tissue, respectively. These values were normalized for stature in order to calculate skeletal muscle index (SMI, cm2/m2) and adipose tissue index (ATI, cm2/m2). Results: Median age at diagnosis was 57 years (18-84 years), with 37 males and 33 females. SMI was significantly higher in male than female patients (P < 0.001). ATI was significantly higher in patients aged 60 years and over than in those under 60 years (P < 0.05). The sex-specific cut-offs for the SMI and ATI were determined by ROC curve analysis. Thirty-five (50%) and 31 (44%) patients were defined as sarcopenia and adipopenia, respectively. Sarcopenia and adipopenia did not significantly differ among various FAB subtypes or cytogenetic risk profiles. The rate of patients with poor performance status (ECOG ≥ 2) was significantly higher in the sarcopenic group (80% vs 45%, P < 0.05), whereas not in the adipopenic group (40% vs 47%). With a median follow-up of 33.5 months, the 3-year overall survival (OS) in the sarcopeniac group was 34% compared with 74% in the non-sarcopenic group (P < 0.001, Figure 1A) and 32% in the adipopenic group compared with 72% in the non-adipopenic group (P < 0.005, Figure 1B). In a multivariate analysis, sarcopenia (HR = 2.84, CI = 1.08-8.08, P < 0.05) and adipopenia (HR = 2.85, CI = 1.19-7.24, P < 0.05) remained predictive of OS. Conclusion: Sarcopenia and adipopenia are independent prognostic factors in patients with AML. Evaluation of skeletal muscle and adipose tissue depletion by CT imaging is a useful objective tool to predict patient outcomes, but a larger prospective study is needed to confirm this effect. Figure 1. Overall survival according to sarcopenic (A) and adipopenic (B) status. Figure 1. Overall survival according to sarcopenic (A) and adipopenic (B) status. Disclosures No relevant conflicts of interest to declare.
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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 | 0.001 |
| 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) | 0.001 | 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".