Relationship Between Angiotensin-Converting Enzyme Gene Polymorphism and Body Composition, Functional Performance, and Blood Biomarkers in Advanced Cancer Patients
Bibliographic record
Abstract
PURPOSE: Nutritional and functional outcome measures have been shown to vary in patients with chronic diseases according to the polymorphic alleles of angiotensin-converting enzyme (ACE), but little is known about the associations between ACE gene polymorphism (ACEGP) and the components of body composition, strength, and selected blood markers in advanced cancer patients (ACP). EXPERIMENTAL DESIGN: Data were collected from an inception cohort of 172 newly diagnosed ACP with gastrointestinal and non-small cell lung cancer. ACEGP status was defined by the presence of one of the following three combinations of alleles: insertion/insertion, insertion/deletion, and deletion/deletion. Body composition measurements using Dual-energy X-ray Absorptiometry comprised of the following: total fat mass, percent body fat, lean body mass, and appendicular lean mass. Body mass index; handgrip force by Jamar dynamometry; subjective recording of nutrition and performance status as per patient-generated subjective global assessment; cell blood count and differential, serum albumin, ACE, and C-reactive protein were also recorded. RESULTS: Multiple regression analysis, controlling for gender, age, diagnosis, treatments (radio/chemo), survival, and medication use (ACE inhibitors, anti-inflammatories, statins) revealed the following significant (P </= 0.05) relationships in the insertion/deletion compared with insertion/insertion group: higher hemoglobin (Hb; beta, 6.39 g/dl; 95% confidence interval, 0.01-12.78), lower total fat mass (-5.78 kg; -11.62 to 0.07), percent body fat (-6.04%; -12.20 to 0.12), and lean body mass (-3.26 kg; -6.78 to 0.26). When comparing the DD to the II group, higher serum ACE (9.10; 1.96-16.25), Hb (6.25 g/dl; -0.63 to 13.12), and handgrip force by Jamar (6.85 lbs; 0.78-12.93) were found. CONCLUSION: Of the variables studied, ACEGP seems to be primarily associated with differences in body composition, Hb, and muscle strength in ACP. Further data are needed to determine the clinical effect of ACEGP in cancer cachexia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".