Comparisons of Immunoassay and Mass Spectrometry Measurements of Serum Estradiol Levels and Their Influence on Clinical Association Studies in Men
Bibliographic record
Abstract
CONTEXT: Immunoassay-based techniques, routinely used to measure serum estradiol (E2), are known to have reduced specificity, especially at lower concentrations, when compared with the gold standard technique of mass spectrometry (MS). Different measurement techniques may be responsible for the conflicting results of associations between serum E2 and clinical phenotypes in men. OBJECTIVE: Our objective was to compare immunoassay and MS measurements of E2 levels in men and evaluate associations with clinical phenotypes. DESIGN AND SETTING: Middle-aged and older male subjects participating in the population-based Osteoporotic Fractures in Men (MrOS) Sweden study (n = 2599), MrOS US (n = 688), and the European Male Aging Study (n = 2908) were included. MAIN OUTCOME MEASURES: Immunoassay and MS measurements of serum E2 were compared and related to bone mineral density (BMD; measured by dual energy x-ray absorptiometry) and ankle-brachial index. RESULTS: Within each cohort, serum E2 levels obtained by immunoassay and MS correlated moderately (Spearman rank correlation coefficient rS 0.53-0.76). Serum C-reactive protein (CRP) levels associated significantly (albeit to a low extent, rS = 0.29) with immunoassay E2 but not with MS E2 levels. Similar associations of immunoassay E2 and MS E2 were seen with lumbar spine and total hip BMD, independent of serum CRP. However, immunoassay E2, but not MS E2, associated inversely with ankle-brachial index, and this correlation was lost after adjustment for CRP. CONCLUSIONS: Our findings suggest interference in the immunoassay E2 analyses, possibly by CRP or a CRP-associated factor. Although associations with BMD remain unaffected, this might imply for a reevaluation of previous association studies between immunoassay E2 levels and inflammation-related outcomes.
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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 | 0.093 | 0.178 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".